Abnormal stability of spontaneous neuronal activity as a predictor of diagnosis conversion from major depressive disorder to bipolar disorder.

[1]  A. Young,et al.  Impulsivity in Bipolar Disorder: State or Trait? , 2022, Brain sciences.

[2]  Jingping Shi,et al.  Correlation between cognitive deficits and dorsolateral prefrontal cortex functional connectivity in first-episode depression. , 2022, Journal of affective disorders.

[3]  A. Jansen,et al.  Association of disease course and brain structural alterations in major depressive disorder , 2022, Depression and anxiety.

[4]  J. Fang,et al.  Altered Brain Function in First-Episode and Recurrent Depression: A Resting-State Functional Magnetic Resonance Imaging Study , 2022, Frontiers in Neuroscience.

[5]  T. Kinoshita,et al.  Disentangling cognitive inflexibility in major depressive disorder: A transcranial direct current stimulation study , 2022, Psychiatry and clinical neurosciences.

[6]  N. Shu,et al.  Abnormal characterization of dynamic functional connectivity in Alzheimer's disease , 2022, Neural regeneration research.

[7]  M. Phillips,et al.  Distinguishing between depression in bipolar disorder and unipolar depression using magnetic resonance imaging: a systematic review , 2022, Bipolar disorders.

[8]  Harin Kim,et al.  Diagnostic conversion from unipolar to bipolar affective disorder: a population-based study. , 2022, Journal of affective disorders.

[9]  M. Korgaonkar Precision in psychiatry—A roadmap to translate neurobiological measures to the clinic , 2021, Bipolar disorders.

[10]  Meng Wang,et al.  Dynamic reconfiguration of human brain networks across altered states of consciousness , 2021, Behavioural Brain Research.

[11]  Chaogan Yan,et al.  DPABISurf: data processing & analysis for brain imaging on surface. , 2021, Science bulletin.

[12]  Tomáš Dvořáčková Blanka Novák,et al.  Insula activity in resting-state differentiates bipolar from unipolar depression: a systematic review and meta-analysis , 2021, Scientific Reports.

[13]  J. Qiu,et al.  Disrupted intrinsic functional brain topology in patients with major depressive disorder , 2021, Molecular Psychiatry.

[14]  J. Yun,et al.  Graph theory approach for the structural-functional brain connectome of depression , 2021, Progress in Neuro-Psychopharmacology and Biological Psychiatry.

[15]  Huawang Wu,et al.  Dynamic changes of large-scale resting-state functional networks in major depressive disorder , 2021, Progress in Neuro-Psychopharmacology and Biological Psychiatry.

[16]  C. Hartmann,et al.  Within- and across-network alterations of the sensorimotor network in Parkinson’s disease , 2021, Neuroradiology.

[17]  D. Hu,et al.  Functional connectivity evidence for state-independent executive function deficits in patients with major depressive disorder. , 2021, Journal of affective disorders.

[18]  C. Sharpley,et al.  Default mode network activity in depression subtypes , 2021, Reviews in the neurosciences.

[19]  U. Hasson,et al.  The default mode network: where the idiosyncratic self meets the shared social world , 2021, Nature Reviews Neuroscience.

[20]  A. Young,et al.  Bipolar disorders , 2020, The Lancet.

[21]  Guanmao Chen,et al.  Shared and specific dynamics of brain segregation and integration in bipolar disorder and major depressive disorder: A resting-state functional magnetic resonance imaging study. , 2020, Journal of affective disorders.

[22]  Ying Wang,et al.  Common and distinct patterns of intrinsic brain activity alterations in major depression and bipolar disorder: voxel-based meta-analysis , 2020, Translational Psychiatry.

[23]  Aixia Zhang,et al.  Altered dynamic functional connectivity across mood states in bipolar disorder , 2020, Brain Research.

[24]  Conor Liston,et al.  Dissecting diagnostic heterogeneity in depression by integrating neuroimaging and genetics , 2020, Neuropsychopharmacology.

[25]  Jia Huang,et al.  Altered brain structural and functional connectivity in schizotypy , 2020, Psychological Medicine.

[26]  A. Voineskos,et al.  Neuroimaging Heterogeneity in Psychosis: Neurobiological Underpinnings and Opportunities for Prognostic and Therapeutic Innovation , 2020, Biological Psychiatry.

[27]  Stefan Brodoehl,et al.  Surface-based analysis increases the specificity of cortical activation patterns and connectivity results , 2020, Scientific Reports.

[28]  G. Parker,et al.  A Review of Antidepressant-Associated Hypomania in Those Diagnosed with Unipolar Depression—Risk Factors, Conceptual Models, and Management , 2020, Current Psychiatry Reports.

