Support Options

Submit a Support Ticket


[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

Launch Tool

You must login before you can run this tool.

Version 1.1a - published on 19 Aug 2013

doi:10.4231/D30R9M41V cite this

This tool is closed source.

View All Supporting Documents

    midbraindopamine1 midbraindopamine2 midbraindopamine3



Published on


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.

Sponsored by


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

Cite this work

Researchers should cite this work as follows:

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

    BibTex | EndNote

Tags, a resource for nanoscience and nanotechnology, is supported by the National Science Foundation and other funding agencies. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.