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Delineating between-subject heterogeneity in alpha networks with Spatio-Spectral Eigenmodes

Abstract:

Between subject variability in the spatial and spectral structure of oscillatory networks can be highly informative but poses a considerable analytic challenge. Here, we describe a data-driven modal decomposition of a multivariate autoregressive model that simultaneously identifies oscillations by their peak frequency, damping time and network structure. We use this decomposition to define a set of Spatio-Spectral Eigenmodes (SSEs) providing a parsimonious description of oscillatory networks....

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.neuroimage.2021.118330

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Institution:
University of Oxford
Division:
MSD
Department:
Psychiatry
Oxford college:
St Edmund Hall
Role:
Author
ORCID:
0000-0003-2267-9897
Publisher:
Elsevier Publisher's website
Journal:
NeuroImage Journal website
Volume:
240
Article number:
118330
Publication date:
2021-07-06
Acceptance date:
2021-07-01
DOI:
ISSN:
1053-8119
Language:
English
Keywords:
Pubs id:
1185101
Local pid:
pubs:1185101
Deposit date:
2021-07-05

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