effects of light and sound on prefrontal cortex activation and emotional responses

Posted comment on ´Effects of light and sound on the prefrontal cortex activation and emotional function:  a functional near-infrared spectroscopy study) written by S. Hori, K. Mori, T. Mashimo and A. Seiyama and published in Frontiers Neuroscience 9th June 2017 doi 10.3389/fnins.2017.00321

SUMMARY

Hori et al. reported in their article the results of their study on the effects on cerebral blood flow (CBF) by emotional changes evoked in response to weak or mild visual and auditory stimuli. Near-infrared spectroscopy (fNIRS) was used to measure the changes in the oxygenated and deoxygenated haemoglobin levels in the blood of certain prefrontal cortex (PFC) areas. The authors` experiments followed on from research results from Hoshi et al. 2011 who were researching with the goal of finding a Mind-Brain-Human Interface (MBHI). Hoshi and colleagues found that intense pleasant emotional changes induced decreases in oxygenated haemoglobin in the left hemispheric dorsolateral PFC (l-DLPFC) and intense unpleasant ones induced increases in the ventrolateral PFC (VLPFC) of both hemispheres. Hori et al. wanted to prove that the hypothesis of Hoshi et al. also applied to weak stimuli.

In their experiments, the authors used 757 subjects with an age range of between 6 and 78. Near- infrared spectroscopy (fNIRS) was used to measure the changes in oxygenated and deoxygenated haemoglobin concentrations and measurements were taken from brain regions in the left and right hemispheres, ie. Brodmann’s areas 9 and 46 (dorsolateral prefrontal cortex region) and Brodmann area 45 (ventrolateral region). In the experiment measurement of the l-DLPFC was taken from channel 5 (ch 5), right hemispheric -VLPFC (r-VLPFC) on channel 2 (ch2), and left hemispheric VLPFC (l-VLPFC) on channel 8 (ch8). The measurements were performed at 70millisecond sampling intervals. Three types of visual stimuli from LED light were used – red (R), green (G) and blue (B) with a gradation sequence between 0 and 100. The colour was calculated according to hue, saturation and brightness (HSB) and the light was generated on the white surface of a cylindrical tube screen in order to achieve whole-body illumination. The auditory stimuli was of the sound of a waterfall which had been divided into 10 band frequencies then equalised and reconstructed as the stimuli. These stimuli were presented through headphones.

The subjects were exposed to the light and sound stimuli which were changed at random according to a feedback loop. The experimental session began with the subject being given an arbitrary colour and sound. If an increase in oxygenated haemoglobin was detected in the left dorsolateral PFC (ch5) then the colour and sound were randomly and independently given. When a decrease in oxygenated haemoglobin level was detected in the left dorsolateral PFC (ch5) then the colour and sound were given continuously until the level increased. Experiment time was kept to 5 minutes. The emotional status of the subjects was assessed from self-reported answers given to a questionnaire completed after the experiment. Only 298 subjects participated and they rated their emotional responses on an 11 point scale (+5 pleasant to -5 unpleasant). Hori et al. compared the valency of the answers to the rates of increase of oxygenated haemoglobin during the stimulus period and then statistical analyses were performed on the results obtained.

The results showed that the light and sound stimuli induced changes in the CBF in the PFC. The authors found a weak but significant negative correlation between the decrease in the l-DLPFC (ch 5 – 59%) and increases at both right VLPFC (ch2 – 35%) and left VLPFC (ch8- 35%). The results from the questionnaires also showed reported correlating emotional changes. These were grouped according to the size of the fNIRS signal changes. For example, group A1 demonstrated a relatively high channel 5 signal change, A4 had both high channel 2 and 8 values. The colour stimuli (red, blue or green) were found to produce no significant differences to oxygenated haemoglobin changes. There were also no effects of colour on pleasant emotions (R 33.5%, G 33.6%, B 32.9) and unpleasant (34.4, 32.8, 32.8) emotions reported. However, sound stimuli did have an effect in both pleasant and unpleasant conditions. High frequency sounds were found to produce emotional change in about 43% of cases independent of whether the stimulus was regarded pleasant or unpleasant. Low frequency sounds induced emotional change in a lower number of cases (approx. 32%) but again, the induction was independent of whether the stimulus was considered pleasant or unpleasant.

In conclusion, Hori et al. wanted to see in their experiments whether mild or weak stimuli would bring about the same results as those observed by other researchers using more intense stimuli. They did. That is the saw that there was a decrease in change in oxygenated haemoglobin level in the l-DLPFC in response to pleasant emotional change and increases in both left and right VLPFC with unpleasant stimuli. However, the correlation was weak, although still significant. The authors also observed no differences between the colours which was a result contrary to other reports which have shown that reddish colours elicit more negative feelings compared to blue and green colours that elicit more pleasant ones. Hori et al. explained this difference by referring to their particular experimental set-up which used a combination of light and sound stimuli. With regards to sound alone though, the authors did show that mild or weak sound effects did in fact lead to emotional change. This did not occur at all frequencies since no change was observed with the M frequency range. The authors explained this discrepancy again by referring to their experimental set-up where their participants were subjected to a particular order of sound frequencies ie. high H, then low L, then medium M. Since sounds in the M frequency range (4,000 to 256 HZ) are ones usually experienced in daily life the authors concluded that emotional change was not induced because of familiarity to sounds within this range. However, the sounds of the H and L ranges did cause activation of the auditory cortex even though both produced the same emotional change results.

With regards to constructing a training free BCI model based on evoked emotional changes, the authors stated in conclusion that although their results indicated weak emotional changes were related to observed fNIRS signals, more refinement would be required before the model would be acceptable.

COMMENT

What makes this article interesting is that it describes the use of a neuroimaging technique as a means of interpreting emotional feelings by third parties. Hori and colleagues looked at the neural representation of particular sensory stimuli not from the perspective of their characteristics, but from the perspective of the personal feelings that were evoked. Therefore, we have two areas to discuss: the first, is from the neurochemical perspective and involves deciding what roles the lateral prefrontal cortex (lateral pfc) areas play in sensory input and emotional responses; and secondly, to what extent is a brain computer interface (BCI) based on the measurement of neuronal functioning as a representation of emotional status a valid and reliable tool for gauging personal opinion?

To begin, we will look at the roles the lateral pfc plays in sensory input and the emotional responses evoked to this input. We know that in general, the pfc has wide-ranging functions eg. attention, working memory, emotions and decision-making and the more popular and widely researched regions lie in the medial part. The lateral areas are less known, but can be said to be more involved in the processing and the working of the material (whether externally or internally sourced) supplied by those medial regions.  Therefore, in general the lateral regions are linked to functions such as playing a role in strategic control (Macdonald) and working memory (maintaining and updating active working memory items). The overall neurochemical characteristics of these areas support this since they are related to high firing capacity. In comparison to the visual cortex V1 area, the lateral pfc regions have a greater density of spines, larger presynaptic density, larger axonal boutons, contain more vesicles and have a higher density of glutamate AMPA receptors suggesting that they have much more powerful synapses than the V1 area which is responsible for incoming visual information (Medalla). Neuronal connectivity also points to a working memory/informational processing use with the lateral pfc and posterior parietal cortex of high capacity individuals being more densely connected (Ekman) and cognitive experience inducing neuronal plasticity. Therefore, the more functioning that occurs then the better the firing capability and connectivity to other brain areas. Not that processing can occur all the time independent of reference to past experiences and therefore, the lateral regions have also been shown to play a role in strategic control with lateral pfc and angular cingulate (ACC) connectivity occurring in complex tasks (Medalla) and also with repeated retrieval of memories leading to decreased functioning of both ACC and pfc areas which is expected in the case of known experiences.

The experiments of Hori and colleagues show that there is a difference in firing relating to emotional responses between the dorsolateral pfc (dlpfc) and the ventrolateral pfc (vlpfc) and therefore, although both areas may be linked to the overall functioning of the lateral regions, they both have their own specialised cognitive uses. Hori and teams` experiments focussed at first on the activity of the left dlpfc. This area is known to be linked to working memory function. In general, the lateral areas are required for maintaining items in the ´activated` neuronal sphere and dlpfc has been described as being more active in reasoning tasks with the right side implicated in plan generation and the left, plan execution. There is evidence of increased activity when actions are selected and initiated (Spencer). In Hori`s experiments this could mean increased activity initially as the sensory information is inputted, assessed and the task (emotional response decided) processed. The dlpfc is also thought to be involved in selecting what is relevant (Niv) from the incoming information and in the suppression of distractor information (Suzuki), both features not applicable in Hori et al.`s experiments here since only the required stimuli (light and sound) are provided and perceived. Therefore, the dlpfc is involved in the fast processing of the stimuli provided and this is reflected in its physiological structure eg. its connectivity to the precuneus sulcus (Mackey), requirement for acetylcholine and GABA firing (Yoon) and high mitochondrial and synaptic bouton capacities.

However, the area also demonstrates reciprocal connections to the ventromedial prefrontal cortex (vmpfc) which is linked to personal values. Therefore, in this way dlpfc firing can be said to be linked to the emotional system and justifies why activity in this area can be linked to personal feelings as in Hori`s experiments. Evidence for this link is that the dlpfc has been shown to perform value assignments (Asaad) and compares strategy values (Wan). The dlpfc has also been linked to performing a causal role in adaptive cognitive control (Gbadeyan) and is involved in the subjective experience of when and how to act in motor behaviour. The observation that increased activity is observed in the dlpfc when actions are selected and initiated (Spencer) could explain Hori and team`s experiments that at first there is sensory input and the requested emotional evaluation is initiated. Since there are reciprocal connections to the vmpfc which is thought to be linked to value establishment then Hori`s experiments link sensory input to emotional worth. It has also been observed that positive expectations of behaviour evoke activity in the dlpfc. This supports the results observed in Hori`s experiments which then show a decrease because of repeated retrieval.

In contrast, the experiments of Hori et al. show that sensory input deemed unpleasant evokes activity in both the left and right vlpfc.  This shows that activity in this area represents subtlety different input to that of the dlpfc. Not only are differences shown between brain areas, but also within since research has shown that different functions of the vlpfc are attributed to different sub-regions and their corresponding connectivity. For example, the ventral inferior frontal gyrus (IFG) connects to the lateral temporal cortex and is part of the ventral functional network whereas the dorsal IFG is connected with the mid-frontal gyrus and is linked to a separate dorsal functional network. Like the dlpfc however, the vlpfc also has general functions that are linked to sensory input and working memory and more importantly, with reference to Hori and team`s experiments with emotional response.

With regards to sensory input and working memory, the vlpfc is likely to be involved in the perception and processing of information obtained from multiple sensory sources. This has been supported by the observed physiological structure with multisensory neurons (Huang) and a reliance on NMDA R and glutamate functioning since ketamine leads to decreased working memory performance and firing. Research has shown that the vlpfc supports different types of working memory. For example it fires in response to information relating to the face and voice (Plakke); is activated in audio-visual situations (here providing a link to Hori et al.`s experiment involving sound and light stimuli); and firing of the vlpfc and dorsomedial pfc is increasingly synchronous as cognitive load is increased when a movie is shown combined with the performance of a secondary task (Oren).

In Hori and team`s experiments, the working memory functioning of the vlpfc region links the presented multiple sensory items together. Then, the individual has to ascertain whether he/she likes or dislikes the presented stimuli. In this case, vlpfc firing is observed when the linking of visual and sound stimuli produces an unpleasant emotional response.  This link to the emotional system is likely through amygdala connectivity. The amygdala is part of the fear attentional and emotional systems and when activity in the vlpfc increases then so does the amygdala connectivity and the fear/unpleasant response is evoked. Indirect evidence for this vlpfc and amygdala connectivity comes from a number of studies. For example by Tetereva where it was found that the functioning of the amygdala in subjects with low and moderate anxiety was linked to an amygdala network which included the emotional pathway, DMN and other areas involved in memory, motor inhibition and emotion suppression. Significant connections between the right amygdala to the right ventrolateral prefrontal cortex were found with right amygdala functioning associated with continuous autonomic evaluation of stimuli whereas left amygdala firing was more responsible for conscious processing of threat situations. Another example is the research showing that self-esteem levels dictate how much defensiveness is exhibited to death-related stimuli. The amygdala-vlpfc connectivity in this case was shown to determine a subject`s responses with subjects having high self-esteem exhibiting increased connectivity, but lower levels of defensiveness. Work by Fowler also showed that rumination in response to stress was linked to higher levels of depressive symptoms in adolescents. Again positive functional connectivity between the amygdala and vlpfc was found to be involved. Therefore, the rise in vlpfc response when the stimuli were deemed unpleasant as shown in Hori et al.`s experiments appears to be justified based on the connectivity of this particular area with the amygdala, important in the fear emotional and attentional systems.

By looking at the functional aspects of the two pfc areas given we can see that a link between sensory stimuli perception and emotional responses exists. This leads on to our next question, which is: to what extent is a biological computer interface (BCI) based on the measurement of this neuronal functioning, a valid and reliable measuring tool for gauging personal opinion?  Experiments described here carried out by Hori et al. centre on blood haemoglobin changes in response to neuronal firing. Firing occurs in the designated areas in response to sensory perception, recognition and evoked emotional response. Hence, the changes in blood characteristics are said to reflect emotional response for the stimulus (or stimuli) presented and therefore, ideally a measurement of blood changes would indicate the personal opinion once a standard has been established. The advantages of such a tool would be that for example, individuals incapable of expressing their feelings through normal means of communication eg. those suffering from locked-in syndrome, would be able to ´express` their feelings through interpreted firing responses in the dorsal and ventral lateral prefrontal cortical areas.

But, there are difficulties and problems with the method which may mean that inaccurate responses are attributed to the stimuli being presented and sensed. The first is that evoked emotional responses are not always consistent. We all know that wonderful  feeling that the first mouthful of chocolate cake gives for example), but after a couple of slices of cake that once wonderful flavour can be regarded with a hatred that can only be relieved by not eating chocolate cake again for months. Or listening to a piece of music is a matter of mood at the time – one day, one piece of music is pleasant, the next day another piece. Or one day a particular event can be highly unpleasant simply because the individual is not open to receiving a new stimulus at that time, preferring something that happened yesterday or the day before rather than having to think about something novel. Therefore, the variability in evoked emotional responses can make it difficult to ascertain a standard since for the tool to work we have to assume that the liked stimulus is always liked and liked to the same degree and similarly for the unpleasant response. Another problem is that we have to assume that even if a person is incapable of communication through usual means, their personal value system is functioning normally, both physiologically and cognitively and that they retain memories and can access memories in order to make comparisons. This may not be possible and therefore, only emotional responses correlating to physiologically-based stimuli may be measured ie. unpleasant emotional response to physical pain.

These two foreseeable problems alone limit the use of the tool and probably there are methods available already that will do this more cheaply, quicker and less intrusively eg. pulse and heart rate monitors compared to functional near-infrared spectroscopy . Therefore, in conclusion to the question is Hori and team`s method a valid and reliable measuring tool for gauging personal opinion, then the answer has to be no. It is a start and the method does show a link between lateral pfc functioning and evoked emotions, but the unreliability of emotional responses in real life may mean that the method is only beneficial in gauging personal opinion of strong physiological and known sensory stimuli and not weak, unreal or non-sensory ones.

Since we`re talking about the topic………………………

……..if the experiments of Hori et al. were repeated but with specific objects linked to sound and colour would the firing of the dorsolateral and ventrolateral prefrontal cortex areas reflect emotional responses to the object or to the audio or visual stimuli?

……a link between infrasound and an evoked unpleasant responses has been reported by some. Can we assume that if Hori et al.`s experiments were repeated using sound stimuli of this range that increased ventrolateral pfc firing would be observed?

……the two prefrontal cortical areas have been linked to working memory functioning and working memory efficiency has been reported as being decreased with increasing age. If Hori and team`s experiments were repeated with the subject group having an advanced  average age can we assume that we would see differences in the firing patterns seen because of lower capability to process the information to satisfy the task demands or would they be unchanged because of the responses being ´gut reactions`?

…..would training or priming in expressing emotional responses quickly and consistently to provided stimuli lead to improved performance of this type of experiment just like they do with other types of cognitive tasks and if so, could this type of experiment be used to stimulate working memory capability in general?

 

 

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Posted in auditory input, emotions, prefrontal cortex, Uncategorized, visual input | Tagged , , ,

substantia nigral dopaminergic function in Parkinson disease

Posted comment on ´Habitual behaviour and dopamine cell vulnerability in Parkinson disease` by L.F. Hernández, P. Redgrave and J.A. Obeso and published in Frontiers Neuroanatomy 6th August 2015 doi 10.3389/fnana.2015.00099

SUMMARY

This opinion article written by Hernández, Redgrave and Obeso begins with a description of brain area degeneration responsible for early Parkinson disease (PD). In PD, the first neurochemical degeneration is thought to involve the dopaminergic neurons of the ventrolateral region of the substantia nigra pars compacta (SNpc), an area which projects mainly to the putamen. This forms part of the caudal region of the human striatum (equivalent to the dorsolateral striatum in rats) which is associated with habitual/autonomic behaviour. Therefore, loss of dopaminergic function and dopamine in this region manifests as impairment of autonomic movements such as walking which is observed in the early phase of PD.

In order to see how the loss of dopaminergic function causes the motor effect, the Hernández, Redgrave and Obeso explore the neurochemical systems involved in controlling behaviour. Hence, the article begins  with a description of the two major systems required for this type of control. These are the goal-directed mechanism (eg. using the stairs instead of the lift) and the autonomic /habit system (eg. used for riding a bike). The former is associated with conscious, voluntary, goal-orientated movements dictated by the highest worth of the outcome compared to other competing movements. This system requires functioning of the prefrontal cortex and dorsolateral striatum areas and is linked to the ´associative loop` which requires connectivity between the SNpc  dorsomedial area to the head of the caudate and rostral putamen. The other control system, the autonomic / habit system, instead uses cues to elicit specific learnt responses via activity of the sensorimotor cortex and posterior putamen re-entrant loop. This is termed the ´motor loop` and requires connectivity between the SNpc ventrolateral area projecting to the posterior putamen. The autonomic system also requires learning dependent on repetition of movement and the learnt response is normally resistant to outcome devaluation. Correction appears only to be by goal-directed action.

Hernández, Redgrave and Obeso continue their article by investigating the link between PD, the SNpc and movement. Their article describes the hypothesis that the onset of PD may be because the ventrolateral area of the SNpc becomes neurochemically ´vulnerable` and hence, the switch of habitual behaviour to goal-directed behaviour as well as the engagement of both goal-directed and habitual behaviour when multitasking are affected. Therefore, there are deficits in both switching and multitasking which may have an impact on daily life.

´Vulnerability` of the ventrolateral SNpc occurs because of physical and functional degeneration of this particular area so that there is subsequent difficulty in performing habitual motor movements. The executive function and goal-directed control system must then take over the performance of previously automatic habitual tasks. This has an added effect by overloading the dopaminergic neurons in the dorsomedial SNpc which could propagate the neurodegeneration. Factors associated with the neurodegeneration of the SNpc and nigro-striatal pathway have been investigated by many researchers, but to date no one definitive factor has been found responsible. One likely factor discussed in the article was mitochondrial stress of the SNpc dopaminergic neurons. Animal models of PD use the toxins 6-OHDA and MPTP and the vulnerability of these neurons to these toxins appears to occur when there is excessive calcium entry through L-type channels. Reduced complex 1 mitochondrial activity and increased oxidant stress are said to be likely factors in PD-related degeneration of SNpc. Another factor to be considered, although not confirmed is the axonal arborisation of the dopaminergic striatal neurons. Although the nigro-striatal projections demonstrate the highest levels of divergent arborisation, the number of dopamine neurons is not at the level of the striatal volume. Therefore, there is greater metabolic and proteostatic load on human dopamine cells that innervate the sensorimotor striatum. However, it has not been confirmed if the neuronal loss of SNpc in PD is paralleled by the degree of arborisation present.

