Chaparro-Vargas Ramiro, Schilling Claudia, Schredl Michael, Cvetkovic Dean
School of Electrical and Computing Engineering, RMIT University, Melbourne, VIC, 3121, Australia.
Sleep laboratory of the Central Institute of Mental Health, Mannheim, Germany.
Med Biol Eng Comput. 2016 Jan;54(1):77-91. doi: 10.1007/s11517-015-1297-4. Epub 2015 Apr 19.
The quantification of interdependencies within autonomic nervous system has gained increasing importance to characterise healthy and psychiatric disordered subjects. The present work introduces a biosignal processing approach, suggesting a computational resource to estimate coherent or synchronised interactions as an eventual supportive aid in the diagnosis of primary insomnia and schizophrenia pathologies. By deploying linear, nonlinear and statistical methods upon 25 electroencephalographic and electrocardiographic overnight sleep recordings, the assessment of cross-correlation, wavelet coherence and [Formula: see text]:[Formula: see text] phase synchronisation is focused on tracking discerning features amongst the clinical cohorts. Our results indicate that certain neuronal oscillations interact with cardiac power bands in distinctive ways responding to standardised sleep stages and patient groups, which promotes the hypothesis of subtle functional dynamics between neuronal assembles and (para)sympathetic activity subject to pathophysiological conditions.
自主神经系统内相互依存关系的量化对于表征健康和患有精神疾病的受试者变得越来越重要。目前的工作引入了一种生物信号处理方法,提出了一种计算资源,用于估计相干或同步相互作用,作为原发性失眠和精神分裂症病理学诊断的最终辅助手段。通过对25份脑电图和心电图夜间睡眠记录应用线性、非线性和统计方法,互相关、小波相干和[公式:见正文]相位同步的评估集中于追踪临床队列中的辨别特征。我们的结果表明,某些神经元振荡以独特的方式与心脏功率带相互作用,对标准化睡眠阶段和患者群体做出反应,这支持了在病理生理条件下神经元集合与(副)交感神经活动之间存在微妙功能动态的假设。