Article ID Journal Published Year Pages File Type
3044219 Clinical Neurophysiology 2013 10 Pages PDF
Abstract

•Region of interest (ROI)-based analysis of intracortical EEG lagged non-linear and linear coherence during rest in unmedicated patients with obsessive compulsive disorder (OCD) in comparison to healthy controls (HC).•Decreased non-linear but not linear coherence is found in OCD for the beta frequency range for connectivity measures between frontal brain areas including the anterior cingulate cortex, the superior frontal gyrus and the left medial frontal gyrus.•Decreased non-linear coherence is only found at high arousal levels when analysis is performed separately for different EEG-vigilance stages.

ObjectiveFunctional magnetic resonance imaging (fMRI) studies found alterations of functional connectivity in obsessive compulsive disorder (OCD). However, there is little knowledge about region of interest (ROI) based electroencephalogram (EEG) connectivity, i.e. lagged non-linear and linear coherence in OCD. Goal of this study was to compare these EEG measures during rest and at different vigilance stages between patients and healthy controls (HC).MethodsA 15 min resting-state EEG was recorded in 30 unmedicated patients and 30 matched HC. Intracortical lagged non-linear coherence of the main EEG-frequency bands within a set of frontal ROIs and within the default mode network (DMN) were computed and compared using intracortical exact low resolution electromagnetic tomography (eLORETA) software.ResultsLagged non-linear but not linear coherence was significantly decreased for patients in comparison to HC for the beta 2 frequency between frontal brain areas but not within the DMN. When analysing separate EEG-vigilance stages, only high vigilance stages yielded decreased frontal phase synchronisation at beta and theta frequencies.ConclusionsThe results underline an altered neuronal communication within frontal brain areas during rest in OCD.SignificanceThese findings encourage further research on connectivity measures as possible biomarkers for physiological homogeneous subgroups.

Related Topics
Life Sciences Neuroscience Neurology
Authors
, , , , , ,