Brittenham Chloe, Gordon James, Zemon Vance M, Siper Paige M
Department of Psychology, The Graduate Center, City University of New York, New York, New York, USA.
Department of Psychology, Hunter College, New York, New York, USA.
Autism Res. 2022 Mar;15(3):464-480. doi: 10.1002/aur.2654. Epub 2021 Dec 14.
Visual evoked potentials (VEPs) provide a means to examine neural mechanisms in autism with high temporal resolution. Conventional VEP analysis relies on subjective inspection of a few points (peaks and troughs) in the time-domain waveform. The current study applied power spectral analysis and magnitude-squared coherence (MSC) statistics (frequency-domain measures) to VEPs recorded during 1-minute runs and with a recently developed short-duration technique that allow for objective examination of the responses (Zemon & Gordon, European Journal of Neuroscience, 2018, 48, 1765-1788) from nonautistic and autistic children. Results indicate that, for both groups, early time-domain measures (P , N , P ) are highly correlated with middle- and high-frequency (14-28 and 30-48 Hz, respectively) mechanisms, and late measures are highly correlated with a low-frequency (6-12 Hz) mechanism. One frequency-domain measure (power in the middle-frequency band) is capable of predicting the key amplitude measure (N -P ) with high accuracy. MSC and power measures were combined to yield separate measures of signal and noise strength to evaluate alternate hypotheses in autism. Linear mixed-effects modeling demonstrated selective differences in early time-domain and middle-to-high frequency-domain measures in autistic children as compared to nonautistic children given both recording techniques, implicating weaker excitatory input to the cortex. Receiver-operating-characteristic curve analysis showed predictive diagnostic accuracy for middle- and high-frequency bands based on MSC. These findings support the value of frequency analysis measures (power spectral analysis and MSC) in the objective examination of neural differences in autism. LAY SUMMARY: Visual evoked potentials (VEPs) are used to assess neural mechanisms. Typically, VEPs are analyzed by subjective examination of time-series waveforms; but here objective techniques were applied to quantify VEP frequency components to investigate neural differences between autistic and nonautistic children. The objective measures demonstrate group differences in brain function that point to weaker excitatory input to the cortex in autism.
视觉诱发电位(VEP)提供了一种以高时间分辨率检查自闭症神经机制的方法。传统的VEP分析依赖于对时域波形中几个点(峰和谷)的主观检查。当前的研究将功率谱分析和幅度平方相干(MSC)统计(频域测量)应用于在1分钟运行期间记录的VEP,并采用了一种最近开发的短持续时间技术,该技术允许对来自非自闭症和自闭症儿童的反应进行客观检查(泽蒙和戈登,《欧洲神经科学杂志》,2018年,48卷,1765 - 1788页)。结果表明,对于两组而言,早期时域测量(P 、N 、P )与中高频(分别为14 - 28赫兹和30 - 48赫兹)机制高度相关,而晚期测量与低频(6 - 12赫兹)机制高度相关。一种频域测量(中频带功率)能够高精度地预测关键幅度测量(N - P )。将MSC和功率测量相结合,以产生信号和噪声强度的单独测量,以评估自闭症中的替代假设。线性混合效应模型表明,与非自闭症儿童相比,自闭症儿童在两种记录技术下,早期时域和中高频域测量存在选择性差异,这意味着皮质的兴奋性输入较弱。接受者操作特征曲线分析表明,基于MSC的中高频带具有预测诊断准确性。这些发现支持了频率分析测量(功率谱分析和MSC)在客观检查自闭症神经差异方面的价值。简述:视觉诱发电位(VEP)用于评估神经机制。通常,通过对时间序列波形的主观检查来分析VEP;但在这里,应用客观技术来量化VEP频率成分,以研究自闭症和非自闭症儿童之间的神经差异。客观测量表明,两组在脑功能上存在差异,这表明自闭症中皮质的兴奋性输入较弱。