Related references
Note: Only part of the references are listed.Electroconvulsive Therapy
Randall T. Espinoza et al.
NEW ENGLAND JOURNAL OF MEDICINE (2022)
Remission of depression is associated with asymmetric hemispheric variation in EEG complexity before antidepressant treatment
Hsin-Jung Tsai et al.
JOURNAL OF AFFECTIVE DISORDERS (2021)
Using CatBoost algorithm to identify middle-aged and elderly depression, national health and nutrition examination survey 2011-2018
Chenyang Zhang et al.
PSYCHIATRY RESEARCH (2021)
The Economic Burden of Adults with Major Depressive Disorder in the United States (2010 and 2018)
Paul E. Greenberg et al.
PHARMACOECONOMICS (2021)
Neurofeedback training in major depressive disorder: A systematic review of clinical efficacy, study quality and reporting practices
Lucas R. Trambaiolli et al.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS (2021)
Hippocampal tail volume as a predictive biomarker of antidepressant treatment outcomes in patients with major depressive disorder: a CAN-BIND report
Nikita Nogovitsyn et al.
NEUROPSYCHOPHARMACOLOGY (2020)
The learning effects and curves during high beta down-training neurofeedback for patients with major depressive disorder
Ting-Chun Chen et al.
JOURNAL OF AFFECTIVE DISORDERS (2020)
Top companies and drugs by sales in 2019
Lisa Urquhart
NATURE REVIEWS DRUG DISCOVERY (2020)
Use of Machine Learning for Predicting Escitalopram Treatment Outcome From Electroencephalography Recordings in Adult Patients With Depression
Andrey Zhdanov et al.
JAMA NETWORK OPEN (2020)
Patients with major depressive disorder have lower cerebral serotonin 4 receptor binding than healthy controls
K. Koehler-Forsberg et al.
EUROPEAN NEUROPSYCHOPHARMACOLOGY (2020)
Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions
David M. Howard et al.
NATURE NEUROSCIENCE (2019)
Prediction of rTMS treatment response in major depressive disorder using machine learning techniques and nonlinear features of EEG signal
Fatemeh Hasanzadeh et al.
JOURNAL OF AFFECTIVE DISORDERS (2019)
Depression biomarkers using non-invasive EEG: A review
Fernando Soares de Aguiar Neto et al.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS (2019)
Electroencephalographic Biomarkers for Treatment Response Prediction in Major Depressive Illness: A Meta-Analysis
Alik S. Widge et al.
AMERICAN JOURNAL OF PSYCHIATRY (2019)
EEG Frequency Bands in Psychiatric Disorders: A Review of Resting State Studies
Jennifer J. Newson et al.
FRONTIERS IN HUMAN NEUROSCIENCE (2019)
Neurofeedback Treatment on Depressive Symptoms and Functional Recovery in Treatment-Resistant Patients with Major Depressive Disorder: an Open-Label Pilot Study
Young-Ji Lee et al.
JOURNAL OF KOREAN MEDICAL SCIENCE (2019)
Epidemiology of Adult DSM-5 Major Depressive Disorder and Its Specifiers in the United States
Deborah S. Hasin et al.
JAMA PSYCHIATRY (2018)
Cost-effectiveness of Electroconvulsive Therapy vs Pharmacotherapy/Psychotherapy for Treatment-Resistant Depression in the United States
Eric L. Ross et al.
JAMA PSYCHIATRY (2018)
Applications of machine learning algorithms to predict therapeutic outcomes in depression: A meta-analysis and systematic review
Yena Lee et al.
JOURNAL OF AFFECTIVE DISORDERS (2018)
Factors related to the improvement in quality of life for depressed inpatients treated with fluoxetine
Wei-Cheng Yang et al.
BMC PSYCHIATRY (2017)
Beyond the Status Quo: A Role for Beta Oscillations in Endogenous Content (Re)Activation
Bernhard Spitzer et al.
ENEURO (2017)
Early improvement predicts outcome of major depressive patients treated with electroconvulsive therapy
Ching-Hua Lin et al.
EUROPEAN NEUROPSYCHOPHARMACOLOGY (2016)
The Efficacy of Neurofeedback in Patients with Major Depressive Disorder: An Open Labeled Prospective Study
Eun-Jin Cheon et al.
APPLIED PSYCHOPHYSIOLOGY AND BIOFEEDBACK (2016)
The role of high-frequency oscillatory activity in reward processing and learning
Josep Marco-Pallares et al.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS (2015)
What Does the Electroencephalogram Tell Us About the Mechanisms of Action of ECT in Major Depressive Disorders?
Faranak Farzan et al.
JOURNAL OF ECT (2014)
The Epidemiology of Depression Across Cultures
Ronald C. Kessler et al.
ANNUAL REVIEW OF PUBLIC HEALTH, VOL 34 (2013)
Severity classification on the Hamilton depression rating scale
Mark Zimmerman et al.
JOURNAL OF AFFECTIVE DISORDERS (2013)
Functional Neuroimaging of Major Depressive Disorder: A Meta-Analysis and New Integration of Baseline Activation and Neural Response Data
J. Paul Hamilton et al.
AMERICAN JOURNAL OF PSYCHIATRY (2012)
Benefits From Antidepressants Synthesis of 6-Week Patient-Level Outcomes From Double-blind Placebo-Controlled Randomized Trials of Fluoxetine and Venlafaxine
Robert D. Gibbons et al.
ARCHIVES OF GENERAL PSYCHIATRY (2012)
Beta-band oscillations - signalling the status quo?
Andreas K. Engel et al.
CURRENT OPINION IN NEUROBIOLOGY (2010)
Free choice activates a decision circuit between frontal and parietal cortex
Bijan Pesaran et al.
NATURE (2008)
Oscillatory interactions between sensorimotor cortex and the periphery
Stuart N. Baker
CURRENT OPINION IN NEUROBIOLOGY (2007)
Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices
Timothy J. Buschman et al.
SCIENCE (2007)
Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: Implications for clinical practice
MH Trivedi et al.
AMERICAN JOURNAL OF PSYCHIATRY (2006)
Size of treatment effects and their importance to clinical research and practice
Helena Chmura Kraemer et al.
BIOLOGICAL PSYCHIATRY (2006)
Relation between frontal 3-7 Hz MEG activity and the efficacy of ECT in major depression
P Heikman et al.
JOURNAL OF ECT (2001)
Share Paper
