On the Most Informative Slice of Bicoherence That Characterizes Resting State Brain Connectivity
- Resource Type
- Conference
- Authors
- Kandemir, Ahmet Levent; Ozkurt, Tolga Esat
- Source
- 2018 26th European Signal Processing Conference (EUSIPCO) Signal Processing Conference (EUSIPCO), 2018 26th European. :1382-1386 Sep, 2018
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Signal Processing and Analysis
Europe
Estimation
Tools
Signal processing
Computational efficiency
Standards
Oscillators
bicoherence
connectivity
quadratic phase coupling
cross-frequency coupling
neural oscillations
- Language
- ISSN
- 2076-1465
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. $f_{1}=f_{2}$