Other factors suggested although considered unlikely as sole causes of the SNpc and nigro-striatal degeneration are neuromelanin, dopamine and vesicular transporters and synuclein deposits. The link with neuromelanin is through the melanised dopaminergic cells which appear to be abundant in the human mesencephalon, although there appears to be no specific vulnerability pattern associated with PD since not all melanised cells die in early PD. In the case of dopamine and vesicular transports, ventral SNpc neurons do not show uniform expression of glycosylated synaptic dopamine transport proteins (DATs) which allow the entry of the neurotoxins, 6OHDA and MPTP. Other midbrain areas also have DATs and therefore, it is considered unlikely that DATs explain the specific vulnerability of the SNpc in PD. In the case of the vesicular transporters, there are reports of decreased vesicular accumulation of DA57 in the ventral SNpc and decreased levels of VMAT2. The failure to store dopamine in presynaptic vesicles leads to higher levels of free dopamine and the formation of cytotoxic free radicals which could lead to the observed degeneration. However, this has not been confirmed and neither has the possible link with synuclein deposits which have been shown to give rise to Lewy bodies. What has been agreed by researchers is that although individual factors may play a role in the degeneration of the nigrostriatal pathway, multiple factors are involved in the onset of PD.

The multiple factors relate to many different areas such as genetic, lifestyle and even the physiology of the SN area itself. Gene mutations and changes in gene expression have been all been associated with the development of PD. For example, mutation of single genes (eg. parkin, LRRK-2, DJ-1, synuclein) as well as the expression of glucocerebrosidase (GBA) correlates to the risk of developing PD and its progression. Several environmental and life-style habits as well as toxic exposure are also associated with higher or lesser risk of developing PD. Hernández, Redgrave and Obeso also suggest in their article that the functional anatomy of the SNpc itself is a significant risk factor. The onset of PD is associated with neuronal cell loss that is highly asymmetrical affecting one unilateral sub-group of dopamine neurons that innervate the sensorimotor regions of the caudal putamen. This loss results in motor deficits restricted to one body area only. The early loss of ventrolateral neurons could be determined by their role in the acquisition and control of automatic movements and the switching between goal-directed and habitual modes.  Research has found that these dopamine neurons are engaged in multiple events in tasks that have both cognitive and sensorimotor components plus events associated with reward prediction. Therefore, it is likely that dopaminergic neurons are subdivided into functionally separate subpopulations ie. ones encoding reward prediction errors that are concentrated medially in the ventral tegmentum (VTA) and others responsive to a wider range of salient sensory events such as reward and these are located in the lateral SNpc.

Hernández, Redgrave and Obeso concluded their article by stating their belief that PD is a consequence of human behaviour. A person has a wide range of sensorimotor, perceptual, cognitive and social skills which are acquired by learning from early in life and with time. These skills have competitive components which form stimulus-response habits and it is this that allows multitasking to occur (one under cognitive control, one under unconscious habit control). The authors believe that PD is the pathological result of increased functional demand on the nigrostriatal system produced by the evolutionary imperative for multitasking. Therefore, there is a link to dopamine and its role in nigrostriatal functioning. This evolutionary increased load of multitasking has appeared to have no apparent negative consequences until recent years since the authors suggest that life expectancy until recently has been shorter and below the age when the risk of developing PD is high. Therefore, the increase in life expectancy in the future will exacerbate the situation. The importance of investigation into the neurochemical basis of the disease was reiterated by Hernández, Redgrave and Obeso at the end of their article and they suggested that there was a need to carry out research to replicate or simulate comparable levels of multitasking in suitable animal models as well as investigating ventrolateral dopamine neuron functioning under long-term functional stress.

COMMENT

What makes this article interesting is that it again shows that deleterious effects in smaller areas of the brain can have larger functional consequences. The article featured in this blog post describes the degeneration of neurons found in the substantia nigra pars compacta (SNpc) area of the brain and its link to Parkinson disease (PD). In this comment we attempt to investigate further the enigma of the neurochemical changes associated with this debilitating disease.

Although there are many symptoms associated with PD, both motor and non-motor. Two specific symptoms for PD are both motor-related. The first is the common slow resting tremor which occurs at a frequency of 4-6HZ and normally afflicts only one arm and hand and usually disappears when the person is given a voluntary task to carry out or when the person is asleep. The second classic symptom is the characteristic slowness of movements (bradykinesia) which is found in every PD case and affects normally automatic movements. PD is then linked with the disturbance of motor planning, initiation and execution and this type of ´slowness` is different to that observed when a person is tired for example. The PD bradykinesia does not allow the sufferer to carry out 2 independent motor tasks at same time. However, there are anomalous observations eg. a PD sufferer can ride a bike or walk down stairs better than walking on a level surface.

The other set of symptoms considered relate to cognitive deficiencies observed with PD sufferers such as those relating to mood, cognition, behaviour and altered sleep patterns. A common dysfunction involves the brain`s executive role and therefore cognitive problems have been observed relating to a wide range of functions such as planning, abstract thinking, rule acquisition, inhibition of inappropriate actions, initiation of appropriate actions, working memory, control of attention, slow cognitive processing speed, impaired recall, impaired perception, and estimation of time and visuospatial difficulties.

However, several problems arise when considering cognitive dysfunction and PD. First of all, is that symptoms relating to this class of deficiency can occur prior to PD diagnosis plus they increase with PD disease progression and therefore the cognitive problems observed may not be attributed to PD neurodegeneration at onset. Alternatively, PD may increase the risk of developing another cognitive disorder. For example, the risk of developing dementia is 2-6 times greater in PD sufferers and also in the case of mood behaviours there are increased levels of depression and/or anxiety with PD with later occurrences of hallucinations and delusions. PD can also be associated with symptoms occurring because of the administration of certain medication, eg. active dopamine agonists administered orally may be linked with impulse control disorders such as pathological gambling. Therefore, the general nature of the cognitive symptoms associated with PD makes it necessary for any research to have precise experimental set-up with visible PD motor deficits in order that causal association can be made.

From a neurochemical perspective, the symptoms relating to motor function described above as attributed to PD are thought to begin to occur when the SNpc is at a particular functioning level ie. around 30% of normal dopaminergic function. So, the question is what roles do the substantia nigra (SN) and particularly the SNpc have in both motor movements and certain cognitive functions and what happens in PD?

With regards to motor control, the SN and the brain areas, subthalamic nucleus (STN) and globus pallidus (GP), are all involved ultimately in the regulation of the levels of ventrolateral thalamus and superior colliculus activities. These brain areas all form part of the motor loop where voluntary movements are planned, initiated and carried out. The motor loop relies on a complex series of excitatory and inhibitory firing events with excitatory firing instigated mainly through dopaminergic and glutamatergic neurons and the relevant neurotransmitter presence and inhibitory firing via GABAergic neurons and interneurons and GABA release. Since a diagram is not possible because of this blog`s editorial limits, a simplified explanation of what occurs and where SN fits in the motor loop is required in order to understand how SN exerts its influence on one particular aspect of motor control. We will begin with the SN which consists of 2 parts, the SNpc described by the authors above in their article and its physiological partner, the substantia nigra pars reticulata (SNpr). The former is considered dopaminergic and exerts output by excitatory dopaminergic firing onto the dopamine receptors of the striatum particularly in the caudate and putamen areas. The SNpc receives excitatory input from the ascending reticular activating system linked to arousal. However,  more importantly it receives shut-down inhibitory GABAergic firing not only from the striatum its output recipient, inhibition elicited through DA1 receptor (DA1 R) binding, but also from the other half of its structure, its partner, the SNpr. The SNpr in comparison is much more connected. It is considered a GABAergic area and receives like the SNpc inhibitory GABAergic input from the DA1 R population of the striatum, but excitatory input from the STN. The SNpr itself exerts inhibitory influences on three areas when activated: as given above, its own SN partner, the SNpc; as well as the superior colliculus (responsible for eye movements); and the ventrolateral area of the thalamus (related to motor movement).

To see how this all works together we need to consider what would happen in normal circumstances, eg. when the ascending reticular activating system fires and activates the SNpc. In this case, the SNpc responds with excitatory firing of its dopaminergic neurons and causes binding activation of the dopamine receptors (DA R) located in the striatum. One of three scenarios may occur: only dopamine type 1 receptors (DA1 Rs) fire; only DA2 Rs fire; or both DA1 Rs and DA2 Rs fire and because of the involvement of the STN and GP there are different outcomes to these receptor firing variations. In the case of DA1 R firing only, which is likely to occur when the dopamine concentration is low, inhibition of the SNpc and SNpr and GPi via the stimulation of direct inhibitory GABAergic pathways results. This is likely to cause the removal of the inhibitory influence of the GPi and SNpr on the ventrolateral thalamus resulting in increased firing or likelihood of firing of this area. There is also removal of the inhibitory influence of the SNpr on the superior colliculus and on its own partner, SNpc, which leads to increased firing or likelihood of firing of these areas. Now compare this to when the DA2 R alone is fired from the SNpc activity. This situation occurs when the dopamine concentration is higher. In this case, only stimulation of the inhibitory pathway to the GPe area occurs resulting in its shut-down with the inhibitory pathways to the SNpc, SNpr and GPi remaining inactive. Hence, the direct inhibitory pathways from the SNpr and GPi on the ventrolateral thalamus are removed and as a result both lead to increased firing or likelihood of firing. However, the first consequence of DA2  R firing is the removal of the inhibition on the STN which leads to the stimulatory pathways to the GPi and to the SNpr to fire. Since both of these have inhibitory effects on the firing of the ventrolateral thalamus, the overall effect of the inhibition is a reduction in its activity. The inhibitory pathways from the SNpr to the superior colliculus and to its partner, SNpc, are also fired resulting in reduced superior colliculus activity and inhibition of the SNpc. When both DA1 Rs and DA2 Rs striatal populations are fired as in the case of high dopamine concentration there is a mix of both scenarios with the activities of the STN, GPe and GPi all being affected. However, the overall outcome appears to be that the ventrolateral thalamus activity is increased through the direct inhibition of the SNpr pathway, but then decreased because of the GPi and STN responses. Superior colliculus activity in this case is decreased.

Diagrams of connectivity detailing these scenarios give approximate increases and decreases in the ventrolateral thalamus activities with the three scenarios eg. only DA1 R involvement 66% increase, only DA2 R 33-66% decrease and both DA1 R and DA2 R influence a 33% increase leading to a 33-66% decrease. Superior colliculus activity is increased with DA1 R and decreased with both DA2 R alone and with combined DA1 R/DA2 R activation. What makes the difference as to which scenario is followed is likely to be the dopamine concentration in the striatum, which can come not only from the SN excitatory pathway, but also from cortical stimulation. It is unlikely to be a difference in number of receptors present since both populations are about equal (around 40%) in the striatal area although exact distribution is not known. It should be also be noted that firing of different receptor populations can have other local effects because although both DA1 and DA2 receptors are linked to the same second messenger system (adenylyl cyclase activity – AC), the DA1 Rs response to low concentrations of dopamine is activation of the AC whereas DA2 Rs respond in high dopamine concentrations by inhibiting it. Therefore, a local response of changed cAMP concentrations with its knock-on effects will occur. The role of cAMP in SN functioning, if any, has not been to date been established.

But it is all very well showing an effect on neuronal firing of the SN and its associated areas, but we have to attribute it to a cognitive purpose. This was hypothesised by Hernández, Redgrave and Obeso in their article and by others and has essentially been determined by looking at the differences between when it is present and functioning correctly to when it is absent (as in the case of PD) or dysfunctional (as with for example, administration of dopamine-based drugs). Hernández, Redgrave and Obeso hypothesised that SN functioning is required in the switching of goal-directed motor tasks to habit/autonomic status and is also required for multitasking two motor movements, one conscious and the other unconscious. In the case of goal-directed tasks, motor control is considered conscious, with the movement having the highest value of its competitors being taken and is part of the ´associative loop` involving the prefrontal cortex (PFC) and dorsolateral striatum. It is thought to require activity in the dorsomedial SNpc area which sends output to the rostral part of the putamen and the caudate. In the case of habitual/ autonomic tasks motor control requires the use of cues to bring about specific learnt responses via the sensorimotor cortex and posterior putamen and is part of the ´motor loop`. This requires activity in the ventrolateral part of the SNpc  with output to the post-putamen area. The switch therefore comes from a shift in activity from the SNpc dorsomedial area to the SNpc ventrolateral area. From a cognitive perspective, the switch between goal-directed conscious to unconscious autonomic control is required so that the brain`s conscious processing capability is freed to perform other tasks. Without it conscious awareness becomes centred on regulating movement whether in the planning, initiating or executing stages and as a consequence motor multitasking where one movement is conscious and the other unconscious is not possible. This switch is not always advantageous or even required. For example, conscious control is needed in learning for example (eg. learning to ride a bike requires conscious thought at the start), but it is important that the capability is available. This is believed not to be the case in PD.

Therefore, the SN is required to be part of the ventrolateral thalamus control system and regulate it according to whether learnt processes are being recalled or conscious control is required. From looking at the connectivity between the motor loop components we can expand on how SN performs and is part of the overall motor ´switching function`. This switching from conscious to unconscious is likely to require that ventrolateral thalamus activity is reduced. This has a knock-on effect of reducing cortical activity. As detailed before, an examination of connectivity patterns unfortunately not able to be displayed here, shows that a reduced ventrolateral thalamus activity occurs when SN functioning (pc and pr areas), STN and GP activity all occur. This happens when the activity of the SNpc switches from the dorsomedial to ventrolateral areas and the excitatory pathway from the SNpc leads to activation of the dopaminergic DA2 Rs or the combined DA1 R/DA2 Rs of the striatum. This relies on the dopamine concentration of the striatum being high. However, when learning occurs or when conscious motor control is required, the activity of the ventrolateral thalamus has to be high and hence, in this case activation of the DA1 R population of the striatum is favoured meaning low dopamine concentration, with no STN/GP override. This correlates to the value system and cortical stimulation as being part of the motor control loop and is supported by the effect on the activity of the superior colliculus which controls eye movements. Both DA2 R activation and combined DA1 R and DA2 R activation lead to reduced superior colliculus activity correlating to habit/autonomous motor control whereas DA1 R activity is linked to vigour of eye movements which has been shown to be linked to value of motor options and conscious decision-making.

Now that we have established how the SN is involved in the switching mechanism of conscious, goal-directed movement control to unconscious, habitual/autonomic control, we can look at how its activity is changed in the case of PD which is known to be deficient in this cognitive area. The ability to rapidly adapt movement schemes is defective in PD sufferers and therefore, motor planning is slower and more cognitively effortful involving the constant generation of conscious plans. The PD symptoms of slowness of movement and tremor for example are thought to be brought about by the ´vulnerability` of the ventrolateral SN area in particular and are elicited by the reported degeneration of dopaminergic neurons in the pc area. There is likely to be a considerable amount of redundancy in the system since PD symptoms are not observed until 50-80% of these neurons are destroyed. If we look at the connectivity diagrams and flow of excitatory and inhibitory pathways of the motor loop as we did for normal motor control we can see that again motor control with regards to switching from conscious to unconscious processing is elicited through the interrelated functioning of the striatum, SN, STN and GP areas. Two conditions can be considered: one, if only the dopaminergic functioning of the SN in PD sufferers is defective, ie. the SNpc area alone; or two, if both the dopaminergic and GABAergic functioning levels are decreased and therefore, both SNpc and SNpr areas exhibit very low functional capability. In the first case of only dopaminergic neuronal degeneration, then ventrolateral thalamus activity is similar to that observed with normal functioning capability (ie. only DA1 R involvement 66% increase, only DA2 R 33-66% decrease and both DA1 R and DA2 R influence with 33% decrease). Changes to superior colliculus activity also reflect the results achieved under normal SN functioning (ie. increased level with DA1 R activation, and decreased with DA2 R and combined DA R). This implies that deficits in SNpc dopaminergic functioning alone does not cause the cognitive symptoms of motor control switching failure observed in PD sufferers.

An investigation into the motor loop functioning when both dopaminergic and GABAergic degeneration occurs (ie. both SNpc and SNpr defective) produces different results more in keeping with the cognitive effects observed in PD sufferers. In these circumstances, both high and low concentrations of dopamine produce increased ventrolateral thalamus activity (only DA1 R involvement 33-66% increase, only DA2 R 66-100% increase and both DA1 R and DA2 R 100%). This is different to the dopamine receptor scenarios under normal, non-PD conditions. Therefore, the cognitive effect of PD is likely to be elicited by high concentrations of striatal dopamine indicating a DA2 receptor involvement (or DA1 R and DA2 R) providing that both dopaminergic and GABAergic functioning in the SN is degenerated. Therefore, reduced SN, STN and GP activity would facilitate involuntary movements and prevent the switch from conscious to unconscious motor control. This is supported by the connectivity diagrams giving increased superior colliculus activity in all dopamine receptor binding combinations.

However, there is a conundrum in this hypothesis and this relates to known PD treatments. Medication that would increase the overall concentration of dopamine (such as L-Dopa-like drugs, DA uptake inhibitors, DA agonists and MAO inhibitors) and specific DA2 agonists leads to alleviation of the symptoms of PD although they may cause motor systems to be active at inappropriate times producing dyskinesia. Therefore, how can high dopamine concentration and importance of DA 2 R binding occur not only under normal conditions, but also in PD sufferers where there is an absence of dopaminergic SN activity? This could possibly be explained by the administered dopamine compound (or specific DA 2 R agonist) specifically compensating for the defective SN input. This may imply that the administration leads to either a local SN effect or a compensatory SN effect at the striatal level. In the case of the local SN effect, this could be achieved by increasing the number of dopamine receptors present on the remaining functional neurons by stimulating production in response to the high dopamine concentration or by increasing the sensitivity of the dopamine receptors remaining to dopamine so that the shut-down of the second messenger system occurs at a lower concentration. An alternative method is to affect the second messenger system directly by decreasing cAMP levels via the activation of alternative neurotransmitter receptors that also use this system. This occurs for example in the PFC where an increase in 5HT activity has an effect on dopamine release.  This implies however, that the ultimate influence of the SN on dopaminergic firing in the striatum comes from its second messenger effect.

These possibilities could also apply to the more global effect of the deficiency of SN influence at the striatal level. It is also possible that the administered dopamine could increase the override effects of the STN and GP areas by making them more sensitive to available dopamine. Another possibility is that only 60-80% of the dopamine effect at the striatal level occurs because of SN activity and the remaining 20-40% comes from striatal input. Administration of dopamine compounds would replace the missing SN contribution. However, this does not fit the PD model since there would be no DA2 R firing since the dopamine concentration would not be high enough without treatment. However, the effect could be propagated via the DA1 R, which fires in low dopamine concentrations because of its higher affinity for the neurotransmitter. This would lead to increased firing by default. It is also possible that the DA Rs attributed to SN input are different to those receiving cortical input. This would indicate specific distribution and receptor structure which is unlikely.

The positive effect of administered dopamine on switching activity may not just be linked to neuron and receptor firing, but also be brought about by the restoration of appropriate brain wave synchronicity in the relevant motor areas. It is possible that the increase in dopamine contribution and SN compensation leads to decreases in beta brain waves in the STN area which as we have said includes the GP and SN areas. Wijk found that beta brain waves were prominent in basal ganglia areas particularly the STN in PD sufferers and these decreased with dopaminergic medication or deep brain stimulation. Although beta wave amplitude in cortical regions has been found not to be affected so much by PD, further research (Cole) shows that there is highly interdependent phase-amplitude coupling between beta and gamma waves in the primary motor cortex in PD. The gamma wave amplitude changes reflected the beta oscillations indicating that no actual firing in the gamma wave frequency band took place. Therefore, any decrease in beta wave synchronicity in the STN area may have an effect on brain wave synchronicity of the cortex and ultimately on motor cortical activity.

