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

Variability: Analysis01:11

Variability: Analysis

254
Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
254
Causes of Similarity-Dissimilarity Effect01:26

Causes of Similarity-Dissimilarity Effect

90
The similarity-dissimilarity effect, a fundamental concept in social psychology, explains how interpersonal similarities and differences influence attraction and social interactions. This effect is supported by three key psychological perspectives: balance theory, social comparison theory, and consensual validation.Balance Theory and Cognitive ConsistencyBalance theory, developed by Fritz Heider, posits that individuals seek cognitive consistency in their relationships. When two people share...
90
How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

39.1K
A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
39.1K
Classification of Systems-II01:31

Classification of Systems-II

298
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
298
Theory of Attribution II: Kelley's Covariation Theory01:29

Theory of Attribution II: Kelley's Covariation Theory

161
Attribution theory plays a crucial role in social psychology, helping to explain how individuals interpret the causes of behavior. One prominent model within this field is Harold Kelley's covariation theory, which provides a systematic approach to determining whether internal traits or external circumstances drive a person's actions. The model posits that individuals rely on three key types of information—consensus, consistency, and distinctiveness—to make these judgments.Consensus:...
161
Classification of Systems-I01:26

Classification of Systems-I

388
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
388

You might also read

Related Articles

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

Sort by
Same author

Context modulates brain state dynamics and behavioral responses during narrative comprehension.

Imaging neuroscience (Cambridge, Mass.)·2026
Same author

Context modulates brain state dynamics and behavioral responses during narrative comprehension.

bioRxiv : the preprint server for biology·2025
Same author

Just do it: A neuropsychological theory of agency, cognition, mood, and dopamine.

Journal of experimental psychology. General·2024
Same author

When instructions don't help: Knowing the optimal strategy facilitates rule-based but not information-integration category learning.

Journal of experimental psychology. Human perception and performance·2021
Same author

A neurocomputational theory of how rule-guided behaviors become automatic.

Psychological review·2021
Same author

Retinal-specific category learning.

Nature human behaviour·2019
Same journal

Testing the predictions of a distinctiveness model of memory: The production effect in backward recall.

Journal of experimental psychology. Learning, memory, and cognition·2026
Same journal

On the impact of adjacency on transposed-word effects under serial presentation.

Journal of experimental psychology. Learning, memory, and cognition·2026
Same journal

It's time to opt out: Metacognitive analysis of time regulation under uncertainty.

Journal of experimental psychology. Learning, memory, and cognition·2026
Same journal

The role of statistical learning in attentional guidance during search through naturalistic scenes.

Journal of experimental psychology. Learning, memory, and cognition·2026
Same journal

Representing objects and features in long-term memory: A case for direct feature-feature binding.

Journal of experimental psychology. Learning, memory, and cognition·2026
Same journal

Crossmodal correspondences influence adaptation during rule-based category learning of objects.

Journal of experimental psychology. Learning, memory, and cognition·2026
See all related articles

Related Experiment Video

Updated: Nov 8, 2025

Creating Objects and Object Categories for Studying Perception and Perceptual Learning
14:38

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

12.0K

Linear separability, irrelevant variability, and categorization difficulty.

Luke A Rosedahl1, F Gregory Ashby1

  • 1Dynamical Neuroscience.

Journal of Experimental Psychology. Learning, Memory, and Cognition
|April 19, 2021
PubMed
Summary
This summary is machine-generated.

Category learning difficulty differs between rule-based (RB) and information-integration (II) tasks. Irrelevant stimulus variability impairs II learning but not RB learning, challenging prior assumptions about linear separability.

More Related Videos

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.7K
Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
07:34

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

17.6K

Related Experiment Videos

Last Updated: Nov 8, 2025

Creating Objects and Object Categories for Studying Perception and Perceptual Learning
14:38

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

12.0K
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.7K
Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
07:34

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

17.6K

Area of Science:

  • Cognitive Psychology
  • Machine Learning
  • Computational Neuroscience

Background:

  • Category learning tasks are broadly divided into rule-based (RB) and information-integration (II) types, with distinct optimal learning strategies.
  • Previous research suggested linear separability simplifies Information Integration (II) category learning, while rule-based (RB) learning relies on explicit rules.
  • The impact of irrelevant stimulus dimension variability on category learning difficulty remained less understood.

Purpose of the Study:

  • To investigate the influence of linear separability and irrelevant stimulus dimension variability on category learning difficulty.
  • To examine potential dissociations in learning effects between rule-based (RB) and information-integration (II) category learning paradigms.
  • To evaluate existing theoretical models of category learning difficulty against empirical findings.

Main Methods:

  • Comparison of learning performance on linearly and nonlinearly separable categories, controlling for other difficulty factors.
  • Manipulation of variability on irrelevant stimulus dimensions across both rule-based (RB) and information-integration (II) tasks.
  • Analysis of learning trajectories and error rates to quantify task difficulty.

Main Results:

  • Linear separability did not significantly affect learning difficulty in information-integration (II) tasks when other factors were equated.
  • Increased variability on irrelevant stimulus dimensions impaired information-integration (II) learning.
  • Increased variability on irrelevant stimulus dimensions did not impair rule-based (RB) learning.

Conclusions:

  • A novel dissociation was identified: irrelevant stimulus variability differentially impacts information-integration (II) and rule-based (RB) category learning.
  • Findings challenge the notion that linear separability is a primary determinant of difficulty in information-integration (II) tasks.
  • The results align with theoretical predictions regarding the distinct mechanisms underlying rule-based (RB) and information-integration (II) learning.