Related Experiment Video
Updated: Mar 17, 2026
Exploring Cognitive Functions in Babies, Children & Adults with Near Infrared Spectroscopy
Published on: July 28, 2009
Weak network efficiency in young children with Autism Spectrum Disorder: Evidence from a functional near-infrared
1Key Laboratory of Child Development and Learning Science of Ministry of Education, Southeast University, Nanjing, Jiangsu, China; Research Center for Learning Science, Southeast University, Nanjing, Jiangsu, China.
Insights
Functional near infrared spectroscopy (fNIRS) reveals reduced network efficiency in young children with Autism Spectrum Disorder (ASD). This neuroimaging technique shows potential for diagnosing ASD in children by analyzing functional brain networks.
Area of Science:
- Neuroscience
- Developmental Psychology
- Biomedical Engineering
Background:
- Functional near infrared spectroscopy (fNIRS) is well-suited for pediatric neuroimaging and ecological assessments.
- Limited research has utilized fNIRS for the clinical diagnosis of Autism Spectrum Disorder (ASD) in young children.
- Understanding functional brain network alterations in young children with ASD is crucial for early diagnosis and intervention.
Purpose of the Study:
- To quantitatively analyze functional brain networks in young children (4.8-8.0 years) with and without ASD using fNIRS.
- To investigate network efficiency and lobe-level connectivity in the functional networks of children with and without ASD.
- To explore the potential of fNIRS-derived network features for ASD classification in young children.
Main Methods:
- Employed functional near infrared spectroscopy (fNIRS) to measure brain activity in young children during cartoon viewing.
- Analyzed functional network efficiency across various thresholds for network binarization.
- Utilized k-means clustering with network efficiencies as feature parameters for classification.
Main Results:
- Young children with ASD exhibited significantly weaker functional network efficiency compared to controls.
- A classification accuracy of 83.3% was achieved in distinguishing ASD from controls using network efficiencies.
- Reduced lobe-level connectivity was observed in the right prefrontal cortex of children with ASD, affecting connections to the left prefrontal and bilateral temporal cortices.
Conclusions:
- The right prefrontal cortex plays a significant role in the psychopathology of young children with ASD at the functional network architecture level.
- Weakened functional lobe-connectivity, particularly involving the right prefrontal cortex, is characteristic of ASD in young children.
- fNIRS-based analysis of functional brain networks shows promise as a diagnostic tool for ASD in early childhood.
Abstract:
Functional near infrared spectroscopy (fNIRS) is particularly suited for the young population and ecological measurement. However, thus far, not enough effort has been given to the clinical diagnosis of young children with Autism Spectrum Disorder (ASD) by using fNIRS. The current study provided some insights into the quantitative analysis of functional networks in young children (ages 4.8-8.0years old) with and without ASD and, in particular, investigated the network efficiency and lobe-level connectivity of their functional networks while watching a cartoon. The main results included that: (i) Weak network efficiency was observed in young children with ASD, even for a wide range of threshold for the binarization of functional networks; (ii) A maximum classification accuracy rate of 83.3% was obtained for all participants by using the k-means clustering method with network efficiencies as the feature parameters; and (iii) Weak lobe-level inter-region connections were uncovered in the right prefrontal cortex, including its linkages with the left prefrontal cortex and the bilateral temporal cortex. Such results indicate that the right prefrontal cortex might make a major contribution to the psychopathology of young children with ASD at the functional network architecture level, and at the functional lobe-connectivity level, respectively.
More Related Videos
11:14A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants
Published on: October 4, 2015
09:13Testing Sensory and Multisensory Function in Children with Autism Spectrum Disorder
Published on: April 22, 2015
