Abstract
We propose a novel algorithm to extract frequency-band specific and non-linear Granger causality (Spectral NLGC) connections between components of a multivariate time series. The advantage of our model over traditionally used VAR based models, as demonstrated in simulations, is the ability to capture complex dependence structures in a network. In addition to the simulations, the proposed method uncovered non-linear dynamics in an epileptic seizure EEG data. Spectral NLGC gives new meaningful insights into frequency specific connectivity changes at the onset of epileptic seizure. Results of both simulated and brain signals confirm the viability of the proposed algorithm as a good tool for exploration of directed connectivity in a network.
Original language | English (US) |
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Title of host publication | 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1401-1405 |
Number of pages | 5 |
ISBN (Electronic) | 9781665405409 |
DOIs | |
State | Published - 2022 |
Event | 47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Virtual, Online, Singapore Duration: May 23 2022 → May 27 2022 |
Publication series
Name | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
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Volume | 2022-May |
ISSN (Print) | 1520-6149 |
Conference
Conference | 47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 |
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Country/Territory | Singapore |
City | Virtual, Online |
Period | 05/23/22 → 05/27/22 |
Bibliographical note
Publisher Copyright:© 2022 IEEE
Keywords
- Directed connectivity
- Electroencephalograms
- Multi-layer perceptrons
- Networks
- Spectral dependence
ASJC Scopus subject areas
- Software
- Signal Processing
- Electrical and Electronic Engineering