Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland.
Department of Neurology, University Medical Centre Utrecht Brain Centre, Utrecht University, Utrecht, The Netherlands.
Hum Brain Mapp. 2019 Nov 1;40(16):4827-4842. doi: 10.1002/hbm.24740. Epub 2019 Jul 26.
Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease primarily affecting motor function, with additional evidence of extensive nonmotor involvement. Despite increasing recognition of the disease as a multisystem network disorder characterised by impaired connectivity, the precise neuroelectric characteristics of impaired cortical communication remain to be fully elucidated. Here, we characterise changes in functional connectivity using beamformer source analysis on resting-state electroencephalography recordings from 74 ALS patients and 47 age-matched healthy controls. Spatiospectral characteristics of network changes in the ALS patient group were quantified by spectral power, amplitude envelope correlation (co-modulation) and imaginary coherence (synchrony). We show patterns of decreased spectral power in the occipital and temporal (δ- to β-band), lateral/orbitofrontal (δ- to θ-band) and sensorimotor (β-band) regions of the brain in patients with ALS. Furthermore, we show increased co-modulation of neural oscillations in the central and posterior (δ-, θ- and γ -band) and frontal (δ- and γ -band) regions, as well as decreased synchrony in the temporal and frontal (δ- to β-band) and sensorimotor (β-band) regions. Factorisation of these complex connectivity patterns reveals a distinct disruption of both motor and nonmotor networks. The observed changes in connectivity correlated with structural MRI changes, functional motor scores and cognitive scores. Characteristic patterned changes of cortical function in ALS signify widespread disease-associated network disruption, pointing to extensive dysfunction of both motor and cognitive networks. These statistically robust findings, that correlate with clinical scores, provide a strong rationale for further development as biomarkers of network disruption for future clinical trials.
肌萎缩侧索硬化症(ALS)是一种进行性神经退行性疾病,主要影响运动功能,并有广泛的非运动参与的证据。尽管人们越来越认识到这种疾病是一种多系统网络紊乱,其特征是连接受损,但皮质通讯受损的确切神经电特征仍有待充分阐明。在这里,我们使用静息态脑电图记录的波束形成源分析来描述 74 名 ALS 患者和 47 名年龄匹配的健康对照者的功能连接变化。通过频谱功率、幅度包络相关(共调制)和虚部相干(同步)来量化 ALS 患者组中网络变化的时空特征。我们显示出 ALS 患者大脑枕叶和颞叶(δ-到β-波段)、外侧/眶额(δ-到θ-波段)和感觉运动(β-波段)区域的频谱功率降低。此外,我们还显示出中央和后部(δ-、θ-和γ-波段)以及额叶(δ-和γ-波段)区域的神经振荡共调制增加,以及颞叶和额叶(δ-到β-波段)和感觉运动(β-波段)区域的同步性降低。这些复杂连接模式的因子分解揭示了运动和非运动网络的明显中断。这些连接的变化与结构 MRI 变化、功能运动评分和认知评分相关。ALS 中皮质功能的观察到的变化表明广泛的疾病相关网络中断,指向运动和认知网络的广泛功能障碍。这些与临床评分相关的统计学上稳健的发现为进一步开发作为未来临床试验中网络中断的生物标志物提供了强有力的理由。