Multimodal brain connectome-based prediction of suicide risk in people with late-life depression

[1]  V. Lo Buono,et al.  Diffusion tensor imaging studies on subjects with suicidal thoughts and behaviors: A descriptive literature review , 2022, Brain and behavior.

[2]  M. Olfson,et al.  Identification of Suicide Attempt Risk Factors in a National US Survey Using Machine Learning. , 2021, JAMA psychiatry.

[3]  Bartosz Bohaterewicz,et al.  Machine Learning-Based Identification of Suicidal Risk in Patients With Schizophrenia Using Multi-Level Resting-State fMRI Features , 2020, Frontiers in Neuroscience.

[4]  Jaclyn S. Kirshenbaum,et al.  Smaller caudate gray matter volume is associated with greater implicit suicidal ideation in depressed adolescents. , 2020, Journal of affective disorders.

[5]  Clive H. Y. Wong,et al.  Connectome-based models can predict processing speed in older adults , 2020, NeuroImage.

[6]  R. Mahendran,et al.  The individualized prediction of cognitive test scores in mild cognitive impairment using structural and functional connectivity features , 2020, NeuroImage.

[7]  P. Bandettini,et al.  Movie-watching outperforms rest for functional connectivity-based prediction of behavior , 2020, NeuroImage.

[8]  Chunshui Yu,et al.  Grab‐AD: Generalizability and reproducibility of altered brain activity and diagnostic classification in Alzheimer's Disease , 2020, Human brain mapping.

[9]  Seong-Jin Cho,et al.  Differences in brain surface area and cortical volume between suicide attempters and non-attempters with major depressive disorder , 2020, Psychiatry Research: Neuroimaging.

[10]  Lynnette A. Averill,et al.  Imaging suicidal thoughts and behaviors: a comprehensive review of 2 decades of neuroimaging studies , 2019, Molecular Psychiatry.

[11]  G. Kranz,et al.  Rumination network dysfunction in major depression: A brain connectome study , 2019, Progress in Neuro-Psychopharmacology and Biological Psychiatry.

[12]  Dustin Scheinost,et al.  A decade of test-retest reliability of functional connectivity: A systematic review and meta-analysis , 2019, NeuroImage.

[13]  Dustin Scheinost,et al.  The Functional Brain Organization of an Individual Allows Prediction of Measures of Social Abilities Transdiagnostically in Autism and Attention-Deficit/Hyperactivity Disorder , 2019, Biological Psychiatry.

[14]  Mark E. Bastin,et al.  The effect of network thresholding and weighting on structural brain networks in the UK Biobank , 2019, NeuroImage.

[15]  Mert R. Sabuncu,et al.  Global signal regression strengthens association between resting-state functional connectivity and behavior , 2019, NeuroImage.

[16]  I. Gotlib,et al.  Reduced dorsal striatal gray matter volume predicts implicit suicidal ideation in adolescents , 2018, Social cognitive and affective neuroscience.

[17]  Sonia J. Lupien,et al.  The effects of chronic stress on the human brain: From neurotoxicity, to vulnerability, to opportunity , 2018, Frontiers in Neuroendocrinology.

[18]  A. Neacsiu,et al.  Suicidal Behavior and Problems with Emotion Regulation , 2018, Suicide & life-threatening behavior.

[19]  C. Beckmann,et al.  How the brain connects in response to acute stress: A review at the human brain systems level , 2017, Neuroscience & Biobehavioral Reviews.

[20]  M. Just,et al.  Machine learning of neural representations of suicide and emotion concepts identifies suicidal youth , 2017, Nature Human Behaviour.

[21]  Jessica S. Damoiseaux,et al.  Effects of aging on functional and structural brain connectivity , 2017, NeuroImage.

[22]  K. Yun,et al.  Classification of Suicide Attempts through a Machine Learning Algorithm Based on Multiple Systemic Psychiatric Scales , 2017, Front. Psychiatry.

[23]  Dustin Scheinost,et al.  Using connectome-based predictive modeling to predict individual behavior from brain connectivity , 2017, Nature Protocols.

[24]  Andrew T. Drysdale,et al.  Resting-state connectivity biomarkers define neurophysiological subtypes of depression , 2016, Nature Medicine.

[25]  Jun Cao,et al.  Resting-state functional MRI of abnormal baseline brain activity in young depressed patients with and without suicidal behavior. , 2016, Journal of affective disorders.

[26]  Nathan D. Cahill,et al.  Sex and Age Effects of Functional Connectivity in Early Adulthood , 2016, Brain Connect..

[27]  L. Brundin,et al.  Role of Inflammation in Suicide: From Mechanisms to Treatment , 2016, Neuropsychopharmacology.

[28]  M. Pompili,et al.  Understanding Suicidal Behavior: The Contribution of Recent Resting-State fMRI Techniques , 2016, Front. Psychiatry.

[29]  H. Tsai,et al.  Development and psychometric testing of the triggers of Suicidal Ideation Inventory for assessing older outpatients in primary care settings , 2016, European Psychiatry.

[30]  E. Gudayol-Ferré,et al.  Changes in brain connectivity related to the treatment of depression measured through fMRI: a systematic review , 2015, Front. Hum. Neurosci..

[31]  Yong He,et al.  A connectivity-based test-retest dataset of multi-modal magnetic resonance imaging in young healthy adults , 2015, Scientific Data.

[32]  B. Draper,et al.  A systematic review of physical illness, functional disability, and suicidal behaviour among older adults , 2015, Aging & mental health.

[33]  Alex R. Smith,et al.  Sex differences in the structural connectome of the human brain , 2013, Proceedings of the National Academy of Sciences.

[34]  Mary E. Meyerand,et al.  The effect of scan length on the reliability of resting-state fMRI connectivity estimates , 2013, NeuroImage.

[35]  Martijn P. van den Heuvel,et al.  Estimating false positives and negatives in brain networks , 2013, NeuroImage.

[36]  Simon B. Eickhoff,et al.  One-year test–retest reliability of intrinsic connectivity network fMRI in older adults , 2012, NeuroImage.

[37]  Huafu Chen,et al.  Altered functional-structural coupling of large-scale brain networks in idiopathic generalized epilepsy. , 2011, Brain : a journal of neurology.

[38]  Joachim M. Buhmann,et al.  Generative Embedding for Model-Based Classification of fMRI Data , 2011, PLoS Comput. Biol..

[39]  Kelly C. Cukrowicz,et al.  Course of suicide ideation and predictors of change in depressed older adults. , 2009, Journal of affective disorders.

[40]  Kuncheng Li,et al.  Altered functional connectivity in early Alzheimer's disease: A resting‐state fMRI study , 2007, Human brain mapping.

[41]  B. Zhong,et al.  Prevalence and recognition of depressive disorders among Chinese older adults receiving primary care: A multi-center cross-sectional study. , 2020, Journal of affective disorders.

[42]  A. Olmer,et al.  Antidepressants Reduce the Risk of Suicide among Elderly Depressed Patients , 2006, Neuropsychopharmacology.

[43]  Z. Y. Wang,et al.  A Chinese version of the Mini-Mental State Examination; impact of illiteracy in a Shanghai dementia survey. , 1988, Journal of clinical epidemiology.