Support

Support Options

Submit a Support Ticket

 

[Illinois]: Predictor-corrector simulation of parabigeminal nucleus neural responses

By Lisa Sproat

University of Illinois at Urbana-Champaign

Implements a predictor-corrector simulation of the responses of neurons in the parabigeminal nucleus

Launch Tool

You must login before you can run this tool.

Version 1.1a - published on 19 Aug 2013

doi:10.4231/D3X05XC6D cite this

This tool is closed source.

View All Supporting Documents

    pbnpredict1 pbnpredict2 pbnpredict3

Category

Tools

Published on

Abstract

This tool mplements a predictor-corrector simulation of the responses of neurons in the parabigeminal nucleus using the following model.

FIGURE 12.14 is a schematic of the target-tracking predictor-corrector model. This causal model takes the form of a dynamic Bayesian network. Random variables T and V stand for target position and visual input, respectively, and (t) represents discrete time in steps from 1 to n. The position of the target on any time step can be probabilistically inferred from the position of the target on the previous time step and the visual input on the current time step.

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

Sponsored by

References

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]: Predictor-corrector simulation of parabigeminal nucleus neural responses," http://nanohub.org/resources/pbnpredict. (DOI: 10.4231/D3X05XC6D).

    BibTex | EndNote

Tags

nanoHUB.org, 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.