Abnormal Spontaneous Neural Activity in Obsessive-Compulsive Disorder: A Resting-State Functional Magnetic Resonance Imaging Study.

Neuroimaging studies of obsessive-compulsive disorder have found abnormalities in orbitofronto-striato-thalamic circuitry, including the orbitofrontal cortex, anterior cingulate cortex, caudate, and thalamus, but few studies have explored abnormal intrinsic or spontaneous brain activity in the resting state. We investigated both intra- and inter-regional synchronized activity in twenty patients with obsessive-compulsive disorder and 20 healthy controls using resting-state functional magnetic resonance imaging. Regional homogeneity (ReHo) and functional connectivity methods were used to analyze the intra- and inter-regional synchronized activity, respectively. Compared with healthy controls, patients with obsessive-compulsive disorder showed significantly increased ReHo in the orbitofrontal cortex, cerebellum, and insula, and decreased ReHo in the ventral anterior cingulate cortex, caudate, and inferior occipital cortex. Based on ReHo results, we determined functional connectivity differences between the orbitofrontal cortex and other brain regions in both patients with obsessive-compulsive disorder and controls. We found abnormal functional connectivity between the orbitofrontal cortex and ventral anterior cingulate cortex in patients with obsessive-compulsive disorder compared with healthy controls. Moreover, ReHo in the orbitofrontal cortex was correlated with the duration of obsessive-compulsive disorder. These findings suggest that increased intra- and inter-regional synchronized activity in the orbitofrontal cortex may have a key role in the pathology of obsessive-compulsive disorder. In addition to orbitofronto-striato-thalamic circuitry, brain regions such as the insula and cerebellum may also be involved in the pathophysiology of obsessive-compulsive disorder.

Decreased regional homogeneity in major depression as revealed by resting-state functional magnetic resonance imaging / 中华医学杂志(英文版)

<p><b>BACKGROUND</b>Functional imaging studies indicate abnormal activities in cortico-limbic network in depression during either task or resting state. The present work was to explore the abnormal spontaneous activity shown with regional homogeneity (ReHo) in depression by resting-state functional magnetic resonance imaging (fMRI).</p><p><b>METHODS</b>Using fMRI, the differences of regional brain activity were measured in resting state in depressed vs. healthy participants. Sixteen participants firstly diagnosed with major depressive disorder and 16 controls were scanned during resting state. A novel method based on ReHo was used to detect spontaneous hemodynamic responses across the whole brain.</p><p><b>RESULTS</b>ReHo in the left thalamus, left temporal lobe, left cerebellar posterior lobe, and the bilateral occipital lobe was found to be significantly decreased in depression compared to healthy controls in resting state of depression.</p><p><b>CONCLUSIONS</b>Abnormal spontaneous activity exists in the left thalamus, left temporal lobe, left cerebellar posterior lobe, and the bilateral occipital lobe. And the ReHo may be a potential reference in understanding the distinct brain activity in resting state of depression.</p>

DPARSF: A MATLAB Toolbox for "Pipeline" Data Analysis of Resting-State fMRI.

Resting-state functional magnetic resonance imaging (fMRI) has attracted more and more attention because of its effectiveness, simplicity and non-invasiveness in exploration of the intrinsic functional architecture of the human brain. However, user-friendly toolbox for "pipeline" data analysis of resting-state fMRI is still lacking. Based on some functions in Statistical Parametric Mapping (SPM) and Resting-State fMRI Data Analysis Toolkit (REST), we have developed a MATLAB toolbox called Data Processing Assistant for Resting-State fMRI (DPARSF) for "pipeline" data analysis of resting-state fMRI. After the user arranges the Digital Imaging and Communications in Medicine (DICOM) files and click a few buttons to set parameters, DPARSF will then give all the preprocessed (slice timing, realign, normalize, smooth) data and results for functional connectivity, regional homogeneity, amplitude of low-frequency fluctuation (ALFF), and fractional ALFF. DPARSF can also create a report for excluding subjects with excessive head motion and generate a set of pictures for easily checking the effect of normalization. In addition, users can also use DPARSF to extract time courses from regions of interest.