Jove
Visualize
Contact Us

Related Concept Videos

Chunking01:12

Chunking

285
Chunking is a powerful cognitive technique that improves short-term memory retention by organizing information into smaller, more manageable units. The brain, limited by working memory capacity, can more easily process and store information when it is divided into "chunks" rather than presented as discrete, unrelated elements. Chunking is especially useful when dealing with large amounts of information, such as numerical sequences, words, or complex ideas.
The principle behind chunking...
285
Chunking and Rehearsal in Sensory Memory01:22

Chunking and Rehearsal in Sensory Memory

425
Improving short-term memory can be achieved through techniques like chunking and rehearsal. Chunking involves organizing information into larger, more manageable units. This technique is particularly useful for information that exceeds the typical memory span of between five and nine items. For instance, logging into an online account with a password like "ta89vq0179gz" involves grouping letters and numbers into three chunks—ta89, vq01, and 79gz. It makes large amounts of...
425
Association Areas of the Cortex01:21

Association Areas of the Cortex

7.7K
Association areas are regions of the cerebral cortex that do not have a specific sensory or motor function. Instead, they integrate and interpret information from various sources to enable higher cognitive processes such as memory, learning, and decision-making. Some key association areas include the following:
Prefrontal Association Area: This area is located in the frontal lobe and is involved in planning, decision-making, and moderating social behavior. It connects with primary motor areas,...
7.7K
Visual Agnosia01:12

Visual Agnosia

647
Visual agnosia is a condition characterized by the inability to recognize visually presented objects despite having normal vision. For instance, a person with visual agnosia can describe the shape and color of an object but cannot identify or name it. This impairment does not affect their visual field, acuity, color vision, brightness discrimination, language, or memory. An example of this condition in a social setting is someone at a dinner party asking for "that silver thing with a round...
647
Gestalt Principles of Perception01:21

Gestalt Principles of Perception

823
Gestalt principles provide a framework for understanding how humans perceive objects as unified wholes within their context. These principles are essential in explaining the cognitive processes that make sense of complex visual stimuli by organizing them into coherent groups. One fundamental principle is proximity, which posits that objects located close to each other are perceived as a collective group. For instance, when dots are positioned near one another, the visual system interprets them...
823

You might also read

Related Articles

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

Sort by
Same author

No observable spatial numerical associations of response codes effect with numbers in nonsymbolic format.

Journal of experimental psychology. Human perception and performance·2025
Same author

Structure transfer and consolidation in visual implicit learning.

eLife·2025
Same author

Rewarding animals based on their subjective percepts is enabled by online Bayesian estimation of perceptual biases.

PLoS biology·2025
Same author

How to reward animals based on their subjective percepts: A Bayesian approach to online estimation of perceptual biases.

bioRxiv : the preprint server for biology·2024
Same author

Different mechanisms underlie implicit visual statistical learning in honey bees and humans.

Proceedings of the National Academy of Sciences of the United States of America·2020
Same author

Unimodal statistical learning produces multimodal object-like representations.

eLife·2019
Same journal

Demonstration of a quantum C-NOT gate in a time-multiplexed fully reconfigurable photonic processor.

Nature communications·2026
Same journal

Nonlinear quantum light source with van der Waals ferroelectric NbOX<sub>2</sub> (X = Br, I).

Nature communications·2026
Same journal

Antagonistic histone H2A variants and autonomous heterochromatin formation shape epigenomic patterns in Arabidopsis.

Nature communications·2026
Same journal

The long tail of nitrate pollution in groundwater challenges governance of global water quality.

Nature communications·2026
Same journal

Select microbial metabolites promote tau aggregation in a murine tauopathy model.

Nature communications·2026
Same journal

Warming climate has lengthened global intense tropical cyclone seasons.

Nature communications·2026
See all related articles
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 Experiment Video

Updated: Nov 21, 2025

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers
12:39

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

Published on: January 18, 2020

7.9K

Statistically defined visual chunks engage object-based attention.

Gábor Lengyel1,2, Márton Nagy3,4,5, József Fiser6,7

  • 1Department of Cognitive Science, Central European University, Budapest, Hungary. lengyel.gaabor@gmail.com.

Nature Communications
|January 12, 2021
PubMed
Summary
This summary is machine-generated.

Implicitly learning visual statistical properties creates object-like effects, influencing attention and search tasks. This suggests statistical learning aids object representation formation without traditional cues.

More Related Videos

Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking
05:58

Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking

Published on: August 29, 2018

9.1K
Central and Divided Visual Field Presentation of Emotional Images to Measure Hemispheric Differences in Motivated Attention
05:36

Central and Divided Visual Field Presentation of Emotional Images to Measure Hemispheric Differences in Motivated Attention

Published on: November 16, 2017

7.8K

Related Experiment Videos

Last Updated: Nov 21, 2025

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers
12:39

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

Published on: January 18, 2020

7.9K
Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking
05:58

Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking

Published on: August 29, 2018

9.1K
Central and Divided Visual Field Presentation of Emotional Images to Measure Hemispheric Differences in Motivated Attention
05:36

Central and Divided Visual Field Presentation of Emotional Images to Measure Hemispheric Differences in Motivated Attention

Published on: November 16, 2017

7.8K

Area of Science:

  • Cognitive Psychology
  • Neuroscience
  • Visual Perception

Background:

  • Objects are key to environmental interpretation, but the mechanism of forming object representations from sensory input remains unclear.
  • Processing information within objects is more efficient than across objects.
  • Traditional segmentation cues are not always present for object formation.

Purpose of the Study:

  • To investigate if learning involuntary consistent visual statistical properties can induce object-like behavioral effects.
  • To determine if implicit learning of statistical regularities is sufficient for object representation.
  • To explore the role of statistical learning in object-based attention and search.

Main Methods:

  • Utilized a visual statistical learning paradigm.
  • Measured search efficiency using a three-alternative forced-choice (3-AFC) task.
  • Assessed object-based attention to evaluate behavioral biases.

Main Results:

  • Statistically defined visual chunks, learned implicitly, biased search task behavior.
  • These statistically learned chunks produced effects similar to objects defined by explicit visual boundaries.
  • Implicit learning of consistent statistical contingencies influenced attentional allocation and search performance.

Conclusions:

  • Learning consistent statistical contingencies from sensory input contributes to the emergence of object representations.
  • Object-like behavioral effects can arise from implicit statistical learning, even without traditional segmentation cues.
  • This highlights a fundamental mechanism for building object representations in the brain.