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

Neuroplasticity01:01

Neuroplasticity

Neuroplasticity reflects the brain's remarkable capacity to adapt and evolve, responding dynamically to learning, experiences, or injury by reorganizing its neural circuitry. This reorganization involves creating new neural connections and refining old ones through a series of biological processes that contribute to the brain's lifelong development and adaptability.
Impact of Schemas01:30

Impact of Schemas

Schemas are cognitive structures that provide a framework for interpreting and organizing social information. They help individuals navigate complex environments by offering expectations about people, events, and behaviors. Schemas influence attention, encoding, and retrieval processes, thereby shaping the entire trajectory of information processing in social contexts.Attention and Cognitive LoadDuring initial attention, schemas function as filters that prioritize schema-consistent information,...
Cognitive Learning01:21

Cognitive Learning

Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
Higher Mental Functions of Brain: Learning and Memory01:26

Higher Mental Functions of Brain: Learning and Memory

Memory is one of the most vital higher mental functions of the brain. Memory is closely related to learning because it enables us to retain information and experiences from our past to use them in our present life. It also helps us to remember facts, events, and skills, such as riding a bike or swimming. There are two types of memory — declarative memory, which involves memorizing facts or events, and procedural memory, which enables us to remember how to do something like writing or playing an...
Working Memory01:24

Working Memory

Working memory refers to a combination of components, including short-term memory and attention, that allow an individual to hold information temporarily as we perform cognitive tasks. It is an essential cognitive function that enables the execution of complex tasks such as problem-solving, comprehension, and reasoning. Unlike short-term memory, which simply involves the storage of information for a brief period, working memory involves the active manipulation and processing of this information.
The Availability Heuristic01:08

The Availability Heuristic

A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):

You might also read

Related Articles

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

Sort by
Same author

Editorial: Rising stars in cognition: 2023/4.

Frontiers in cognition·2026
Same author

Neural evidence of deprioritizing to-be-forgotten information in visual working memory.

Frontiers in cognition·2026
Same author

Activated long-term memory and visual working memory during hybrid visual search: Effects on target memory search and distractor memory.

Memory & cognition·2024
Same author

Differences in the duration of the attentional blink when viewing nature vs. urban scenes.

Attention, perception & psychophysics·2023
Same author

Loss aversion in the control of attention.

Psychonomic bulletin & review·2023
Same author

Behavioral and electrophysiological evidence for the flexible recruitment of feature- and object-based processing in visual working memory comparison.

Biological psychology·2023
Same journal

Memory for scene details in eye-movement behavior, with and without awareness.

Consciousness and cognition·2026
Same journal

When one part feels, the whole belongs: associations between local touch referral and illusory full-limb ownership in individuals with leg amputation.

Consciousness and cognition·2026
Same journal

Inhibitory control and mind wandering; more difficult inhibition decreases mind wandering, within limits.

Consciousness and cognition·2026
Same journal

Autism and Aphantasia.

Consciousness and cognition·2026
Same journal

Absolute pitch and sound-color synesthesia provide for unique learning opportunities.

Consciousness and cognition·2026
Same journal

Could we perceive the world differently than we do? Neuroscience-based emergentism and the biological function of consciousness.

Consciousness and cognition·2026
See all related articles

Related Experiment Video

Updated: May 28, 2026

A Method for Investigating Change Blindness in Pigeons (Columba Livia)
06:14

A Method for Investigating Change Blindness in Pigeons (Columba Livia)

Published on: September 7, 2018

The change probability effect: incidental learning, adaptability, and shared visual working memory resources.

Amanda E van Lamsweerde1, Melissa R Beck

  • 1Louisiana State University, Department of Psychology, 236 Audubon Hall, Baton Rouge, LA 70803, USA. avanla1@lsu.edu

Consciousness and Cognition
|October 4, 2011
PubMed
Summary
This summary is machine-generated.

Statistical learning improves visual working memory (VWM) by leveraging predictable changes. This study found that people learn and adapt to feature change probabilities, enhancing detection for probable changes but sometimes hindering improbable ones.

More Related Videos

Visualizing Visual Adaptation
04:43

Visualizing Visual Adaptation

Published on: April 24, 2017

A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss
07:12

A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss

Published on: April 11, 2025

Related Experiment Videos

Last Updated: May 28, 2026

A Method for Investigating Change Blindness in Pigeons (Columba Livia)
06:14

A Method for Investigating Change Blindness in Pigeons (Columba Livia)

Published on: September 7, 2018

Visualizing Visual Adaptation
04:43

Visualizing Visual Adaptation

Published on: April 24, 2017

A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss
07:12

A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss

Published on: April 11, 2025

Area of Science:

  • Cognitive psychology
  • Neuroscience
  • Visual perception

Background:

  • Statistical regularities in the environment influence cognitive processes.
  • Visual working memory (VWM) performance can be enhanced by statistical learning.
  • The change probability effect describes how performance improves when changes are predictable.

Purpose of the Study:

  • To investigate the incidental learning of statistical regularities in the visual environment.
  • To examine how learning change probabilities affects visual change detection performance.
  • To determine if intentional strategies enhance the change probability effect.

Main Methods:

  • Participants performed a change detection task with varying probabilities for feature changes (shape, color, location).
  • Incidental learning of change probabilities was assessed.
  • The impact of intentional strategies on the change probability effect was evaluated.

Main Results:

  • A significant change probability effect was observed for color and shape changes, but not location changes.
  • The effect emerged and adapted rapidly to new probability information.
  • Intentional strategies did not enhance the change probability effect.
  • Performance gains for probable changes sometimes resulted in performance decrements for improbable changes.

Conclusions:

  • The visual system can incidentally learn and utilize statistical regularities in the environment to optimize visual working memory.
  • The change probability effect is feature-dependent and adaptable.
  • This learning mechanism can lead to trade-offs between detecting probable and improbable events.