Functional Near-Infrared Spectroscopy in Schizophrenia Research: Progress, Challenges, and Future Directions

This review comprehensively examines the application and progress of functional near-infrared spectroscopy (fNIRS) in schizophrenia research. Schizophrenia is a complex neuropsychiatric disorder characterized by extensive dysfunction in the prefrontal-limbic system and dysregulation of brain network connectivity. fNIRS, with its advantages of high portability, resistance to motion interference, and non-invasive real-time monitoring of cerebral hemodynamic responses, has emerged as a valuable tool in exploring the neural mechanisms of schizophrenia. It can capture the overactivity of the default mode network (DMN) during resting states and the under-activation of brain regions such as the prefrontal and temporal lobes during task states. Studies have demonstrated that combining fNIRS with neuromodulation techniques, including transcranial direct current stimulation (tDCS) and theta burst stimulation (TBS), can improve negative symptoms and offer a potential approach for individualized diagnosis and treatment. However, challenges remain in fNIRS research, such as signal noise processing, insufficient ability to detect deep brain regions, and research heterogeneity. Future research will focus on technological innovations (eg, high-density fNIRS and multimodal fusion), machine-learning-driven biomarker mining, and clinical translation (eg, optimizing individualized neuroregulatory targets). Through interdisciplinary integration, fNIRS is expected to facilitate breakthroughs in the individualized diagnosis and treatment of schizophrenia and enhance understanding of its neural mechanisms. This review also discusses the potential of fNIRS as a biomarker for schizophrenia, its role in monitoring treatment efficacy, and the importance of addressing technical limitations to advance its clinical application.