Overview

Major depressive disorder (MDD) is a complex and severe mental illness, characterized by multiple symptoms, and is a leading cause of non-fatal health loss. Despite this, approximately 30% of patients do not respond to standard pharmacological or psychological treatments. Currently, we lack objective brain-based biomarkers to differentiate between natural mood fluctuations and situations requiring intervention. To address this issue, we employed a novel electrophysiology recording device and applied deep brain stimulation (DBS) to 12 MDD patients. Our study aims to use long-term invasive neural signal collection and machine learning techniques to reveal the complex relationship between these signals and depressive symptoms. By applying advanced machine learning algorithms, our goal is to establish highly accurate prediction models to identify biomarkers associated with the occurrence and progression of depression. The research will focus on the spatiotemporal features of neural signals and build personalized depression decoding models based on individual differences through the integration and analysis of large-scale data. By delving into the information contained in neural signals, we hope to contribute to the development of personalized treatment approaches for depression.

Eligibility

Inclusion Criteria:

• 1) Participants in the study should sign a research informed consent form before starting any research-related procedures; 2) Participants must be between the ages of 16 and 30, regardless of gender; 3) Diagnosed with Major Depressive Disorder (MDD) according to the diagnostic criteria in the DSM-V; 4) Participants must have medical records of their current depressive episode that has lasted for ≥2 years, or recurrent episodes, with a minimum of 4 episodes (with the current episode lasting at least 1 year); 5) Have previously failed at least 3 courses of adequate antidepressant therapy, using 2 or more different classes of antidepressants; and have refused, been unable to tolerate, or found electroconvulsive therapy (ECT) to be ineffective; 6) Participants must have a HAMD-17 score of ≥20 or a MADRS score of ≥25; 7) Participants must be able to communicate effectively, and the participant and their legal guardian must sign a written informed consent form.

Exclusion Criteria:

• 1) Participants with bipolar disorder, schizoaffective disorder, schizophrenia, or other psychotic disorders; 2) Severe personality disorders; 3) Severe physical diseases or organic brain diseases; 4) Participants with alcohol or substance abuse and dependence diagnosed within 1 year prior to screening according to DSM-IV criteria; 5) Participants with surgical contraindications, such as significant comorbid medical conditions or inability to discontinue anticoagulation medications; 6) Structural imaging abnormalities evident on MRI performed within 1 year prior to screening; 7) MRI contraindications (excluding DBS implantation or the device itself); 8) Pregnant or breastfeeding; 9) Participants who are enrolled in another study unrelated to the current study; 10) Any condition that may currently or potentially endanger the participant's safety or preclude their successful participation in the study (family support, medical, psychological, social, or geographic factors).