Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
408771 | Neurocomputing | 2006 | 7 Pages |
Abstract
Biomathematical methods were applied to investigate how cortical neurodynamics depends on network connectivity. In particular, we study changes in the EEG pattern of depressed patients, following electroconvulsive therapy (ECT). The aim is to gain a better understanding of the neural mechanisms responsible for these changes, which include clear phase shifts in the EEG dynamics. This understanding is intended to provide clinical guidance in predicting ECT dose and response in depressed patients.
Keywords
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Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Y. Gu, G. Halnes, H. Liljenström, D. von Rosen, B. Wahlund, H. Liang,