The art of scaling up : a computational account on action selection in basal ganglia

Bhargav Teja Nallapu 1 Nicolas P. Rougier 2, 3 Bapi Raju Surampudi 1
3 Mnemosyne - Mnemonic Synergy
LaBRI - Laboratoire Bordelais de Recherche en Informatique, Inria Bordeaux - Sud-Ouest, IMN - Institut des Maladies Neurodégénératives [Bordeaux]
Abstract : What makes a model 'large scale' ? Is it the number of neu-rons modeled? Or the number of structures modeled in a network? Most of the higher cognitive processes span across coordinated activity in different brain areas. However at the same time, the basic information transfer takes place at a single neuron level, together with multiple other neurons. We explore modeling a neural system involving some areas of cortex, the basal ganglia (BG) and thalamus for the process of decision making, using a large-scale neural engineering framework, Nengo. Early results tend to replicate the known neural activity patterns as found in the previous action selection model [2], besides operating with a larger neuronal populations. The power of converting algorithms to efficiently weighed neural networks in Nengo [10, 1] is exploited in this work. Crucial aspects in a computational model, like parameter tuning and detailed neural implementations, while moving from a simplistic to large-scale model, are studied.
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Bhargav Teja Nallapu, Nicolas P. Rougier, Bapi Raju Surampudi. The art of scaling up : a computational account on action selection in basal ganglia. 3rd Annual Conference on Cognitive Science (ACCS 2016), Oct 2016, Gandhinagar, India. ⟨hal-01354041⟩

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