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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.
Tolman introduced the idea that behavior is influenced by...
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Long-term Potentiation01:35

Long-term Potentiation

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Long-term potentiation, or LTP, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTP is the process of synaptic strengthening that occurs over time between pre- and postsynaptic neuronal connections. The synaptic strengthening of LTP works in opposition to the synaptic weakening of long-term depression (LTD) and together are the main mechanisms that underlie learning and memory.
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Higher Mental Functions of Brain: Learning and Memory01:26

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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...
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Purposive Learning01:22

Purposive Learning

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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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Parallel Processing01:20

Parallel Processing

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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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System of Memory01:23

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Memory is categorized into three major systems: sensory memory, short-term memory (STM), and long-term memory (LTM). These systems differ in their capacity and the duration for which they can hold information. Sensory memory captures raw sensory input from the environment, holding it for just a few seconds or less. For example, on hearing a brief, loud sound, like a car horn honking, the sound seems to linger in the mind for a moment even after it stops. This is an instance of sensory memory...
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Related Experiment Video

Updated: Sep 25, 2025

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss
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Identifying Long- and Short-Term Processes in Perceptual Learning.

Jia Yang1,2, Fang-Fang Yan1,2, Lijun Chen1,2

  • 1Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences.

Psychological Science
|April 28, 2022
PubMed
Summary

Perceptual learning involves both long-term and short-term memory processes. This study introduces a framework to model these components, revealing distinct learning, forgetting, and adaptation patterns across various perceptual tasks.

Keywords:
adaptationforgettinglearning formlong-term memoryoff-line gainopen dataperceptual learningrelearning

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Area of Science:

  • Cognitive Psychology
  • Neuroscience
  • Perception

Background:

  • Perceptual learning is crucial for skill acquisition, yet the underlying mechanisms of improvement are not fully understood.
  • Existing models often simplify the complex interplay of memory processes involved in learning.

Purpose of the Study:

  • To develop and validate a multicomponent theoretical framework for modeling perceptual learning.
  • To differentiate between long-term and short-term processes contributing to perceptual skill enhancement.

Main Methods:

  • A theoretical framework was developed to model perceptual learning.
  • The framework was applied to learning curves from 49 participants across seven diverse perceptual tasks.
  • Key findings were replicated in a new experiment for specific tasks.

Main Results:

  • Ubiquitous long-term general learning and within-session relearning were observed in most tasks.
  • Specific tasks exhibited between-session forgetting (e.g., vernier-offset discrimination), offline gain (e.g., visual shape search), or both (e.g., contrast detection).
  • The model successfully identified distinct component processes in perceptual learning.

Conclusions:

  • Perceptual learning is characterized by a combination of general long-term learning, within-session adaptation, and between-session memory consolidation or decay.
  • The multicomponent model offers a robust framework for analyzing perceptual learning dynamics.
  • This framework has potential applications for optimizing learning strategies in both typical and clinical populations.