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