Until now, we have only considered the motor control role of the SN and the effect of its deficiency, but as given at the start of this blog comment, there are other cognitive effects associated with PD and therefore, we will conclude with a quick look at two aspects of cognitive functioning where the SN may play some sort of role. As given above, a common dysfunction observed in PD involves the brain`s executive role which relates to a wide range of effects such as in planning, abstract thinking, rule acquisition, working memory, control of attention, slow cognitive processing speed, impaired recall, impaired perception and estimation of time and visuospatial difficulties for example. Two areas where SN is likely to have an effect spring to mind to explain these cognitive defects: the first is the role of the SN in learning and reward; and the second its role in informational timing. The SN role in reward and learning appears to come from its effect on the functional activity of the striatum instigated via its excitatory dopaminergic input. The SNpc is known to be required for the learnt responses to known stimuli, spatial learning and is required for the retrieval of value/saliance with regards to movement. It is not linked with encoding of either information or emotional worth (value). Therefore, it can be hypothesised that the role of SN in those cognitive functions associated with executive control comes from its ability to switch on or off the capability which allows emotional worth to be considered in any motor-related informational process, eg. motor planning and decision-making. For example, motor control which is conscious requires an evaluation of value (dorsomedial SNpc) whereas unconscious or habit/autonomic movements can be retrieved without (switch to dorsolateral SNpc). This is particularly important in the retrieval of sequence memories (procedural memory) where a pause to reflect on value would be detrimental to the flow of sequential movements.

The other cognitive role SN plays is believed to be in temporal processing (timing). Correct timing is important in linking events together in the appropriate order and hence, it is important in movement recall in response to stimuli and sequence recall. Timing is also required to link informational characteristics together to form a single neural representation of an event. This is shown by the SN`s  role in spatial learning which is also timing related since it is a record of the features of an event at the same time as its location. It appears that the SN is required for temporal processing since lesions and deficiencies have led to deficits in a number of capabilities eg. lesions of the SNpc appear to lead to deficits in the repetition of identical movements and freezing and slowness of gait in PD sufferers. It is hypothesised that SN takes part in the timing of the automatic recall of movements. This may be achieved by pauses in firing which are common in normal neurochemical processes linked to movement. For example, it is known that the supplementary motor area (SMA) evokes a pause in firing before a movement is initiated. This is also supported by fast spiking inhibitory interneuron firing in the striatum before movement, TAN firing in the VTA and pauses in beta wave stimulation observed in the STN. The firing bursts and pauses may affect the activity of the whole motor loop area and hence, the SN also plays a part. It should be noted that SNpc activity is itself ´paused` by feedback inhibition by the dopamine binding of the striatum and its own partner structure, the SNpr, which has an inhibitory effect on the SNpc when activated.

Therefore, we can see that although the SN is primarily considered as important in motor control regarding the ´switching` between conscious, goal directed movement and habit/autonomous movement it also is part of the wider physiology required for successful motor learning and informational timing. These cognitive roles manifest as a result of neurochemical mechanisms in the SN and associated areas. A look at the connectivity and functionality results of the motor loop components show that specific dopamine activity in the SN with related striatal, STN and GP inhibition or stimulation can lead eventually to either the reduction or increase in activity of the ventrolateral thalamus and the cortex. Therefore, neurochemical deficiencies in SN activity resulting from loss of neurons or lesions can have wide ranging effects on cognitive functions and as PD shows on movement. However, there is still a lot more to learn about the SN, but although studies on the SN and its neurochemical mechanisms alone may be beneficial, it is the investigations of its connectivity to other areas which may actually bring the answers we are looking for.

Since we are talking about the topic………..

…….can we assume that radioactive ligand binding assays of striatal tissue of the animal model of PD using agonists specific for DA1 Rs or DA2Rs would resolve the issue of whether DA2 Rs are solely responsible for PD-like symptoms, or not?

……deep brain stimulation of the STN appears to alleviate the symptoms of PD. Would neural imaging of the motor loop SN, STN and GP areas demonstrate changes in functioning levels associated with the treatment?

…..it is thought that one possible cause of PD is increased iron uptake associated with neuroinflammation. Would the measurements of the microglial populations and neuronal cell iron transporters of both the SNpc and SNpr areas determine whether or not this is indeed the case in the animal model? Would the administration of neuroinflammatory inhibitors have a beneficial effect on preventing or slowing the progression of the development of the disease and would this effect be long-term?

 

Posted in brain waves, dopamine, globus pallidus, neuronal connectivity, neuronal firing, Parkinson disease, striatum, substantia nigra, Uncategorized | Tagged , , , , , , ,

updating beliefs under perceived threat

Posted comment on ´Updating beliefs under perceived threat` by N. Garrett, A.M. Gonzalez-Garzon, L. Levita and T. Sharot and published in Journal of Neuroscience 2018 vol. 38 (36) p. 7901 doi.org/10.1523/JNEUROSCI.0716-18.2018

SUMMARY

Garrett and colleagues sought with their experiments described in this article to explain and verify the results of other researchers that state that humans are better at updating positive, agreeable information into their established beliefs than undesirable ones. This process has been termed valence dependent learning asymmetry and the alleged consequence of this type of information bias is that risk can be underestimated and precautionary action not taken.

In their experiments, Garrett and team used a laboratory constructed fear situation where threat was perceived (Experiment 1) and a naturally occurring fear situation (Experiment 2). For Experiment 1, a total of 35 male and female students with a mean age of around 25 took part. The perceived threat, which was unrelated to the information of the task, was that the participants were informed that they must deliver a speech on a surprise topic at the end of the task to a panel of their staff members who would record it and judge it in front of them. Participants of the control group were told instead that they had to write an essay on a surprise topic, but no judging or live recording would take place. Then, all participants were given 6 mathematical problems to solve in 30 seconds (a variation of Trier Social Stress Test), with the threat manipulation subjects being given more difficult problems than the control group.

Certain physiological and psychological tests eg. self-report of anxiety level, skin conductance level, cortisol levels, and a behavioural task were also carried out to determine the level of perceived threat being experienced. For the self-report test, the participants were asked to record their current state of anxiety according to 6 statements (Spielberger State Trait Anxiety Inventory) with high scores indicating high levels of anxiety. For the skin conductance level test, the skin conductance of 2 fingers of the non-dominant hand were measured for 2 minutes while the subjects stared at a fixation cross and the results were analysed to see any change in the participant`s autonomic arousal levels. For the levels of cortisol, saliva samples were taken at specific times before, during and after the task to rule out the delay in HPA axis responses.

The behavioural task undertaken consisted of the participants being presented with 40 short descriptions of negative life events which included such things as domestic burglary and fraud. Each event had been assessed previously as to the probability of it occurring at least once to a person living in the UK within the same age range as the participants. The probability for each event was between 10 and 70%. The participants were asked to estimate how likely it was that each presented event could happen to them in the future. Each event was treated separately and presented for 3 seconds. The participants were then given 5 seconds to estimate the likelihood of it happening to them. They were then asked to focus on a fixation cross for 5-10 seconds before the actual probability rate was presented to them for 2 seconds. The second session followed immediately after the first and here the participants were asked again to provide estimates of the likelihood of encountering the same event. This was carried out to give the level of information updating that had or had not occurred and hence, the level of updating was calculated by assuming that positive updates indicated a change toward the probability presented (first estimate minus second estimate) and negative updates a change away from the probability presented (second estimate  minus first estimate).

Garrett and colleagues included certain controls in their experiments such as a test to see whether memory capability was affected by the experimental method. In this case the participants were asked at the end of the experiment to record the actual probability values given at the start of the first session. Participants were also asked about how they rated themselves for vividness, familiarity with the type of life events given, prior self-experience of the type of life events given, level of emotional arousal incurred and level of negativity if that event was experienced. Statistical analyses were performed on all results.

Different subjects were used for Experiment 2 than Experiment 1. In Experiment 2, the authors used on-duty firefighters who would naturally experience personal fear at varying levels in the course of their work.  In total 28 participants (27 males) with a mean age of 43 took part but because of logistics and time commitments an online version of the task used in Experiment 1 was used. The test period began with demographic and work-related questions. The participants were then presented with 40 negative life events and asked to estimate how likely it was that this event would happen to them in the future.  Experiment 2 followed the same pattern as Experiment 1 except for a few differences. These were that: the fixation cross was presented only once and only for 1 second; the memory control and subjective ratings were only applied to half the stimuli; the participants had to complete only a short self-report on anxiety levels; and there were no measures of autonomic arousal. Again, statistical analyses were performed on all the results obtained.

The results of Experiment 1 showed Garrett and colleagues that the subjective self-reports of anxiety and the other physiological measures of stress such as cortisol and skin conductance were higher in the threat manipulation group of their student participants relative to the control. The authors also interpreted their results as a loss of biasness for positive information in response to perceived threat in the environment. The information integration parameters for good/desirable life events were according to the figures given approximately the same (0.56) whether the participants belonged to the control group or to the threat manipulation group. However, in the case of bad/undesirable life events the information integration parameter for the threat manipulation group was 0.54, but only 0.4 for the control group. This was interpreted by the authors as showing that the participants in the threat manipulation group were more likely to effectively integrate bad news into their beliefs relative to those in the control group. Therefore, the bias of information updating had disappeared in respect to perceived threat while the information integration for good news had not changed. Garrett and colleagues also found that memory capability did not play a role since recall scores did not differ between the groups, valence, or any interaction. The participant`s first estimates of good or bad news did not differ between the threat manipulation group and control group, but the threat manipulation group did give lower first estimates than the control for good news even if there was no significant difference for the bad news.

The selective fluctuation in the integration of information relating to bad/undesirable life events was concluded to be associated with changes in self-reported anxiety and a change in physiological stress as indicated by the skin conduction test. The participants who showed the greatest increase in both measurements were most likely to change their belief in proportion to the difference between their first estimates and the probability given for the undesirable life events. Cortisol did not relate to this information integration and therefore, a link to the HPA axis was not demonstrated if the type II error was excluded. An alternative mathematical analysis of the results bearing in mind within-subject factors such as vividness, familiarity, past experience and emotional arousal also produced in the case of the negative life events a significant correlation between information integration and self-reported anxiety and skin conductance. However, the information integration parameters for good news/positive life events found no significant effects on cortisol, self-anxiety and skin conductance.

Therefore, it was concluded by Garrett and colleagues from the results of their Experiment 1 that in a low threat environment information was integrated asymmetrically with good news being incorporated into the personal belief system and bad news being disregarded. However, under perceived threat, this asymmetry was lost and the integration of bad news was increased, ie. the biasness of information integration observed by other researchers was abolished  with perceived threat in the environment. Increased physiological arousal and self-reported anxiety correlated to the increased integration of the negative life events/bad news, but increased memory capability or attention were not factors involved in the observed bias change.

In Experiment 2, Garrett and co-workers used participants who were on-duty fight-fighters who were used to regular occurrences of high stress/personal threat. Self-reported anxiety was found to be significantly correlated to information integration bias with heightened anxiety reducing the bias, ie. the higher the acute anxiety reported the more likely the fire-fighter was to integrate the bad news into his/her personal beliefs. However, an opposite effect was observed with good news where it was shown that the greater the self-reported anxiety than the lower the level of information integration of good news occurred. The results of Experiment 2 suggested that anxiety related to a valence dependent increase in the ability to adjust beliefs in response to new information. This was interpreted as fire-fighters who reported a higher level of anxiety also showed increased integration of bad news and that bias towards positive information integration was not seen under these conditions. Again, increased memory capability or attentional focus were not considered reasons for the bias change.

The authors then went on in their article to discuss the ramifications of their study results. From a biochemical perspective, they discussed the neurochemical changes accompanying stress from perceived threat. They said that stress could interfere with top-down control mechanisms which inhibit the integration of unwanted information, or it could directly boost the neural representation of estimation errors generated from bad news, but not good. This latter hypothesis is supported by the observation that negative prediction errors in dopamine rich striatal nuclei are increased in threat situations due to the release of the dopamine neurotransmitter. However, the main discussion of the results was from a psychological perspective. Garrett and colleagues stated that the change in bias of updating of positive information according to the level of threat could be an adaptive mechanism. A bias towards positive information (optimism bias) could lead to behavioural effects some of which are positive (ie. increased exploration, motivation, increased courage to take on more riskier situations) and others negative (ie. failure to take precautionary action, overestimating the true value of a situation). This was observed to be greater in environments where potential gains are sufficiently greater than costs. However, the authors state that in environments of potential harm then optimism bias is a disadvantage and hence, the disappearance of the information integration bias would enable a more accurate assessment of risk. They went on to discuss the case of prolonged threat or dissociation from reality where increased integration of negative information could lead to psychiatric problems and gave examples of where this was shown to be the case such as in major depressive disorder, clinical anxiety and phobia.

In conclusion, the experiments of Garrett and colleagues were said to confirm the reports of other researchers that show that an asymmetry in belief formation in favour of positive news disappears when the person is under threat and leads to an improvement in the participant`s tendency to incorporate undesirable news into personal belief systems. This was found to be associated with physiological arousal signals such as skin conductance responses and self-reported anxiety. They linked the physiological observations to behaviour by saying that the bias in information integration towards good news and its abolishment during episodes of threat could have behavioural ramifications. Flexibility in how individuals integrate information may enhance the likelihood of responding to warnings with caution in environments rife with threat, while maintaining a positivity bias which can increase well-being.

COMMENT

What makes this article so interesting is that it explores the association between the value placed on presented information and the performance of updating memories. The work by Garrett and colleagues in this article and the work of other researchers can be summarised briefly as that there appears to be a bias towards the updating of ideas when it applies to good news in preference to undesirable or ´bad` news and this biasness appears to be abolished when the person is in a threat situation. This type of processing and learning biasness is known as valence dependent learning asymmetry.  The consequence of such an unequal learning preference is that information pertaining to situations likely to be negative or riskier are ignored or underestimated and hence, the person could be ill-prepared for an unfavourable future. Before we go on to look at this type of biasness from a psychological and a neurochemical perspective we have to ask whether the results and conclusions from the experiments undertaken by Garrett and colleagues are valid since they appear to conflict with what we would naturally think about the memory process under conditions of physiological stress/fear/anxiety,  ie. that a person would be more likely to remember and update their ideas if confronted with something bad than something good and this preference would also exist if the person was anxious, fearful or stressed.

If we look at the set-up of Garrett and colleagues experiments we can see that on paper the conclusions from the results appear to be correct even if the conclusions are not so clear-cut. The ´threat` situation appears to be genuine since the students of Experiment 1 show physiological signs of a stress response via changes in cortisol levels, skin conductance and self-reports of anxiety. The threat situation however is a ´mental` stress rather than a physiological one which is normally and regularly endured by the participants of Experiment 2.  Experiment 2 was structured differently to Experiment 1 and the participants were fire-fighters, mainly male and of a higher average age to those participating in Experiment 1. The fire-fighters of Experiment 2 were asked to report their level of self-anxiety because of the long-distance, online experimentation set-up. No definitive threat situation was given to the participants of Experiment 2 as such since Garrett and team proposed that the job as fire-fighter itself puts participants in a stress/fear situation. The fire-fighters too reported a change in level of self-anxiety which although slightly less than Experiment 1 was still considered by the authors as acceptable. There might be slight disagreement on this point since although fire-fighting is without a doubt a more stressful job than being a student, the participants of Experiment 2 were probably not newcomers to that job and would have been trained to cope with long-term stress plus they were not being confronted at the time of the experiment with fire itself or any other physically dangerous situation. We also have to consider that there is also an age difference between the groups of participants since the fire-fighters of Experiment 2 were older and they were predominantly male.

If we look at the results obtained we can also see that there might be slight differences in interpretation of them. In the case of the updating of good news, the integration parameter ratios appear to be approximately the same for both Experiment 1 and 2. We can also see that in Experiment 1 the level of updating for good news is roughly the same whether for the control condition or for the threat situation. This means that according to the results obtained here the attentional level, information processing and memory capabilities relating to good news are unchanged by the participant working under a higher level of threat/stress. In the case of Experiment 2, the integration parameter is slightly less.  This means that for the fire-fighters self-diagnosis of increased levels of anxiety correlates to a slight decrease in the integration of good news relative to the control. A closer examination of the actual ratio values of the Experiment 2 individuals as shown in the Figures gives a wide distribution of values and therefore when value deviation is considered then there is probably no difference. In the case of the updating of bad news, then the integration parameter ratio for Experiment 1 and the students rose by a definitive 35% when they were in the threat situation and this correlated to the higher physiological levels of stress observed. Therefore, the higher the level of stress then the higher the information integration parameter observed. This was also observed in Experiment 2 with fire-fighters reporting increased anxiety correlating to increased updating of bad or negative (undesirable) news.

Therefore, the results made by the authors of the article appear to be correct even if the experimental set-up is not ideal. However, Garrett and colleagues interpret their results by saying that anxiety/stress/threat decreases the biasness of updating information for good news so that there is greater updating of bad news. Maybe a better way of interpreting the results is by avoiding the use of the word ´bias` which implies that one type of information is preferred to another. The results of Garrett and team`s experiments show that this is actually not the case since the level of updating of good news remains roughly the same for both control and threat condition. On the other hand there is a definite increase in the updating of bad news in the threat situation for the students of Experiment 1 and for the fire-fighters of Experiment 2 when reported anxiety levels are high. Therefore, the questions that have to be answered are; why updating good news is one level and updating bad news is another level in the case of the younger students (Experiment 1) in normal circumstances; why anxiety/stress increases the level of updating of bad news by participants of both experiments; and whether the difference in results of the younger students and the older firefighters reflects cognitive changes associated with age, or not.

   We begin by looking at why the updating of good news is one level and the updating of bad news is another level in the case of the younger students  under normal circumstances (Experiment 1). The first question is whether there is a difference in cognitive systems and neurochemical mechanisms relative to the value of the information. The value of information stems from its emotional worth which is individual in amount, but relies on the common balanced neurochemical systems attributed to the emotions of pleasure and fear. In summary, pleasure (positive values) can be associated with the dopaminergic systems of the higher brain and relies on the level of activity and interconnectivity of brain areas such as prefrontal cortex, striatum and nucleus accumbens and fear (negative values) is associated with the noradrenergic systems of the higher brain and activity and interconnectivity of brain areas such as the prefrontal cortex, cingulate cortex and amygdala. For each informational unit, an ´emotional tag` can be assumed to be attached to the neural representation and therefore, we build up our own personal data base of information stored in the form of memories in the higher cortical areas plus an additional piece of information corresponding to our own individual emotional worth of that information. This tag consists of a graded ´like/pleasure` value or a single ´dislike/fear` value. Research has shown that these memories of pleasure and fear are encoded and stored in the same part of brain (the ventromedial prefrontal cortex, vmpfc) but are stored along separate paths (Gross) with a ventral versus dorsal topographical organisation (McNamee). The areas are then linked to different brain regions.

