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EEG functional connectivity is partially predicted by underlying white matter connectivity.

Abstract：

:Over the past decade, networks have become a leading model to illustrate both the anatomical relationships (structural networks) and the coupling of dynamic physiology (functional networks) linking separate brain regions. The relationship between these two levels of description remains incompletely understood and an area of intense research interest. In particular, it is unclear how cortical currents relate to underlying brain structural architecture. In addition, although theory suggests that brain communication is highly frequency dependent, how structural connections influence overlying functional connectivity in different frequency bands has not been previously explored. Here we relate functional networks inferred from statistical associations between source imaging of EEG activity and underlying cortico-cortical structural brain connectivity determined by probabilistic white matter tractography. We evaluate spontaneous fluctuating cortical brain activity over a long time scale (minutes) and relate inferred functional networks to underlying structural connectivity for broadband signals, as well as in seven distinct frequency bands. We find that cortical networks derived from source EEG estimates partially reflect both direct and indirect underlying white matter connectivity in all frequency bands evaluated. In addition, we find that when structural support is absent, functional connectivity is significantly reduced for high frequency bands compared to low frequency bands. The association between cortical currents and underlying white matter connectivity highlights the obligatory interdependence of functional and structural networks in the human brain. The increased dependence on structural support for the coupling of higher frequency brain rhythms provides new evidence for how underlying anatomy directly shapes emergent brain dynamics at fast time scales.

journal_name

Neuroimage

journal_title

NeuroImage

authors

Chu CJ,Tanaka N,Diaz J,Edlow BL,Wu O,Hämäläinen M,Stufflebeam S,Cash SS,Kramer MA

doi

10.1016/j.neuroimage.2014.12.033

subject

Has Abstract

pub_date

2015-03-01 00:00:00

pages

23-33

eissn

1053-8119

issn

1095-9572

pii

S1053-8119(14)01025-8

journal_volume

108

pub_type

杂志文章

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