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

Generalization, Discrimination, and Extinction01:24

Generalization, Discrimination, and Extinction

Generalization, discrimination, and extinction are key concepts in operant conditioning that influence how behaviors are learned and maintained.
Generalization occurs when a behavior reinforced in one context is performed in similar situations. For instance, a student who studies diligently for calculus and receives excellent grades might apply the same study habits to psychology and history, expecting similar results. Generalization shows how learning in one setting can influence behavior in...
Causes of Similarity-Dissimilarity Effect01:26

Causes of Similarity-Dissimilarity Effect

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...
Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
Survival Tree01:19

Survival Tree

Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a survival tree begins...

You might also read

Related Articles

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

Sort by
Same author

AATF alleviates cerebral ischemia-reperfusion injury by suppressing endoplasmic reticulum stress-induced ferroptosis through upregulating the PI3K/Akt pathway.

Neurological research·2025
Same author

Follow-up Optical Coherence Tomography Evaluation of Endothelialization in Drug-eluting Stents for Symptomatic Vertebral Artery Stenosis: a Report of Nine Cases.

Clinical neuroradiology·2025
Same author

Angiogenesis-driven hybrid hydrogel with pH/ROS-activated anti-infection and enhanced cellular metabolism for efficient MRSA-impaired wound repair.

Acta biomaterialia·2025
Same author

Sequence homology between sex chromosomes leads to apparent heterozygosity at the DYS572 locus in massively parallel sequencing.

International journal of legal medicine·2025
Same author

Compound heterozygous variants in <i>PCDH15</i> non-coding regions in an Usher Syndrome Type 1F patient: minigene assay reveals pathogenicity of c.3123-1G>C.

Ophthalmic genetics·2025
Same author

Comparative effects of 2 Hz vs. 100 Hz transcutaneous electrical nerve stimulation on upper limb motor function post-stroke: design and rationale for a randomized trial.

Frontiers in neurology·2025
Same journal

Zero-shot reconstruction of mutant spatial transcriptomes.

Patterns (New York, N.Y.)·2026
Same journal

Dendritic nonlinearities mitigate communication costs.

Patterns (New York, N.Y.)·2026
Same journal

Erratum: Agentic AI as a coordination paradigm in digital health and agri-food systems.

Patterns (New York, N.Y.)·2026
Same journal

A multi-modal foundation model for brain disease diagnosis and medical imaging.

Patterns (New York, N.Y.)·2026
Same journal

DuoMod-Net: Logarithmic balancing and geometric refinement for imbalanced semi-supervised medical image segmentation.

Patterns (New York, N.Y.)·2026
Same journal

SelfCheck-Eval: A multi-module framework for zero-resource hallucination detection in large language models.

Patterns (New York, N.Y.)·2026
See all related articles

Related Experiment Video

Updated: Jun 23, 2026

An Operant Intra-/Extra-dimensional Set-shift Task for Mice
08:35

An Operant Intra-/Extra-dimensional Set-shift Task for Mice

Published on: January 22, 2016

Spacing effect improves generalization in biological and artificial systems.

Guanglong Sun1,2,3, Ning Huang1,2, Hongwei Yan1,2,3

  • 1School of Life Sciences, IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China.

Patterns (New York, N.Y.)
|June 22, 2026
PubMed
Summary
This summary is machine-generated.

The spacing effect, inspired by biological learning, improves artificial intelligence generalization. Spaced training with variations enhances performance in neural networks and fruit fly experiments, revealing a shared learning principle.

Keywords:
NeuroAIbio-inspired learningensemble learninggeneralizationspacing effect

Related Experiment Videos

Last Updated: Jun 23, 2026

An Operant Intra-/Extra-dimensional Set-shift Task for Mice
08:35

An Operant Intra-/Extra-dimensional Set-shift Task for Mice

Published on: January 22, 2016

Area of Science:

  • Artificial Intelligence
  • Computational Neuroscience
  • Machine Learning

Background:

  • Generalization is key to learning effectiveness, posing challenges for AI compared to biological intelligence.
  • The spacing effect in biological learning demonstrates improved performance with spaced training intervals.
  • A hypothesis suggests spaced training enhances generalization by integrating input and innate variations.

Purpose of the Study:

  • To investigate the hypothesis that spaced training enhances generalization by integrating variations.
  • To implement bio-inspired spacing effects in artificial neural networks.
  • To validate the findings through biological experiments.

Main Methods:

  • Introduced bio-inspired spacing effect into artificial neural networks.
  • Integrated input and innate variations across spaced intervals at neuronal, synaptic, and network levels.
  • Conducted biological experiments on *Drosophila*.

Main Results:

  • Spaced ensemble strategies significantly improved performance across benchmark datasets and network architectures.
  • Biological experiments validated the complementary effect of variations and spaced intervals.
  • Demonstrated significant performance gains in artificial neural networks.

Conclusions:

  • Spaced training with integrated variations offers a convergent computational principle for both biological and machine learning.
  • The study highlights a novel method for enhancing AI generalization capabilities.
  • Findings suggest a unified mechanism underlying learning and memory across species.