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

Area of Science:

• Neuroscience
• Genetics
• Developmental Biology

Background:

• Neuronal activity modeling as nonlinear dynamical systems offers insights into neuronal function and dysfunction.
• Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with underlying cellular and genetic alterations.

Purpose of the Study:

• To characterize the dynamical complexity of neurons derived from individuals with ASD compared to controls.
• To investigate the correlation between neuronal dynamical complexity, electrophysiological measures, gene expression, and clinical endpoints in ASD.

Main Methods:

• Utilized minimum embedding dimension (MED) analysis on electrical recordings of stem cell-derived neurons.
• Correlated MED findings with bursting and spike interval measures, clinical endpoints (e.g., nonverbal intelligence), and differentially expressed genes.
• Performed spatiotemporal analysis to identify prenatal enrichment patterns in brain structures.

Main Results:

• ASD neurons exhibited significantly reduced dynamical complexity during differentiation compared to controls.
• Reduced dynamical complexity correlated with specific bursting and spike interval patterns.
• MED analysis linked to clinical endpoints and 53 differentially expressed genes, including ASD risk genes involved in neurodevelopment, cell morphology, and migration.
• Spatiotemporal analysis indicated prenatal temporal enrichment in cortical and deep brain structures.

Conclusions:

• Dynamical analysis provides a novel paradigm for distinguishing disease-associated electrophysiological and transcriptional signatures in neurodevelopmental disorders like ASD.
• This approach accounts for patient variability, offering a more nuanced understanding of neuropsychiatric disorders at the cellular level.