Developing Advanced AI Ecosystems to Enhance Diagnosis and Care for Patients with Depression.

Major Depressive Disorder (MDD) has a significant impact on the daily lives of those affected. This concept paper presents a project that aims at addressing MDD challenges through innovative therapy systems. The project consists of two use cases: a multimodal neurofeedback (NFB) therapy and an AI-based virtual therapy assistant (VTA). The multimodal NFB integrates EEG and fNIRS to comprehensively assess brain function. The goal is to develop an open-source NFB toolbox for EEG-fNIRS integration, augmented by the VTA for optimized efficacy. The VTA will be able to collect behavioral data, provide personalized feedback and support MDD patients in their daily lives. This project aims to improve depression treatment by bringing together digital therapy, AI and mobile apps to potentially improve outcomes and accessibility for people living with depression.

Gaze-based attention refocusing training in virtual reality for adult attention-deficit/hyperactivity disorder.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is characterized by substantial interindividual heterogeneity that challenges the systematic assessment and treatment. Considering mixed evidence from previous neurofeedback research, we present a novel feedback system that relies on gaze behavior to detect signs of inattention while performing a neuropsychological attention task in a virtual seminar room. More specifically, an audiovisual feedback was given whenever participants averted their gaze from the given task. METHODS: Eighteen adults with ADHD and 18 healthy controls performed a continuous performance task (CPT) in virtual reality under three counterbalanced conditions in which either gaze-based feedback, sham feedback, or no feedback was provided. In all conditions, phases of high and low virtual distraction alternated. CPT errors and reaction times, proportions of gaze dwell times (e.g., task focus or distraction focus), saccade characteristics, EEG theta/beta ratios, head movements, and an experience sampling of ADHD symptoms were analyzed. RESULTS: While patients can be discriminated well from healthy controls in that they showed more omission errors, higher reaction times, higher distraction-related dwell times, and more head movements, the feedback did not immediately improve task performance. It was also indicated that sham feedback was rather associated with an aggravation of symptoms in patients. CONCLUSIONS: Our findings demonstrate sufficient suitability and specificity for this holistic ADHD symptom assessment. Regarding the feedback, a single-session training was insufficient to achieve learning effects based on the proposed metacognitive strategies. Future longitudinal, multi-session trials should conclusively examine the therapeutic efficacy of gaze-based virtual reality attention training in ADHD. TRIAL REGISTRATION: drks.de (identifier: DRKS00022370).