Although we can see that the vmpfc (or orbitofrontal cortex, ofc) links informational events to reward values (Favonik, Winecoff) and represents contexts that guide memory retrieval , other brain areas also appear to be involved in this emotional worth system. These include the ventral striatum where phasic dopamine levels appear to be involved in the assignment of value to stimuli in this area (Wieland) plus areas such as the basilar lateral amygdala, the insular cortex, superior temporal gyrus and anterior cingulate cortex (acc). The acc has been found to be essential for the learning of the value of actions (Kimmerley) and encoding competitive effort which is important in cost-benefit type decision-making (Hillamn).  Connectivity between areas also appears to be important for encoding, eg. between the temporal cortical junction and dorsal lateral pfc for utilitarian appraisals (Hutchenson). The activity and connectivity of brain areas also appears to be important for the retrieval of values. For example, the insular cortex is important for the retrieval of guide choices (Parkes) and also with connectivity to the nucleus accumbens plays a role in mediating the retrieval of outcome values and the subsequent choice between goal-directed actions. The connectivity between the ofc and the basilar lateral amygdala also appears to take part in the decision-making process where appropriate assessment of reward value influences choices made (Zeeb, Rhodes). We can assume that since no differences were seen with good news and bad news that values attributed to these events were formed by the same neurochemical mechanisms and pathways in all participants and therefore, it is unlikely that the differences observed between levels of updating for the good news and bad news did not occur because of different neurochemical systems alone.

The possibility also has to be considered that it is the updating mechanism itself that may be different between updating good news and bad news, but again like the encoding and retrieval mechanisms of values it is unlikely that this is the case. Updating implies that what is expected is not received or additional information is added and this can apply to both information and emotional worth. Research has shown that neuronal firing relating to emotions can show emotional conflict earlier than cognitive conflict and that emotional conflict processing is also modulated by top-down attention like the cognitive conflict (Zhou). Again the ofc and acc appear to be involved in the updating process. The ofc has been reported not only to regulate emotion and enhance behavioural flexibility (Rudebeck) through inhibitory control, but also to regulate the updating valuations on the basis of current motivational states. The acc also appears to play a role with the dorsal area linked to expectancy and the ventral region with the unexpected (Somerville).

Areas linked to working memory are also required for the correct updating of information irrespective of value and this is one area where individual differences may provide an explanation to the variations seen between the participants of Garrett and team`s experiments . Processing of information with the selection and updating process is said to require attention (Blauriske) and this has been linked to alpha brain wave activity centred between the relevant areas (Manza). It also appears to be linked to cognitive load and therefore, the efficiency of the attentional system, working memory and hence, individual level of load may reflect differences between individuals. In the case of the alpha brain wave connectivity, it has been shown that neural oscillations in the alpha brain wave band play an important role in inhibiting incoming distracting information during tasks and that the amplitude of the brain waves varied with memory maintenance and updating demands (Manza). A greater brain wave amplitude was associated with high load of relevant material and the difference was correlated with performance accuracy. There were no significant effects in relation to irrelevant load. This was supported by work by Gorgoraptis who showed that updating precision for sequential objects decreased with increasing working memory load. Load was also associated with working memory performance when the connectivity of the pfc and parietal cortex was considered. It was found that the lateral pfc and posterior parietal cortex of high-capacity individuals was more densely connected compared with low-capacity individuals (Ekman). This connectivity was required to maintain and update working memory items and it was predictive of working memory capacity in relation to updating. Therefore, attention and working memory capacities may be areas which contribute to individual performance levels, but the differences are unlikely to be the cause of the variations between the updating levels of good and bad news.

Therefore, if there is no reasonable neurochemical reason why there bad news is not updated to the same level as good news under normal conditions, we must consider the problem from a psychological perspective and here, there may be a possible explanation. Updating is important because as the authors said, the recall and comparison of information plus value are the core processes involved in decision-making and action or future action taken. The value systems of those participants in Experiment 1 appear to be geared to positive, favourable news when they are under no stress, ie. participants with an average age of 25 appear to take in new information when it is good, but ignore it when it is bad. A possible explanation for this is that the examples of bad news given in the experiment were disregarded since they were deemed: not applicable to students eg. mortgage rate increase not applicable to people who are not house-owners, pension income for people who are 40 years from their retirement date; were unlikely to happen eg. street mugging in an area with low crime rate, fire in an all-electric house; or were examples of things that the participants themselves could not alter eg. increased tax rate, diesel car ban. This explanation is supported in some way by work by Fetsch who showed that people weighted each cue in their experiments in proportion to its reliability with more weight associated with the more reliable cue. Neural activity in the dorsal medial superior temporal area was found to be closely related to the observed weighting. The work by Fetsch and colleagues showed an example of where statistical inference correlated to event value and therefore, it is possible that such a weighting is also shown in Garrett and team`s experiments where the value of bad news is ´rated` as less appropriate to the participant of Experiment 1 than good news and is therefore, ´dismissed` as unworthy of updating pre-established beliefs.

Another possible explanation from a psychological perspective is the preference of good news so that the person remains positive from an emotional status perspective. It is known that a positive system is more geared to increased well-being, increased exploration and increased motivation. Indeed as Friedrickson hypothesised positive states of mind lead to increased cognitive skills and expand the boundaries of experience allowing the person to take in more information and it has also been shown that attentional system and working memory system both work more efficiently when the person is in a more positive emotional state. Therefore, in order to maintain the positivity, the bad news being presented could be actively avoided. Therefore, the information may be inputted but it is not learnt. (It should be noted that the decision-making method does not change whether the bad news is considered irrelevant/not appropriate or avoided simply because of the desire to remain in a positive frame of mind. In both cases the decision-making methods give the person, his/her wellbeing and wishes priority and hence, a number of decision strategies are possible eg. consequence and sequel, comparison relative to personal goals, and plus and minus points. It is only the informational input which is affected.) There are several pieces of evidence that suggest that this is a possible explanation. For example work by Gupta showed that when having to learn a string of letters, participants when shown a face and told to identify if that face was happy or sad performed the task to the same level independent of load if the face was happy, but learning performance was worse when the load was high. Also Storbeck found that emotions promoted cognitive tendencies that were goal incompatible with task demands and therefore, greater cognitive effort was required to perform well.  And Cohen and colleagues found that emotion and executive control was modulated by how the emotional information was processed. They found that explicit processing of the emotional content of pictures resulted in emotional interference for congruent, but not incongruent stimuli. However, implicit processing where responses to emotional and non-emotional content occurred resulted in emotional interference for both congruent and incongruent stimuli. Their findings indicated that explicit emotional processing of emotional pictures led to reduced emotional interference because of the recruitment of executive control whereas implicit emotional processing affected performance independently of any executive control.

Therefore, with relevance to the experiments described here then the emotional worth of the option (ie. the news item) would lead to the recruitment of executive control which would lead to bad news being disregarded in order to maintain the cognitive performance level.  The training sessions and the number of items considered in each test would reinforce this standard as indicated by Hickey. Hickey showed that in reinforcement learning theory and approach behaviour reward can increase the perceived value of incoming information to ensure that potential predictors of outcome are favoured in the future. They found that high-magnitude reward feedback boosted the lingering representation of target categories (in this case good news) while reducing the representation of non-target categories (ie. the bad news). Such an accreditation system caused the visual system to become sensitized for similar objects in future encounters and was found to involve the brain`s dopaminergic midbrain region. In the experiments of Garrett and team, it is likely that the value system would place a priority on the good news items and so updating of bad news would be less favoured.

Therefore, we have given above possible explanations why good news is favourably updated and the updating of bad news is less favoured under normal circumstances by the participants of Experiment 1 and this may be against what we would normally think ie. I am more likely to remember something that is negative or bad. And this is indeed proven to be the case in both Experiment 1 and Experiment 2 where it was shown that there was a high level of updating relating to bad news when the participants were under higher levels of stress/anxiety. This is likely to be due to a number of reasons. Even in anxiety/ stress situations the value of updating information is linked to decision-making and taking action whether now or in the future. The decision-making strategies employed in the Garrett and team`s experiments do not change ie. the person still places priority on his own wellbeing and wishes. However, the negative emotional state changes the activity and connectivity of the brain areas involved in that decision-making process. In anxiety and stress situations, the dominant emotional system is fear –based and the brain is under the influence of the noradrenaline system and activity of brain areas such as the anterior cingulate cortex and amygdala. The attentional system also shows a change in focus when under stress conditions with information volume being increased, but quality of that information decreased via more ´gist` content rather than details. There is also a negative impact on the working memory system with a reported impairment of verbal working memory (Storbeck) which would influence decision-making capability. Through the change to the emotional status and emotional responses, fear/stress/anxiety also has an impact on our value system and our approach to reward and risk. Stress is reported to lead to bias towards larger rewards, an effect blocked by the inactivation of the amygdala (Graham). Lenow and colleagues found in their experiments regarding foraging-like decisions that both acute and chronic stress leads to a biasness in decision-making towards the over-exploitation of current options relative to those that would be optimal ie. there is an increase in risk or and a reduction in motivation related to reward. Engelmann and team supported this since they found that in cases of high incidental anxiety the activities in the vmpfc and ventral striatum showed a decrease in the neural coding of the expected subjective value of risky options and there was decreased connectivity with other areas of the valuation system. They also found that activity in the anterior insular cortex increased the neural coding of negative expected subjective values for risky options and this neural activity predicted whether the risky options would be rejected. Lenow and colleagues concluded from their results that anxiety appears to shift the focus of neural valuation from possible positive consequences to anticipated negative consequences of choice options and proposed that this could explain why anxiety may lead to the development of chronic reward desensitization and a maladaptive focus on negative cognitive behaviour seen in affective and anxiety disorders.

So how can these observations relating to value and risk be related to the results observed by Garrett and colleagues in their experiments? Garrett and team showed that according to the value systems of their participants, anxiety/stress increased the value or worth of the bad news so that instead of being dismissed or ignored at the level of input or processing, the information received was processed and memories and beliefs updated to reflect the information provided. This is in accordance with the Graham and Lenow in that in order to take riskier options then the information must be received, processed and active decisions made to choose the option in preference to the safer alternative. Therefore, the ´safe option` would correlate to Garrett`s ´good news` and the ´bad news` would correlate to the ´riskier` option. Since the fear system is then dominant there would be a shift to negative information and elements of risk in order to remedy the current threat situation.

Before we conclude this comment, one factor has to be considered with relation to the experiments carried out by Garrett and colleagues and that is whether an age difference in updating was demonstrated. It appears that for good news there was no difference. However, in the case of the bad news, the younger participants of Experiment 1 produced a 35% increase in updating of this type of information in a threat situation, but there was a bigger increase observed in Experiment 2 where the participants` average age was higher. This may suggest that for bad news there is age difference in updating capability. There are several reports on cognitive changes associated with increasing age. Decreases in working memory and attentional capability because of neurochemical changes have been reported for the elderly. However,  the average age of the participants of Experiment 2 was only 45 which would not qualify them for this definition. Again, the question of value system comes into play and the influence of the emotional status. The positivity effect was described by Mather and colleagues which says that older adults allocate more attention to and are better able to memorize positive emotional material than negative stimuli. This may be associated with neurochemical changes such as lower activity in the right insular cortex associated with risk avoidance and weaker and less extensive striatal activation and from the behavioural perspective, an increased number of trials for learning the association between stimuli and reward. Also, Goh found that ageing could cause in some individuals changes in the frontal, striatal and medial temporal areas of the reward system which hindered the accurate assessment of value as well as feedback processing in the decision-making process. They found that some older participants made less optimal decisions preferring riskier options and this correlated to connectivity of the frontal, striatal, and medial temporal areas with people who avoided risk showing increased neural responses when options became more desirable and risk-takers the opposite. Goh also found in a separate study that ageing appeared to preserve gain anticipation which was associated with nucleus accumbens activity, but reduced loss anticipation which was said to be associated with anterior insula cortex activity. Older adults were also shown to have decreased reward learning, which could be related to lower nucleus accumbens responsiveness to non-received reward expectations in addition to observed decreased connectivity between the medial pfc and nucleus accumbens. However, the effect of ageing on decision-making may not be so clear cut with some researchers reporting that the preference for safer choices may be task dependent (Lee, Zamarian). Therefore, although ageing may have an effect on neuronal systems, emotional assessment and behaviour at some stage, we have to conclude that it should not be considered a factor in Garrett and team`s experiments because the average age of the participants in Experiment 1 was only 25 and for Experiment 2 45, neither of which could be considered to be in the risk category.

Therefore, we can conclude that the experiments of Garrett and colleagues show that the association between the value placed on presented information and memory updating performance can be affected by emotional status at the time of learning. The difference in the levels of updating of memories and established ideas with either good news, or undesirable or ´bad` news appear to disappear when the person is in a threat situation. From an experimental point of view, Garrett and colleagues set-up may not be ideal since the participants of the two experiments had a definitive age difference and one group was subjected to a psychological threat situation and the other to long-term physiological stress/threat situations. Also the word ´bias` used by the authors to describe the difference in updating levels may not be the best description of what is going on since the updating level of good news remains the same and it is only the updating of bad news which increases in the threat situation. A cursory look at the biochemical mechanisms and activities and connectivity of the brain areas involved in order to explain such a difference in levels shows that the decision-making process and updating process systems appear unaffected by the news content. Attentional system and working memory system levels may reflect individual performances. However, the value placed on the news items through the application of the emotional systems for positive/pleasure and fear/anxiety appear to play a role in why the news items have differing levels of updating. The updating of good news appears to be unaffected by emotional state, but bad news for the applicants of Experiment 1 was suggested as being ignored or dismissed because of a variety of personal reasons such as lack of appropriateness and low interest. These opinions were changed when the emotional status of the participants heightened because of the perceived threat situation. In this state the fear system caused neurochemical changes that altered how the information was perceived and hence, the level of updating of the bad news was increased. This was expected in Garrett and colleagues experiments and was expected in general according to how we think memory mechanisms are influenced by emotional status. What is interesting from the experiments of Garrett and colleagues is that it shows that there is clear difference in memory performance in relation to informational content. Such a finding can for example influence how experiments of this type are set-up in future since just by changing the nature of the task or the type of information we can alter performance and maybe resulting conclusions, and on a more general level rephrasing of statements may aid memory efficiency and may be a useful technique to increase memory capability in those suffering from reduced memory capacity.

Since we´re talking about the topic………………..

……Rutledge and colleagues in their experiments on decision making showed that by boosting dopamine levels the number of risky options chosen in trials involving potential gains increased, but not trials involving potential losses. Can we assume that if Garrett and team`s experiments were repeated after the administration of L-dopa (which would increase the level of dopamine), positive changes in the updating of the bad news items would also be observed even in the control situation?

…….Robinaugh and colleagues showed that depressed adults demonstrated a biasness towards the retention of negative information in working memory. The team developed a task designed to modify this cognitive bias by having subjects repeatedly practice removing negative words from their working memory, hence enabling them to retain positive and neutral words. If the experiments of Garrett and team were repeated but the bad news items were rephrased using positive words (ie. a type of ´glass half full not half empty` approach) would a positive change in the level of updating of the former bad news items be observed?

…..can we assume that the administration of anti-anxiety medication would result in the abolishment of the threat situation for the relevant participants and a positive change in vmpfc activity and connectivity (according to Amat, Carpenter) would result leading to positive changes in working memory performance and level of bad news updating?

Posted in ageing, anxiety, emotions, fear learning, learning, memory recall, prefrontal cortex, Uncategorized, values | Tagged , , , , , , ,

hippocampus firing defines event boundaries in continuous experiences

Posted comment on ´The hippocampal film editor: sensitivity and specificity to event boundaries in continuous experience`  by A.B. Yakov and R.N. Henson and published in Journal of Neuroscience 2018 vol 38 (47) p. 10057 doi.org/10.1523/JNEUROSCI.0524-18.2018

SUMMARY

Yakov and Henson in their article described the results of their investigation into hippocampal functioning during continuous sensory experiences. The authors hypothesised that the hippocampus would be sensitive to event boundaries which they defined as the moments in time between sensory events and their experiments confirmed this.

The experiments carried out involved two groups of subjects: one large group of 131 females who viewed an 8.5 minute long film (an abridged version of a Hitchcock film) that was compelling and unfamiliar to them (termed the Cam-CAN study) and a smaller group of 16 females who watched a familiar 120 minute long film (´Forrest Gump`) which was divided into 8 segments of  15 minutes (termed Studyforrest). (Eight participants watched this film in German, their native language and 8 watched it in English and dubbed in German. However, a lack of difference in results of the two language groups meant that the results were combined.) Film segmentation was achieved by the participants pressing a key when they felt that one event (termed the meaningful unit) ended and another began. A reaction time of 0.9 seconds was subtracted from the logged key press times. If more than 5 different observers marked boundaries within approx. 2 secs of each other (termed 1 TR) the period was treated as a single boundary. In the Cam-CAN study 19 boundaries were identified separated by 6.5 to 93.7 seconds. The observed boundaries were divided into 3 levels according to the number of observers that identified them (the salience). There were 7 low salience events (5-6 observers), 5 medium (7-12) and 7 high (13-16 observers). In the Studyforrest 161 boundaries were defined and these were separated by 4.9 to 167.7 seconds with 60 low, 43 medium and 54 high salient values.

The neuronal functioning of the hippocampus was assessed using functional MRI. The imaging conditions (eg. type of scanner, TR length, axial thickness) were slightly different for the two studies, but considered comparable. Regions of Interest (ROIs) included the anterior and posterior hippocampus where the end results were averaged, the visual cortex V1, auditory cortex and angular gyrus (AG). The AG was included in Yakov and Henson`s experiments because other researchers had reported a change in activity patterns in this area which appeared to correspond to event boundaries. Data from the imaging was pre-processed for the purpose of correlation and then various statistical analyses were performed to determine significance. Various other analyses were performed relating to event boundary characteristics such as isLoc/isTemp (shift in location/time), visDist (visual distance between frames immediately preceding and frames immediately following a boundary), visCorr (visual correlation between frames immediately preceding and frames immediately following a boundary), visHistDist (distance between the colour histograms of the frames before and after a boundary), lumdist (difference in overall luminance before and after a boundary), DCNN (the correlation between the layers of a deep neural net run on the frames before and after a boundary), psdCorr (correlation of the power spectral density before and after a boundary as a measure of auditory similarity), psdDist (the distance of the PSD across a boundary), absVolDist (absolute difference in volume across a boundary), V1 and A1 betas (average V1/A1 response across participants to each event) and isAG (binary predictor indicating whether a boundary coincided with a pattern shift in the AG). Therefore, the role of hippocampal activity during continuous experience was assessed for both sensitivity (the hypothesis-driven approach via examining hippocampal response at event boundaries defined by the observers) and specificity (the data-driven approach involving the identification of hippocampal events based on the amplitude of the hippocampal firing response and by testing the overlap between these events and subjective boundaries).

Yakov and Henson found from their experiments using film watching to simulate continuous experience that there was a strong hippocampal response at event boundaries for both film watching studies. This was determined by an overall higher response when a larger number of observers marked the event boundary (ie. high salience). For the Cam-CAN study, the size of the response was small, but was still significant. The authors continued their investigation by looking at the effect of various predictors such as shifts in time, location and sound for example between one event and the boundary and the following event. They found that if all the predictors were added together then the results were not significant, but when each predictor was added to the model separately then both the number of observers in total (termed nObservers) and the number of observers of each group reflecting salience of high/medium/low values remained significant. Most event boundaries were found to be characterised by a change in location such as that determined by the predictor isLocTemp and the authors found that the predictor and nObservers results were highly dependent and therefore, their relative contributions could not be dissociated. Therefore, it was concluded that no definitive statement could be made about whether modulation by boundary salience could be accounted for by other perceptual factors such as spatial and temporal change.

