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

Ligand-Gated Ion Channel Receptor: Gating Mechanism01:30

Ligand-Gated Ion Channel Receptor: Gating Mechanism

4.6K
Ligand-gated ion channels are transmembrane proteins that play a vital role in intercellular communication and functions of the nervous system. They allow the influx of ions across the membrane once the neurotransmitter binds, allowing the subsequent transmission of electrical excitation across the neurons. Other ligand-gated ion channels, like the γ-aminobutyric acid (GABA) receptor, permit anions like chloride into the cells on the binding of the GABA molecule. Their entry into the cell...
4.6K

You might also read

Related Articles

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

Sort by
Same author

Towards robust foundation models for digital pathology.

Nature communications·2026
Same author

Widespread use of invalid statistical tests in biomedical machine learning.

bioRxiv : the preprint server for biology·2026
Same author

Physical contact reveals a hidden layer of cortical architecture.

bioRxiv : the preprint server for biology·2026
Same author

How simple can you go? An off-the-shelf transformer approach to molecular dynamics.

The Journal of chemical physics·2026
Same author

A preregistered, open pipeline for early cerebral palsy risk assessment from infant videos.

GigaScience·2026
Same author

Software for dataset-wide XAI: From local explanations to global insights with Zennit, CoRelAy, and ViRelAy.

PloS one·2026
Same journal

Inherent tissue homeostasis of the juvenile metaphysis provides a foundation for osteosarcoma development.

Nature communications·2026
Same journal

Slowing the spread of treatment failure to artemisinin-based combination therapies in Uganda.

Nature communications·2026
Same journal

Harnessing interfacial click polymerization using pyridinium-yne films as photochromic, radical generation and sensing platforms.

Nature communications·2026
Same journal

Potential role of a CRISPR-Cas-activated toxin-antitoxin system in bacterial immunity.

Nature communications·2026
Same journal

Diverse radical transformations of allenic C(sp)-C(sp<sup>2</sup>) and C(sp<sup>3</sup>)-C(sp<sup>2</sup>) bonds enabled by silyl substitution.

Nature communications·2026
Same journal

Experience-dependent modulation of collective behavior in larval zebrafish.

Nature communications·2026
See all related articles
  1. Home
  3. Modeling Attention And Binding In The Brain Through Bidirectional Recurrent Gating.
  1. Home
  3. Modeling Attention And Binding In The Brain Through Bidirectional Recurrent Gating.

Related Experiment Video

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

14.3K

Modeling attention and binding in the brain through bidirectional recurrent gating.

Saeed Salehi1,2,3, Jordan Lei4, Ari S Benjamin5

  • 1Machine Learning Group, Technical University of Berlin, Berlin, Germany. ai.neuro.io@gmail.com.

Nature Communications
|May 5, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

This study introduces a novel computational model for attention, unifying diverse attentional phenomena within a single framework. The model successfully replicates key attentional tasks and neural properties, offering insights into brain computation.

More Related Videos

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.7K
Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control
09:37

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control

Published on: July 5, 2015

8.8K

Related Experiment Videos

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

14.3K
Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.7K
Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control
09:37

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control

Published on: July 5, 2015

8.8K

Area of Science:

  • Cognitive Neuroscience
  • Computational Neuroscience
  • Artificial Intelligence

Background:

  • Attention is crucial for cognition, enabling information selection, feature binding, and behavior guidance.
  • Existing models lack a unified framework for diverse attentional phenomena like spatial, feature-based, and object-based attention.
  • A neurally plausible computational model is needed to integrate these aspects.

Purpose of the Study:

  • To propose a unifying computational model for attention based on a bidirectional recurrent gating mechanism.
  • To integrate this mechanism within the ventral visual stream architecture.
  • To demonstrate the model's ability to replicate attentional tasks and neural properties.

Main Methods:

  • Developed a computational model with feedforward pathways for feature extraction and recurrent connections for modulatory signals.
  • Trained the model on recognition and segmentation tasks.
  • Evaluated the model on canonical attention tasks (orienting, filtering, visual search) and psychophysical phenomena.

    • Main Results:

    • The model successfully performed orienting, filtering, and visual search on complex scenes.
    • It replicated key psychophysical phenomena, including perceptual load and inattentional blindness.
    • Internal model units exhibited neural properties consistent with primate physiology (e.g., gain modulation, border-ownership coding).

    Conclusions:

    • Diverse attentional and binding phenomena can emerge from error-backpropagation within specific architectural constraints.
    • The proposed model offers a powerful tool for neuroscience research.
    • Presents a bio-inspired alternative to conventional AI architectures.