Major Depressive Disorder Classification Based on Different Convolutional Neural Network Models: Deep Learning Approach

Leveraging Machine Learning Approaches for Predicting Antidepressant Treatment Response Using Electroencephalography (EEG) and Clinical Data

(2019) Natalia Jaworska et al.   Frontiers in Psychiatry

A Long Short-Term Memory deep learning network for the prediction of epileptic seizures using EEG signals

(2018) Κostas Μ. Tsiouris et al.   COMPUTERS IN BIOLOGY AND MEDICINE

A Deep Learning Architecture for Temporal Sleep Stage Classification Using Multivariate and Multimodal Time Series

(2018) Stanislas Chambon et al.   IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING

Task-positive and task-negative networks in major depressive disorder: A combined fMRI and EEG study

(2018) Gennady G. Knyazev et al.   JOURNAL OF AFFECTIVE DISORDERS

Deep learning for hybrid EEG-fNIRS brain–computer interface: application to motor imagery classification

(2018) Antonio Maria Chiarelli et al.   Journal of Neural Engineering

Deep Convolution Neural Network and Autoencoders-Based Unsupervised Feature Learning of EEG Signals

(2018) Tingxi Wen et al.   IEEE Access

An end-to-end deep learning approach to MI-EEG signal classification for BCIs

(2018) Hauke Dose et al.   EXPERT SYSTEMS WITH APPLICATIONS

A deep learning approach for Parkinson’s disease diagnosis from EEG signals

(2018) Shu Lih Oh et al.   NEURAL COMPUTING & APPLICATIONS

A Deep Learning Scheme for Motor Imagery Classification based on Restricted Boltzmann Machines

(2017) Na Lu et al.   IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING

Deep Learning Representation from Electroencephalography of Early-Stage Creutzfeldt-Jakob Disease and Features for Differentiation from Rapidly Progressive Dementia

(2017) Francesco Carlo Morabito et al.   International Journal of Neural Systems

Permutation Disalignment Index as an Indirect, EEG-Based, Measure of Brain Connectivity in MCI and AD Patients

(2017) Nadia Mammone et al.   International Journal of Neural Systems

Predicting tDCS treatment outcomes of patients with major depressive disorder using automated EEG classification

(2017) Alaa M. Al-Kaysi et al.   JOURNAL OF AFFECTIVE DISORDERS

Using deep learning to investigate the neuroimaging correlates of psychiatric and neurological disorders: Methods and applications

(2017) Sandra Vieira et al.   NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS

Major Depression Detection from EEG Signals Using Kernel Eigen-Filter-Bank Common Spatial Patterns

(2017) Shih-Cheng Liao et al.   SENSORS

Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals

(2017) U. Rajendra Acharya et al.   COMPUTERS IN BIOLOGY AND MEDICINE

EEG-based mild depressive detection using feature selection methods and classifiers

(2016) Xiaowei Li et al.   COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE

The Brain's Default Mode Network

(2015) Marcus E. Raichle   Annual Review of Neuroscience

Depressive Rumination, the Default-Mode Network, and the Dark Matter of Clinical Neuroscience

(2015) J. Paul Hamilton et al.   BIOLOGICAL PSYCHIATRY

Data mining EEG signals in depression for their diagnostic value

(2015) Mahdi Mohammadi et al.   BMC Medical Informatics and Decision Making

Nonlinear analysis of EEGs of patients with major depression during different emotional states

(2015) Saime Akdemir Akar et al.   COMPUTERS IN BIOLOGY AND MEDICINE

A wrapper-based approach for feature selection and classification of major depressive disorder–bipolar disorders

(2015) Turker Tekin Erguzel et al.   COMPUTERS IN BIOLOGY AND MEDICINE

A Novel Depression Diagnosis Index Using Nonlinear Features in EEG Signals

(2015) U. Rajendra Acharya et al.   EUROPEAN NEUROLOGY

A Longitudinal EEG Study of Alzheimer's Disease Progression Based on A Complex Network Approach

(2015) Francesco Carlo Morabito et al.   International Journal of Neural Systems

EEG power, cordance and coherence differences between unipolar and bipolar depression

(2015) Cumhur Tas et al.   JOURNAL OF AFFECTIVE DISORDERS

Artificial intelligence approach to classify unipolar and bipolar depressive disorders

(2015) Turker Tekin Erguzel et al.   NEURAL COMPUTING & APPLICATIONS

The Default Mode Network and EEG Regional Spectral Power: A Simultaneous fMRI-EEG Study

(2014) Irene Neuner et al.   PLoS One

Ant Colony Optimization Based Feature Selection Method for QEEG Data Classification

(2014) Turker Tekin Erguzel et al.   Psychiatry Investigation

EEG-Based Emotion Recognition Using Deep Learning Network with Principal Component Based Covariate Shift Adaptation

(2014) Suwicha Jirayucharoensak et al.   TheScientificWorldJOURNAL

Anti-anhedonic effect of ketamine and its neural correlates in treatment-resistant bipolar depression

(2014) N Lally et al.   Translational Psychiatry

A machine learning approach using EEG data to predict response to SSRI treatment for major depressive disorder

(2013) Ahmad Khodayari-Rostamabad et al.   CLINICAL NEUROPHYSIOLOGY

Resting state EEG power and coherence abnormalities in bipolar disorder and schizophrenia

(2013) Julia W.Y. Kam et al.   JOURNAL OF PSYCHIATRIC RESEARCH

Distinguishing Quantitative Electroencephalogram Findings between Adjustment Disorder and Major Depressive Disorder

(2013) Hyun-Ghang Jeong et al.   Psychiatry Investigation

Antidepressants Normalize the Default Mode Network in Patients With Dysthymia

(2013) Jonathan Posner et al.   JAMA Psychiatry

A Randomized Trial of a Low-Trapping Nonselective N-Methyl-D-Aspartate Channel Blocker in Major Depression

(2012) Carlos A. Zarate et al.   BIOLOGICAL PSYCHIATRY

Classifying depression patients and normal subjects using machine learning techniques and nonlinear features from EEG signal

(2012) Behshad Hosseinifard et al.   COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE

Default-Mode and Task-Positive Network Activity in Major Depressive Disorder: Implications for Adaptive and Maladaptive Rumination

(2011) J. Paul Hamilton et al.   BIOLOGICAL PSYCHIATRY

EEG delta oscillations as a correlate of basic homeostatic and motivational processes

(2011) Gennady G. Knyazev   NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS

The change of prefrontal QEEG theta cordance as a predictor of response to bupropion treatment in patients who had failed to respond to previous antidepressant treatments

(2010) Martin Bares et al.   EUROPEAN NEUROPSYCHOPHARMACOLOGY

Slow EEG pattern predicts reduced intrinsic functional connectivity in the default mode network: An inter-subject analysis

(2010) Jaroslav Hlinka et al.   NEUROIMAGE

Increased self-focus in major depressive disorder is related to neural abnormalities in subcortical-cortical midline structures

(2009) Simone Grimm et al.   HUMAN BRAIN MAPPING

EEG default mode network in the human brain: Spectral regional field powers

(2008) Andrew C.N. Chen et al.   NEUROIMAGE