rat perirhinal cortical firing represents more than one object characteristic

Posted comment on ´Neural Correlates of Object-Associated Choice Behaviour in the Perirhinal Cortex of Rats` by J-R. Ahn and I. Lee published in Journal of Neuroscience 28th January 2015, vol 35(4) p. 1692


The aim of Ahn and Lee`s study was to investigate whether in rats the perirhinal cortex was involved in the neural correlates relating to the visual processing of just objects, as in the case of primates, or whether other factors such as location and choice were also recorded. Rats were trained in an object-cued spatial choice (OCSC) task which required them looking at a picture on a screen which was then removed and replaced by two discs. The study rat had to press where the picture had been shown. If the press response was correct, the rat was given a food reward and a sound played. Once the rats were trained appropriately, hyperdrive (a microdrive array of 16 tetrodes) implantation surgery was performed in the right hemisphere close to the perirhinal cortex.
The rats were also tested to discern ambiguity in the given pictures. In these ambiguity sessions (AMB) the objects were changed using computer software into a range of 12 different pictures for each object. A reward was given for the correct location of half the images closest to the appearance of the standard object. Involvement of the perirhinal cortex was investigated by implanting cannulae with either saline (control) or muscimol, a GABA receptor agonist. The spread of the muscimol was observed using epifluorescence microscopy and head and eye direction was also recorded. The activity of 100 neurons in the area was measured and this was recorded twice – once in the pre-choice period (object onset to choice) and once post-choice (choice to food-tray entry plus auditory feedback).
Ahn and Lee found that the perirhinal cortex was required for their OCSC task with 80% correct responses for the standard objects session and 70% for the AMB depending on the level of picture ambiguity. Use of muscimol indicated that normal responses were mainly located in the A36 area which has rich visual inputs. Muscimol led to a decrease in standard performance indicating perirhinal involvement of GABA dependent neurons.
The spiking properties of the active perirhinal neurons were also investigated. Ahn and Lee found on analysis of mean firing rates that the neurons could be categorized as putative interneurons with a firing rate of 250microHZ in spike width whereas the rest were probably pyramidal neurons. A calculation of mean spike width found that it was about 2.5 times greater for the pyramidal cells with firing rates twice as high. Three types of firing were found in the perirhinal cortex: bursting neurons (20%), regular spiking neurons (72%), and unclassified neurons (8%). Analysis of the firing results led Ahn and Lee to the conclusion that neural activity in the area was strongly modulated by the critical events in the given OCSC task. Firing rates either increased or decreased with a majority of 83% from the baseline before and after the choice response was made. 19% caused firing before choice and 22% after, 59% for both pre and after. The direction of the firing for the majority of cells was opposite pre- and post-choice with the majority demonstrating excitatory firing. There were also a few mixed patterns.

