Overview

The objective of this subproject is to validate the efficacy of the fNIRS real-time anxiety monitoring and neurofeedback system. In the first year, the cerebral hemodynamics measured by commercial fNIRS during resting state and cognitive tasks from 60 generalized anxiety disorder (GAD) patients and 30 healthy subjects will be processed and analyzed using AI algorithms. The novel anxiety fNIRS biomarker will be identified and correlated to clinical anxiety scales (such as HARS and STAI). In the second year, the reliability, validity, and responsiveness of the AI-fNIRS biomarker will be validated. The accuracy of using AI-fNIRS biomarker to predict the diagnosis of GAD (according to DSM-5) and anxiety rating scales will be calculated from 60 GAD patients and 30 healthy subjects. In the third year, a neurofeedback method using AI-fNIRS biomarkers to guide digital cognitive behavior therapy (dCBT) through visual/audio cues will be developed. A pilot study with 12 GAD patients will be performed to test the feasibility of mindfulness training during AI-fNIRS neurofeedback. In the fourth year, a large scale RCT will be performed to validate the therapeutic efficacy of AI-fNIRS neurofeedback dCBT in 40 patients with GAD. The protocol of using real-time AI-fNIRS biomarkers as a neurofeedback to augment mindfulness training will be optimized according to previous year.

Eligibility

Inclusion Criteria:

• Being diagnosed with generalized anxiety disorder (GAD) by psychiatrists based on DSM-V.
• Native Chinese speakers.
• Right-handers.
• Normal vision without or after correction.
• Normal hearing and verbal expression.
• Regular returns of medical or psychological intervention during participation.

Exclusion Criteria:

• Being diagnosed with other major neurological or mental disorders.