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How to Build a BrainA Neural Architecture for Biological Cognition$
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Chris Eliasmith

Print publication date: 2013

Print ISBN-13: 9780199794546

Published to Oxford Scholarship Online: January 2014

DOI: 10.1093/acprof:oso/9780199794546.001.0001

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. Biological Cognition–Memory and Learning

. Biological Cognition–Memory and Learning

(p.209) 6. Biological Cognition–Memory and Learning
How to Build a Brain

C. Eliasmith

X. Choo

T. Bekolay

Chris Eliasmith

Oxford University Press

This chapter is devoted to consideration of adaptive processes in neural processing. This adaptation includes both weight changes (what is usually meant by ‘learning’), and dynamic stability of network activity states (what is usually taken to be a model of ‘memory’). A serial working memory model is described in detail, that exploits the syntactic representations of the SPA. In addition, a biologically detailed spike-based learning rule is presented and applied to learning arbitrary vector functions, reinforcement learning, and explaining STDP effects. Finally, this rule is applied to a network that explains the results of the Wason Card Selection task. Tutorial: Learning in Nengo

Keywords:   learning, working memory, STDP, reinforcement learning, adaptation, Wason Card task

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