Shedding new light on disorders of consciousness diagnosis: The dynamic functional connectivity

It has been proposed that awareness may depend on the highly-dynamic functional connectivity of large-scale cortico-thalamo-cortical networks. We investigated how brain connectivity changes over time in the resting state in a group of patients with chronic disorders of consciousness (DoC). To this e...

Full description

Saved in:
Bibliographic Details
Published inCortex Vol. 103; pp. 316 - 328
Main Authors Naro, Antonino, Bramanti, Alessia, Leo, Antonino, Cacciola, Alberto, Manuli, Alfredo, Bramanti, Placido, Calabrò, Rocco S.
Format Journal Article
LanguageEnglish
Published Italy Elsevier Ltd 01.06.2018
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:It has been proposed that awareness may depend on the highly-dynamic functional connectivity of large-scale cortico-thalamo-cortical networks. We investigated how brain connectivity changes over time in the resting state in a group of patients with chronic disorders of consciousness (DoC). To this end, we assessed dynamic functional connectivity (DFC) in the resting state by analyzing the time-dependent EEG phase synchronization in five frequency bands (δ, θ, α, β, and γ). Patients in Minimally Conscious State (MCS) showed changes in DFC matrices and topography over time (mainly in the γ range), which were significantly different from those observed in patients with Unresponsive Wakefulness Syndrome (UWS). The degree of DFC significantly correlated with the level of behavioral responsiveness measured using the Coma Recovery Scale-Revised. The analysis of DFC seems promising to differentiate patients with DoC. Moreover, sharpening the current knowledge of DFC by using EEG-based approaches may shed light on the processes of consciousness and their pathophysiology, and may help to design neuromodulation protocols aimed at targeting maladaptive and dysfunctional FC.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0010-9452
1973-8102
DOI:10.1016/j.cortex.2018.03.029