Resting-State Functional Connectivity Bias of Middle Temporal Gyrus and Caudate with Altered Gray Matter Volume in Major Depression

Magnetic resonance imaging (MRI) studies have indicated that the structure deficits and resting-state functional connectivity (FC) imbalances in cortico-limbic circuitry might underline the pathophysiology of MDD. Using structure and functional MRI, our aim is to investigate gray matter abnormalities in patients with treatment-resistant depression (TRD) and treatment-responsive depression (TSD), and test whether the altered gray matter is associated with altered FC. Voxel-based morphometry was used to investigate the regions with gray matter abnormality and FC analysis was further conducted between each gray matter abnormal region and the remaining voxels in the brain. Using one-way analysis of variance, we found significant gray matter abnormalities in the right middle temporal cortex (MTG) and bilateral caudate among the TRD, TSD and healthy controls. For the FC of the right MTG, we found that both the patients with TRD and TSD showed altered connectivity mainly in the default-mode network (DMN). For the FC of the right caudate, both patient groups showed altered connectivity in the frontal regions. Our results revealed the gray matter reduction of right MTG and bilateral caudate, and disrupted functional connection to widely distributed circuitry in DMN and frontal regions, respectively. These results suggest that the abnormal DMN and reward circuit activity might be biomarkers of depression trait.

[1]  Justin L. Vincent,et al.  Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[2]  Raymond C K Chan,et al.  Abnormal regional spontaneous neural activity in treatment‐refractory depression revealed by resting‐state fMRI , 2011, Human brain mapping.

[3]  A R Damasio,et al.  Neuropsychology. Towards a neuropathology of emotion and mood. , 1997, Nature.

[4]  Steven C. R. Williams,et al.  The Neural Correlates of Anhedonia in Major Depressive Disorder , 2005, Biological Psychiatry.

[5]  Feng Liu,et al.  Alterations of the amplitude of low-frequency fluctuations in treatment-resistant and treatment-response depression: A resting-state fMRI study , 2012, Progress in Neuro-Psychopharmacology and Biological Psychiatry.

[6]  Xiaoqi Huang,et al.  Disrupted Brain Connectivity Networks in Drug-Naive, First-Episode Major Depressive Disorder , 2011, Biological Psychiatry.

[7]  M. Greicius.  Resting-state functional connectivity in neuropsychiatric disorders , 2008, Current opinion in neurology.

[8]  Karl J. Friston,et al.  Functional Connectivity: The Principal-Component Analysis of Large (PET) Data Sets , 1993, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[9]  Maurizio Corbetta,et al.  The human brain is intrinsically organized into dynamic, anticorrelated functional networks. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[10]  A. Hariri,et al.  Altered striatal activation predicting real-world positive affect in adolescent major depressive disorder. , 2009, The American journal of psychiatry.

[11]  M. Fox,et al.  The global signal and observed anticorrelated resting state brain networks. , 2009, Journal of neurophysiology.

[12]  Stéphane Lehéricy,et al.  In search of the depressive self: extended medial prefrontal network during self-referential processing in major depression. , 2009, Social cognitive and affective neuroscience.

[13]  H. Walter,et al.  Dorsolateral prefrontal cortex modulates striatal reward encoding during reappraisal of reward anticipation. , 2011, Cerebral cortex.

[14]  John Ashburner,et al.  Computational anatomy with the SPM software. , 2009, Magnetic resonance imaging.

[15]  Chunshui Yu,et al.  Increased neural resources recruitment in the intrinsic organization in major depression. , 2010, Journal of affective disorders.

[16]  T. Iidaka,et al.  Quantitative regional cerebral flow measured by Tc-99M HMPAO SPECT in mood disorder. , 1997, Psychiatry research.

[17]  Chaogan Yan,et al.  DPARSF: A MATLAB Toolbox for “Pipeline” Data Analysis of Resting-State fMRI , 2010, Front. Syst. Neurosci..

