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

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...
Signal and System01:26

Signal and System

A signal x(t) is a set of data or a time function representing a variable of interest. Signals typically convey information about a phenomenon, such as atmospheric temperature, humidity, human voice, television images, a dog's bark, or birdsongs. More generally, a signal can be a function of more than one independent variable. For instance, images depend on horizontal and vertical positions and can be regarded as two-dimensional signals. However, this text will focus on one-dimensional signals...
Classification of Systems-I01:26

Classification of Systems-I

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:
Associative Learning01:27

Associative Learning

Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
Complement System01:27

Complement System

The complement system is a group of approximately 20 plasma proteins that strengthen the body's defenses against infections through opsonization, inflammation, and cell lysis. Opsonization involves coating pathogens with complement proteins, making them more recognizable and facilitating phagocyte engulfment. Certain complement proteins induce inflammation that attracts immune cells to the site of infection. Cell lysis involves the destruction of pathogens through the formation of a membrane...
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...

You might also read

Related Articles

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

Sort by
Same author

Synaptic Plasticity as a Function of the Temporal Derivative.

bioRxiv : the preprint server for biology·2026
Same author

Slowdown vs. breakdown of memory recall by retrieval stopping.

Memory & cognition·2025
Same author

Memory out of context: Spacing effects and decontextualization in a computational model of the medial temporal lobe.

Psychological review·2024
Same author

A complementary learning systems model of how sleep moderates retrieval practice effects.

Psychonomic bulletin & review·2024
Same author

A Neural Network Model of Continual Learning with Cognitive Control.

CogSci ... Annual Conference of the Cognitive Science Society. Cognitive Science Society (U.S.). Conference·2023
Same author

Closed-Loop tACS Delivered during Slow-Wave Sleep Reduces Retroactive Interference on a Paired-Associates Learning Task.

Brain sciences·2023
Same journal

Pronoun Resolution in Turkish: The Interplay of Referential Form, Word Order, and Implicit Causality.

Cognitive science·2026
Same journal

What's in a Color?: Language, Synesthesia, and Categorical Perception.

Cognitive science·2026
Same journal

Reasoning Beyond Explicit Rules: Adults' and Children's Use of Closure Principles in Novel Cases.

Cognitive science·2026
Same journal

Intermediary Object States Are Activated by Sentences Describing Completed Events.

Cognitive science·2026
Same journal

Large Language Models Estimate Fine-Grained Human Color-Concept Associations.

Cognitive science·2026
Same journal

Computational Models of Causal Reasoning: Bayesian Accounts of Normative Violations.

Cognitive science·2026
See all related articles

Related Experiment Video

Updated: May 26, 2026

Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

Complementary learning systems.

Randall C O'Reilly1, Rajan Bhattacharyya, Michael D Howard

  • 1Department of Psychology and Neuroscience, University of Colorado BoulderHRL Laboratories, LLC, Malibu, CA.

Cognitive Science
|December 7, 2011
PubMed
Summary
This summary is machine-generated.

The complementary learning systems (CLS) framework explains the brain's dual memory systems: the hippocampus for rapid episodic learning and the neocortex for gradual semantic learning. Recent data confirms its core principles.

Keywords:
ConsolidationHippocampusLearningMemoryNeocortexNeural network models

Related Experiment Videos

Last Updated: May 26, 2026

Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

Area of Science:

  • Neuroscience
  • Cognitive Psychology
  • Computational Neuroscience

Background:

  • The complementary learning systems (CLS) framework, proposed by McClelland, McNaughton, and O'Reilly (1995), posits two distinct brain systems for learning and memory.
  • It differentiates the hippocampus's role in rapid episodic memory formation from the neocortex's function in gradual semantic structure extraction.

Purpose of the Study:

  • To review the evolution and current status of the CLS framework's central tenets.
  • To examine the empirical evidence supporting the CLS framework across various memory research domains.

Main Methods:

  • Literature review of studies applying the CLS framework.
  • Analysis of research on hippocampal and neocortical memory functions.

Main Results:

  • The CLS framework accurately describes hippocampal function as a sparse, pattern-separated system for rapid learning.
  • It correctly identifies neocortical function as a distributed, overlapping system for gradual semantic integration.
  • Empirical data over the last 15 years largely supports the CLS framework's key principles.

Conclusions:

  • The CLS framework remains a significant theoretical model in memory research.
  • The framework's core concepts regarding hippocampal and neocortical roles are empirically validated.
  • The synergistic interaction between the hippocampus and neocortex is crucial for memory consolidation and retrieval.