Abstract
Autism spectrum disorder (ASD) has been defined as a pervasive neurodevelopmental disorder, involving communication, social interaction and repetitive behaviors. Currently, it is still challenging to understand the differences of brain activity between ASD and healthy children. In this study, we propose calculating the Rényi entropy of the eigenvalues derived from the signal correlation matrix to measure the global synchronization in multichannel electroencephalograph (EEG) from 16 children with ASD (aged 8–12 years) and 16 age‐ and sex‐matched healthy controls at the resting state. The results indicate that there is a significantly diminished global synchronization from ASD to healthy control. The proposed method can help to reveal the intrinsic characteristics of multichannel EEG signals in children with ASD and aspects that distinguish them from healthy children.
Highlights
Autistic spectrum disorders (ASD) have been defined as heterogeneous neurodevelopmental disorders with some core characteristics that highlight social and communication impairments as well as repetitive and restricted interests and behaviors [1,2]
Atypical functional connectivity features have been considerably investigated as a primary
Atypical functional connectivity features have been considerably investigated as a primary deficit deficit in individuals with autism spectrum disorder (ASD)
Summary
Autistic spectrum disorders (ASD) have been defined as heterogeneous neurodevelopmental disorders with some core characteristics that highlight social and communication impairments as well as repetitive and restricted interests and behaviors [1,2]. An increasing amount of evidence, from physiological and electrophysiological studies, has proven that abnormalities in the synchronous oscillatory activity of neurons may dominate in the pathophysiology of brain disorder [15,16,20,21], and these will be reflected in EEG signals. Bivariate measures have been widely used in many studies These measures involve cross-correlation, coherence, mutual information, and phase synchronization in neural signals that demonstrate abnormalities of synchronization in different brain region [22,23]. These mentioned bivariate approaches fail to imply the global synchronization of multivariate neural signals [24]. Following the Rènyi entropy methodology [25], this paper focuses on revealing the differences of global synchronization between children with ASD and healthy subjects through resting-state EEG
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