Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Cardiff, United Kingdom; Neuroinformatics Group, Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Cardiff, United Kingdom; Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, College of Biomedical and Life Sciences, Cardiff University, Cardiff, United Kingdom; School of Psychology, College of Biomedical and Life Sciences,Cardiff University, Cardiff, United Kingdom; Neuroscience and Mental Health Research Institute, School of Medicine, College of Biomedical and Life Sciences,Cardiff University, Cardiff, United Kingdom; MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, College of Biomedical and Life Sciences, Cardiff University, Cardiff, United Kingdom.
Prog Neuropsychopharmacol Biol Psychiatry. 2021 Jun 8;108:110073. doi: 10.1016/j.pnpbp.2020.110073. Epub 2020 Aug 14.
Electroencephalography (EEG) based biomarkers have been shown to correlate with the presence of psychotic disorders. Increased delta and decreased alpha power in psychosis indicate an abnormal arousal state. We investigated brain activity across the basic EEG frequencies and also dynamic functional connectivity of both intra and cross-frequency coupling that could reveal a neurophysiological biomarker linked to an aberrant modulating role of alpha frequency in adolescents with schizophrenia spectrum disorders (SSDs). A dynamic functional connectivity graph (DFCG) has been estimated using the imaginary part of phase lag value (iPLV) and correlation of the envelope (corrEnv). We analyzed DFCG profiles of electroencephalographic resting state (eyes closed) recordings of healthy controls (HC) (n = 39) and SSDs subjects (n = 45) in basic frequency bands {δ,θ,α,α,β,β,γ}. In our analysis, we incorporated both intra and cross-frequency coupling modes. Adopting our recent Dominant Coupling Mode (DοCM) model leads to the construction of an integrated DFCG (iDFCG) that encapsulates the functional strength and the DοCM of every pair of brain areas. We revealed significantly higher ratios of delta/alpha, power spectrum in SSDs subjects versus HC. The probability distribution (PD) of amplitude driven DoCM mediated by alpha frequency differentiated SSDs from HC with absolute accuracy (100%). The network Flexibility Index (FI) was significantly lower for subjects with SSDs compared to the HC group. Our analysis supports the central role of alpha frequency alterations in the neurophysiological mechanisms of SSDs. Currents findings open up new diagnostic pathways to clinical detection of SSDs and support the design of rational neurofeedback training.
基于脑电图（EEG）的生物标志物已被证明与精神病的存在相关。精神病中 delta 波增加和 alpha 波减少表明异常觉醒状态。我们研究了基本 EEG 频率范围内的大脑活动，以及跨频耦合的动态功能连接，这可能揭示与精神分裂症谱系障碍（SSDs）青少年中 alpha 频率异常调节作用相关的神经生理学生物标志物。使用相滞后值的虚部（iPLV）和包络相关（corrEnv）来估计动态功能连接图（DFCG）。我们分析了健康对照组（HC）（n=39）和 SSDs 受试者（n=45）在基本频带{δ、θ、α、β、β、γ}中的静息状态（闭眼）脑电图记录的 DFCG 谱。在我们的分析中，我们结合了内频和跨频耦合模式。采用我们最近的主导耦合模式（DοCM）模型，可以构建一个集成的 DFCG（iDFCG），它包含每个大脑区域的功能强度和 DοCM。我们发现 SSDs 受试者的 delta/alpha 比值和功率谱明显高于 HC。由 alpha 频率驱动的幅度主导 DoCM 的概率分布（PD）将 SSDs 与 HC 区分开来，具有绝对准确性（100%）。与 HC 组相比，SSD 受试者的网络灵活性指数（FI）显著降低。我们的分析支持 alpha 频率改变在 SSDs 神经生理机制中的核心作用。目前的研究结果为 SSDs 的临床检测开辟了新的诊断途径，并支持合理的神经反馈训练的设计。
