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Related Concept Videos

Autism Spectrum Disorder01:19

Autism Spectrum Disorder

177
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.
177
Modeling in Therapy01:26

Modeling in Therapy

130
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
Participant modeling involves therapists demonstrating calm and effective behaviors in...
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Related Experiment Video

Updated: Aug 4, 2025

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants
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Study subnetwork developing pattern of autism children by non-negative matrix factorization.

JinLin Zheng1, LiCheng Shao1, Zheng Yan1

  • 1College of Information Science and Engineering, Huaqiao University, 668 Jimei Road, Xiamen 361021, China.

Computers in Biology and Medicine
|April 1, 2023
PubMed
Summary
This summary is machine-generated.

This study used non-negative matrix factorization (NMF) to analyze brain networks in children with autism, revealing distinct developmental trajectories and subnetwork expressions related to cognitive and developmental indices.

Keywords:
AutismBrain networkNMFNetwork developingSubnetwork

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Area of Science:

  • Neuroscience
  • Developmental Psychology
  • Computational Biology

Background:

  • Autism Spectrum Disorder (ASD) is a developmental disorder characterized by abnormal brain network patterns.
  • Differences in brain networks between autistic and typically developing children evolve over time.
  • Investigating developmental trajectories of brain networks is crucial for understanding ASD.

Purpose of the Study:

  • To identify differences in brain network development between autistic and typically developing children.
  • To explore the relationship between brain network subnetworks and cognitive/developmental indices in ASD.
  • To apply Non-negative Matrix Factorization (NMF) for unsupervised subnetwork discovery.

Main Methods:

  • Magnetoencephalography (MEG) data from autistic and control children were used to estimate brain network association matrices.
  • Non-negative Matrix Factorization (NMF) was employed to decompose these matrices into common subnetworks.
  • Subnetwork expression was quantified using energy and entropy indices, and correlated with cognitive and developmental scores.

Main Results:

  • A left-lateralized subnetwork in the alpha (α) band exhibited differential expression patterns between groups.
  • Expression indices of this α-band subnetwork showed opposing correlations with cognitive indices in autistic and control groups.
  • A right-hemisphere-dominant subnetwork in the gamma (γ) band negatively correlated with developmental indices in the autism group.

Conclusions:

  • NMF effectively decomposes brain networks into meaningful subnetworks, aiding in the study of developmental disorders.
  • Observed abnormal lateralization in the α-band subnetwork aligns with previous findings in autism.
  • Potential links between decreased subnetwork expression and mirror neuron dysfunction or high-frequency neuron processes are hypothesized.