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Related Concept Videos

Autism Spectrum Disorder01:19

Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by persistent deficits in social communication and interaction alongside restrictive and repetitive behaviors or interests. ASD is sometimes accompanied by intellectual impairment.
These core symptoms manifest differently among individuals, ranging from mild to severe. The disorder's complexity extends beyond its clinical presentation, encompassing a diverse range of biological, cognitive, and sociocultural influences.
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Modeling in Therapy

Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
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A computational model for cerebral cortical dysfunction in autism spectrum disorders.

Shashaank Vattikuti1, Carson C Chow

  • 1Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health, Bethesda, Maryland 20892-5621, USA.

Biological Psychiatry
|November 3, 2009
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Altered synaptic balance in the cerebral cortex can explain autism spectrum disorder (ASD) traits like saccade issues. This computational model offers insights for diagnosing and treating ASD behaviors.

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Area of Science:

  • Neuroscience
  • Computational Biology
  • Autism Spectrum Disorder Research

Background:

  • Autism spectrum disorder (ASD) is linked to imbalances in synaptic excitation and inhibition within the cerebral cortex.
  • The precise mechanisms connecting these neural perturbations to ASD-related cognitive behaviors remain unclear.

Purpose of the Study:

  • To investigate how synaptic imbalance and neuron organization in the cerebral cortex influence autism spectrum disorder (ASD) traits.
  • To generate clinically relevant predictions for diagnosing and pharmacologically managing ASD.

Main Methods:

  • Utilized a computational microscopic model of the cerebral cortex with detailed synaptic kinetics.
  • Simulated oculomotor saccade tasks to analyze model predictions of saccade hypometria and dysmetria.
  • Varied parameters including excitatory-inhibitory synaptic balance, neuron density, and neuron clustering.

Main Results:

  • Increased synaptic excitation relative to inhibition led to greater saccade hypometria and dysmetria.
  • Changes in neuron anatomy affecting excitatory neuron distance impacted hypometria but not dysmetria.
  • Pharmacological interventions targeting synaptic balance may aid in ASD screening and treatment.

Conclusions:

  • Computational modeling of local cortical circuits can replicate saccade abnormalities observed in ASD.
  • This approach establishes a potential link between cerebral cortical function and the behavioral manifestations of ASD.