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DOI 10.3390/bioengineering13060694

Медицинская библиотека · Bioengineering (Basel, Switzerland) · 2026

Decoding Visual Pathway Dysfunction with SERF-MEG: A Study in Patients with Optic Neuropathy.

Wang Helei, Qi Yuankun, Lou Yu, Zhang Xu, Song Xinda

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Аннотация

This study aimed to characterize cortical dysfunction and frequency-specific network reorganization following optic nerve injury using spin-exchange relaxation-free magnetoencephalography (SERF-MEG), and to assess the potential of MEG-derived multiscale features as sensitive functional biomarkers for clinical evaluation. In this prospective case-control study, SERF-MEG recordings were acquired during a pattern-reversal visual stimulation paradigm. Time-domain evoked components (M100/M135), global electrophysiological indices, energy-based metrics, and alpha- and beta-band phase-based functional connectivity were extracted. Network topology was quantified using graph-theoretical measures, including global and local efficiency, clustering coefficient, and assortativity. Group-level differences between patients and healthy controls were statistically analyzed. Patients showed significantly reduced M100/M135 amplitudes, prolonged M100 latency, and a lower early-component energy ratio. Functional connectivity was significantly decreased in the alpha and beta bands, accompanied by reduced global and local efficiency, mean strength, and clustering coefficient. Seed-based analyses revealed reduced connectivity predominantly in occipito-parietal and occipito-temporal pathways. SERF-MEG provides sensitive identification of cortical- and network-level functional impairments following optic nerve damage. MEG has significant clinical potential for disease diagnosis and therapy monitoring, providing a novel objective assessment tool for neuro-ophthalmological disorders.

Для цитирования: Wang Helei, Qi Yuankun, Lou Yu, Zhang Xu, Song Xinda. Decoding Visual Pathway Dysfunction with SERF-MEG: A Study in Patients with Optic Neuropathy.. Bioengineering (Basel, Switzerland). 2026. DOI: 10.3390/bioengineering13060694.
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