[29]  Zhening Liu,et al.  Altered Temporal Variability of Local and Large-Scale Resting-State Brain Functional Connectivity Patterns in Schizophrenia and Bipolar Disorder , 2020, bioRxiv.

[30]  Huijuan Wang,et al.  Dynamic Functional Connectivity Reveals Abnormal Variability and Hyper‐connected Pattern in Autism Spectrum Disorder , 2020, Autism research : official journal of the International Society for Autism Research.

[31]  D. Louis Collins,et al.  A sub+cortical fMRI‐based surface parcellation , 2019, bioRxiv.

[32]  Kun Bi,et al.  Early identification of bipolar from unipolar depression before manic episode: Evidence from dynamic rfMRI , 2019, Bipolar disorders.

[33]  Q. Hu,et al.  Delineating functional segregations of the human middle temporal gyrus with resting‐state functional connectivity and coactivation patterns , 2019, Human brain mapping.

[34]  Huafu Chen,et al.  Altered dynamics of brain segregation and integration in poststroke aphasia , 2019, Human brain mapping.

[35]  Wesley T. Kerr,et al.  Differentiating weight-restored anorexia nervosa and body dysmorphic disorder using neuroimaging and psychometric markers , 2019, PloS one.

[36]  J. Qiu,et al.  Reduced default mode network functional connectivity in patients with recurrent major depressive disorder , 2019, Proceedings of the National Academy of Sciences.

[37]  Kyu-Man Han,et al.  Differentiating between bipolar and unipolar depression in functional and structural MRI studies , 2019, Progress in Neuro-Psychopharmacology and Biological Psychiatry.

[38]  Qian Cui,et al.  Endless Fluctuations: Temporal Dynamics of the Amplitude of Low Frequency Fluctuations , 2019, IEEE Transactions on Medical Imaging.

[39]  L. Itti,et al.  Detection of Children/Youth With Fetal Alcohol Spectrum Disorder Through Eye Movement, Psychometric, and Neuroimaging Data , 2019, Front. Neurol..

[40]  Michael D Fox,et al.  Mapping Symptoms to Brain Networks with the Human Connectome. , 2018, The New England journal of medicine.

[41]  Xia Wu,et al.  Shared and specific functional connectivity alterations in unmedicated bipolar and major depressive disorders based on the triple-network model , 2018, Brain Imaging and Behavior.

[42]  Cheng Luo,et al.  Reconfiguration of Dynamic Functional Connectivity in Sensory and Perceptual System in Schizophrenia. , 2018, Cerebral cortex.

[43]  N. Ryan,et al.  A Risk Calculator to Predict the Individual Risk of Conversion From Subthreshold Bipolar Symptoms to Bipolar Disorder I or II in Youth. , 2018, Journal of the American Academy of Child and Adolescent Psychiatry.

[44]  Viviana Betti,et al.  Cortical cores in network dynamics , 2018, NeuroImage.

[45]  Yi Guo,et al.  Response and Remission Rates Following High-Frequency vs. Low-Frequency Repetitive Transcranial Magnetic Stimulation (rTMS) Over Right DLPFC for Treating Major Depressive Disorder (MDD): A Meta-Analysis of Randomized, Double-Blind Trials , 2018, Front. Psychiatry.

[46]  L. Parkkonen,et al.  Evidence for a general performance‐monitoring system in the human brain , 2018, Human brain mapping.

[47]  Fei Wang,et al.  Shared and distinct regional homogeneity changes in bipolar and unipolar depression , 2018, Neuroscience Letters.

[48]  V. Calhoun,et al.  Changing brain connectivity dynamics: From early childhood to adulthood , 2018, Human brain mapping.

[49]  M. Tohen,et al.  Early Intervention in Bipolar Disorder. , 2018, The American journal of psychiatry.

[50]  Yong-Ku Kim,et al.  Application of machine learning classification for structural brain MRI in mood disorders: Critical review from a clinical perspective , 2018, Progress in Neuro-Psychopharmacology and Biological Psychiatry.

[51]  Jessica A. Turner,et al.  Characterizing dynamic amplitude of low-frequency fluctuation and its relationship with dynamic functional connectivity: An application to schizophrenia , 2017, NeuroImage.

[52]  E. Seifritz,et al.  Resting state brain network function in major depression - Depression symptomatology, antidepressant treatment effects, future research. , 2017, Journal of psychiatric research.

[53]  J. Bukh,et al.  Rate and predictors of conversion from unipolar to bipolar disorder: A systematic review and meta‐analysis , 2017, Bipolar disorders.

[54]  Y Li,et al.  Clinical utility of a short resting‐state MRI scan in differentiating bipolar from unipolar depression , 2017, Acta psychiatrica Scandinavica.

[55]  Danielle S. Bassett,et al.  Positive affect, surprise, and fatigue are correlates of network flexibility , 2017, Scientific Reports.

