Dynamic Estimation of Auditory Temporal Response Functions via State-Space Models with Gaussian Mixture Process Noise

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Publication or External Link

External Link to Data Files

Date

2020-08-02

Authors

Advisor

Jonathan, Simon
Babadi, Betash

Citation

"Dynamic Estimation of Auditory Temporal Response Functions via State-Space Models with Gaussian Mixture Process Noise", PLOS Computational Biology (2020), in press

DRUM DOI

https://doi.org/10.13016/di6h-cav9

Abstract

MEG data used for the "Switching attention" experiment

Notes

MEG data were collected from 157 sensors + 35 additional channels (158 - 192) used for reference and trigger. Each mat file contains information about the data, such as sampling frequency. A 3D matrix is used to store the 3 repetitions recorded.

URI (handle)

http://hdl.handle.net/1903/26351

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Collections

Institute for Systems Research Technical Reports