The results obtained for the Studyforrest differed slightly from the Cam-CAN study in that an increase in boundary salience was observed, but unlike the shorter film study the value remained significant even if the predictors were added together or considered separately. This included the predictors for spatial and temporal changes. The authors therefore, concluded that in both studies that the hippocampus was sensitive to boundary salience and to the number of observers who reported the event shifts. The difference between studies was attributed to the Studyforrest being longer and having an increased number of event boundaries which then made the assessment of the relative contributions of various additional drivers easier. Therefore, it was found that although changes in visual/auditory contributions or location and time occur and modulate hippocampal activity they did not account for its sensitivity to boundary salience. The modulation of hippocampal response by boundary salience was concluded to be sensitive to other factors.

Yakov and Henson continued their investigation by looking at the effect of AG activity on the hippocampus since it had been suggested by other researchers that a possible hypothesis for the increase in hippocampal activity at event boundaries was that event boundaries elsewhere in the brain cause cortical pattern shifts which have an effect on hippocampal activity. In their experiments, Yakov and Henson found that there was an increased hippocampal response to overall AG pattern shifts, but this increase was only found for AG pattern shifts that matched event boundaries. Therefore, they concluded that both AG pattern shifts and increased hippocampal activity are driven by event boundaries rather than patterns of AG activity changes and hippocampal activity being directed related. Other brain areas were also investigated for this type of effect on hippocampal activity. 55 ROIs were tested in total by the authors, but only 5 produced possible correlational event boundary firing and these were the hippocampus, the posterior cingulate cortex, precuneus, posterior parahippocampal cortex and lingual gyrus. Further analysis however showed  that only the hippocampus and posterior cingulate cortex results remained significant when adding in the perceptual and objective shift predictors or by testing with the nObserver analysis condition.  Yakov and Henson also tested for the specificity of event boundaries and found significant results with 58% of hippocampal events matching predefined boundaries in the Cam-CAN study and 38% in the longer Studyforrest.

Therefore, the authors concluded that event boundaries play a key role in shaping activity during the neuronal encoding of continuous experiences. The hippocampus was an area of interest since it was found to be sensitive to event boundaries. Yakov and Henson found in their experiments that there was an increase in hippocampal activity relating to event boundaries and this correlated to boundary salience. It did not however, appear to reflect the differences in the degree of perceptual change since changes in factors such as visual information, auditory change, time, location did not produce significant changes to the observed event boundaries. The increase in hippocampal activity was also found to coincide with shifts in cortical patterns observed with the AG where also event boundaries had been identified with continuous experience. Therefore, it was concluded that event boundaries and not shifts in cortical firing patterns per se drive hippocampal activity. This observation was also recorded for the brain area, posterior cingulate cortex.

COMMENT

What makes Yakov and Henson`s article so interesting is that gives information about a neural event that is normally not considered ´an event` and by doing so elucidates further the role of one particular brain area, the hippocampus in sequence memory (or continual experience).  What we mean by ´a neural event not normally considered as an event` is that in the case of sensory input relating to an external event we normally concentrate on neuronal activity linked to characteristics of that event such as visual and auditory information and even personal emotional worth. This information is all bound together in a period of synchronised firing in the different relevant brain areas and is stabilised to form a neural representation of the external perceived event. Yakov and Henson have shown with their experiments that this indeed goes on and we are well aware that this synchronised activity and neural representation is extremely important for cognitive capability such as in the stages of perception, memory, decision-making and behaviour for example.  But, what Yakov and Henson claim to have done in their experiments is to look at what happens to neuronal firing when one external event ends and another begins which is a natural occurrence in continuous experiences (or sequences). These ´periods` are termed event boundaries and they are said to correspond to the shift, the break or the interval between one event and the next. In Yakov and Henson`s experiments these event boundaries were identified by their participants being aware of a change in external events and reporting it to a third party (hypothesis-driven approach) and the neuronal firing responses in the hippocampus measured using fMRI (data-driven approach). Yakov and Henson reported that these two events occurred simultaneously and that hippocampus firing modulated strongly with the identified event boundaries.

It is unlikely that this is a true reflection of what is occurring at this time and to explain why we have to look at how information is inputted from external event sequences or continual experiences. If we consider the initial event of a sequence (Event 1), information about that event is inputted via the sensory pathways and ends up activating cells in the higher brain areas where the information is processed (working memory) and identified (perception, object recognition) or simply stored short-term. In this case, the hippocampus acts as a relay of information sending it on its way to the higher brain areas  or providing conditions via its connectivity to the adjoining entorhinal cortex, parahippocampal cortex and rhinal cortex areas and its own complex physiological structure to allow information binding and sustained firing to occur. There is likely to be conscious awareness to begin with plus functioning attentional and working memory systems. At the higher brain areas a neural representation of this Event 1 would be formed from the synchronised firing at that time all bound together in one active unit. The next event in the sequence would also present with incoming information and again the information would be relayed via the hippocampus to the higher brain areas or directly to them via the thalamus. However, since many of the elements would be the same as those of the initial event it is likely that this information is not treated as a separate entity but as a continuation of Event 1. This means that it is likely that the matching active cells as part of the Event 1 neural representation would continue to fire with their firing strengthened by this continuation and the novel information which would be the subsequent changes, are added to it in order in the form of complementary representations.  (The continual repetition of the unchanged elements of the event means that the conditions required for memory formation such as constant firing are fulfilled.) This process would continue for all incoming information where the majority of characteristics of the initial representation remain. With reference to Yakov and Henson`s experiment this would refer to the time from onset to the end of the first event.

What happens when the external event massively changes as in change of film topic if we relate it to Yakov and Henson`s experiments? If we consider it only from the point of neurochemical firing at this point, we can see that there is a huge change in characteristics of the neural representation for the elements of this Event 2. The hippocampus again relays the incoming information to the higher areas or provides the conditions via its connectivity to the surrounding entorhinal cortex, parahippocampal cortex areas and its own complex physiological structure to allow binding and sustained firing to occur. Again a neural representation of this Event 2 would be formed from the synchronised firing at that time in the higher brain areas. However, the expected continued firing of the already present representation (Event 1 plus changes) would not occur and this would then begin to die out with the stronger representation of Event 2 taking its place. It is unlikely that an ´error signal` is instigated at this time by the higher brain areas as seen with conditioning experiments and unexpected reward because no stored representations exist to which the input can be compared. However, the formation of multiple competing representations would bring about changes in attentional systems, working memory (leading to updating) and more importantly with relation to Yakov and Henson`s experiments, conscious awareness. This change in awareness would be the point when the experiment`s participants would be aware of a change in topic and would report the change to the third party (ie. the subjective event boundary, hypothesis-driven approach).

So, here as we can see we have a slight problem in the so-called simultaneous event boundary as indicated by the participants and the hippocampal response as indicated by the fMRI (data-driven approach). If the above description of event elements and neural representation is correct for sequences then the subjective recognition of the event boundary should come after the change in neuronal firing representing the shift from Event 1 to Event 2. That is, a person can only know that something is changed after it has happened in real-time. Therefore, the subjective event boundaries would be later than the neuronal firing responses.

This leads to the question as to what the observed modulation of hippocampal firing actually represents. It is likely that the hippocampal firing observed at so-called event boundaries is likely to represent the multiple representations present at the time shortly after event shift. That is, it would represent the dying out activation from the input relating to the previous topic and the growing stronger activation of the novel topic. These would counteract one another so that strong modulation of firing would on average be seen. Any attempt to separate the images would need extremely accurate and small scale neural imaging techniques that may not be available at this time. This is supported by Yakov and Henson who demonstrated that changes in predictors such as location produced no significant effects on firing. The shared event boundaries observed between the hippocampus, AG and post-cingulate cortex (PCC) observed by the authors can be explained by considering the conscious experience. They probably represent the roles of the AG and PCC in conscious awareness with AG known to be linked to linking the SELF with episodic memories and PCC with the DMN and are independent of event content, but are dependent on shared timing also with the hippocampus and other cortical areas.

Therefore, in conclusion Yakov and Henson`s experiments have added to the limited knowledge we have about sequence memory by reaffirming that the hippocampus acts as a neuronal firing relay station in this type of memory in the same way it does with single events. It is likely that it can hold multiple items simultaneously albeit at different strengths and this is logical if we consider that we can simultaneously input and process information consciously and unconsciously. The area`s connectivity with other brain areas allows information to be processed, perceived, remembered or used according to the demands placed upon it and modulation of it whether structurally or through other areas functional connectivity can have wide-ranging cognitive effects. Therefore, it remains an area of great importance and great interest.

Since we`re talking about the topic………………………………..

……….Yakov and Henson`s experiments featured real events pictured on a screen. Can we assume that an imagined sequence of events instigated through auditory commands would produce the same effects on other brain areas, but the input relay system of the hippocampus would not show event boundary activation?

…….certain factors can upset the synchronisation between brain areas such as jet lag, endocannabinoid agonists. Is it likely that such factors would also disrupt the subjective and objective event boundaries observed in the hippocampus especially since this area is known to be affected?

…..sensitivity to time is reported with things like caffeine (increased arousal leading to a longer perceived duration) and mindful meditation (increased sensitivity to time and a lengthening of time). If the experiments of Yakov and Henson were repeated would a change in event boundary similarity between participants be observed and can we assume that individual event boundaries would still relate to strong hippocampal firing modulation?

Posted in binding, hippocampus, input memory, neuronal firing, sequences, Uncategorized | Tagged , , , ,

role of angular gyrus in autobiographical memory and the Self

Posted comment on ´Specifying a causal role for angular gyrus in autobiographical memory` by H.M. Bonnici, L.G. Cheke, D.A.E. Green, T.H.M.B. FitzGerald and J.S. Simons and published in Journal of Neuroscience 2018 vol 38 (49) p. 10438 doi.org/10.1523/JNEUROSCI.1239-18.2018

SUMMARY

In their investigation, Bonnici and colleagues investigated the role of the parietal cortical area, angular gyrus (AG), in brain memory. Studies carried out by others show that dysfunction of this particular area does not lead to amnesia, but impairs aspects of episodic memory and hypotheses have been developed in relation to how this occurs. These include the reduced ability of memories to capture attention spontaneously, or the reduced ability of subject to ´re-live` personal events.  Inconsistencies in the different study results exist with some finding that parietal lobe lesions lead to deficits in free recall of autobiographical events, but not with cued recall and others showing that the inhibitory stimulation of AG has no effect on free or cued recall. Bonnici and colleagues therefore sought to resolve the conflict in opinion.

Twenty-two healthy individuals aged 19-35 were used in the authors` experiments. The subjects were subjected to continuous theta burst stimulation (cTBS) of the left AG and a control vertex location and memory tests of free and cued recall of autobiographical memories and word pairs were carried out. Testing of the two conditions was one week apart for all individuals and each session was structured to begin with the autobiographical memory gathering phase (AM) leading on to a  study phase for the word pairs task, the cTBS procedure, the autobiographical memory recall phase and the word pairs test phase. For testing of autobiographical memory function, the authors used the modified version of the Autobiographical Interview test where each participant had to name 5 personal significant events from four life periods.  Recall was free and cued after the stimulation and scored according to the number and type of details each recollection contained. For the testing of word pair memory performance, subjects were presented both audibly and visually to 2 sets of 64 noun pairs.The participants had to create a sentence within 10 seconds that contained both words and say it aloud. Free recall meant participants had to remember as many words as they could within 2 minutes and cued recall meant that participants were presented randomly with 1 word out of the pair and had 3 seconds to remember the second. The cTBS procedure consisted of 3 pulses at 50Hz every 200msec for 40secs at 70% of the participants motor threshold and was aimed at the AG or at a vertex centre both of which were determined by the neuronavigation system, Brainsight.

The results obtained showed a selective reduction in free recall of autobiographical memories after cTBS of the AG and this manifested as fewer details recorded. Further examination showed that the effect centred around fewer internal details with no differences in the production of external details. Cued recall brought about no reduction in remembering the personal events after cTBS of the AG and therefore, it was concluded that the cTBS of the AG affected the production of relevant details.

Bonnici and team performed experimentation to further explore the nature of the details that were lacking. They found that subjects reported fewer autobiographical episodes from a first-person perspective after cTBS of the AG and therefore, concluded that the AG enables the subjective experience of remembering by integrating memory features within an egocentric framework. This result supported work carried out by others on patients with parietal lesions who were found to be impaired where egocentric spatial navigation tasks were concerned, but not with map-based spatial tasks that were sensitive to hippocampal damage (ie. reliant on the memory of facts).

The results of the word pair memory experiments were clear-cut. It was assumed that a greater impairment of free recall of word pairs than cued would indicate an effect on attentional processes whereas a greater impairment of source recollection confidence than accuracy would be consistent with the subjective experience view. The authors found that subjects produced significantly fewer word pair responses in free recall than cued independent of the stimulation condition. This was suggested to be due to the highly demanding nature of the task on the attentional processes rather than the effect of the stimulation of the AG. Therefore, it was said that the results indicated no effect of AG stimulation on word pair memory which supported the work of others.

Bonnici and colleagues concluded that their experiments supported the view that the AG is part of the network of brain areas responsible for episodic recollection. Their experiments were designed to try to resolve the dispute in observations between parietal damage and cTBS of AG on memory function. They found that because of the differences observed in the results obtained between the autobiographical memory and word pair memory tests after AG stimulation that the AG played a role in autobiographical memory, but not word pair memory. In addition, Bonnici and colleagues concluded that the AG plays a role in the integration of memory features within an egocentric framework forming a representation from the first-person perspective so that a person can remember events subjectively from their own past. Their results support the subjective-experience account of AG function. The findings are less indicative of the so-called attention-to-memory hypothesis since the memory deficits appeared to be related to internal words than external words, deficits were in first-person perspective events and there was a lack of effect on word pair recall. Therefore, Bonnici and colleagues concluded that the AG plays a role in the subjective experience of remembering.

COMMENT

What makes this article so interesting is that it explores further the neurochemical basis of the ´Self` or what makes up the concept of ´Me, Myself, I`. Normally we look at the Self from the point of view of consciousness, but if look at it relating to information processing and memory for example we can see that the concept of the Self from this first-person perspective can actually involve functioning of different brain areas. What we mean by this and what is shown by the work of Bonnici and colleagues is that ´I` referring to my real-time conscious experience which includes awareness of my surroundings, my feelings, physiological status (eg. breathing rate) is brought about by activities in multiple brain areas (eg. medial prefrontal cortex, insular cortex and anterior cingulate cortex), but these may vary from those that are active when we consider for example the awareness and role of  ´Me` in the recalled events from my past. In this case the memories reactivated indicate events and characteristics that apply to ´Me` or are relevant to ´Me` and Bonnici and colleagues have shown that this first-person perspective involves the functioning of the parietal brain area, the angular gyrus (AG). This idea is not new in that consciousness theorists have long proposed the concepts of proto-Self (neural patterns mapping the state of the being moment to moment), core-Self (the transient entity re-created for each object to which the brain interacts) and autobiographical-Self (involving learning and recall of memories). We assume from the work of Bonnici and colleagues that the AG is involved in the autobiographical-Self part.

So, what can we say about the role of AG in autobiographical memory and how this area provides the awareness of personal involvement in recalled events? The AG sits in the parietal cortex and is in a strategic neural location for processing speech, touch, auditory and visual information. Therefore, the information that we deem as necessary for the definition of ´Me` such as what do I see, what do I hear, how can I tell others what I see and hear require activity of this AG area. Extending this idea the AG has been found to provide the salience of spatial features in attention and even the ability to infer intention in decision-making tasks. These roles appear to be subtleties of systems taking place elsewhere. For example, emotional content and assessment of value is undertaken by the medial prefrontal cortex areas and striatum for example and attention the parietal and prefrontal areas amongst others. Therefore, the neuronal networking required to fulfil these capabilities do not include the AG, but activity of the AG means that a personal ´I, Me` perspective is acquired. This is achieved through two characteristics of AG functioning: the first is, as said above, that AG functioning collaborates in the recall of autobiographical memories to bind ´Me` to that recall; and the second is that the activity of the area is associated with speech and the processing of language.

With regards to the first, the recall of autobiographical memories occurs under the same conditions as recall of third-person memories and both sets of memories are stored in the appropriate cortical areas. Reactivation of the memories also initiates the recall of emotional feelings (´emotional tags`) and values that may be associated with them whether they apply to the person or to another. The application of the first-person perspective appears to give distinctive qualities to the memories envisaged in that there is a ´detachment` between ´I`, the now, conscious first-person and this applied ´Me` perspective. This is supported by the observation that when recalling autobiographical memories we appear to experience them from the third-person perspective, detaching ourselves from the fact that we actually did the action, or experienced the event. Also on reflection we rate the past as ´inferior` to now even though the event may be the same, or the past event provided more pleasure than the same contemporary one, and pain cannot be re-experienced on recall of a painful event only the description of it. Therefore, the quality of the Self applied to autobiographical memories is different to the conscious awareness of the Self in real-time experiences and it appears that the AG is required for the first, but not the second. This capability of having two separate areas (or groups of areas) allows the two ´I`s to function at the same time. For example, there can be real-time awareness of heart-rate, incoming visual information for example as well as recall of autobiographical memories in the pursuit of a solution to a problem for example. However, only one will have conscious awareness at any one time although switching is possible just like in the case of divided attention. The ability to ´detach` the first-person perspective from memories from real-time first-person experience is also an advantage in certain cognitive functions such as decision-making since it allows decisions to be made objectively, separate from the real-time emotional state at the time.  It could also explain the development of self-recognition and empathy which allows the transference of experience from the first-person perspective to explain the actions of others.  (In the case of empathy, this may make use of the neighbouring locations of the AG with the supramarginal gyrus which is a major contributor to the empathy function.) It may also explain why some people report ´out of body` experiences and self-transcendence.

The second aspect of first-person perspective is speech and language processing of which the AG plays a role. Conscious awareness can be reported verbally using speech and language or proven by unreported actions or physiological measurements. However, descriptions whether of facts or feelings and problem-solving for example require language (common to others and learnt) and speech. The AG is required for speech processing and therefore, the Self requires the functioning of this area if the first-person perspective is to be communicated to others. The AG is not alone in this function and is part of a network of active areas responsible for the movements of muscles involved in speech, even language structure and phonetics.

Therefore, to summarise, the AG is an area that appears to be involved in the expression of the Self`s ´Me, Myself, I` and it appears to have two distinctive roles.  The first is that activation of the area in the recall of autobiographical memories leads to the application of ´Me` to those memories. This is carried out in such a way that there appears to be a ´detachment` between ´I` being recalled and ´I` existing now and part of the conscious experience. Such a ´detachment` is brought about by AG activity in the former only and allows the two perspectives to occur simultaneously. Hence, we can recall the past and our involvement in that past and be aware of what is happening in the present at the same time even if only one is conscious at any time. The second role of the AG is simpler neurochemically, but is even more fundamental to the concept of the Self in that activity in this area is required for speech processing. Without it our ability to communicate verbally and describe our memories, feelings and so to others or internally to think and solve problems for example is not possible. Therefore, the AG should be ear-marked as a key player in the neural correlates of consciousness and the Self. The continuing development of real-time neuroimaging techniques and computer analyses will no doubt in the future make it possible to investigate this area further and maybe lead to identification of spatial divisions within it that are specific for the two functional roles it appears to plays.

Since we`re talking about the topic………………………

….Bonnici and colleagues asked their subjects to recall pleasant autobiographical memories and by doing this they saw the involvement of the AG. Would the recall of unpleasant autobiographical memories instead lead not only to the involvement of the AG, but also to activity in the amygdala even though this area is not believed to be neurally connected to the AG?

……can we assume that if we examined AG activity in a repeat experiment with subjects suffering from autism there would be a correlation between weaker AG firing and lack of first person and third person awareness?

