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

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Publication or External Link

Date

2020-08-02

Citation

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

Abstract

MEG data used for the "Switching attention" experiment. This set of data refers to the part of the "forced" switching of attention

Notes

Experiment Description:

MEG signals recorded in a magnetically sheilded room from a whole-head recording system with 157 channels. Initial sampling resolution: 1000 Hz Downsampling rate: 5 (downsamples to 200 Hz)

  • Attention Switch: Two speakers peresented monaurally (7 subjects). Listeners attenended to one of the speakers for 0-28 s and switched to the other speaker for 30-60 s. (a pause presented at 28-30 s as a switching cue)

    1. 2-speakers (Sp1+Sp2, Sp1 attended from 0-28 s, Sp2 attended from 30-60s)
    2. 2-speakers (Sp1+Sp2, Sp2 attended from 0-28 s, Sp1 attended from 30-60s)

Folders:

  • Speech: original audio files
  • MEG:Neural data

Data Structure:

  • data_DSSDomain: Data in DSS domain time (1 min) * DSS channels * trials
  • data_DSSed: Clean data projected back into the sensor domain time (1 min) * sensor channels * trials

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