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Stem Cell Reports. 2019 Sep 10;13(3):474-484. doi: 10.1016/j.stemcr.2019.08.001. Epub 2019 Aug 29.

Dynamical Electrical Complexity Is Reduced during Neuronal Differentiation in Autism Spectrum Disorder.

Author information

1
The Salk Institute, Laboratory of Genetics, La Jolla, CA 92037, USA; University of California San Diego, Department of Neurosciences, La Jolla, CA 92093, USA.
2
The Salk Institute, Laboratory of Genetics, La Jolla, CA 92037, USA.
3
The Salk Institute, Laboratory of Genetics, La Jolla, CA 92037, USA; Institute of Psychiatry and Neuroscience of Paris (UMR_S1266 INSERM, University of Paris), Laboratory of Dynamic of Neuronal Structure in Health and Disease, Paris, France.
4
The Salk Institute, Integrative Genomics and Bioinformatics Core, La Jolla, CA 92037, USA.
5
The Salk Institute, Computational Neurobiology Laboratory, La Jolla, CA 92037, USA; University of California San Diego, Division of Biological Sciences, La Jolla, CA 92093, USA.
6
The Salk Institute, Computational Neurobiology Laboratory, La Jolla, CA 92037, USA.
7
The Salk Institute, Laboratory of Genetics, La Jolla, CA 92037, USA. Electronic address: marchetto@salk.edu.
8
The Salk Institute, Laboratory of Genetics, La Jolla, CA 92037, USA; Department of Child and Adolescent Psychiatry, National Center for Mental Health, 127 Yongmasanro, Gwangjin-gu, Seoul 04933, South Korea. Electronic address: yenikim@korea.kr.

Abstract

Neuronal activity can be modeled as a nonlinear dynamical system to yield measures of neuronal state and dysfunction. The electrical recordings of stem cell-derived neurons from individuals with autism spectrum disorder (ASD) and controls were analyzed using minimum embedding dimension (MED) analysis to characterize their dynamical complexity. MED analysis revealed a significant reduction in dynamical complexity in ASD neurons during differentiation, which was correlated to bursting and spike interval measures. MED was associated with clinical endpoints, such as nonverbal intelligence, and was correlated with 53 differentially expressed genes, which were overrepresented with ASD risk genes related to neurodevelopment, cell morphology, and cell migration. Spatiotemporal analysis also showed a prenatal temporal enrichment in cortical and deep brain structures. Together, we present dynamical analysis as a paradigm that can be used to distinguish disease-associated cellular electrophysiological and transcriptional signatures, while taking into account patient variability in neuropsychiatric disorders.

KEYWORDS:

autism spectrum disorder; dynamical complexity; minimum embedding dimension; multielectrode array; neurodevelopmental disorder models

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