……would we be able to distinguish areas within the AG for conscious awareness and unconscious awareness if the experiment was repeated using subjects suffering from blindsight instead and exposing them to pleasant personal photographs on their ´sighted` side and unpleasant personal photographs on their blind side?

 

Posted in angular gyrus, consciousness, memory recall, Uncategorized | Tagged , ,

reduced ventrolateral prefrontal cortex gray matter volume correlates to decision-making irrationality in aging

Posted comment on ´The reduction of ventrolateral prefrontal cortex gray matter volume correlates with loss of economic rationality in aging` by H-K. Chung, A. Tymula and P. Glimcher and published in Journal of Neuroscience 2017 37(49 12068

SUMMARY

In their article Chung, Tymula and Glimcher describe the results of their investigation into whether a reduction in efficiency of economic decision-making observed for adults aged 65 years and above correlated with a decrease in gray matter volume found in the brain area ventrolateral prefrontal cortex (vlpfc).

Fourteen healthy males and 25 healthy female adults aged between 65 and 92, who recorded Mini-Mental states of between 26 and 30 and had no recorded medication for any psychiatric condition, developmental disorder or dementia, took part in the study. The subjects performed a behavioural experiment to determine the degree of their rationality in a decision-making task. This meant that the subjects had to perform 11 different trials, each one of which was to select a bundle of 2 goods from 3-7 different alternatives. The goods in the bundles were carefully selected by the experimenters to be equally desirable for the subject being tested. This was achieved by first presenting the subjects with a range of objects thought to be favoured by elderly people eg. hand cream, pocket tissues, teabags, chocolates, puzzle books and asking them to rate the goods by their desirability. This test was performed twice. Bundles were then constructed of two types of goods (eg. sudoko books and crossword books) with variations in the number of each type (eg. one bundle would have 3 sudoko books and 4 crossword books and another bundle would have 6 sudoko book and 1 crossword book) for each participant and for each trial. The experimenters asked the participants to choose the bundle they liked the most. This experimental set-up assumed that the subject would choose the bundle that had the best selection for them personally and would reject the bundle with more of the not so good. Trade-offs between the 2 classes of goods and the amounts of the 2 goods would have to be made with the assumption that people would trade-off the quantity of one good choice for the other good one. Once the decision had been made, the subjects were then asked to press the number of the corresponding bundle onto a numeric keyboard and the result was displayed on a screen. The subjects were then told to recheck their choice and press enter to continue. No time limit was placed on this choosing period so that choice was not based on either the inclusion of undesirable objects, lack of interest or time pressure. At the end of the trial each subject was ´paid` according to his/her choice made in one randomly selected trial.

In Chung, Tymula and Glimcher`s experiments choice was correlated to the increase in number of Generalised Axiom of Revealed Preference (GARP) violations. Participants were considered as violating GARP when the chosen bundles consisted of one favourite and one non-favourite object rather than two favourite objects. Mathematical analysis was performed and 2 quantifiable measures were used to determine the level of irrationality of the choices made. These were: frequency of irrationality where the number of selected bundles violating GARP were calculated; and severity of irrationality dictated by the Houtman-Maks (HM) index which rated the assessment of the loss from small to severe. Whilst the subjects performed the behavioural tasks described above,  MRI neuroimaging was also carried out. Voxel-based morphometry (VBM) analysis was performed using a VBM8 toolbox for identifying gray and white matter and CSF followed by SPM8 and Matlab for adjustments and analysis. The brain activities of particular areas and their co-activations were identified using Neurosynth.

The results of the technical rationality experiment carried out showed that there was a decline in rationality in the older subjects compared with the younger control subjects. The elderly subjects presented varying levels of irrationality in choices with 42% making two or more GARP violations from the 11 trials. In comparison to other studies, elderly people appeared to violate rationality slightly more than college undergraduates (35%), the same as younger people with blood alcohol levels at or above 0.8% of the legal limit, less than second-grade children (74%) and less than patients with ventromedial frontal lobe lesions (89%). The severity of the irrationality correlated to its frequency. Further investigation showed that although there was a decline in rationality compared with younger subjects, chronological age itself did not correlate to irrationality levels observed either in frequency or severity. Participants made on average 1.37 irrational choices with one participant making 6.

Having established that technical irrationality was increased in older subjects, but did not correlate to chronological age, Chung, Tymula and Glimcher investigated the relationship between economic rationality and gray matter density of the vlpfc using whole-brain VBM analysis. The authors found that there was a reduction of gray matter volume of a cluster in the left vlpfc  (identified as lateral Brodmann 10, rostral 46 and lateral 47 areas) correlating to the irrational economic behaviour observed. This area corresponded to more GARP violations in both frequency and severity than other brain areas. Testing of the right vlpfc produced a less robust MRI signal and therefore, functioning of the right vlpfc was examined by other means. Using these alternative methods, the authors found the same results for the right vlpfc  as for the left and therefore, concluded that there was significant correlations between frequency and severity of irrationality for both left and right vlpfc.

The final part of their study saw Chung, Tymula and Glimcher investigating brain area connectivity associated with economic rationality by creating a reward associated map using Neurosynth. The authors found that the left vlpfc was associated with reward regions and co-activated with other brain areas traditionally linked to decision-making processing including the dorsal lateral prefrontal cortex (dlpfc), striatum and posterior parietal cortex. These areas were also shown to demonstrate strong co-activation patterns to the right vlpfc as well.

Chung, Tymula and Glimcher concluded their article by summarising the impact of their study on current cognitive thinking and the impact that this type of cognitive deficiency has on a society that is getting older. They showed that in older adulthood, the decline in decision-making rationality was not reliant on memory or complicated processing rules, but occurred because of unknown reasons. They looked at whether a change in decision-making capability for known alternatives was caused by physical changes in brain structure and found that for their experimental set-up it did. Using a task that involved multiple cognitive capabilities mainly relating to value, Chung, Tymula and Glimcher showed that the region left and right vlpfc is involved in decision-making including the elderly and co-activates with other decision-making and reward associated brain areas. The authors found that in the case of economic rationality, irrationality in their decision-making task correlated to a decrease in  volume of gray matter in the vlpfc of their elderly subjects and therefore, concluded that the vlpfc area is linked to the mechanism required for utility maximisation.

COMMENT

What makes this article interesting is that it describes the role of the lesser known ventrolateral prefrontal cortex region (vlpfc) in the type of decision-making that requires a person to choose between two things that they deem to be of equal value. According to Chung, Tymula and Glimcher this particular brain area has been found to be physically affected by age which could explain the observations of decreased  performance in  ´success` of this type of decision making when  ´success` is defined as being consistent choice. Therefore, the vlpfc area is indicated as having functional importance in maintaining decision choices. The experimental set-up of Chung, Tymula and Glimcher was aimed at looking at economic rationality based on personal value of an object, but the authors extended this beyond the realms of ventromedial prefrontal cortex (vmpfc) functioning by making their subjects choose from between two objects which from initial testing were given the same value rating. The experimental set-up with emphasis on object recognition, emotional worth and physical movement also removed the need for language and language processing. This is important to note since the vlpfc is known as the Broca region and is associated with language production. In the experiments carried out by Chung, Tymula and Glimcher articulate speech was not required since the subjects were not asked to provide explanations of why their choices were made, there was no complicated, step-wise problem solving and the decision was ´reported` to the observers by a physical action. The behavioural part of the experiment was accompanied by neuroimaging which gave an indication of firing activity during the course of the task. Therefore, from their experiments, Chung, Tymula and Glimcher were able to associate physical changes in their studied brain area to behavioural changes. It should be noted here, that the experimental results support to some extent the observations of others, but there are difficulties in consistency of results and interpretations simply because different tasks have different cognitive requirements, or require other levels of engagement and therefore, it is necessary to know exactly what the nature of the task is before any conclusions can be made. Also, experimentation using human subjects leads to another set of problems because humans can alter their behaviour for a number of reasons such as tiredness, inattention, boredom, or even over-confidence. From the neurochemical side, real-time imaging of small areas particularly of human beings can be difficult and the interrelated activity of multiple brain areas can suffer from inaccuracy through the averaging analysis for example. However, Chung, Tymula and Glimcher investigated a particular example of decision-making and strived in their experiment to remove inconsistencies.

In order to interpret what the authors found out we have to first look at what is going on in the decision-making mechanism their subjects faced and see where the differences lie between elderly and younger people. We assume firstly that the method used for both groups is ´head` based. By this we mean that the participants do not just look at the object bundles and choose on gut feeling (ie. ´heart` based decision-making) which bundle to take. Instead there is some processing deduction carried out to see which bundle is best for them personally. This occurs because the objects in the bundles are deemed to be of equal value to the subject according to what was ascertained in the preliminary testing phase.  Therefore, each subject has set before them a bundle of two equally favourable objects, but the amount of each varies. The first stage of the decision-making process is the input of sensory information relating to the objects and this we assume employs the same mechanisms whether in the elderly or younger people. Only the efficiency may change. The second stage of the decision-making process is also independent of the age of the subject. This stage involves what is termed the ´construction of options`. This means that the strategies that can be used in order to solve this decision-making problem are identified. We all have a series of strategies that we use to problem solve and the chosen one varies because it has to match the situation or sometimes because we favour one method more than another. In both the elderly and the younger subjects the ideal strategy in this decision-making task is the same and is either comparison of personal emotional value of the objects, or less likely the assessment of plus and minus points of the objects. The former involves the subject choosing the object bundle which provides him with the highest reward status. Other possible strategies such as consequence and sequel, agreement and disagreement, other people`s views are in this experiment not applicable as there are no consequences of action apart from personal gain. This is why it is important to determine what the needs are for the task involved for any experiment since one cannot associate brain area functioning with behaviour if the cognitive demand is different.

In Chung, Tymula and Glimcher`s decision-making experiment the third stage of the decision-making processing is the mental ´running through` for all the bundles on offer using the core features of the objects such as title of book or object characteristics with the acknowledgement of the end result of each of the options ie. the intended reward status for each option. This is the first area that may be affected by age and hence, a difference may be observed in performance between the elderly and younger participants. Age is known to affect working memory (ie. processing power) and sensory input and hence, if information is being inputted and processed, the greater the amount and level of detail, the better the electrical representation formed in the brain areas. Biasness towards one feature or another can sway the electrical trace formed and may lead to inconsistencies in decision-making rationality.

Stage 3 then leads on to Stage 4 which is neurochemically an important stage and is where the physical firing traces of the objects are ´constructed`. Behaviour comes from neurochemical reactions and Stage 4 is the acknowledgement that decisions are based on, according to the hypothesis proposed by the author of this blog, by an assessment of firing activation of the individual traces. The assessment is carried out by comparison of the strength of firing through extent, similarity and emotional response. Strength of firing is achieved through the amount of activated cells obtained from frequent firing ie. something that is liked will possibly be visited more than once and according to neurochemical firing rules the trace will exhibit stronger firing. Similarity of firing is attributed to the number of shared characteristics of the traces being reactivated at that one time with the greater  number of characteristics being shared leading to the stronger firing. In the case of decision-making, similarity can also be assessed by the strength of firing of the option trace compared to the goal or purpose trace. The third neurochemical firing comparator is the firing associated with emotional response accompanying the information (ie. the ´emotional tag`). This represents the personal emotional value attributed to the characteristics of the representation encoded in the firing trace. Therefore, there are three ways in which an option can be judged from a neurochemical perspective. The first two depend on firing traces reactivated at the information storage and processing sites and the third through reactivation of the object`s  emotional tag stored in the pfc (likely the orbitofrontal cortex area, ofc) alongside the information. Again, this is another stage of the decision-making mechanism that may differ with regards to elderly and younger participants. Firing details, for example biasness towards one feature or another and emotional values eg. personal value of object may be subject to inconsistent input, poor recall or renewed skewed processing and this may provide several opportunities for the traces of new bundles to contradict ratings of previous ones. It is likely that the younger people show greater consistency in their assessments of objects during the course of the experiment and this therefore, would be one stage where the decision-making mechanism can differ between the elderly and younger participants.

In the experiments carried out by Chung, Tymula and Glimcher Stage 5 of the decision-making mechanism is the stage where the participant decides yes or no to a particular bundle. This decision is based on looking for the bundle which gives the his/her the highest reward value and therefore, I requires that the emotional tags associated with each bundle are compared. Once this decision is made, then the subjects are asked to perform a physical action (Stage 6), but are then asked re-check their decision. This involves repeating Stage 5 and possibly Stage 4. Stage 5 like Stage 4 is dependent on the relevant information and emotional responses reactivated at the time. Therefore, it too can be affected by age. The mechanism remains the same, but in the case of Chung, Tymula and Glimcher`s experiments inconsistencies of choice occur in the elderly participants in comparison to the younger. This indicates that the values assigned to the bundles is skewed in the subsequent presentations and irrationality of deciding which bundle provides the best reward is induced. Unlike Stage 5, Stage 6 which is the action stage (ie. performance of a physical motor action to select the option chosen), does not differ between the subjects since the action is the same independent of age. Under some circumstances, but not here, the decision-making mechanism concludes with one further stage that of feedback (Stage 7). This is where there is acknowledgement of the outcome of the decision-making process based on physical and emotional feedback. Stage 7 is not carried out here because virtual bundles are used and there is no opportunity to provide feedback.

Now that we have seen how decisions are made and what stages could be affected by changes in neurochemical functioning and structure we have to ask if aging affects the behavioural decision-making process in Chung, Tymula and Glimcher`s experiment, where does the small brain area vlpfc fit in? Essentially we are looking to see what happens when this area is not functioning correctly. Previous research supports Chung, Tymula and Glimcher`s findings since it has been shown that vlpfc lesions leads to a loss in strategy based performance. This is a more complicated type of decision-making than the one demonstrated here, but it still links performance on the basis of rationality of decisions. Aging is also associated with: the decreased ability to multitask which could be attributed to matching the goal to the input (Stage 5); and decreased capability to input novel information in real time which could relate to the input of option material (Stage 3).

There are various areas where changes in vlpfc functioning may give rise to behavioural changes. Chung, Tymula and Glimcher gave one such effect in their article and that is the loss of gray matter material in the vlpfc with increasing age. Functional changes can be attributed to loss of gray matter in both right and left vlpfc areas and this is important because for example, the pfc in general is known to play a role in many cognitive functions eg. working memory, emotions, central executive, attention and decision-making. It achieves this through neuronal and interneuronal firing and glial cell functioning at the micro level scale and connectivity between appropriate areas at the macro scale. Firing has different characteristics dependent on general brain area and even at the local level such as via neurotransmitter trigger involved, balance between excitation and inhibition and the presence of multitasking neurons. Underactivity or overactivity of areas can lead to different psychological disorders such as depression (linked to 5HT and overactivity of the pfc) and stress (pfc underactivity). Therefore, the decrease in gray matter volume of the vlpfc and reported substantial decrease in number of cells can have effects on the excitatory/inhibitory balance of the area. The observed decrease in gray matter in the lateral pfc lies at a 3% loss in volume per decade and the pattern of gray matter loss shows it beginning with the frontal areas leading to later loss in the temporal areas with a sparing of the sensory areas. The number and volume of white matter cells are also observed as decreased with increasing age, but to a lesser extent than gray matter and the pattern of loss in the frontal areas is reported later than for the gray matter.There is however, a greater loss with age in the vmpfc, which is the area known to be linked to personal values and comparison of subjective values.

On the macro scale connectivity between brain areas is important for cognitive function. For example it is known that pfc and hippocampus connectivity is required for information context guided memory. This capability is required here in Chung and team`s experiment since the assessment of the bundles relies on object recognition memory in addition to emotional memory. Connectivity of brain areas leads to stimulation of neurons that are not initially activated by the stimulus and also leads to the synchronisation of firing between cells and brain areas to produce brain waves. These are said to reflect the cognitive function at the time. For example theta waves are required by the pfc areas for maintenance of information, alpha waves for maintenance and recall, and gamma waves indicating possible manipulation of material. A number of areas are reported as being connected to the vlpfc, eg. vmpfc, dlpfc, striatum, post parietal cortex and others. Therefore, disturbances in connectivity brought about by reduced number of brain cells can have a major effect on cognitive function associated primarily with other areas. For example, the anterior cingulate cortex (acc) (which also demonstrates reduced volume and activity in elderly) is known to be linked to monitoring and fear response, but it also has connectivity to the vlpfc.  Effort invested in attaining rewards is demonstrated to be linked to activity in the vmpfc and acc and acc lesions produces normal responses to reduced reward with improved behavioural strategy not being maintained. This indicates that the acc is essential for learning the value of actions and guided voluntary choices based on the history of outcomes and actions. Lesions of the area made monkeys unable to sustain rewarded responses in a reinforcement guided choice task and to integrate risk and payoff in a dynamic foraging task. It was also found that vlpfc and dlpfc demonstrate acc connectivity that is decreased in repeated retrieval of information. Therefore, any change in vlpfc volume as indicated with age could cause changes to dlpfc and acc connectivity and ultimately affect informational input. This could impact decision-making rationality as demonstrated here.

    Therefore, physical changes such as cell number, firing and connectivity  can have an effect on cognitive capability. Several areas relating to Chung, Tymula and Glimcher`s experiment could be affected. We have already discussed briefly the first in our description of the biochemical mechanism associated with decision-making and that is that the change in value assessment demonstrated from trial to trial by the elderly participants in the experiment has an effect on rationality performance. We assume that the value of an object remains the same from the preliminary test to the end of experiment and this is likely to be the case with the younger test subjects. They are more likely to stick with their choices assessed in the preliminary testing phase providing there is no change to the information given or the experimental conditions. Therefore, economic rationality is observed with the younger participants.  In the case of the more elderly test participants, the expectation that the choices they made early on in the preliminary testing phase remained constant was not realised. It appeared that the value of the objects changed in the course of experiment leading to inconsistent choices and a demonstration of economic irrationality (GARP violations). The biasness towards certain choices in the later trials that was observed with the younger participants did not occur with the elderly test subjects and instead there was a move toward the less frequent / less automatic responses. This observation has also been reported with visuomotor conditioning and correlates to changes in pfc functioning. In the case of Chung, Tymula and Glimcher`s experiments the irrationality observed in the elderly subjects could mean that there is a change in emotional tag associated with the presented objects, or there is a change in the mechanism rating the emotional tags. In the biochemical decision-making process described above, Stages 3, 4, or 5 could be affected in the elderly. With regards to Stage 3, this could mean that the assessment of the bundle as a source of reward could be affected, but this is unlikely since the participant will still choose one and still acknowledge that the reward would come from that bundle. With Stage 4, the alteration in function could relate to the assessment of each bundle as level of reward achievable and could lead to different ratings for each bundle during the course of the experiment. Finally, Stage 5 would also be affected if the personal value ratings were different during the course of the experiment. Since the decision is taken to provide the participant with the highest level of reward, it is still assumed that the participant will choose the bundle with the highest reward rating, but the values are not consistent throughout the experiment and therefore, at the decision-making stage inconsistencies in choice would be seen. The value system relies on vmpfc functioning which is known to be involved in comparing values of different units of goods on the same scale as would be the case here. Vlpfc and vmpfc exhibit two-way directional interconnectivity and therefore, reduced vlpfc functioning would influence vmpfc region functioning or at least have an effect on vmpfc firing and connectivity.

A second area where there could be an influence on decision-making in the elderly in this type of task is the effect of age on attentional processes. This does not mean concentration, but refers the level of relevant and irrelevant information taken in. It is known that aging leads to an increase in the input of irrelevant information. This would have an effect on the decision-making process because in Stage 1 where core features are required to define the electrical representation, the traces would be swamped with additional information that is irrelevant to the task involved, eg. colour of sudoko book cover. This means that at the later stage where the decision is actually made, there may be a shift from neurochemical emotional value strategy to similarity strategy because irrelevant features would strength the matching of the firing traces from an information perspective in comparison to a weaker emotional value perspective. The lack of suppression of irrelevant information observed in elderly people could lead to inconsistency of choice compared to the younger participants who do not suffer from this increase in irrelevant informational input. Since attentional filtering relies on functioning and interconnectivity of parietal, temporal and prefrontal cortical areas, it is likely that any physical change in an area such as vlpfc will have wider ranging effects in attentional functioning whether in informational strategy shifting or content.

