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      Whole Brain Resting-State Analysis Reveals Decreased Functional Connectivity in Major Depression

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          Abstract

          Recently, both increases and decreases in resting-state functional connectivity have been found in major depression. However, these studies only assessed functional connectivity within a specific network or between a few regions of interest, while comorbidity and use of medication was not always controlled for. Therefore, the aim of the current study was to investigate whole-brain functional connectivity, unbiased by a priori definition of regions or networks of interest, in medication-free depressive patients without comorbidity. We analyzed resting-state fMRI data of 19 medication-free patients with a recent diagnosis of major depression (within 6 months before inclusion) and no comorbidity, and 19 age- and gender-matched controls. Independent component analysis was employed on the concatenated data sets of all participants. Thirteen functionally relevant networks were identified, describing the entire study sample. Next, individual representations of the networks were created using a dual regression method. Statistical inference was subsequently done on these spatial maps using voxel-wise permutation tests. Abnormal functional connectivity was found within three resting-state networks in depression: (1) decreased bilateral amygdala and left anterior insula connectivity in an affective network, (2) reduced connectivity of the left frontal pole in a network associated with attention and working memory, and (3) decreased bilateral lingual gyrus connectivity within ventromedial visual regions. None of these effects were associated with symptom severity or gray matter density. We found abnormal resting-state functional connectivity not previously associated with major depression, which might relate to abnormal affect regulation and mild cognitive deficits, both associated with the symptomatology of the disorder.

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          Most cited references25

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          Functional connectivity in single and multislice echoplanar imaging using resting-state fluctuations.

          A previous report of correlations in low-frequency resting-state fluctuations between right and left hemisphere motor cortices in rapidly sampled single-slice echoplanar data is confirmed using a whole-body echoplanar MRI scanner at 1.5 T. These correlations are extended to lower sampling rate multislice echoplanar acquisitions and other right/left hemisphere-symmetric functional cortices. The specificity of the correlations in the lower sampling-rate acquisitions is lower due to cardiac and respiratory-cycle effects which are aliased into the pass-band of the low-pass filter. Data are combined for three normal right-handed male subjects. Correlations to left hemisphere motor cortex, visual cortex, and amygdala are measured in long resting-state scans.
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            Frequencies contributing to functional connectivity in the cerebral cortex in "resting-state" data.

            In subjects performing no specific cognitive task ("resting state"), time courses of voxels within functionally connected regions of the brain have high cross-correlation coefficients ("functional connectivity"). The purpose of this study was to measure the contributions of low frequencies and physiological noise to cross-correlation maps. In four healthy volunteers, task-activation functional MR imaging and resting-state data were acquired. We obtained four contiguous slice locations in the "resting state" with a high sampling rate. Regions of interest consisting of four contiguous voxels were selected. The correlation coefficient for the averaged time course and every other voxel in the four slices was calculated and separated into its component frequency contributions. We calculated the relative amounts of the spectrum that were in the low-frequency (0 to 0.1 Hz), the respiratory-frequency (0.1 to 0.5 Hz), and cardiac-frequency range (0.6 to 1.2 Hz). For each volunteer, resting-state maps that resembled task-activation maps were obtained. For the auditory and visual cortices, the correlation coefficient depended almost exclusively on low frequencies (<0.1 Hz). For all cortical regions studied, low-frequency fluctuations contributed more than 90% of the correlation coefficient. Physiological (respiratory and cardiac) noise sources contributed less than 10% to any functional connectivity MR imaging map. In blood vessels and cerebrospinal fluid, physiological noise contributed more to the correlation coefficient. Functional connectivity in the auditory, visual, and sensorimotor cortices is characterized predominantly by frequencies slower than those in the cardiac and respiratory cycles. In functionally connected regions, these low frequencies are characterized by a high degree of temporal coherence.
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              Neurobiology of emotion perception II: Implications for major psychiatric disorders.

              To date, there has been little investigation of the neurobiological basis of emotion processing abnormalities in psychiatric populations. We have previously discussed two neural systems: 1) a ventral system, including the amygdala, insula, ventral striatum, ventral anterior cingulate gyrus, and prefrontal cortex, for identification of the emotional significance of a stimulus, production of affective states, and automatic regulation of emotional responses; and 2) a dorsal system, including the hippocampus, dorsal anterior cingulate gyrus, and prefrontal cortex, for the effortful regulation of affective states and subsequent behavior. In this critical review, we have examined evidence from studies employing a variety of techniques for distinct patterns of structural and functional abnormalities in these neural systems in schizophrenia, bipolar disorder, and major depressive disorder. In each psychiatric disorder, the pattern of abnormalities may be associated with specific symptoms, including emotional flattening, anhedonia, and persecutory delusions in schizophrenia, prominent mood swings, emotional lability, and distractibility in bipolar disorder during depression and mania, and with depressed mood and anhedonia in major depressive disorder. We suggest that distinct patterns of structural and functional abnormalities in neural systems important for emotion processing are associated with specific symptoms of schizophrenia and bipolar and major depressive disorder.
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                Author and article information

                Journal
                Front Syst Neurosci
                Front. Syst. Neurosci.
                Frontiers in Systems Neuroscience
                Frontiers Research Foundation
                1662-5137
                25 June 2010
                20 September 2010
                2010
                : 4
                : 41
                Affiliations
                [1] 1simpleLeiden Institute for Brain and Cognition Leiden, Netherlands
                [2] 2simpleDepartment of Radiology, Leiden University Medical Center Leiden, Netherlands
                [3] 3simpleInstitute of Psychology, Leiden University Leiden, Netherlands
                [4] 4simpleOxford Centre for Functional Magnetic Resonance Imaging of the Brain, University of Oxford Oxford, UK
                [5] 5simpleDepartment of Clinical Neuroscience, Imperial College London London, UK
                [6] 6simpleDepartment of Psychiatry, Leiden University Medical Center Leiden, Netherlands
                [7] 7simpleDepartment of Radiology, Division of Image Processing, Leiden University Medical Center Leiden, Netherlands
                [8] 8simpleDepartment of Psychiatry, VU Medical Center Amsterdam, Netherlands
                [9] 9simpleBCN NeuroImaging Center, University of Groningen Groningen, Netherlands
                Author notes

                Edited by: Silvina G. Horovitz, National Institutes of Health, USA

                Reviewed by: Cameron Craddock, Department of Neuroscience, Baylor College of Medicine, USA; Martin Walter, Otto-von-Guericke-Universität Magdeburg, Germany

                *Correspondence: Ilya M. Veer, Department of Radiology, Leiden University Medical Center, Postzone C2-S, P.O. Box 9600, 2300 RC Leiden, Netherlands. e-mail: i.m.veer@ 123456lumc.nl
                Article
                10.3389/fnsys.2010.00041
                2950744
                20941370
                517fb0eb-4dd6-4989-a51a-f5dbb9b18f55
                Copyright © 2010 Veer, Beckmann, van Tol, Ferrarini, Milles, Veltman, Aleman, van Buchem, van der Wee and Rombouts.

                This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited.

                History
                : 29 April 2010
                : 23 July 2010
                Page count
                Figures: 2, Tables: 4, Equations: 0, References: 59, Pages: 10, Words: 8445
                Categories
                Neuroscience
                Original Research

                Neurosciences
                amygdala,major depression,independent component analysis,functional connectivity,resting-state functional magnetic resonance imaging

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