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

You might also read

Related Articles

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

Sort by
Same author

Editorial: Highlights in cognition: visual-spatial processing.

Frontiers in psychology·2026
Same author

Selective Visual Attention in ADHD: A Narrative Review.

Current neurology and neuroscience reports·2025
Same author

Technostress and academic motivation: direct and indirect effects on university students' psychological health.

Frontiers in psychology·2023
Same author

Technostress, Coping, and Anxious and Depressive Symptomatology in University Students During the COVID-19 Pandemic.

Europe's journal of psychology·2022
Same author

Cultural differences in visual perceptual learning.

International journal of psychology : Journal international de psychologie·2021
Same author

Functional and emotional outcomes after transient ischemic attack: A 12-month prospective controlled cohort study.

International journal of stroke : official journal of the International Stroke Society·2019

Related Experiment Video

Updated: Mar 20, 2026

Simultaneous Eye Tracking and Single-Neuron Recordings in Human Epilepsy Patients
07:43

Simultaneous Eye Tracking and Single-Neuron Recordings in Human Epilepsy Patients

Published on: June 17, 2019

8.4K

Temporal Binding and Segmentation in Visual Search: A Computational Neuroscience Analysis.

Eirini Mavritsaki1,2, Glyn Humphreys2

  • 1Birmingham City University.

Journal of Cognitive Neuroscience
|June 1, 2016
PubMed
Summary
This summary is machine-generated.

This study simulates human visual search over time using a computational model. It demonstrates that temporal binding and neural suppression explain how we prioritize new items while ignoring old ones in dynamic visual scenes.

More Related Videos

Author Spotlight: Exploring the Link Between Time Perception of Visual Stimuli and Reading Skills
09:27

Author Spotlight: Exploring the Link Between Time Perception of Visual Stimuli and Reading Skills

Published on: January 19, 2024

1.8K
Topographical Estimation of Visual Population Receptive Fields by fMRI
06:02

Topographical Estimation of Visual Population Receptive Fields by fMRI

Published on: February 3, 2015

9.7K

Related Experiment Videos

Last Updated: Mar 20, 2026

Simultaneous Eye Tracking and Single-Neuron Recordings in Human Epilepsy Patients
07:43

Simultaneous Eye Tracking and Single-Neuron Recordings in Human Epilepsy Patients

Published on: June 17, 2019

8.4K
Author Spotlight: Exploring the Link Between Time Perception of Visual Stimuli and Reading Skills
09:27

Author Spotlight: Exploring the Link Between Time Perception of Visual Stimuli and Reading Skills

Published on: January 19, 2024

1.8K
Topographical Estimation of Visual Population Receptive Fields by fMRI
06:02

Topographical Estimation of Visual Population Receptive Fields by fMRI

Published on: February 3, 2015

9.7K

Area of Science:

  • Cognitive Psychology
  • Computational Neuroscience
  • Visual Attention

Background:

  • Human visual search involves processing items in both space and time.
  • Preview search paradigms reveal efficient search when old distractors are ignored and new targets prioritized.
  • Temporal gaps disrupt preview search benefits, suggesting temporal binding of stimuli.

Purpose of the Study:

  • To simulate temporal coding effects in visual search using the spiking search over time and space (sSoTS) model.
  • To investigate the roles of temporal binding and neural suppression in human visual search.
  • To account for the impact of brain lesions on preview search performance.

Main Methods:

  • Utilized the spiking search over time and space (sSoTS) computational model.
  • Introduced temporal binding mechanisms to the model to simulate effects of temporal gaps.
  • Simulated neural suppression to account for memory effects across temporal gaps.

Main Results:

  • The sSoTS model successfully simulated the loss of preview search benefits with temporal gaps by incorporating temporal binding.
  • Continued neural suppression in the model explained the role of memory for old items.
  • The model accurately captured the effects of brain lesions on preview search under varying temporal conditions.

Conclusions:

  • Temporal binding and neural suppression are sufficient mechanisms to explain human visual search over time and space.
  • The sSoTS model provides a computational framework bridging physiological processes and behavioral outcomes in visual attention.
  • This research offers a proof-of-principle for understanding complex visual search dynamics through neural mechanisms.