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

Organization of the Brain01:30

Organization of the Brain

The brain is an integral component of the nervous system and serves as the center for processing sensory inputs, making decisions, and directing bodily actions. This complex organ is organized into three primary sections: the hindbrain, midbrain, and forebrain, each responsible for a range of vital functions.
Hindbrain
The hindbrain, located at the base of the brain, plays a vital role in regulating automatic processes that sustain life. It includes the medulla oblongata, which is essential for...
Brain Imaging01:14

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic Stimulation (TMS).

You might also read

Related Articles

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

Sort by
Same author

Topological Neural Coding: The associative memory representation of graphs, groups and knots.

Bio Systems·2026
Same author

Memory Gate Controlled by Contexts: Potential Key Structure That Could Link Small Associative Failures With Severe Cognitive Disorders.

BioEssays : news and reviews in molecular, cellular and developmental biology·2025
Same author

Inhibitory dynamics in dual-route evidence accumulation account for response time distributions from conflict tasks.

Cognitive neurodynamics·2024
Same author

A memory access gate controlled by dynamic contexts.

Bio Systems·2024
Same author

Homeostasis and information processing: The key frames for the thermodynamics of biological systems.

Bio Systems·2024
Same author

Load sharing between synergistic muscles characterized by a ligand-binding approach and elastography.

Scientific reports·2023
Same journal

Adaptive memristor-based LIF neuron circuit for energy efficient SNN crossbar array.

Cognitive neurodynamics·2026
Same journal

Dynamic bi-domain discriminator adversarial network for EEG emotion recognition.

Cognitive neurodynamics·2026
Same journal

Olfactory Perception and Neural Rhythms: A Simulation-Based EEG Analysis Using Power Spectral Density FeaturesOlfactory perception and neural rhythms: a simulation-based eeg analysis using power spectral density features.

Cognitive neurodynamics·2026
Same journal

An event-related potentials account of brain predictive coding.

Cognitive neurodynamics·2026
Same journal

A recurrent neural network model for a decision-making task based on sequential evidence accumulation.

Cognitive neurodynamics·2026
Same journal

Synaptic neurotransmitter concentration modulation during learning in bio-inspired spiking neural network.

Cognitive neurodynamics·2026
See all related articles

Related Experiment Video

Updated: Jun 22, 2026

Tracking Sugar-Elicited Local Searching Behavior in Drosophila
03:53

Tracking Sugar-Elicited Local Searching Behavior in Drosophila

Published on: November 17, 2023

Dynamic searching in the brain.

Eduardo Mizraji1, Andrés Pomi, Juan C Valle-Lisboa

  • 1Group of Cognitive Systems Modeling, Biophysical Section, Facultad de Ciencias, Universidad de la República, Iguá 4225, Montevideo, 11400 Uruguay.

Cognitive Neurodynamics
|June 5, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces context-dependent memory models to understand brain search engines for cognitive functions. These models use thematic packing and association matrices for efficient information retrieval and problem-solving.

More Related Videos

Simultaneous Eye Tracking and Single-Neuron Recordings in Human Epilepsy Patients
07:43

Simultaneous Eye Tracking and Single-Neuron Recordings in Human Epilepsy Patients

Published on: June 17, 2019

Multi-layer Cortical Ca2+ Imaging in Freely Moving Mice with Prism Probes and Miniaturized Fluorescence Microscopy
10:35

Multi-layer Cortical Ca2+ Imaging in Freely Moving Mice with Prism Probes and Miniaturized Fluorescence Microscopy

Published on: June 13, 2017

Related Experiment Videos

Last Updated: Jun 22, 2026

Tracking Sugar-Elicited Local Searching Behavior in Drosophila
03:53

Tracking Sugar-Elicited Local Searching Behavior in Drosophila

Published on: November 17, 2023

Simultaneous Eye Tracking and Single-Neuron Recordings in Human Epilepsy Patients
07:43

Simultaneous Eye Tracking and Single-Neuron Recordings in Human Epilepsy Patients

Published on: June 17, 2019

Multi-layer Cortical Ca2+ Imaging in Freely Moving Mice with Prism Probes and Miniaturized Fluorescence Microscopy
10:35

Multi-layer Cortical Ca2+ Imaging in Freely Moving Mice with Prism Probes and Miniaturized Fluorescence Microscopy

Published on: June 13, 2017

Area of Science:

  • Cognitive Science
  • Computational Neuroscience
  • Information Retrieval

Background:

  • Cognitive functions depend on accessing stored information, a complex search task.
  • Understanding biological search engines is key to studying cognition.
  • Existing models often lack the context-dependent mechanisms found in human memory.

Purpose of the Study:

  • To propose and analyze multi-modular network models for cognitive information search.
  • To extend context-dependent memory models for complex problem-solving.
  • To bridge computational memory models with information retrieval techniques.

Main Methods:

  • Developing context-dependent memory models based on Kronecker products.
  • Utilizing association matrices for vector-based information processing.
  • Extending models to multi-modular networks with input-output contexts.

Main Results:

  • Demonstrated that vector coding and association matrices link memory models to information retrieval procedures.
  • Showcased 'thematic packing' where contexts retrieve related concepts.
  • Presented 'neuromimetic' devices solving tasks like decision-making and word sense disambiguation.

Conclusions:

  • Context-dependent memory models offer a framework for understanding cognitive search.
  • Multi-modular networks, using context as 'passwords,' can perform complex cognitive tasks.
  • The models' dynamics can be described at the cognitive variable level.