A Computational Model for Cerebral Cortical Dysfunction in Autism Spectrum Disorders

Shashaank Vattikuti, Carson C Chow

Abstract:

Background—Perturbations to the microscopic level balance between synaptic excitation and
inhibition and neuron organization in the cerebral cortex are suggested to underlie autism
spectrum disorder (ASD) traits. The mechanism linking these perturbations to cognitive behaviors
in ASD is unknown. This study strives to bridge this gap by generating clinically testable
diagnostic and pharmacological predictions based on the effect of synaptic imbalance and neuron
distribution on a computational local circuit model of the cerebral cortex.
Methods—We use a computational microscopic model of the cerebral cortex that incorporates Nmethyl-D-aspartate and gamma-aminobutyric acid synaptic kinetics. We employ the model circuit
during model tasks similar to visually guided and gap oculomotor saccade tasks and interpret
qualitative model predictions of saccade hypometria and dysmetria. We consider the effects of
varying the excitatory to inhibitory synaptic balance, neuron density, and neuron clustering in this
model.
Results—An increase of synaptic excitation over synaptic inhibition results in increased
hypometria and dysmetria. Similar effects by either reduced inhibition or increased excitation
suggest that a variety of pharmacological compounds can be used for both screening and medical
management. On the other hand, any change to the microscopic neuron anatomy that increases the
effective maximum distance between excitatory neurons decreases hypometria but has no affect on
dysmetria.
Conclusions—Perturbations to a computational model of a local cerebral cortical circuit can
account for saccade hypometria and dysmetria reported in ASD studies. This app