[18]  M. Mintun,et al.  Resting-state functional MRI in depression unmasks increased connectivity between networks via the dorsal nexus , 2010, Proceedings of the National Academy of Sciences.

[19]  S. Debener,et al.  Default-mode brain dysfunction in mental disorders: A systematic review , 2009, Neuroscience & Biobehavioral Reviews.

[20]  M. Fava,et al.  A quantitative magnetic resonance imaging study of caudate and lenticular nucleus gray matter volume in primary unipolar major depression: relationship to treatment response and clinical severity , 1998, Psychiatry Research: Neuroimaging.

[21]  K. Kendrick,et al.  Depression uncouples brain hate circuit , 2011, Molecular Psychiatry.

[22]  H. Walter,et al.  Aberrant functional connectivity of dorsolateral prefrontal and cingulate networks in patients with major depression during working memory processing , 2008, Psychological Medicine.

[23]  K. Doya,et al.  A Neural Correlate of Reward-Based Behavioral Learning in Caudate Nucleus: A Functional Magnetic Resonance Imaging Study of a Stochastic Decision Task , 2004, The Journal of Neuroscience.

[24]  J. P. Hamilton,et al.  Neural Substrates of Increased Memory Sensitivity for Negative Stimuli in Major Depression , 2008, Biological Psychiatry.

[25]  Qiyong Gong,et al.  Resting-state functional connectivity in treatment-resistant depression. , 2011, The American journal of psychiatry.

[26]  J. Stephenson.  World health report. , 2004, Lancet.

[27]  M. Kringelbach.  The human orbitofrontal cortex: linking reward to hedonic experience , 2005, Nature Reviews Neuroscience.

[28]  John Ashburner,et al.  A fast diffeomorphic image registration algorithm , 2007, NeuroImage.

[29]  M. Delgado,et al.  Event-related functional magnetic resonance imaging of reward-related brain circuitry in children and adolescents , 2004, Biological Psychiatry.

[30]  Klaus P. Ebmeier,et al.  Chronic, treatment-resistant depression and right fronto-striatal atrophy. , 2002, The British journal of psychiatry : the journal of mental science.

[31]  N. Laird,et al.  A 40-year perspective on the prevalence of depression: the Stirling County Study. , 2000, Archives of general psychiatry.

[32]  M. Lowe,et al.  Antidepressant Effect on Connectivity of the Mood-Regulating Circuit: An fMRI Study , 2005, Neuropsychopharmacology.

[33]  Binbin Nie,et al.  Cerebral and cerebellar gray matter reduction in first-episode patients with major depressive disorder: a voxel-based morphometry study. , 2011, European journal of radiology.

[34]  Xiang Wang,et al.  Evidence of a Dissociation Pattern in Resting-State Default Mode Network Connectivity in First-Episode, Treatment-Naive Major Depression Patients , 2012, Biological Psychiatry.

[35]  K. Krishnan,et al.  Magnetic resonance imaging of the caudate nuclei in depression. Preliminary observations. , 1992, Archives of general psychiatry.

[36]  S. Montgomery.  Why do we need new and better antidepressants? , 2006, International clinical psychopharmacology.

[37]  C. Naranjo,et al.  Brain reward system activity in major depression and comorbid nicotine dependence. , 2002, The Journal of pharmacology and experimental therapeutics.

[38]  C. Carter,et al.  Reward-related decision-making in pediatric major depressive disorder: an fMRI study. , 2006, Journal of child psychology and psychiatry, and allied disciplines.

[39]  A. Heinz,et al.  Psychopathological correlates of reduced dopamine receptor sensitivity in depression, schizophrenia, and opiate and alcohol dependence. , 2001, Pharmacopsychiatry.

[40]  T. Prentice.  World Health Report , 2013 .

[41]  M. Ernst,et al.  fMRI of alterations in reward selection, anticipation, and feedback in major depressive disorder. , 2009, Journal of affective disorders.

