Department of Neuropsychiatry, Faculty of Medical Sciences, University of Fukui, Fukui, Japan; Department of Psychiatry, University of Pittsburgh School of Medicine, Western Psychiatric Institute and Clinic, 3811 O'Hara St, Pittsburgh, PA 15213, USA.
Neuroimage. 2010 May 15;51(1):173-82. doi: 10.1016/j.neuroimage.2010.02.009. Epub 2010 Feb 10.
Multiscale entropy (MSE) analysis is a novel entropy-based approach for measuring dynamical complexity in physiological systems over a range of temporal scales. To evaluate this analytic approach as an aid to elucidating the pathophysiologic mechanisms in schizophrenia, we examined MSE in EEG activity in drug-naive schizophrenia subjects pre- and post-treatment with antipsychotics in comparison with traditional EEG analysis. We recorded eyes-closed resting-state EEG from frontal, temporal, parietal, and occipital regions in drug-naive 22 schizophrenia and 24 age-matched healthy control subjects. Fifteen patients were re-evaluated within 2-8 weeks after the initiation of antipsychotic treatment. For each participant, MSE was calculated on one continuous 60-s epoch for each experimental session. Schizophrenia subjects showed significantly higher complexity at higher time scales (lower frequencies) than did healthy controls in fronto-centro-temporal, but not in parieto-occipital regions. Post-treatment, this higher complexity decreased to healthy control subject levels selectively in fronto-central regions, while the increased complexity in temporal sites remained higher. Comparative power analysis identified spectral slowing in frontal regions in pre-treatment schizophrenia subjects, consistent with previous findings, whereas no antipsychotic treatment effect was observed. In summary, multiscale entropy measures identified abnormal dynamical EEG signal complexity in anterior brain areas in schizophrenia that normalized selectively in fronto-central areas with antipsychotic treatment. These findings show that entropy-based analytic methods may serve as a novel approach for characterizing and understanding abnormal cortical dynamics in schizophrenia and elucidating the therapeutic mechanisms of antipsychotics.
多尺度熵（MSE）分析是一种新的基于熵的方法，用于测量生理系统在多个时间尺度上的动态复杂性。为了评估这种分析方法作为阐明精神分裂症病理生理机制的辅助手段，我们在未经药物治疗的精神分裂症患者中，在抗精神病药物治疗前后，将 MSE 应用于 EEG 活动，与传统 EEG 分析进行了比较。我们记录了 22 名未经药物治疗的精神分裂症患者和 24 名年龄匹配的健康对照者闭眼静息状态的额、颞、顶和枕部 EEG。15 名患者在开始抗精神病药物治疗后 2-8 周内再次接受评估。对于每个参与者，在每个实验会话中，都对一个连续的 60 秒的片段进行 MSE 计算。与健康对照组相比，精神分裂症患者在前额-中央-颞叶区域表现出更高的复杂性（更低的频率），而在顶-枕叶区域则没有。治疗后，这种更高的复杂性选择性地降低到健康对照组水平，而颞叶部位的增加复杂性仍然更高。比较性功率分析在前治疗的精神分裂症患者的额区识别出了频谱减速，与之前的发现一致，而没有观察到抗精神病药物的治疗效果。总之，多尺度熵测量方法识别出了精神分裂症患者前脑区异常的动态 EEG 信号复杂性，抗精神病药物治疗后，仅在前额中央区域恢复正常。这些发现表明，基于熵的分析方法可以作为一种新的方法来描述和理解精神分裂症中异常的皮质动力学，并阐明抗精神病药物的治疗机制。
