Decoding Visual Pathway Dysfunction with SERF-MEG: A Study in Patients with Optic Neuropathy
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.
Authors
- Xinda Song (ORCID: https://orcid.org/0000-0003-2837-7646)
- Helei Wang
- Xi Zhang (ORCID: https://orcid.org/0000-0002-4638-3997)
- Yu Lou
- Yuankun Qi (ORCID: https://orcid.org/0009-0000-0512-7471)
Institutions
- State Administration of Traditional Chinese Medicine of the People's Republic of China (CN)
- Extreme Light Infrastructure - Nuclear Physics (RO)
- Beihang University (CN)
Publication Details
- Journal
- Bioengineering
- Published
- 2026-06-17
- DOI
- https://doi.org/10.3390/bioengineering13060694
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Beijing Science and Technology Planning Project