[42]  G. Glover,et al.  Resting-State Functional Connectivity in Major Depression: Abnormally Increased Contributions from Subgenual Cingulate Cortex and Thalamus , 2007, Biological Psychiatry.

[43]  M. Corbetta,et al.  Control of goal-directed and stimulus-driven attention in the brain , 2002, Nature Reviews Neuroscience.

[44]  Karl J. Friston,et al.  Voxel-Based Morphometry—The Methods , 2000, NeuroImage.

[45]  M. Fava,et al.  Reduced hedonic capacity in major depressive disorder: evidence from a probabilistic reward task. , 2008, Journal of psychiatric research.

[46]  Philip K. McGuire,et al.  Prognostic prediction of therapeutic response in depression using high-field MR imaging , 2011, NeuroImage.

[47]  B. Biswal,et al.  Functional connectivity of human striatum: a resting state FMRI study. , 2008, Cerebral cortex.

[48]  M. Yücel,et al.  Structural brain abnormalities in major depressive disorder: a selective review of recent MRI studies. , 2009, Journal of affective disorders.

[49]  J. Amsterdam,et al.  Treatment-resistant depression: definition and treatment approaches. , 1990, The Journal of clinical psychiatry.

[50]  M. Hamilton,et al.  Development of a rating scale for primary depressive illness. , 1967, The British journal of social and clinical psychology.

[51]  D. Zald,et al.  Reconsidering anhedonia in depression: Lessons from translational neuroscience , 2011, Neuroscience & Biobehavioral Reviews.

[52]  Yufeng Zang,et al.  DPARSF: A MATLAB Toolbox for “Pipeline” Data Analysis of Resting-State fMRI , 2010 .

[53]  M. Lowe,et al.  Activity and Connectivity of Brain Mood Regulating Circuit in Depression: A Functional Magnetic Resonance Study , 2005, Biological Psychiatry.

[54]  E. Rolls,et al.  Abstract reward and punishment representations in the human orbitofrontal cortex , 2001, Nature Neuroscience.

[55]  Paul B. Fitzgerald,et al.  A magnetic resonance imaging study of the entorhinal cortex in treatment-resistant depression , 2008, Psychiatry Research: Neuroimaging.

[56]  H. Mayberg.  Modulating dysfunctional limbic-cortical circuits in depression: towards development of brain-based algorithms for diagnosis and optimised treatment. , 2003, British medical bulletin.

[57]  C. Bell.  DSM-IV: Diagnostic and Statistical Manual of Mental Disorders , 1994 .

[58]  Martin Wiesmann,et al.  Functional Connectivity Bias of the Orbitofrontal Cortex in Drug-Free Patients with Major Depression , 2010, Biological Psychiatry.

[59]  Antonio R. Damasio,et al.  Towards a neuropathology of emotion and mood , 1997, Nature.

[60]  D. Kupfer,et al.  Is treatment-resistant depression a unique subtype of depression? , 2003, Biological Psychiatry.

[61]  Glyn Lewis,et al.  Randomised controlled trials investigating pharmacological and psychological interventions for treatment-refractory depression , 2002, British Journal of Psychiatry.

[62]  Tetsuya Iidaka,et al.  Quantitative regional cerebral blood flow measured by Tc-99m HMPAO SPECT in mood disorder , 1997, Psychiatry Research: Neuroimaging.

[63]  Karl J. Friston,et al.  Unified segmentation , 2005, NeuroImage.

[64]  Pienie Zwitserlood,et al.  Reduced amygdala-prefrontal coupling in major depression: association with MAOA genotype and illness severity. , 2009, The international journal of neuropsychopharmacology.

[65]  Yang Wang,et al.  Reciprocal effects of antidepressant treatment on activity and connectivity of the mood regulating circuit: an FMRI study. , 2007, The Journal of neuropsychiatry and clinical neurosciences.