The art of scaling up : a computational account on action selection in basal ganglia
Year: 2016
Type: conference-paper
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.
Source: HAL
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2735896532