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Related Concept Videos

Cognitive Learning01:21

Cognitive Learning

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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.
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Perception01:28

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E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...
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Perceptual Constancy01:12

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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...
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The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
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Updated: Apr 23, 2026

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss
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Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

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Perceptual learning: toward a comprehensive theory.

Takeo Watanabe1, Yuka Sasaki

  • 1Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, Rhode Island 02912;

Annual Review of Psychology
|September 25, 2014
PubMed
Summary
This summary is machine-generated.

Visual perceptual learning (VPL) involves long-term performance gains from visual experience. A new dual plasticity model explains both task-relevant and task-irrelevant VPL by distinguishing feature-based and task-based plasticity.

Keywords:
early visual cortexlocation specificityreweightingtask-irrelevant perceptual learningtask-relevant perceptual learningtransfer

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Area of Science:

  • Cognitive Neuroscience
  • Visual Perception Research

Background:

  • Visual perceptual learning (VPL) describes performance improvements from visual experience.
  • Existing research faces challenges in identifying the specific information processing stages affected by task-relevant VPL.
  • A significant gap exists in models explaining both task-relevant and task-irrelevant VPL.

Purpose of the Study:

  • To propose a novel dual plasticity model for visual perceptual learning.
  • To differentiate and integrate feature-based and task-based plasticity within a unified framework.
  • To provide a comprehensive explanation for previously contradictory findings in VPL research.

Main Methods:

  • Conceptual modeling approach.
  • Theoretical framework development.
  • Analysis of existing VPL literature and experimental results.

Main Results:

  • Proposed a dual plasticity model encompassing feature-based and task-based plasticity.
  • Feature-based plasticity involves changes in learned feature representation.
  • Task-based plasticity involves changes in trained task processing.

Conclusions:

  • Task-relevant VPL is underpinned by both feature-based and task-based plasticity.
  • Task-irrelevant VPL is solely explained by feature-based plasticity.
  • The dual plasticity model offers a unified framework to reconcile diverse VPL phenomena.