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<p>Steady-state visual evoked potentials (SSVEPs) in patients with schizophrenia and healthy controls are significantly different and have a potential application in distinguishing between these groups. However, the underlying neural dynamic mechanism of SSVEPs in schizophrenia remains unclear. Here, we investigated this mechanism by stimulating SSVEP responses and analyzing them using large-scale computational brain models based on neuroimaging data from schizophrenia patients and healthy controls. The results revealed that SSVEP responses to alpha-band (8–12&#xa0;Hz) visual stimulation were significantly attenuated in schizophrenia patients compared with healthy controls under alpha-band, whereas the opposite pattern was observed under low-band (2–3&#xa0;Hz) visual stimulation. The efficiencies of these functional networks followed a similar pattern of change, and differences in internetwork functional connectivity (FC), especially the visual network (VIS) and default mode network (DMN), between schizophrenia patients and healthy controls were identified as contributors to SSVEP responses. We subsequently developed a regulatory strategy using the large-scale brain model of schizophrenia, and this strategy improved the SSVEP response to levels similar to those in healthy controls. This study not only elucidates the underlying mechanisms of the differences in SSVEP responses between patients with schizophrenia and healthy controls but also validates the application of large-scale brain modeling for brain disorders.</p>

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Computational exploration of the SSVEP response and regulation in schizophrenia by large-scale brain dynamics modeling

  • 期刊论文

  • 发表日期：

    2025年4月21日

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  • Ge Zhang,
  • Yan Cui,
  • Shuqi Guo,
  • Yue Xiong,
  • Feiyan Wang,
  • Dezhong Yao,
  • Daqing Guo

摘要

Steady-state visual evoked potentials (SSVEPs) in patients with schizophrenia and healthy controls are significantly different and have a potential application in distinguishing between these groups. However, the underlying neural dynamic mechanism of SSVEPs in schizophrenia remains unclear. Here, we investigated this mechanism by stimulating SSVEP responses and analyzing them using large-scale computational brain models based on neuroimaging data from schizophrenia patients and healthy controls. The results revealed that SSVEP responses to alpha-band (8–12 Hz) visual stimulation were significantly attenuated in schizophrenia patients compared with healthy controls under alpha-band, whereas the opposite pattern was observed under low-band (2–3 Hz) visual stimulation. The efficiencies of these functional networks followed a similar pattern of change, and differences in internetwork functional connectivity (FC), especially the visual network (VIS) and default mode network (DMN), between schizophrenia patients and healthy controls were identified as contributors to SSVEP responses. We subsequently developed a regulatory strategy using the large-scale brain model of schizophrenia, and this strategy improved the SSVEP response to levels similar to those in healthy controls. This study not only elucidates the underlying mechanisms of the differences in SSVEP responses between patients with schizophrenia and healthy controls but also validates the application of large-scale brain modeling for brain disorders.