Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Modeling in Therapy01:26

Modeling in Therapy

127
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...
127

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

The Behavioural and Neurophysiological Effects of Set-for-Variability (SfV) Reading Intervention for Children With Sustained Word Reading Difficulties.

Dyslexia (Chichester, England)·2026
Same author

Critical role of EEG signals in assessment of sex-specific insights in neurological diagnostics via machine learning approach.

Scientific reports·2025
Same author

Reading Disability in Children: Exploring the N400 and its Associations with Set-For-Variability.

Developmental neuropsychology·2024
Same author

No transfer of 3D-Multiple Object Tracking training on game performance in soccer: A follow-up study.

Psychology of sport and exercise·2024
Same author

Auditory Noise Facilitates Lower Visual Reaction Times in Humans.

Biology·2024
Same author

Investigating sensitivity to multi-domain prediction errors in chronic auditory phantom perception.

Scientific reports·2024
Same journal

Developmental Trajectories in Young Autistic Children Receiving Parent-Mediated Intervention Through In-Person and Telehealth Service Delivery Models: A Naturalistic, Nonrandomized Clinical Study.

Journal of autism and developmental disorders·2026
Same journal

The Effect of Participation in the Let's Play Program on Autistic Children's Engagement and Caregiver Well-Being: A Randomized Controlled Trial.

Journal of autism and developmental disorders·2026
Same journal

Trends in Self-Reported Autism Among Adults in England: Analysis of a Repeated Cross-Sectional Patient Survey Series of 5,999,433 Adults.

Journal of autism and developmental disorders·2026
Same journal

Sentiment and Topic Analysis of Autism Spectrum Disorder Discussions on Chinese Social Media: Evidence From Bilibili and Rednote.

Journal of autism and developmental disorders·2026
Same journal

Motor Competence and Physical Fitness in Children and Adolescents With ADHD: A Comparative Study with Typically Developing Peers.

Journal of autism and developmental disorders·2026
Same journal

Assessing Camouflaging in Adolescence: Psychometric Evaluation of the German Camouflaging Autistic Traits Questionnaire (CAT-Q/DE).

Journal of autism and developmental disorders·2026
See all related articles

Related Experiment Video

Updated: Jul 26, 2025

Comparing Eye-tracking Data of Children with High-functioning ASD, Comorbid ADHD, and of a Control Watching Social Videos
05:32

Comparing Eye-tracking Data of Children with High-functioning ASD, Comorbid ADHD, and of a Control Watching Social Videos

Published on: December 7, 2018

9.0K

Characterizing Attention Resource Capacity in Autism: A Multiple Object Tracking Study.

Domenico Tullo1, Bianca Levy2, Jocelyn Faubert3

  • 1University of California Irvine, Irvine, CA, USA. dtullo@uci.edu.

Journal of Autism and Developmental Disorders
|June 21, 2023
PubMed
Summary
This summary is machine-generated.

Attention differences in autism may be linked to intelligence, not attention capacity. When fluid reasoning was considered, autistic individuals showed similar performance on attention tasks compared to neurotypicals, suggesting intelligence impacts attention assessment.

Keywords:
AttentionAttention resource capacity, multiple object trackingAutismFluid reasoning intelligence

More Related Videos

Eye Tracking Young Children with Autism
09:03

Eye Tracking Young Children with Autism

Published on: March 27, 2012

45.7K
Gaze in Action: Head-mounted Eye Tracking of Children's Dynamic Visual Attention During Naturalistic Behavior
07:09

Gaze in Action: Head-mounted Eye Tracking of Children's Dynamic Visual Attention During Naturalistic Behavior

Published on: November 14, 2018

10.7K

Related Experiment Videos

Last Updated: Jul 26, 2025

Comparing Eye-tracking Data of Children with High-functioning ASD, Comorbid ADHD, and of a Control Watching Social Videos
05:32

Comparing Eye-tracking Data of Children with High-functioning ASD, Comorbid ADHD, and of a Control Watching Social Videos

Published on: December 7, 2018

9.0K
Eye Tracking Young Children with Autism
09:03

Eye Tracking Young Children with Autism

Published on: March 27, 2012

45.7K
Gaze in Action: Head-mounted Eye Tracking of Children's Dynamic Visual Attention During Naturalistic Behavior
07:09

Gaze in Action: Head-mounted Eye Tracking of Children's Dynamic Visual Attention During Naturalistic Behavior

Published on: November 14, 2018

10.7K

Area of Science:

  • Neuroscience
  • Cognitive Psychology
  • Developmental Psychology

Background:

  • Existing research on attention in autism spectrum disorder (ASD) presents conflicting results.
  • Inconsistencies may stem from varied definitions and methods for assessing attention in autistic individuals.

Purpose of the Study:

  • To investigate differences in attentional resource allocation and capacity between autistic and neurotypical individuals.
  • To examine if fluid reasoning intelligence influences attention task performance in autism.

Main Methods:

  • Utilized the Multiple Object-Tracking (MOT) task to measure selective, sustained, and distributed attention.
  • Manipulated attentional load within the MOT task to assess resource allocation.
  • Compared performance between autistic individuals (n=55) and age-matched neurotypicals (n=55) without ADHD comorbidity.

Main Results:

  • Autistic individuals initially showed lower performance on the MOT task.
  • This performance gap diminished when fluid reasoning intelligence was statistically controlled.
  • Both groups exhibited similar patterns of performance as attentional load increased, indicating comparable resource allocation.

Conclusions:

  • Fluid reasoning intelligence is a critical factor to consider when evaluating attention in autistic populations.
  • Attentional capacity and resource allocation may not fundamentally differ between autistic and neurotypical individuals when cognitive abilities are accounted for.
  • Findings have implications for clinical diagnosis, treatment strategies, and support for autistic individuals.