Abnormal stability of spontaneous neuronal activity as a predictor of diagnosis conversion from major depressive disorder to bipolar disorder.
暂无分享,去创建一个
Rui Yan | Z. Yao | Q. Lu | Lingling Hua | Zhilu Chen | Yi Xia | Yinghong Huang | Xiaoqin Wang | Hao Sun | Qiudong Xia
[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.