[56]  V. Arolt,et al.  Differential Abnormal Pattern of Anterior Cingulate Gyrus Activation in Unipolar and Bipolar Depression: an fMRI and Pattern Classification Approach , 2017, Neuropsychopharmacology.

[57]  S. Whitfield-Gabrieli,et al.  Dynamic Resting-State Functional Connectivity in Major Depression , 2016, Neuropsychopharmacology.

[58]  Xiang Wang,et al.  Cognitive Vulnerability to Major Depression: View from the Intrinsic Network and Cross-network Interactions , 2016, Harvard review of psychiatry.

[59]  Yufeng Zang,et al.  DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging , 2016, Neuroinformatics.

[60]  N. Trujillo-Barreto,et al.  Attentional Bias Predicts Increased Reward Salience and Risk Taking in Bipolar Disorder , 2016, Biological Psychiatry.

[61]  Ya-li Wang,et al.  Altered functional interaction hub between affective network and cognitive control network in patients with major depressive disorder , 2016, Behavioural Brain Research.

[62]  D. Bassett,et al.  Dynamic reconfiguration of frontal brain networks during executive cognition in humans , 2015, Proceedings of the National Academy of Sciences.

[63]  L. Yao,et al.  Altered effective connectivity model in the default mode network between bipolar and unipolar depression based on resting-state fMRI. , 2015, Journal of affective disorders.

[64]  J. P. Hamilton,et al.  Depressive Rumination, the Default-Mode Network, and the Dark Matter of Clinical Neuroscience , 2015, Biological Psychiatry.

[65]  Dorothee P. Auer,et al.  Localized connectivity in depression: A meta-analysis of resting state functional imaging studies , 2015, Neuroscience & Biobehavioral Reviews.

[66]  M. Oquendo,et al.  Bipolar I and II versus unipolar depression: Clinical differences and impulsivity/aggression traits , 2015, European Psychiatry.

[67]  Dimitri Van De Ville,et al.  On spurious and real fluctuations of dynamic functional connectivity during rest , 2015, NeuroImage.

[68]  V. Calhoun,et al.  The Chronnectome: Time-Varying Connectivity Networks as the Next Frontier in fMRI Data Discovery , 2014, Neuron.

[69]  Feng Li,et al.  Regional homogeneity of resting-state brain abnormalities in bipolar and unipolar depression , 2013, Progress in Neuro-Psychopharmacology and Biological Psychiatry.

[70]  G. Zunta-Soares,et al.  Is impulsivity a common trait in bipolar and unipolar disorders? , 2013, Bipolar disorders.

[71]  T. Suslow,et al.  Discriminating unipolar and bipolar depression by means of fMRI and pattern classification: a pilot study , 2013, European Archives of Psychiatry and Clinical Neuroscience.

[72]  V. Menon Large-scale brain networks and psychopathology: a unifying triple network model , 2011, Trends in Cognitive Sciences.

[73]  Paul E. Croarkin,et al.  Psychomotor retardation in depression: Biological underpinnings, measurement, and treatment , 2011, Progress in Neuro-Psychopharmacology and Biological Psychiatry.

[74]  V. Menon,et al.  Saliency, switching, attention and control: a network model of insula function , 2010, Brain Structure and Function.

[75]  Bharat B. Biswal,et al.  The oscillating brain: Complex and reliable , 2010, NeuroImage.

[76]  Robert T. Knight,et al.  Superior Temporal SulcusIt's My Area: Or Is It? , 2008, Journal of Cognitive Neuroscience.

[77]  Angela R Laird,et al.  A meta‐analytic study of changes in brain activation in depression , 2008, Human brain mapping.

[78]  D. Hsu,et al.  The bipolar spectrum: a clinical perspective. , 2003, Bipolar disorders.

[79]  R. Hirschfeld,et al.  Perceptions and impact of bipolar disorder: how far have we really come? Results of the national depressive and manic-depressive association 2000 survey of individuals with bipolar disorder. , 2003, The Journal of clinical psychiatry.

[80]  Fei Wang,et al.  Common and distinct neural activities in frontoparietal network in first-episode bipolar disorder and major depressive disorder: Preliminary findings from a follow-up resting state fMRI study. , 2019, Journal of affective disorders.

[81]  Thomas T. Liu,et al.  Dynamic Functional Connectivity in Bipolar Disorder Is Associated With Executive Function and Processing Speed: A Preliminary Study , 2017, Neuropsychology.

[82]  M. Berk,et al.  Meta-analysis A systematic review and meta-analysis of prospective transition from major depression to bipolar disorder , 2017 .

[83]  D. Sheehan,et al.  The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. , 1998, The Journal of clinical psychiatry.