Extending a biologically inspired model of choice: multi-alternatives, nonlinearity and value-based multidimensional choice.

The leaky competing accumulator (LCA) is a biologically inspired model of choice. It describes the processes of leaky accumulation and competition observed in neuronal populations during choice tasks and it accounts for reaction time distributions observed in psychophysical experiments. This paper d...

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Main Authors: Bogacz, R, Usher, M, Zhang, J, McClelland, J
Format: Conference item
Published: 2007
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author Bogacz, R
Usher, M
Zhang, J
McClelland, J
author_facet Bogacz, R
Usher, M
Zhang, J
McClelland, J
author_sort Bogacz, R
collection OXFORD
description The leaky competing accumulator (LCA) is a biologically inspired model of choice. It describes the processes of leaky accumulation and competition observed in neuronal populations during choice tasks and it accounts for reaction time distributions observed in psychophysical experiments. This paper discusses recent analyses and extensions of the LCA model. First, it reviews the dynamics and examines the conditions that make the model achieve optimal performance. Second, it shows that nonlinearities of the type present in biological neurons improve performance when the number of choice alternatives increases. Third, the model is extended to value-based choice, where it is shown that nonlinearities in the value function explain risk aversion in risky choice and preference reversals in choice between alternatives characterized across multiple dimensions.
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spelling oxford-uuid:184fbb67-5d36-417b-bee3-1aa4227980882022-03-26T10:42:42ZExtending a biologically inspired model of choice: multi-alternatives, nonlinearity and value-based multidimensional choice.Conference itemhttp://purl.org/coar/resource_type/c_5794uuid:184fbb67-5d36-417b-bee3-1aa422798088Symplectic Elements at Oxford2007Bogacz, RUsher, MZhang, JMcClelland, JThe leaky competing accumulator (LCA) is a biologically inspired model of choice. It describes the processes of leaky accumulation and competition observed in neuronal populations during choice tasks and it accounts for reaction time distributions observed in psychophysical experiments. This paper discusses recent analyses and extensions of the LCA model. First, it reviews the dynamics and examines the conditions that make the model achieve optimal performance. Second, it shows that nonlinearities of the type present in biological neurons improve performance when the number of choice alternatives increases. Third, the model is extended to value-based choice, where it is shown that nonlinearities in the value function explain risk aversion in risky choice and preference reversals in choice between alternatives characterized across multiple dimensions.
spellingShingle Bogacz, R
Usher, M
Zhang, J
McClelland, J
Extending a biologically inspired model of choice: multi-alternatives, nonlinearity and value-based multidimensional choice.
title Extending a biologically inspired model of choice: multi-alternatives, nonlinearity and value-based multidimensional choice.
title_full Extending a biologically inspired model of choice: multi-alternatives, nonlinearity and value-based multidimensional choice.
title_fullStr Extending a biologically inspired model of choice: multi-alternatives, nonlinearity and value-based multidimensional choice.
title_full_unstemmed Extending a biologically inspired model of choice: multi-alternatives, nonlinearity and value-based multidimensional choice.
title_short Extending a biologically inspired model of choice: multi-alternatives, nonlinearity and value-based multidimensional choice.
title_sort extending a biologically inspired model of choice multi alternatives nonlinearity and value based multidimensional choice
work_keys_str_mv AT bogaczr extendingabiologicallyinspiredmodelofchoicemultialternativesnonlinearityandvaluebasedmultidimensionalchoice
AT usherm extendingabiologicallyinspiredmodelofchoicemultialternativesnonlinearityandvaluebasedmultidimensionalchoice
AT zhangj extendingabiologicallyinspiredmodelofchoicemultialternativesnonlinearityandvaluebasedmultidimensionalchoice
AT mcclellandj extendingabiologicallyinspiredmodelofchoicemultialternativesnonlinearityandvaluebasedmultidimensionalchoice