fNIRS-Based Minimum Spanning Tree Analysis inNeuropsychiatric Disorders

Although minimum spanning tree (MST) analysis has been used in previous neuroimaging research, this study is the first tointegrate task-based functional near-infrared spectroscopy (fNIRS), multiple neuropsychiatric groups, behavioral correlations,and additional measures such as survival ratio and hemispheric distribution within a single framework. This approach identifiesboth shared and disorder-specific network differences beyond what resting-state or single-disorder MST analyses reveal. Weinvestigated prefrontal cortex network topology differences using MST analysis of fNIRS data collected during a computerizedStroop task from healthy controls and patients with migraine, obsessive–compulsive disorder, and schizophrenia. MSTs wereconstructed from partial correlation–based functional connectivity matrices obtained from oxygenated hemoglobin time seriesduring neutral, congruent, and incongruent Stroop stimuli. Seven global MST metrics, survival ratio, and hemispheric edgecounts were derived, and their associations with reaction time and accuracy were evaluated. Schizophrenia exhibited a lessintegrated network than controls, characterized by longer path length and trends toward larger diameter, lower leaf fraction, andlower degree divergence, while slower responses correlated with less integrated MST patterns. Within-group similarity waslower in obsessive–compulsive disorder and schizophrenia, whereas hemispheric organization remained stable, and migraineshowed no robust differences from controls. Overall, MST metrics provide unbiased, threshold-free descriptors of large-scalebrain organization and reveal diagnosis-related topology changes in task-based fNIRS studies.