Autism, spectrum or clusters? An EEG coherence study

BMC neurology(2019)

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摘要
Background Autism prevalence continues to grow, yet a universally agreed upon etiology is lacking despite manifold evidence of abnormalities especially in terms of genetics and epigenetics. The authors postulate that the broad definition of an omnibus ‘spectrum disorder’ may inhibit delineation of meaningful clinical correlations. This paper presents evidence that an objectively defined, EEG based brain measure may be helpful in illuminating the autism spectrum versus subgroups (clusters) question. Methods Forty objectively defined EEG coherence factors created in prior studies demonstrated reliable separation of neuro-typical controls from subjects with autism, and reliable separation of subjects with Asperger’s syndrome from all other subjects within the autism spectrum and from neurotypical controls. In the current study, these forty previously defined EEG coherence factors were used prospectively within a large ( N = 430) population of subjects with autism in order to determine quantitatively the potential existence of separate clusters within this population. Results By use of a recently published software package, NbClust, the current investigation determined that the 40 EEG coherence factors reliably identified two distinct clusters within the larger population of subjects with autism. These two clusters demonstrated highly significant differences. Of interest, many more subjects with Asperger’s syndrome fell into one rather than the other cluster. Conclusions EEG coherence factors provide evidence of two highly significant separate clusters within the subject population with autism. The establishment of a unitary “Autism Spectrum Disorder” does a disservice to patients and clinicians, hinders much needed scientific exploration, and likely leads to less than optimal educational and/or interventional efforts.
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关键词
Asperger’s syndrome (ASP),Autism spectrum disorder (ASD),Cluster analysis,Connectivity,Discriminant analysis,EEG coherence factors,Hierarchical,K-means,NbClust
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