Measuring the Task Induced Oscillatory Brain Activity Using Tensor Decomposition
Zhu, Y., Li, X., Ristaniemi, T., & Cong, F. (2019). Measuring the Task Induced Oscillatory Brain Activity Using Tensor Decomposition. In ICASSP 2019 : Proceedings of the 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (pp. 8593-8597). IEEE. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing. https://doi.org/10.1109/ICASSP.2019.8682355
Published inProceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing
© 2019 IEEE
The characterization of dynamic electrophysiological brain activity, which form and dissolve in order to support ongoing cognitive function, is one of the most important goals in neuroscience. Here, we introduce a method with tensor decomposition for measuring the task-induced oscillations in the human brain using electroencephalography (EEG). The time frequency representation of source-reconstructed singletrail EEG data constructed a third-order tensor with three factors of time ∗ trails, frequency and source points. We then used a non-negative Canonical Polyadic decomposition (NCPD) to identify the temporal, spectral and spatial changes in electrophysiological brain activity. We validate this method using both simulation EEG data and real EEG data recorded during a task of irony comprehension. The results demonstrated that proposed method can track dynamics of the temporal-spectral modes of the rhythm in the brain on a timescale commensurate to the task they are undertaking. ...
Parent publication ISBN978-1-4799-8131-1
ConferenceIEEE International Conference on Acoustics, Speech and Signal Processing
Is part of publicationICASSP 2019 : Proceedings of the 2019 IEEE International Conference on Acoustics, Speech and Signal Processing
ISSN Search the Publication Forum1520-6149
Publication in research information system
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