Transfer Learning Between fMRI-Based Predictors of Treatment Outcome with Psilocybin and Escitalopram in Patients with Major Depression

Keyphrases

• Functional Magnetic Resonance Imaging 100%
• Transfer Learning 100%
• Psilocybin 100%
• Major Depressive Disorder 100%
• Escitalopram 100%
• Clinical Outcome Prediction 100%
• Resting-state Functional Connectivity (rs-FC) 33%
• Treatment Efficacy 33%
• Mood Disorders 33%
• Brain Connectivity 33%
• Functional Connection 33%
• Connectivity Pattern 33%
• Learning Scheme 33%
• Default Mode 33%
• Large-scale Functional Networks 33%
• Validation Scheme 33%
• Pharmacological Intervention 33%
• Symptom Improvement 33%
• Brain Activity Measurement 33%
• Patient's Will 33%
• SSRI Drugs 33%
• Visual Mode 33%
• Drug Type 33%
• Psychedelics 33%
• Mode Area 33%
• Novel Therapies 33%

INIS

• learning 100%
• patients 100%
• prediction 100%
• brain 66%
• drugs 66%
• connections 33%
• capacity 33%
• accuracy 33%
• values 33%
• therapy 33%
• symptoms 33%
• interventions 33%
• validation 33%
• nmr imaging 33%

Neuroscience

• Psilocybin 100%
• Escitalopram 100%
• Major Depressive Disorder 100%
• Functional Magnetic Resonance Imaging 100%
• Functional Connectivity 33%
• Mood Disorder 33%
• Psychotomimetic 33%
• Selective Serotonin Reuptake Inhibitor 33%