We have already discussed in the effect of attention another area which may lead to inconsistencies in choice demonstrated by more elderly participants and that is the choice of decision-making strategy. It is said above that the rise in irrelevant material in an object`s biochemical electrical representation may lead to the decision-making strategy going away from emotional value to one of similarity. The experimental set-up is such that the emotional value of the reward (ie. the bundle) dictates the choice made for each individual and we have said that this is a decision-making method reliant on using the ´head` meaning that informational processing is involved. We assume that this method is used continually during the experimental task, but it could be that with elderly participants there is a shift to a ´heart` type decision-making method during the trials. This may still rely on emotional value assessment, but it can indicate non-processing such as in the case of where ´gut` instinct takes over. Gut instinct can be based on ´false` presumptions of value for the reason given above that irrelevant information is taken into account that would bias the decision-making or lead to relevant information being ignored. Younger people, because of the nature of the experiment are more likely to remain in ´head` decision-making mode for the entire test period whereas the more elderly participants due to the reduced level of vlpfc would succumb to the higher influence of the vmpfc functioning linked to subjective values.

The final area discussed here as possibly influencing decision-making in the elderly is the lack of feedback with Chung, Tymula and Glimcher`s experimental set-up. The absence of Stage 7 could indicate that feedback is more important for elderly people in sustained decision-making tasks. Feedback requires monitoring mechanisms which involve the acc and we have already seen that this area too is affected in volume and cell number in elderly people. Therefore, in the absence of feedback, the acc is not stimulated and irrationality of decision-making in the elderly is neither noticed, nor compensated for. If the conflict in decisions was made apparent to the elderly participants then may be rationality would be restored. Younger people appear to be more capable of sustaining consistency in the absence of feedback for the period of trial undertaken here. This could reflect normal acc functioning in this age group rather than the vlpfc .

The comment given here supports the observation of Chung, Tymula and Glimcher that in the case of decision-making between objects of equal value vlpfc functioning is involved and is required for consistency of choice over an unmoderated experimental test period. With relation to Chung, Tymula and Glimcher`s findings that there is a loss of vlpfc gray matter in the elderly, we have also identified where a loss in grey matter of the vlpfc whether volume or firing cells has effects on firing of that region and interconnectivity of that region to other brain areas resulting in the described cognitive effects. Unfortunately, it appears that loss of function of the vlpfc (and even the acc) because of structural changes although not directly dependent on chronological age is related to aging and therefore, under normal circumstances loss of cognitive capability will occur to some degree. Structural changes may not be directly halted, but it could be that the loss of vlpfc functioning can be compensated for cognitively by changing our approach to information and information processing. For example, the stimulation in interest generally may lead to improved performances of object recognition, spatial memory for example. We know that the more something is processed the better it is remembered. Another compensatory method may relate to value assessment and the use of our own definitive judgement relating to value, reward and risk on a more regular basis in particular in making clear and repeated decisions. Another possible way to compensate for decision-making inconsistency may be to provide or demand feedback and constantly monitor the results of decisions made and assess the success or failure of those decisions. This maintains awareness and attention and leads to increased engagement, increased memory capability and information processing. We may not be able to hinder the functional changes linked purely to age of tissue, but we may be able to compensate for the effects that such changes in structure have on our cognitive capabilities.

Since we`re talking about the topic…………………………..

….can we assume that if the choice made was based on fear and risk and not on reward and personal gain that the level of irrationality would not be decreased to such a level observed by Chung, Tymula  and Glimcher because the vlpfc functioning would not have the same influence on the decision-making mechanism since the amygdala would be involved instead?

…..the pfc requires glutamate, dopamine and GABA neurotransmitters for its functioning. Would it be possible to ascertain whether the decrease in vlpfc functioning in Chung, Tymula and Glimchers`s experiments was dependent on lower dopamine functioning by pre-administrating COMT? This would assume that the pre-administered COMT would lead to compensatory increased activity and restore economic rationality in the elderly participants? Would the pre-administration of ketamine which would block glutamate receptor functioning show involvement of NMDA receptors in vlpfc functioning during the experiment by a weakened signal or firing in the information representation observed?

…..would the use of optogenetics of layer 5 of the prefrontal cortex neurons during performance of the task allow the selective effects on dendrite activity of the elderly participants to be observed and show a difference between them and the younger participants?

 

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firing differences of tonically active interneurons in the striatum to reward events

Published comment on ´Differences between dorsal and ventral striatum in the sensitivity of tonically active neurons to rewarding events` by K. Marche, A-C. Martel and P. Apicella and published in Frontiers in Systems Neuroscience 24th July 2017 doi.org/10.3389/fnsys.2017.00052

SUMMARY

Marche, Martel and Apicella investigated a small group of cholinergic interneurons found in the striatum called TANs. These interneurons are tonically active and even although they are only 3% of the total number of neurons present they act to modulate the local striatal output. The TANs are known to be involved in stimulus-reward events and can be identified by their distinctive firing characteristics ie. the stop in firing in response to stimulus and reward (termed pauses) and the following rebound to baseline activity (termed rebounds). In their article, the authors described their study into whether the TAN responses are uniformly distributed throughout the dorsal striatal region (motor and associative striatum) and ventral region (limbic striatum) and how TAN firing responses can differ.

In order to study the striatal TANs in a stimulus-reward type scenario, Marche, Martel and Apicella used a Pavlovian conditioning task and 2 adult male monkeys (F and T) as experimental subjects. The task consisted of a given visual stimulus (0.3secs) and the restrained monkey having to perform reaching arm movements to receive a liquid as reward response. Test conditions were: fixed reward timing (FRT) – the liquid reward was given at a fixed time interval (1sec) after the visual stimulus independent of any behaviour shown;  variable reward timing (VRT) – the interval between the stimulus and reward was varied; and unpredicted (free) reward timing (URT) – where the reward was given independent of stimulus. Blocks of 30 to 40 tests with each trial lasting 6 secs were carried out with randomly alternating conditions. The locations of the total 62 TANs observed were plotted for each monkey (Monkey F, had 37; Monkey T, 25) and firing was recorded. The neuronal activity observed was analysed by detecting changes in the TAN firing. A test period of 100ms was monitored in 10ms time periods starting at the presentation of the stimulus or delivery of reward and the average spike counts within that interval was calculated across all trials. The onset of a modulation was taken to be the beginning of the first of at least 5 time periods that showed a significant difference in spike activity compared to the control. The offset of modulation was taken to be the first of 5 time periods when activity returned to control values and the magnitude of change in TAN activity was measured by counting the firing spikes between the onset and offset and expressed as a percentage above or below baseline activity. The activities of the populations of TANs were pooled across the samples for the different striatal regions corresponding to the functional territories conventionally defined for a primate. The striatal regions investigated were: the motor region (corresponded to part of the posterior putamen to anterior commissure) and contained a total of 26 neurons; an associative region (included dorsal pre-commissural parts of both the caudate nucleus and putamen) – 21 neurons; a limbic striatum region – the ventral part of the caudate nucleus and putamen rostral to the anterior commissure – 15 neurons.

Marche, Martel and Apicella found that the mean firing frequency of the TANs was similar in all three regions (approx. 5.3 spikes/sec). Their study also showed that 68% of the neurons had changes in activity after the presentation of the visual stimulus and 69% after the delivery of the reward in the FRT condition which indicated that the fractions of responsive TANs within the regions did not differ between the stimulus and reward. Twenty one out of the total 62 neurons responded to only one event, ie. either to the stimulus or reward. The proportion of TANs displaying a response to the visual stimulus were said not to vary significantly among the striatal regions (limbic striatum 80%; motor 58%; associative 71%), but the percentage of TANs responsive to the reward showed some variation with the limbic striatum having a higher proportion of firing TANs than the other two regions (100% limbic; 65% motor; 52% associative). The proportion of TANs responding to both stimulus and reward was higher in the limbic striatum, but the responses were not specifically related to the stimulus. This was shown by the excitatory component of firing not being influenced by the subsequent delivery of the reward.

Marche, Martel and Apicella also looked at the durations and magnitudes of the pauses and rebounds of the TAN responses they observed. They found that the duration of the pause responses to stimuli were significantly longer in the limbic region than in the motor and associative regions. The magnitudes of the pauses were also greater in the limbic and associative regions than the motor region. Investigation of the rebounds from the pauses initiated by the stimuli showed similar patterns with the durations of the rebounds being longer in the limbic and associative regions than the motor area, but the magnitudes did not significantly differ although it was said that there was a trend towards the limbic region. In the case of the pauses and rebounds of the TAN firing in response to the rewards, then few differences between the areas were shown. Only the durations of the pauses following reward gave a significant difference with the highest values being obtained in the limbic and associative areas.

An investigation into the average activity of the entire population of TANs regardless of responsiveness to stimulus or reward found that there was clear modulation of the whole sample recorded in each striatal region after each task event. Population activity was found to be the same for all regions for the control period at 110-120ms after the onset of the stimulus, but the duration of the pause differed with 70 msecs for the motor region, 110msecs for the associative area and 160msecs for the limbic striatum. There were no differences in the duration of the rebound period. After the delivery of reward, again population activity appeared at 110-120msecs and the durations of the pauses were again area specific with the motor region giving a pause length of 70msecs and the associative and limbic regions both 120msecs.

Marche, Martel and Apicella also investigated whether there were differences in TAN responses between the regions when the timing of the reward was changed (ie. the VRT condition). In this case under VRT conditions the same number of neurons and the fraction responded to the stimulus and reward as in the FRT condition. Durations of the pauses in response to the stimuli were the same for all three striatal regions, but the magnitudes of the pause responses were significantly different in the VRT condition with a higher result obtained for the limbic region than the associative striatum. No differences in the durations or magnitudes of the TAN responses to reward were observed under the VRT condition for all 3 regions. When the population activity was investigated as a whole (ie. averaged values of all 27 TANs activities) then the durations of the pauses after stimuli were different with 30msecs for the motor striatum, 80 msecs for the associative striatum and 120msecs for the limbic striatum. Following the reward the population responses ranged from 50msecs for the motor striatum to 110msecs for both the associative and limbic regions.

The third condition investigated by Marche, Martel and Apicella was with the reward being delivered randomly in their conditioning task (URT). This condition ensured that any activity observed was linked to the reward and was independent of the stimulus. The authors found that in the URT condition approximately the same proportion of neurons responded to the reward as in the FRT condition. In the URT condition, the duration of the pause response to the random reward was significantly different for the studied regions ie.  longer durations in limbic and associative striatum areas compared to the motor area. This was different to the results obtained for the FRT condition and was supported to some extent when the activities of the populations as a whole were investigated. The averaged population activity of the duration of the pauses in response to the rewards was found to be 170msecs for the limbic region, 80msecs for the associative area and 70msecs for the motor area.   The limbic area neurons also produced the stronger responses.

The authors concluded their article by saying that in the striatum`s role of processing motivational information, the ventral striatal TANs exhibit stronger responses to rewarding stimuli than those found in the dorsal striatum. Not only was a higher proportion of neurons in the ventral striatum responsive the TANs present also demonstrated particular response features eg. the duration and magnitudes of the pause and rebound periods for stimulus onset and reward delivery were greater in the ventral area than in the dorsal striatum. This supported the view that the ventral TAN system is different to that found dorsally with possible greater local cholinergic input that could parallel the functional specialisation within the striatum. Marche, Martel and Apicella continued their discussion by noting the similarity of the TANs observed in rodents to those found in their primate subjects and went on to consider whether the afferent signals into the areas may be responsible for the pause response of the TANs. They also considered how TAN activity could be linked to reward predictability and action selection.

COMMENT

What makes Marche, Martel and Apicella`s article interesting is that it again brings to attention the fact that a brain area serving a particular function does not necessarily mean that all neuronal cells in that area act in the same way. Marche, Martel and Apicella describe in their article a small subset of neuronal firing cells called TANs that are located in the striatum and that are tonically active (ie. active without specific synaptic input), but have distinctive excitatory firing characteristics compared to the other excitatory cells present. This comment explores where TAN activity fits in with the cognitive functioning of the striatum and why the identifiable pauses and rebounds in firing are necessary for the neurochemical functioning of the area.

The experimental basis used by the authors to investigate TAN functioning was a conditioning task with a visual stimulus, motor movement (arm reaching) and reward (liquid). This type of experiment is ideal for looking at brain area and neurochemical functioning linked to learnt behaviour based on emotional value and expectations in relation to a reward given after a specific stimulus – core functions associated with the striatal region. The dorsal region (traditionally said to consist of the caudate and putamen) is linked with motor and associative functions (ie. cognition involving motor function),  certain executive functions (eg. inhibitory control and impulsivity) and stimulus response learning. The ventral region (traditionally said to consist of the nucleus accumbens, hereafter termed NA, and the olfactory bulb) is said to be linked to mediating reward cognition, reinforcement, and motivational salience. There is a small degree of overlap as the dorsal striatum is also a component of the reward system that, along with the NA core, mediates the encoding of new motor programs associated with future reward acquisition (eg. the conditioned motor response to the reward cue). Before we continue it should be noted that the divisions of the striatum used by Marche, Martel and Apicella in their article do not agree with more common striatal partition. For example, the motor region is described by the authors as that area between part of the posterior putamen to the anterior commissure; the associative area as the dorsal pre-commissural parts of the caudate and putamen; and the limbic area as the ventral part of the caudate and putamen rostral to the anterior commissural. This means that the ´dorsal` term used here reflects the dorsal parts of the caudate and putamen and the ´ventral` term the ventral parts of the same areas. Cognitive roles attributed to the dorsal and ventral areas therefore relate to the caudate and putamen regions and not the more well-known NA.

When we are looking at the striatum and it`s roles in motivationally salient events we can see that it is linked to reward value, the expectation of that reward and the updating of the value of that reward. The input and interpretation of the information relating to the reward itself is not the responsibility of the striatum alone with multiple brain areas involved including sensory systems for informational input and associative areas for assessment, eg. the ventral tegmentum (VTA) with its dopaminergic system (work by Mortig et al, Wittman et al). In the VTA case, the lateral hypothalamus is said to send projections to the VTA which are believed to be important for behaviour and corticotrophin releasing factor (CRF) acts on the VTA to decrease the motivation to work for rewards also by regulating the DA activity (Tyree et al. and Wanat et al.). Also the prefrontal cortex (PFC) plays a major role with immediate and delayed rewards separately represented in the dorsal medial PFC (mPFC) and compared in the ventral PFC in order to guide decisions (Wang et al.). The orbitofrontal cortex (OFC) is known to be linked to the waiting for rewards and their subjective value (McGuire et al). The activity of this area is believed to be controlled by various neurotransmitters such as 5HT, GABA and glutamate eg. citalopram (a 5HT inhibitor) pretreatment is said to lead to increased OFC responses to reward (Delben et al).

The importance of the reward lies not just in its characteristics, but the value placed upon it by the individual. The determination and storage of values also require the inter-connectivity and inter-functionality of multiple brain areas. For example, the encoding and retrieval of values occurs through the firing and  connectivity of particular brain areas such as the basal amgydala and the insular cortex. Connectivity here mediates encoding and retrieval of outcome values with the amygdala encoding and the insular cortex retrieving such values in guide choices (Parkes et al.). The PFC again has a number of different functions eg. the mapping of the value of events on a common scale (Gross et al.) and particularly the OFC which links events to reward values (Winecoff et al., Favonik et al.). This area allows the representation of contexts that guide memory retrieval and the comparison of the subjective value of outcome (Hornick t al.). The anterior cingulate cortex also plays a role and is important for encoding competitive effort ie. learning the value of actions.

It is in the role of values and the subtleties of the value system that the striatum shows like the PFC, different functionality for different local areas. The traditionally termed dorsal striatum is said to comprise of the caudate and putamen. In the case of the caudate, activity relating to values was said to rely on dopaminergic functioning eg. Tai et al. found that stimulation of the dorsal striatal dopamine D1 and D2 receptor–expressing neurons during decision-making in mice introduced opposing biases in the distribution of choices. The effect of that stimulation on choice was dependent on recent reward history and mimicked an additive change in the action value. Other researchers found such subtleties in the dorsal striatal functioning relating to values. For example Wunderlich et al. found that the computational processes underlying forward planning are expressed in the anterior caudate nucleus as values of the individual options in a decision tree, ie. competing values of available options. In contrast, the team found that values represented in the putamen pertained solely to the values learnt during extensive training. During the actual choice stage, both of these areas demonstrated functional coupling to the ventromedial PFC which was consistent with it acting as a value comparator integrating the outputs of the two striatal regions. This link with the PFC functioning was further corroborated by Campbell-Meiklejohn et al. who showed that values computed from choices were weighted by their associated confidence and specifically represented in the ventromedial area of the PFC. The tendency to self-monitor predicted a selectively enhanced response to accordance with other`s results in the right temporal-parietal junction  and therefore, indicated that using cues of the reliability of other peoples’ knowledge to enhance expectation of personal success generated value correlates that were anatomically distinct from those concurrently computed from direct, personal experience. It also indicated that representation of decision values in the ventromedial PFC was sub-organized according to computed values. Meder et al. found another subtlety of the value system. They found that when gathering valued goods, risk and reward are often coupled and escalated over time. This requires increasing activity and connectivity of a cortico-subcortical ´braking` network that increased with gains and included the caudate as well as the pre-supplementary motor area, inferior frontal gyrus and subthalamic nucleus. The putamen was also linked with value computation and definition although less so than the caudate and more in the area of information processing and storage. Jang et al. reported a link between the putamen and hippocampus with the inter-regional connectivity associated with binding of more abstract information such as attentional state, emotional state that could be recorded with the specific data information to the stimulus and reward in order to increase the chance of perception and appropriate behavioural response.

The description given above for the role of the caudate and putamen relates to the traditionally called dorsal striatum although in the case of Marche, Martel and Apicella`s study this covers both the limbic and associative striatum areas. Although they do not include the NA in their studies this particular area (traditionally termed the ventral striatum and linked with the olfactory bulb) is known to play an important role in values and again relies on the activity of the dopaminergic neurochemical system. Wieland et al. found that phasic dopamine is involved in the assignment of values to stimuli and synaptic plasticity was specific depending on input. West et al. also found that NA neurons encode features of stimulus and behaviour learning and selection associated with rewards. Cue-selective encoding during training by the NA core neurons reliably predicted subsequent behaviour whereas NA shell neurons significantly decreased cue-selective encoding in the devalued condition compared with the non-devalued condition. This indicated that even the NA demonstrated regional specificity to value.

In addition to its role in encoding and retrieving value, the striatum has also been shown to play a role in expectation of reward and the subsequent updating of information on the basis of feedback. These functions can be adequately investigated using conditioning experiments, one of which was carried out by Marche, Martel and Apicella. For example, the striatum is known to play a key role in reinforcement learning specifically in the encoding of the teaching signals such as reward prediction errors (RPEs). The attribution of incorrect values is associated with impaired coding of RPE and an increased turnover of dopamine in the striatum (particularly in the ventral striatal region) and prefrontal cortex connectivity (Boehme et al.). Both negative and positive expectations are linked with striatal activity. For example, negative expectations influence behaviour with activity of the head of the caudate plus NA. In addition activity in the ACC, PFC (including mPFC and OFC), left hippocampus, insular cortex, insular cortex and amygdala plus others is observed whereas positive expectations are linked with the striatum and particularly the NA as well as the dorsolateral PFC, ACC and frontal operculum. The list shows that multiple areas are involved and hence, it is difficult to distinguish unique roles for the dorsal and ventral striatal regions alone. Therefore, higher levels of research are carried out on the other strong cognitive areas such as the ventromedial PFC, VTA and ACC.

