Towards person-centered neuroimaging markers for resilience and vulnerability in Bipolar Disorder

[1]  M. Hamilton.  A RATING SCALE FOR DEPRESSION , 1960, Journal of neurology, neurosurgery, and psychiatry.

[2]  R. Liberman,et al.  Symptom monitoring in the rehabilitation of schizophrenic patients. , 1986, Schizophrenia bulletin.

[3]  J. Barendregt,et al.  Global burden of disease , 1997, The Lancet.

[4]  R. Coppola,et al.  Physiological characteristics of capacity constraints in working memory as revealed by functional MRI. , 1999, Cerebral cortex.

[5]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[6]  John A. Rice,et al.  The long-term natural history of the weekly symptomatic status of bipolar I disorder. , 2002, Archives of general psychiatry.

[7]  Kathryn M. McMillan,et al.  N‐back working memory paradigm: A meta‐analysis of normative functional neuroimaging studies , 2005, Human brain mapping.

[8]  J. Os,et al.  Meta-analyses of cognitive functioning in euthymic bipolar patients and their first-degree relatives , 2007, Psychological Medicine.

[9]  S. Lawrie,et al.  Progressive Gray Matter Loss in Patients with Bipolar Disorder , 2007, Biological Psychiatry.

[10]  P. Mitchell,et al.  Diagnostic guidelines for bipolar depression: a probabilistic approach. , 2008, Bipolar disorders.

[11]  S. Frangou.  Risk and resilience in bipolar disorder: rationale and design of the Vulnerability to Bipolar Disorders Study (VIBES). , 2009, Biochemical Society transactions.

[12]  S. Frangou,et al.  Corpus callosum size and shape alterations in individuals with bipolar disorder and their first-degree relatives , 2009, Progress in Neuro-Psychopharmacology and Biological Psychiatry.

[13]  N. Craddock,et al.  Polarity at illness onset in bipolar I disorder and clinical course of illness. , 2009, Bipolar disorders.

[14]  Carl E. Rasmussen,et al.  Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.

[15]  D. Collier,et al.  Dissociable Brain Structural Changes Associated with Predisposition, Resilience, and Disease Expression in Bipolar Disorder , 2009, The Journal of Neuroscience.

[16]  E. Vassos,et al.  Effects of the CACNA1C risk allele for bipolar disorder on cerebral gray matter volume in healthy individuals. , 2009, The American journal of psychiatry.

[17]  E. Bora,et al.  Cognitive endophenotypes of bipolar disorder: a meta-analysis of neuropsychological deficits in euthymic patients and their first-degree relatives. , 2009, Journal of affective disorders.

[18]  D. Collier,et al.  The impact of the Val158Met catechol-O-methyltransferase genotype on neural correlates of sad facial affect processing in patients with bipolar disorder and their relatives , 2010, Psychological Medicine.

[19]  S. Frangou,et al.  Pituitary volume in patients with bipolar disorder and their first-degree relatives. , 2010, Journal of affective disorders.

[20]  Janaina Mourão Miranda,et al.  Quantitative prediction of subjective pain intensity from whole-brain fMRI data using Gaussian processes , 2010, NeuroImage.

[21]  H. Nicolini,et al.  Neurocognitive endophenotypes for bipolar disorder identified in multiplex multigenerational families. , 2010, Archives of general psychiatry.

[22]  J. van os,et al.  Risk factors predicting onset and persistence of subthreshold expression of bipolar psychopathology among youth from the community , 2010, Acta psychiatrica Scandinavica.

[23]  E. Vassos,et al.  The Cognitive Impact of the ANK3 Risk Variant for Bipolar Disorder: Initial Evidence of Selectivity to Signal Detection during Sustained Attention , 2011, PloS one.

[24]  A. Simmons,et al.  Structural neuroimaging studies in major depressive disorder. Meta-analysis and comparison with bipolar disorder. , 2011, Archives of general psychiatry.

[25]  E. Bullmore,et al.  A quantitative meta-analysis of fMRI studies in bipolar disorder. , 2011, Bipolar disorders.

[26]  Katya Rubia,et al.  Familial and disease specific abnormalities in the neural correlates of the Stroop Task in Bipolar Disorder , 2011, NeuroImage.

[27]  E. Vassos,et al.  Initial evidence for the role of CACNA1C on subcortical brain morphology in patients with bipolar disorder , 2011, European Psychiatry.

[28]  R. Murray,et al.  Structural Magnetic Resonance Imaging in Bipolar Disorder: An International Collaborative Mega-Analysis of Individual Adult Patient Data , 2011, Biological Psychiatry.

[29]  S. Frangou,et al.  The impact of general intellectual ability and white matter volume on the functional outcome of patients with Bipolar Disorder and their relatives. , 2011, Journal of affective disorders.

