Erasmus School of Social and Behavioural Sciences, Institute of Psychology, Erasmus University Rotterdam, Rotterdam, The Netherlands.
Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, The Netherlands.
Eur J Neurosci. 2018 Oct;48(8):2928-2937. doi: 10.1111/ejn.13973. Epub 2018 Jun 19.
The autism spectrum hypothesis states that not only diagnosed individuals but also individuals from the general population exhibit a certain amount of autistic traits. While this idea is supported by neuroimaging studies, there have been few electrophysiological studies. In particular, there have been no spontaneous resting-state studies yet. In order to examine the autism spectrum hypothesis, the present study tried to predict the level of autistic traits typically developing young adults (n = 93) exhibit from spontaneous resting-state gamma power, a measure that has been linked to social functioning impairments seen in autism. The influence of age and gender was controlled for by employing regression. It was expected that enhanced gamma activity would be predictive of self-reported autistic traits. The model with only age and gender included reached significance, with higher age within this student population being related to more autistic traits. However, no relationship between either low (30-50 Hz) or high (50-70 Hz) gamma power and autistic traits was found. Models with eyes closed low gamma asymmetry and eyes closed high gamma asymmetry included did reach significance, but these findings were not robust, and the gamma asymmetry explained very little additional variance above age and gender. In addition, exploratory correlation analyses showed no relationship between the other power spectra (delta, theta, alpha and beta) on the one hand and autistic traits on the other hand, suggesting that any relationship between spontaneous resting-state brain electrophysiology and autistic traits might not be strong enough to be detected in the general population.
自闭症谱系假说指出，不仅是被诊断出的个体，一般人群中的个体也表现出一定程度的自闭症特征。虽然神经影像学研究支持这一观点，但很少有电生理研究。特别是，目前还没有自发性静息态研究。为了检验自闭症谱系假说，本研究试图从自发性静息态伽马功率预测典型发展的年轻成年人（n=93）表现出的自闭症特征水平，伽马功率是与自闭症中所见的社交功能障碍相关的指标。通过回归控制年龄和性别影响。预计增强的伽马活动将能够预测自我报告的自闭症特征。包含仅年龄和性别的模型达到了显著水平，该学生群体中年龄较高与更多自闭症特征相关。然而，并未发现低伽马（30-50 Hz）或高伽马（50-70 Hz）功率与自闭症特征之间存在任何关系。包含闭眼时低伽马不对称和闭眼时高伽马不对称的模型达到了显著水平，但这些发现并不稳健，伽马不对称在年龄和性别之上仅能解释非常小的额外方差。此外，探索性相关分析表明，一方面脑电功率谱（delta、theta、alpha 和 beta）与自闭症特征之间没有关系，这表明自发性静息态脑电生理与自闭症特征之间的任何关系可能不够强，以至于无法在一般人群中检测到。
