Spectrally resolved fast transient brain states in electrophysiological data
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- 作者：Diego Vidaurrea ; diego.vidaurre@ohba.ox.ac.uk" class="auth_mail" title="E-mail the corresponding author ; Andrew J. Quinna ; andrew.quinn@psych.ox.ac.uk" class="auth_mail" title="E-mail the corresponding author ; Adam P. Bakera ; adam.baker@ohba.ox.ac.uk" class="auth_mail" title="E-mail the corresponding author ; David Dupretb ; david.dupret@pharm.ox.ac.uk" class="auth_mail" title="E-mail the corresponding author ; Alvaro Tejero-Canterob ; c ; tejero@bio.lmu.de" class="auth_mail" title="E-mail the corresponding author ; Mark W. Woolricha ; mark.woolrich@ohba.ox.ac.uk" class="auth_mail" title="E-mail the corresponding author
- 关键词：multivariate autoregressive model ; MEG ; Transient connectivity ; Bayesian modelling ; Spectral estimation ; Multitaper ; Coherence ; Partial directed coherence ; Sign ambiguity
- 刊名：NeuroImage
- 出版年：2016
- 出版时间：1 February 2016
- 年：2016
- 卷：126
- 期：Complete
- 页码：81-95
- 全文大小：3709 K
文摘
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We identify short-lived recurrent transient brain states of distinct multi-region spectral properties
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The method can be used to find time periods of quasi-stationary power spectra and phase locking
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The method can be used to produce denoised, task-locked time-frequency maps of power and coherence
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The approach is broadly applicable to any electrophysiological data in rest or task