Parsing the network mechanisms of electroconvulsive therapy

AM Leaver, R Espinoza, B Wade, KL Narr - Biological psychiatry, 2022‏ - Elsevier
Electroconvulsive therapy (ECT) is one of the oldest and most effective forms of
neurostimulation, wherein electrical current is used to elicit brief, generalized seizures under …

Magnetic resonance imaging for individual prediction of treatment response in major depressive disorder: a systematic review and meta-analysis

SE Cohen, JB Zantvoord, BN Wezenberg… - Translational …, 2021‏ - nature.com
No tools are currently available to predict whether a patient suffering from major depressive
disorder (MDD) will respond to a certain treatment. Machine learning analysis of magnetic …

Predicting treatment outcomes in major depressive disorder using brain magnetic resonance imaging: a meta-analysis

F Long, Y Chen, Q Zhang, Q Li, Y Wang, Y Wang… - Molecular …, 2024‏ - nature.com
Recent studies have provided promising evidence that neuroimaging data can predict
treatment outcomes for patients with major depressive disorder (MDD). As most of these …

Enhanced default mode network functional connectivity links with electroconvulsive therapy response in major depressive disorder

Y Pang, Q Wei, S Zhao, N Li, Z Li, F Lu, J Pang… - Journal of affective …, 2022‏ - Elsevier
Background Electroconvulsive therapy (ECT) is an effective neuromodulatory treatment for
major depressive disorder (MDD), especially for cases resistant to antidepressant drugs …

Magnetic resonance-guided focused ultrasound capsulotomy for refractory obsessive compulsive disorder and major depressive disorder: clinical and imaging results …

B Davidson, C Hamani, JS Rabin, M Goubran… - Molecular …, 2020‏ - nature.com
Obsessive compulsive disorder (OCD) and major depressive disorder (MDD) are common,
often refractory, neuropsychiatric conditions for which new treatment approaches are …

Prediction of remission among patients with a major depressive disorder based on the resting-state functional connectivity of emotion regulation networks

H Wu, R Liu, J Zhou, L Feng, Y Wang, X Chen… - Translational …, 2022‏ - nature.com
The prediction of antidepressant response is critical for psychiatrists to select the initial
antidepressant drug for patients with major depressive disorders (MDD). The implicated …

Machine learning of schizophrenia detection with structural and functional neuroimaging

D Shi, Y Li, H Zhang, X Yao, S Wang, G Wang… - Disease …, 2021‏ - Wiley Online Library
Schizophrenia (SZ) is a severe psychiatric illness, and it affects around 1% of the general
population; however, its reliable diagnosis is challenging. Functional MRI (fMRI) and …

Cross‐cohort replicable resting‐state functional connectivity in predicting symptoms and cognition of schizophrenia

C Zhao, R Jiang, J Bustillo, P Kochunov… - Human Brain …, 2024‏ - Wiley Online Library
Schizophrenia (SZ) is a debilitating mental illness characterized by adolescence or early
adulthood onset of psychosis, positive and negative symptoms, as well as cognitive …

[HTML][HTML] Predicting treatment outcome based on resting-state functional connectivity in internalizing mental disorders: a systematic review and meta-analysis

C Meinke, U Lueken, H Walter, K Hilbert - Neuroscience & Biobehavioral …, 2024‏ - Elsevier
Predicting treatment outcome in internalizing mental disorders prior to treatment initiation is
pivotal for precision mental healthcare. In this regard, resting-state functional connectivity (rs …

Breakthroughs and challenges for generating brain network-based biomarkers of treatment response in depression

S Prompiengchai, K Dunlop - Neuropsychopharmacology, 2024‏ - nature.com
Abstract Treatment outcomes widely vary for individuals diagnosed with major depressive
disorder, implicating a need for deeper understanding of the biological mechanisms …