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 Experiment Videos

Neural stability and flexibility: a computational approach.

Hans Liljenström1

  • 1Department of Biometry and Informatics, SLU, Box 7013, S-750 07 Uppsala, Sweden. hans.liljenstrom@bi.slu.se

Neuropsychopharmacology : Official Publication of the American College of Neuropsychopharmacology
|June 27, 2003
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

A Neurocomputational Model of Observation-Based Decision Making with a Focus on Trust.

Brain sciences·2026
Same author

Circular causality in volition.

Frontiers in network physiology·2025
Same author

Computational modeling of attractor-based neural processes involved in the preparation of voluntary actions.

Cognitive neurodynamics·2024
Same author

Consciousness, decision making, and volition: freedom beyond chance and necessity.

Theory in biosciences = Theorie in den Biowissenschaften·2021
Same author

Computational modeling aids in linking structure, dynamics, and function of neural systems: A commentary on Wright, J.J., & Bourke, P.D. "The growth of cognition: Free energy minimization and the embryogenesis of cortical computation", Physics of Life Reviews.

Physics of life reviews·2020
Same author

Modeling effects of neural fluctuations and inter-scale interactions.

Chaos (Woodbury, N.Y.)·2018
Same journal

Auditory event-related potentials and psychosis dimensions.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology·2026
Same journal

Cultural humility in the teaching and practice of clinical care.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology·2026
Same journal

Kappa opioid receptors mediate aversion-and it matters.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology·2026
Same journal

Splice isoforms of the histone variant macroH2A1 differentially regulate hippocampal gene expression and memory formation.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology·2026
Same journal

Chronic ethanol self-administration alters dopamine in the caudate nucleus and putamen of rhesus macaques in a sex-dependent manner.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology·2026
Same journal

In memoriam-Shigeto Yamawaki, M.D., Ph.D. (1954-2026).

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology·2026
See all related articles

This study explores balancing neural system stability and flexibility using a cortical neural network model. Findings suggest that regulating neurodynamics and neural circuitry, through synaptic modification and pruning, enhances information processing and learning.

Area of Science:

  • Computational Neuroscience
  • Cognitive Neuroscience
  • Systems Neuroscience

Background:

  • Neural systems require a balance between stability for memory retention and flexibility for learning new information.
  • The stability-flexibility dilemma is a critical challenge in understanding brain function and cognitive processes.

Purpose of the Study:

  • To investigate how regulating neurodynamics in a cortical neural network model can achieve a balance between stability and flexibility.
  • To explore the relationship between neural system structure, dynamics, and function, particularly concerning information processing, learning, and associative memory.

Main Methods:

  • Utilized a cortical neural network model to simulate and analyze neural system dynamics.
  • Investigated the role of synaptic modification and network pruning in modulating neurodynamics.

Related Experiment Videos

  • Examined how regulation of complex neurodynamics impacts learning and associative memory.

    • Main Results:

    • Demonstrated that proper regulation of neurodynamics can lead to efficient information processing, enhancing learning and associative memory.
    • Identified specific mechanisms, including synaptic modification and network pruning, that contribute to solving the stability-flexibility dilemma.
    • Established a link between neural circuitry, complex neurodynamics, and overall system function.

    Conclusions:

    • Achieving a balance between stability and flexibility in neural systems is crucial for efficient cognitive function.
    • Modulation of neurodynamics through synaptic and network-level changes offers a viable solution to the stability-flexibility dilemma.
    • The findings have implications for understanding neural computation and potential links to mental disorders.