However, it is known that the dopaminergic system is involved in the expectation and receipt of expected reward as well as unexpected reward timing and character and striatal areas are known to have dopaminergic functioning. The ability to predict favourable outcomes is said to require dopamine release once the conditioned sequence of events is learnt. At first, dopamine release occurs with the presentation of the reward leading to signaling a predictive cue onset after learning (Day et al.).  Eschel et al. found marked homogeneity among individual dopamine neurons with their responses to both unexpected and expected rewards following the same function, but just scaled up or down. As a result, they were able to describe both individual and population responses using just two parameters. Research narrows this type of functioning to the traditionally termed ventral striatum and particularly the NA, which was not part of the experimental model used by Marche, Martel and Apicella. However, NA neurons demonstrated a subtlety of the system with subsets of NA neurons being responsible for particular responses. Owesson-Wright et al. found that DA neurons that projected from the VTA to the NA fired in response to predicted and unpredicted rewards or cues. Both cue presentation and action caused dopamine release that predicted reward delivery, but distinct populations of NA neurons were found to encode the behavioral events at the same specific locations selectively. This was thought possible through different dopamine receptor population activity. A subset of DA-2 receptors mediated responses to the cue whereas the dopamine responses acting after the performance of the required behavioural action was found to be the DA-1 receptor.

This capability of expectation can also be linked to the opposite, that of unexpected reward whether relating to timing or character. Again, such a function is correlated to dopaminergic system functioning in the striatum such as in unpredicted reward in conditioning experiments (Redgrave et al. and Steinberg et al.). The signal requires a reporting of errors in reward prediction (Niv et al.) which Steinberg et al. found required strong activation of midbrain dopamine neurons. The phasic signal which signals the discrepancies between actual and expected outcomes (the so-called reward prediction error) represented an opportunity for new learning (ie. updating) which is well known in conditioning experiments, as that occurring in extinction for example. Again it appears that the VTA-NA connectivity is important. Chowdhury et al. found that abnormal expected values resulted in healthy elderly subjects exhibiting incomplete RPEs in the NA and this signal was tightly coupled to inter-individual differences in the connectivity between the VTA and NA as indicated above. In their experiments the administration of the dopamine precursor L-DOPA increased task performance as it restored the necessary dopaminergic system. Such errors in reward prediction or unexpected rewards whether due to timing or character require the updating of stored information and this too, appears to require striatal involvement particularly the caudate (Chiu et al.) and its dopamine functioning (Diederen et al.).

Therefore, we can see that the striatum is important in the encoding and retrieval of values and particular regions have specific functions. We can assume that these areas function like other brain regions and have a number of excitatory and inhibitory cells whose activity is linked to the demands of the area`s function at that time. There is a lot of research on excitatory neuronal cells particularly the glutamate and dopamine regulated cells and also certain inhibitory cells particularly the GABA regulated ones. Marche, Martel and Apicella instead investigated a particular subset of excitatory neurons found in the striatum, which we have to assume are important for the correct functioning of those areas. Therefore, we have to ask what are these TANs there for particularly when there are other excitatory mechanisms in place? However, before we continue we have to discuss the work on TANs of this region by others, particularly that of Garr (2016) because not all Marche, Martel and Apicella`s conclusions support the views of others. Garr also described a subset of tonically active interneurons (TANs) in the striatum that are also cholinergic and were said to modulate medium spiny neurons (MSN) excitability and sensitivity to cortical input. Just like Marche, Martel and Apicella, these interneurons were found at a population level, to respond to motivationally relevant stimuli with a pause in firing followed by a subsequent increase in firing above baseline (the rebound). In the case of Marche, Martel and Apicella this population was found to be just 3% of the total striatal neuronal cell population and only 62 cells responded in total with 21 responding to only one event. Both Garr and the authors here appear to agree that the patterns observed in the population may not accurately represent the responses of the individual cells and Marche, Martel and Apicella compared both in their study.

On closer investigation of the conditioning experiments used by both sets of investigators, certain discrepancies appear. In the case of Garr, the action of the TANs was investigated using a conditioning task where the two monkeys used were trained to press a lever for a water reward in the presence of the following two cues: one that signaled the amount of force required for a successful response (high or low force) and one that signaled the magnitude of the reward to be earned (high or low reward). The experimental set-up gave four cue combinations: low force/high reward; high force/high reward; low force/low reward; or high force/low reward and after training the results collected from the TANs showed that the majority of them were located in the caudate nucleus. This correlates to the results of Marche, Martel and Apicella who found that limbic and associative regions both containing caudate regions had higher levels of TANs (71, 80% for stimuli response and 52%, 100% for reward response) than the motor region that consisted only of the putamen region.

The TANs in both studies demonstrated the typical TAN firing responses of pause followed by increase in firing (rebound) in response to both the cue and reward. However, in Garr`s study the TANs activity was investigated further and they were found to be separate groups modulated during the two task demands ie. the TANs that paused in response to the cue presentation were generally not the same cells that paused in response to reward delivery, and the same was true for increases in firing. Garr found that few TANs showed a pause during cue presentation, but many showed an elevation response. This could indicate that other excitatory TAN cells are fired rather than just those exhibiting the distinctive firing pattern. These firing cells could relate to the information processing capability of the striatum in binding information of the event with the activity of the hippocampus as given above. Following the delivery of the reward, a similar number of TANs responded with pauses and rebounds which indicate that these are the interneurons associated with reward value and expectation as indicated above to elicit striatal motivational salience function. This supports Garr`s interpretation of results which showed that the majority of pauses preceded the lever press (behavioural action required in this conditioning experiment) and the majority of rebounds coincided with the lever press. If the above view is correct then the ´rebounds` would coincide with the assessment of the value of performing the lever press to obtain the reward (expected and feedback) and may not reflect the same cell firing as that experienced by the reward response.

Garr`s experiments also looked at the effect of effort in performing the action (ie. force modulation) against the size of the reward (eg. high or low water). He found that the magnitude of the pauses and rebounds during the cue and reward stages were dependent on the trial type with separate groups of TANs modulated by the amount of required force and the amount of reward. Only few TANS responded to the cue with pauses, but more were found to rebound. The vast majority was modulated only during the high-force trials and these were seen to be separate from those showing reward magnitude-modulated rebounds during cue presentation where the vast majority of these were modulated during low-reward trials. Therefore, Garr interpreted his results as the presence of two separate groups: one firing for high-force trials, and one for low-reward trials. This correlates to the interpretation given above that the TANS ´rebounds` would correlate to value assessment of the lever press reward.

Therefore, Garr concluded that there were different populations of TANs in the striatum responding to different stages of the condition task and even to different conditions (eg. effort and reward size). Marche, Martel and Apicella did not go into the same depth of conditions that Garr did preferring to look at reward timing, but they did show to some extent a difference in TAN populations that went beyond the limbic and associative striatal location. They found that in relation to their fixed interval reward trials that the proportion of TANs responding to the stimulus was on average 70% and to reward 72% and indicated that the same cells are likely to respond to both even though they showed that  a third of their TANs only responded to one or the other. They showed that the proportion of TANs responding to the stimuli did not vary significantly with region (58-80%) whereas they did for reward (65% motor, 52% associative and 100% limbic). In each case the subtle differences may be masked by averaging. For example, a closer look at the results shows that more cells in the associative region respond to the stimuli than to the reward (71% to 52%) and conversely, more cells respond to the reward in the limbic system than to the stimuli (80% to 100%). The duration and magnitudes of the responses were the same so it can be said that the studied responses are TAN cell responses. The results obtained indicate a difference in caudate and putamen functioning dependent on location and task demand. Dorsally located TANs in the caudate and putamen are more active during stimulus presentation and stimulus response and ventrally located TANs in the caudate and putamen are more active during reward presentation and reward response. This may be loosely translated to the functions attributed to dorsal and ventral striatal regions given above although we must assume that term ´ventral` relates to caudate and putamen areas and not just nucleus accumbens as given in the more traditional definitions. Dorsal areas are linked to the computing of options and personal reward value as well as binding of abstract information that may aid in the assessment. Therefore, this definition of function supports the observation that TANs are more active in the dorsal caudate and putamen (associative areas) during the stimulus presentation ie. when value of cue and learnt reward are assessed. The observation that ventrally located TANs in the caudate and putamen are more active during reward presentation and response may support the role of ventral areas in expectation of reward, but may be indicative of specific location of function as given by Garr in his study above where cells responded to different levels of effort and reward.

So we have discussed why the TANs are there functionally, but why are they present from a neurochemical perspective? Why not just a set of normal-acting firing excitatory neurons or interneurons rather than cells that fire, stop firing and then fire again? We know that the mechanism for firing is acetylcholine binding and this results in dopamine release and we have to assume that the pauses are brought about by mechanisms responsible for hyperpolarization of firing cells (eg. GABA binding or chloride ion/potassium ion channel opening). These characteristics are shared by other neuronal cell types that are also present in the striatum. In fact, the principle type of cell in this area constituting 95% of the population are medium spiny neurons (MSN) which are GABAergic inhibitory neurons. They too can be influenced by dopamine and this leads to 2 subpopulations of neurons depending on the presence of DA1 type and DA2 type receptors with 40% of cells having both. The interneuron population consists of excitatory and inhibitory cells. The inhibitory interneurons are GABAergic and are of many different types. The best known are the parvalbumin expressing interneurons (also known as fast-spiking interneurons) which are responsible for fast feedforward inhibition of the principle neurons, but there are also types responding to tyrosine hydroxylase, somatostatin, nitric oxide synthase and neuropeptide-y. The excitatory interneurons of which TANs are a subset also influence striatal cell firing and are influenced by both dopamine (via DA5 receptor) and acetylcholine. For example, large aspiny interneurons release acetylcholine and respond to the salient environment with stereotypical responses which are temporally aligned with responses of DA neurons of the substantia nigra.

Therefore, the first possible reason for the presence of TANs in the striatum is the fine control of firing within the striatum itself and between it and other brain areas. The striatum must perform neurochemically to fulfil its cognitive demands which in the case of conditioning means reacting to sensory input, informational processing in the working memory state of input and value of reward, long term storage of information and its subsequent recall on repetition of trial conditions plus monitoring of expected reward.  The striatum must also be linked to other areas that perform these functions. Interneuron functioning allows control of overall striatal functioning by switching on and switching off adjoining neurons and interneurons and this type of modulatory control can be seen in other areas. For example the firing of the GABA interneurons in the hippocampus is linked to short term responses to repeated stimuli, also a requirement in the learning the task in the conditioning experiments carried out in this article. In the hippocampus, pyramidal neurons represent the major postsynaptic target of most interneurons, whereas a small fraction of synaptic contacts (5–15%) from interneurons is made onto other GABAergic cells. The GABA interneurons that innervate each other (the so-called interneuron-specific interneurons) are controlled via specific inhibitory mechanisms.  In this example, information reaches the pyramidal cells of the CA3 region in the hippocampus via mossy fibre synapses made by dentate gyrus (DG) cell axons whereas small terminals and filopodial extensions target GABA containing interneurons. These synapses are unusual since they exhibit low basal release probability, pronounced frequency facilitation and exhibit a lack of involvement of the glutamate receptor, NMDA receptor in long-term potentiation (LTP). Synaptically released glutamate mediates both negative and positive feedback acting on presynaptic metabotropic glutamate receptors and kainite receptors, but no post-synaptic activation of NMDA receptors.  LTP at the mossy fibre pyramidal synapses occurs through the increase in neurotransmitter release, presynaptic binding, presynaptic calcium ion release and activation of presynaptic adenylate cyclase. The mossy fibre interneuron interaction range of short-term responses to repetitive stimulation goes from pronounced depression to modest facilitation of the firing. This is also seen in the excitatory cholinergic interneuron firing of the TAN subset of cells in the striatum. In the case of the hippocampus cells, glutamate released here activates post synaptic AMPA receptors and this calcium-permeable AMPA receptor activation leads to NMDA receptor-independent LTP and presynaptic decrease in neurotransmitter release whereas activation of calcium-impermeable AMPA receptors shows robust NMDA receptor-dependent LTP and down regulation of post-synaptic population of AMPA receptors (Nicoll et al.).

The TAN firing can also control activation that stems from outside the region. For example in the case of hippocampal long-range input interneurons, the activity of these cells can be controlled by extrinsic GABAergic projections: one arising from the medial septum (MS) and the other from the medial entorhinal cortex (MEC). Activation of the septal GABAergic afferents produces a silencing of interneurons and is associated with rescinding inhibition in the adjoining pyramidal cells. Two distinct populations of MS interneurons have been identified for this function: fast-firing and burst-firing cells. A subset of these cells expresses hyperpolarization-activated and cyclic-nucleotide-gated non-selective cation channels and exhibits firing and rebound spiking in response to rhythmic inhibition. These MS interneurons show a different phase preference during hippocampal theta activity and are thought to target different types of hippocampal interneurons cells that are active at the positive peak of the theta oscillation control dendritic inhibition of the CA1 pyramidal cells.

Therefore, TANs may be a unique subset of interneurons that control firing in the striatum via their own short-range interactions or long-range connectivity. The second reason for having TANs is that the TANs may keep the firing of the area ´ticking over` when there is no outside stimulus since the interneuronal subset also demonstrates tonic activity. The experiments of Marche, Martel and Apicella were performed with a conditioning task and therefore, there were definite responses to stimuli and reward. However, TANs can fire spontaneously and this has been observed with other neurons and interneurons within the striatum. Yorgason and colleagues showed that certain neurons in the NA (part of the traditional ventral striatum) demonstrate spontaneous DA release which is regulated by a number of factors including voltage-gated ion channels, DA2-autoreceptors, and nicotinic acetylcholine receptors (also seen in TAN cells) on cholinergic interneurons. The spontaneous release was described as infrequent (0.3 per minute), but the rate and amplitude of the firing were increased after blocking the potassium Kv channels. The firing of these cholinergic interneuron cells could be increased by a number of different factors eg. blocking glutamate reuptake, but it was found that only the effect on potassium kv channels influenced dopamine release. This could indicate that spontaneous dopamine release via cholinergic interneurons in the NA area are independent of stimulus activated firing and could be responsible as suggested above for ´ticking-over` like functionality, a role played by TANs in the caudate and putamen striatal regions observed by Marche, Martel and Apicella. However, this hypothesis is unlikely since the area is inclined to be permanently active to some degree because of its functioning (eg. value assessment) and connectivity to the major sensory input and processing brain areas (eg. VTA, PFC).

Another possible reason for the existence of TANs is that their activity may also compensate for the refractory periods of activated neuronal cells during task performance. This would allow continuity of firing that could satisfy the conditions required for learning (eg. sustained firing) or information processing (eg.  theta wave synchrony of multiple brain areas). This hypothesis could be supported by the fact that the pauses come after the stimulus or reward at times when there is peak activity from other firing cells within the striatum and established connectivity to other areas and rebounds when those cells reach their refractory periods and stop firing in order to replenish their neurochemical stores and restore firing capability.  In the case of LTP, a condition for long-term memory required in the correct performance of conditioning tasks, the continued activation of the area may require not only synaptic plasticity of the neuronal cells, but also of the interneurons too. LTP and long-term depression (LTD) have been found at GABAergic interneuron synapsing onto other cells eg. the pyramidal cells of the PFC, but the mechanisms of plasticity at these GABAergic synapses may differ significantly from those formed onto neuronal cells. For example, it has found that LTP occurs in both RAD interneurons and CA1 pyramidal cells and can be induced by theta-burst synaptic stimulation, but they are regulated differently. In the pyramidal cells, LTP is mediated by the activation of both GABA B receptors and a group of metabotropic glutamate receptors, whereas in interneurons, neither is required. This compensation for refractory periods can also be linked to the maintenance of firing so that synchronous firing of multiple brain areas can occur. We have already seen the extent of connectivity of the striatal regions in the establishment of values and their assessment and this has been linked to theta brain wave activity. For example, Murty and colleagues found that there was increased connectivity of category-selective visual cortex with both the VTA and the anterior hippocampus that predicted associative memory for high- but not low-reward memories and therefore, maintenance of synchronous firing is important for the value assessment process.

A fourth reason for the presence of TANs and their distinctive firing pattern relates again to their possible role in switching on or off neurons by aiding the establishment of temporal coordination of firing. In conditioning tasks and others where there is a distinctive order eg. stimulus-to-behaviour, the switching on-off ´pulsing` of interneuron firing could be akin to that seen in Morse code signaling. The switch-off periods would stop firing for a period after the stimulus or reward as given in the case of Marche and colleagues experiments, hence providing a distinctive period for informational content for the two parts of the task. This would of course be contrary to the third reason for their presence given above that of sustaining firing during the refractory periods since it would require the shut-down signal to be shared simultaneously by other cells in the area and this has to date not been shown. However, temporal coordination of neuronal activity via several types of cortical GABAergic interneurons has been shown in the hippocampus and extra-hippocortical areas. For example, Unal et al. suggested that oscillatory septal neuronal firing at delta, theta, and gamma synchrony frequencies during stimulus may phase interneuron activity and Jacobs et al. has also linked hippocampus cells to informational timing. Allen et al. showed that hippocampal activity differed depending on the temporal context of items. Salz et al. found that CA3 cells exhibited robust temporal modulation similar to the pattern of timed cell activity in the CA1 and the same populations of cells also exhibited typical place coding patterns in the same task. Middleton et al. investigated further and found that silencing CA3 cells disrupted temporal coding in the CA1 with gamma synchrony important for information binding temporal context and background timing was given by theta synchrony. The hippocampus may, because of its natural spiral physical structure and forced order of firing (eg. DG firing to CA3 to CA1), have natural conditions for timing and order that cannot be achieved through the striatum`s physiology and therefore, the TANs may establish the firing conditions necessary for temporal order of information.

Therefore, we can conclude that TANs although only a small subset of excitatory interneurons in the striatal regions must have a function important to the role that these brain areas have in event salience. They again, confirm the complexity of neurochemical systems in the brain and the need for detailed investigation and understanding of not only neuronal firing, but internal and external brain area connectivity. It is unlikely that manipulation by external means of such a small subset of neurons is possible in order to gain cognitive advantage not only because of their population size but also because they appear to work and be regulated by the ´giants` of the neurochemical world such as acetylcholine and dopamine. However, investigation does lead to a greater understanding of how brain area cognitive functioning relates to neurochemical mechanisms and should be continued.

Since we`re talking about the topic…………………………….

………can we assume that conditioning experiments of the type performed by the authors, but demonstrating successive approximation learning or extinction would lead to no change in the distinctive TAN firing pattern for either if the function of the TANs is to exert fine control over general striatal firing or compensate for refractory periods of other firing cells so sustained firing is achieved?

………if fear conditioning experiments were performed instead of positive reward ones would striatal firing be reduced and hence, a reduction in TAN firing population be observed because of an increase in firing to other brain areas such as the amygdala rather than the striatum?

……..would the administration of the GABA blocker etomidate establish a role of GABA in TAN firing in the conditioning experiment?

…….sleep deprivation is said to increase motivation for reward. Therefore, if the conditioning experiments were performed with sleep deprived subjects would an increase in TAN population number be observed and if so, would this reflect that the extent of TAN firing itself reflecting personal values rather than being a product of firing of other excitatory cells present in the striatal areas?

 

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