Evolutionary game theory and the evolution of neuron populations, ring rates, and decisionmaking
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- Department of Fisheries, Wildlife and Conservation Biology, University of Minnesota
- Vanderbilt Vision Research Center, Vanderbilt Brain Institute, Department of Psychology, Vanderbilt University
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- Document Type:
- Manuscript
- Date:
- Received 25 June 2009 19:04 UTC; Posted 29 June 2009
- Subjects:
- Neuroscience
- Abstract:
Ours, is the first application of dynamical evolutionary games to decision making in neuroscience. Firing neurons are the players. The strategy is their firing rate. Neurons with equal firing rates define a population. The neurons do not know the rules of the game, they do not know what the reward is, they are not required to be rational and they do not even know they are playing the game. Interactions are inhibitory. The theory confirms experimental data about decision making in vision: (i ) A parameter of the game model determines how many populations of neurons participate in the decision; (ii ) the solution of the game dictates how many loci in the brain participate in the decision; (iii ) the theory clarifies the difference between ultimate and proximate factors and predicts that quick decisions are associated with more errors and slow decision are associated with fewer errors.
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- This document is licensed to the public under the Creative Commons Attribution 3.0 License
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Cohen, Yosef and Cohen, Jeremiah. Evolutionary game theory and the evolution of neuron populations, ring rates, and decisionmaking. Available from Nature Precedings <http://hdl.handle.net/10101/npre.2009.3373.1> (2009)
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