A computational model of basal ganglia involved in the cognitive control of visual perception

Abstract

Event Abstract Back to Event A computational model of basal ganglia involved in the cognitive control of visual perception Fred H. Hamker1* and Julien Vitay2 1 Technichal University Chemnitz, Computer Science Department, Germany 2 Westfalischen Wilhelms Universitat, Psychologisches Institut II, Germany Goal-directed visual perception requires to maintain and manipulate a template of the desired target in visual working memory (WM) that allows to bias processing in the posterior lobe. It is still unclear how such goal-directed perception is implemented in the brain. We propose that such interaction between visual WM and attentional processing involves a network of brain areas consisting of inferotemporal cortex (IT) for the retrieval of visual information associated to the target, dorsolateral-prefrontal cortex (dlPFC) for the manipulation and maintenance of the target template in face of distractors, medial temporal lobe (MTL) regions for rapid encoding and novelty detection, as well as basal ganglia (BG) for the switching and activation of WM representations in dlPFC.We designed a novel computational model of BG, while it interacts with a model of perirhinal cortex (PRh, part of the medial temporal lobe) and a simple model of dlPFC for memorizing objects, to explore how the BG might be involved in the cognitive control of visual perception. The BG model is composed of the striatum receiving connections from PRh and dlPFC. The striatum inhibits SNr which in turn tonically inhibits a thalamic nucleus interacting with PRh. Homeostatic Hebbian learning takes place simultaneously in the connections from cortical areas to the striatum (representing the context of of the task) and in the connections from striatum to SNr as well as within SNr (learning to retrieve the correct representation). Moreover, a dopaminergic cell learns to compute the difference between the reward actually received and the expectation of reward based on striatal representations and modulates learning in the other areas.We applied this model to simultaneously learn delayed matching-to-sample (DMS) and delayed nonmatching-to-sample (DNMS) tasks. Whether DMS or DNMS should be performed is defined by a contextual information presented after the sample and before the search array composed of two targets. Reward is given to the system when it selects the correct target through thalamic stimulation of PRh. The model has to represent efficiently the context in the striatum to solve the tasks and is able to learn them concurrently after 400 trials, independently of the number of cells in SNr, what denotes a parallel search of the correct representation. If at the beginning of learning, several cells in SNr can become selective for the same striatal pattern, the learned competition between them progressively selects the only one that disinhibits the correct target. The reward-predictive value of striatal representations also takes into account the probability of reward associated to an object.Similarly to the PVLV model of O'Reilly and Frank, our model reproduces the reward-related firing pattern of dopaminergic cells in conditioning. However, our model highlights the role of BG processing in visual WM processes, not only in its cognitive component but also in the retrieval of target information. It explains how vision can be guided by the goals of the task at hand. Conference: Bernstein Conference on Computational Neuroscience, Frankfurt am Main, Germany, 30 Sep - 2 Oct, 2009. Presentation Type: Poster Presentation Topic: Decision, control and reward Citation: Hamker FH and Vitay J (2009). A computational model of basal ganglia involved in the cognitive control of visual perception. Front. Comput. Neurosci. Conference Abstract: Bernstein Conference on Computational Neuroscience. doi: 10.3389/conf.neuro.10.2009.14.006 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 25 Aug 2009; Published Online: 25 Aug 2009. * Correspondence: Fred H Hamker, Technichal University Chemnitz, Computer Science Department, Chemnitz, Germany, fred.hamker@informatik.tu-chemnitz.de Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. 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