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[Illinois]: Midbrain dopamine neuron responses to temporal-difference learning

By Lisa Sproat

University of Illinois at Urbana-Champaign

Simulates the responses of midbrain dopamine neurons using temporal difference learning

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Version 1.1a - published on 19 Aug 2013

doi:10.4231/D30R9M41V cite this

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Abstract

This tool simulates the responses of midbrain dopamine neurons using temporal-difference learning as shown in the model below.

FIGURE 11.12 Temporal-difference learning implemented in a neural network model of the midbrain dopamine system. The input units xj project to the difference unit y over connections with weights values) vj (j = 1 , . . . , 20). The response of the difference unit y(t) is the difference between its weighted input sums at times t and t - 1. The difference unit y and the reward unit r project to the prediction error unit z over connections that both have weight 1. The response of the prediction error unit z(f) is the sum of its inputs from y and r at time t. The prediction error unit z represents a dopamine neuron.

This tool is built from the MATLAB scripts for Tutorial on Neural Systems Modeling by Thomas J. Anastasio.

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References

Anastasio, T. J. (2009). Tutorial on neural systems modeling. Sinauer Associates, Incorporated.

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Researchers should cite this work as follows:

  • Lisa Sproat (2013), "[Illinois]: Midbrain dopamine neuron responses to temporal-difference learning," http://nanohub.org/resources/midbraindopamin. (DOI: 10.4231/D30R9M41V).

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