Proceedings of the Annual Meeting of the Cognitive Science Society

Disorders of consciousness (DoC) are primarily diagnosed using behavioral assessments, which are prone to high misdiagnosis rates. Objective neural markers are therefore needed. This study investigated residual neural responses to naturalistic auditory stimuli in DoC patients to better reflect covert consciousness. Four auditory conditions were presented: natural speech sentences, music, animal sounds, and pure tones as a baseline. Functional near-infrared spectroscopy (fNIRS) was used to assess cortical activation, hemodynamic responses, and functional network alterations during auditory processing. A support vector machine (SVM) classifier was applied to distinguish vegetative state (VS) from minimally conscious state (MCS) patients and to identify the most informative neural features. Complex natural stimuli, particularly speech and music, elicited more specific hemodynamic and network responses than pure tones. Patients with higher consciousness levels showed selectively enhanced left-hemispheric activity and stronger long-range network connectivity during speech perception. The model achieved an overall accuracy of 86.84% (VS: 78.57%; MCS: 91.67%), with the top contributing features exclusively network-based. These findings support the value of naturalistic auditory paradigms and network features for precise DoC assessment.