Ahn and Lee also demonstrated with their experiments that neuronal discharge in the perirhinal cortex was modulated by both the object cue and its associated response, but not by the object alone. Bubble charts were constructed for each neuron looking at the left or right choices linked to the object. The researchers found in the pre-choice period nearly 28% of neurons fired specifically for a particular choice response and only 18% in the post-period. Hence, perirhinal cortex neurons were firing specifically for particular spatial responses often in conjunction with the cueing object, but the exclusive object-specific firing was rarely observed.
Ahn and Lee also found that the activity of the neuronal population in the perirhinal cortex was influenced by the perceptual ambiguity of the test object. In the pre-choice period, a very low level of single unit neurons showed firing patterns significantly correlating to ambiguity, but it was observed in firing populations. The similarity in the population firing patterns associated with the original object became disrupted as the ambiguity level rose for both the toy object categories (slow rise) and abrupt for the egg object.
Ahn and Lee also reported that neuronal firing of the perirhinal cortex was strongly mediated by choice outcome. Many perirhinal cortex neurons conveyed uniting information for object identity and response in the post-choice period and this could be closely related to the choice response and its outcome given by the auditory feedback. This could have the function as a feedback signal which could have influenced the decision in the next trial. It was found that the firing was not linked to whether the responses were correct or not, neither was there any reward expectation. The selective neurons found in the post-choice period were of 2 subtypes: correct-up cells (firing increased following correct choices) and error-up (firing increased following error choices) cells. Ahn and Lee looked at whether pre-choice cells were better predictors of upcoming response and found that the error-up category predicted upcoming choice response better for the next trial, but not for those several trials later. The correct-up cells were found not to significantly influence the choice response in the next trial.
Ahn and Lee´s investigation of rat perirhinal cortex found differences to that of primates. Although they found that the perirhinal cortex was essential for object recognition, they also found that the neurons in this region rarely signalled object-specific information before making a choice. Ahn and Lee speculated on why such a difference exists. For example in primate studies, there are broader inferotemporal areas including the perirhinal cortex and enterorhinal cortex and that species-species differences may exist relating to function with object recognition being earlier in the brain hierarchy than the rat. A difference in behavioural paradigms may also account for the difference, e.g. sensory differences such as rats with 3D capability and primates 2D with rats tuned to multimodality. Also test differences may play a role with for example the inclusion of delay for primates, but not here in the case of the rat.
The author`s study also demonstrated in the case of the rat concurrent processing of spatial and object information. Hence, communication between the perirhinal cortex and postrhinal cortex was essential. Previous research showed the perirhinal cortex as being responsible for non-spatial information and the postrrhinal cortex for spatial, but the experiments of Ahn and Lee showed that single units in the postrhinal cortex conveyed information for both object and space. Other studies also show specific location neurons in the perirhinal cortex and other theories position the perirhinal cortex at the final stage of visual perception in the ventral, WHAT pathway. Ambiguity produced mixed results in other research, but in Ahn and Lee´s investigation, appropriate firing was clearly demonstrated at the population level. Morphing the toy object found that the ambiguity influenced outer shape, with the inner details being preserved. The opposite was found with the egg shape. Therefore, the results suggested that the perirhinal cortex was important for detailed visual features, but not shape and contour.
Ahn and Lee`s study also found significant outcome-dependent modulation of perirhinal cortex neuronal activity after the test rat had made a choice response. This could be interpreted as a feedback of choice, but other research also found involvement of other areas, e.g. prefrontal cortex (dorsomedial and medial), striatum and hippocampus. It was found here that strong error-driven signals attributed to strong connections between the perirhinal cortex and the amygdala. In the case of a correct response, connectivity might have stemmed from strong dopaminergic projections to the perirhinal cortex from the subcortical regions including ventral tegmental area, ventral striatum, and substantia nigra.
Therefore, Ahn and Lee concluded that the perirhinal cortex in rats may be responsible for more than just object memory when choice is involved after recognition. The area may provide neuronal space in which a variety of object-associated variables e.g. emotional significance, motivational feedback, response requirements can be represented dynamically according to task demands.


