TOPOLOGICAL DATA ANALYSIS IN MENTAL-HEALTH RESEARCH: SYSTEMATIC REVIEW

Abstract

Mental disorders involve complex and overlapping changes that cannot be readily described by one variable or an equation.The PRISMA-based review process is focused on diseases, databases, and analysis objectives to which the TDA approach was applied.Papers eligible in this study included schizophrenia, depression, severe mental disorder, autism, ADHD, obsessive-compulsive disorder, and substance abuse disorder.Among the data sources used were the ADHD-200 and ABIDE which were the most reused open datasets, COBRE, UK Biobank, ENIGMA-OCD, and several local cohorts.Persistent homology was useful for multi-level analysis independent from one threshold while Mapper was used for identification of subgroups and outcomes.Features extracted by TDA have shown promise in distinguishing individuals with mental illness from control groups; however, these results are insufficient for clinical diagnosis.Therefore, topological features need to be validated and examined alongside statistical, machine learning, and clinical techniques.

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