[30]  M. Breakspear,et al.  Comparison of depressive episodes in bipolar disorder and in major depressive disorder within bipolar disorder pedigrees. , 2011, The British journal of psychiatry : the journal of mental science.

[31]  E. Vassos,et al.  The impact of the CACNA1C gene polymorphism on frontolimbic function in bipolar disorder , 2011, Molecular Psychiatry.

[32]  Katya Rubia,et al.  Dissociable functional connectivity changes during the Stroop task relating to risk, resilience and disease expression in bipolar disorder , 2011, NeuroImage.

[33]  O. Howes,et al.  Mapping vulnerability to bipolar disorder: a systematic review and meta-analysis of neuroimaging studies. , 2012, Journal of psychiatry & neuroscience : JPN.

[34]  S. Frangou,et al.  Frontopolar cortical inefficiency may underpin reward and working memory dysfunction in bipolar disorder , 2012, The world journal of biological psychiatry : the official journal of the World Federation of Societies of Biological Psychiatry.

[35]  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.

[36]  G. MacQueen,et al.  Systematic review of the neural basis of social cognition in patients with mood disorders. , 2012, Journal of psychiatry & neuroscience : JPN.

[37]  Kristen A. Lindquist,et al.  The brain basis of emotion: A meta-analytic review , 2012, Behavioral and Brain Sciences.

[38]  Kimberly L. Ray,et al.  Meta-analytic evidence for a superordinate cognitive control network subserving diverse executive functions , 2012, Cognitive, affective & behavioral neuroscience.

[39]  P. Falkai,et al.  Common and distinct neural correlates of emotional processing in Bipolar Disorder and Major Depressive Disorder: A voxel-based meta-analysis of functional magnetic resonance imaging studies , 2012, European Neuropsychopharmacology.

[40]  S. Frangou,et al.  Sex differences in bipolar disorder: a review of neuroimaging findings and new evidence , 2012, Bipolar disorders.

[41]  Janaina Mourão Miranda,et al.  PRoNTo: Pattern Recognition for Neuroimaging Toolbox , 2013, Neuroinformatics.

[42]  A. Altamura,et al.  Assessing Working Memory via N-Back Task in Euthymic Bipolar I Disorder Patients: A Review of Functional Magnetic Resonance Imaging Studies , 2013, Neuropsychobiology.

[43]  D. Kupfer,et al.  Pattern recognition analysis of anterior cingulate cortex blood flow to classify depression polarity† , 2013, British Journal of Psychiatry.

[44]  E. Vassos,et al.  Independent modulation of engagement and connectivity of the facial network during affect processing by CACNA1C and ANK3 risk genes for bipolar disorder. , 2013, JAMA psychiatry.

[45]  A. Simmons,et al.  Examination of the predictive value of structural magnetic resonance scans in bipolar disorder: a pattern classification approach , 2012, Psychological Medicine.

[46]  C. Sabatti,et al.  Multisystem component phenotypes of bipolar disorder for genetic investigations of extended pedigrees. , 2014, JAMA psychiatry.

[47]  Rachel M. Brouwer,et al.  Can structural MRI aid in clinical classification? A machine learning study in two independent samples of patients with schizophrenia, bipolar disorder and healthy subjects , 2014, NeuroImage.

[48]  S. Frangou,et al.  Dynamic causal modeling of load‐dependent modulation of effective connectivity within the verbal working memory network , 2014, Human brain mapping.

[49]  T. Suslow,et al.  Amygdala excitability to subliminally presented emotional faces distinguishes unipolar and bipolar depression: An fMRI and pattern classification study , 2014, Human brain mapping.

[50]  M. Phillips,et al.  Brain morphometric biomarkers distinguishing unipolar and bipolar depression. A voxel-based morphometry-pattern classification approach. , 2014, JAMA psychiatry.

[51]  B. Mwangi,et al.  Prediction of pediatric bipolar disorder using neuroanatomical signatures of the amygdala , 2014, Bipolar disorders.

[52]  B. Franke,et al.  From estimating activation locality to predicting disorder: A review of pattern recognition for neuroimaging-based psychiatric diagnostics , 2015, Neuroscience & Biobehavioral Reviews.

[53]  Daniel L. Koller,et al.  Assessment of first and second degree relatives of individuals with bipolar disorder shows increased genetic risk scores in both affected relatives and young At‐Risk Individuals , 2015, American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics.

[54]  Steven H. Jones,et al.  Candidate Risks Indicators for Bipolar Disorder: Early Intervention Opportunities in High-Risk Youth , 2015, The international journal of neuropsychopharmacology.

[55]  F. Goodwin,et al.  Antidepressants worsen rapid-cycling course in bipolar depression: A STEP-BD randomized clinical trial. , 2015, Journal of affective disorders.

[56]  M. Adler.  Diagnostic and Statistical Manual of Mental Disorders, 4th Edition , 2016 .