On the Most Informative Slice of Bicoherence That Characterizes Resting State Brain Connectivity

Date

2018-08-07

Author

Kandemir, Ahmet Levent
Özkurt, Tolga Esat

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Bicoherence is a useful tool to detect nonlinear interactions within the brain with high computational cost. Latest attempts to reduce this computational cost suggest calculating a particular 'slice' of the bicoherence matrix. In this study, we investigate the information content of the bicoherence matrix in resting state. We use publicly available Human Connectome Project data in our calculations. We show that the most prominent information of the bicoherence matrix is concentrated on the main diagonal, i.e., f(1)=f(2).

Subject Keywords

Bicoherence, Connectivity, Quadratic phase coupling, Cross-frequency coupling, Neural oscillations

URI

https://hdl.handle.net/11511/55963

Conference Name

European Signal Processing Conference (EUSIPCO)

Collections

Graduate School of Informatics, Conference / Seminar

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Citation Formats

A. L. Kandemir and T. E. Özkurt, “On the Most Informative Slice of Bicoherence That Characterizes Resting State Brain Connectivity,” presented at the European Signal Processing Conference (EUSIPCO), Rome, ITALY, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/55963.