The investigation of Ahn and Lee is interesting because it demonstrates a difference between systems and mechanisms in the rat and human brain. This observation poses a problem because conclusions about systems and mechanisms and deductions about mental health matters such as Alzheimer`s disease are quite often made using mice or rat models. Therefore, the usage of such an experimental system may not be as simple or effective as once indicated.
Ahn and Lee in their article describe their investigation of a type of conditioning task on the activity of the inferotemporal region, the perirhinal cortex. They linked a visual stimulus to an action which was subsequently rewarded if correctly performed. The test involved a learning period and test period where firing activity of the relevant areas was recorded. The systems involved in the test were ones usually required for conditional tasks, such as attention, visual input and processing, working memory, decision-making and memory and hence, required multiple brain area activation. During the test phase Ahn and Lee looked at the activity of particular areas such as the post-rhinal cortex (POR) and perirhinal cortex (PRC). These can be considered normal areas to look at since it has been previously reported that in conditioning, the basolateral amygdala increases transmission from the PRC to the entorhinal cortex (EC) when presented with an unexpected reward. Activity in the PRC is found to be inhibited by the administration of muscimol implying the involvement of GABA and previous research has shown interneurons in the hippocampus or dopamine neuromodulation of GABA receptors in the striatum. GABA dysfunction with age has also been reported leading to decreased working memory and this would apply in this case since working memory would be required to distinguish during the learning period between correct and false responses and also in the test of the ambiguous pictures.
The role of PRC or EC is important because of its alleged association with dementia in humans. As stated by Ahn and Lee, there are two pathways for object processing in the medial temporal lobe – spatial memory (processed in the POR to medial EC and then to the hippocampus) and non-spatial memory (perirhinal cortex to lateral EC to hippocampus). There is much evidence of the role of the PRC in object recognition in primates and Ahn and Lee`s study shows that although the neurons of the PRC of the rat are involved in object recognition, they are representative of slightly different information to that of primates. In the rat, PRC neurons are suggested as being linked to multiple object characteristics such as object image and space. The idea of multi-informational neurons is not new. For example, hippocampal neurons link information about the object and location in the case of spatial memory and of course, the hippocampus is strongly connected to firing of the PRC and EC. The concept of multi-functional neurons has also been suggested (Messinger) as in multi-tasking neurons linked to working memory and attentional functions.
An explanation to the multi-informational neurons in the PRC suggested here could be that they follow that of the hippocampal place cells that record object and location in spatial memory. It is possible that the visual object characteristics are linked to location with respect to the screen frame. The rat deduces and learns that the position of the object relative to the screen frame or edge is an important reference point that needs to be remembered in order to receive the reward. This may explain the discrepancy between human PRC functioning and rat. In human visual processing remembering the picture of a house would count as a single unit. The windows of the house would be referenced to one another and it likely that once recognized they would be ignored. Constancy in human visual information, e.g. colour would mean that even if there are more objects, less information is required to be stored since constancy rules apply and hence, after initial learning conscious input of this information would be unnecessary. In humans, the context of the visual information would be important and this is thought to be the responsibility of the EC area.
In Ahn and Lee`s study visual information was linked with reward and the PRC was suggested as not only responsible for OR, but also stores other factors such as reward. Their view is substantiated by the fact that the PRC is heavily connected to the POR, with the POR having reciprocal connectivity to the medial EC, plus connectivity to the amygdala, striatum, ventral tegmentum which suggests reward related firing of these areas may modulate firing of the PRC. This is observed in typical conditioning situations.
An explanation of what is happening in the conditioning task may elucidate the connections further. In the pre-choice stage, cognitive processes are required for OR and decision-making (i.e. left or right disc). This is an example of both bottom-up and top-down processing and requires the association of the information concerning object image and location in the short-term memory. Only short-term memory is required since the response is required shortly after the presentation. As expected the PRC is activated in the rat and in humans, the same task would likely activate the EC. It is also likely that there is caudate activity which according to reports closely correlates to the rate of learning and peaks when new associations are acquired in learning tasks with reinforcement. The presentation of the discs causes memory recall of the visual image, the location and the required response so that the appropriate action is made, i.e. a mini sequence of learnt events. This probably correlates in some way to the three types of firing observed in the PRC neurons such as the small number of bursting neurons, larger number of spiking neurons and the few unclassified ones. Therefore, the neuronal firing in the PRC is as Ahn and Lee suggest modulated by both the object cue and associated response, but not by the object alone.
The post-choice period involves essentially the feedback of the informational input and the action taken. If the press response was correct then the study rat received a reward and heard a sound. Learning at this time associated the object and its position to the reward supplemented by a sound. Therefore, in the rat the olfactory, auditory and visual senses were all being used and information stored was multimodal. The conditioned reward probably was linked to activity in the caudate and orbitofrontal cortex (OFC). It is known that immediate and delayed rewards are represented by activity in the dorsal medial prefrontal cortex (PFC) and ventral PFC to guide decisions and that subjective value of the outcome by PFC and OFC linking events to reward values and representing contexts that guide memory retrieval. Connectivity has been reported to link EC activity and the PRC and to these particular brain areas.
In the post-choice phase, Ahn and Lee reported selective neurons in the PRC of 2 subtypes. One subtype of cells was termed correct-up cells (firing increased following correct choices) and the other, error-up (firing increased following error choices). When they looked at if pre-choice cells were better at predicting the upcoming response, they found that the error-up category predicted upcoming choice response better for the next trial, but not for those several trials later. Correct-up cells, however did not significantly influence the choice response in the next trial. This can be explained by the feedback setting up error signaling involving activity in the cingulate cortex and 41 other regions. Such a response would increase the attentional pathway activity so that the object images would be more closely observed in the following trials. Each trial would provide feedback so that the rat learns by repetition and each time the action is correct the connectivity would be strengthened.
The discrepancy in explanations of PRC activity between rat and human could therefore be the result of how humans discern this type of data and perform this type of task. There is little EC activity because the object is a single image, not part of a group and hence not in context. Humans are used to seeing multiple presentations of the same image. They also readily learn conditioning tasks and sequences of events. In the case of the rat, visual information is linked to the smell of food and hence, context is needed so the object image is linked to the visual frame location. In this case the PRC gives context and also strong connections to other areas linked to reward. This study indicates one of the problems in using mice or rat models to help elucidate cognitive functioning linked to area activity, e.g. Alzheimer`s illness linked to object recognition and memory and brain area dysfunction. Mice and rat models may provide easier vehicles for experimentation, but the differences in brain area activity and cognitive functions may lead to incorrect conclusions when results are transferred to human mechanisms.

Since we`re talking about the topic

….the ambiguity of object image was tested in this experiment, but what would happen if the position of the disc was also changed on each side? Would the activity of individual neurons change to either left or right independent of where the disc was actually located? Would image ambiguity be more difficult if black and white images were used?

…can we assume that if there is a delay between object presentation and choice of disc and then reward and auditory sound that neuronal activity in the PRC would remain the same, but the possibility of error would increase? Can we assume that the speed of the presentation and steps of the conditioning task could be increased to a point when the rat would find it impossible to respond correctly?

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