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

A dynamic neural network with temporal coding and functional connectivity

M Watanabe1, K Aihara, S Kondo

  • 1Department of Quantum Engineering and Systems Science, School of Engineering, University of Tokyo, Japan.

Biological Cybernetics
|April 3, 1998
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

Detection of current-sheet and bipolar ion flows in a self-generated antiparallel magnetic field of laser-produced plasmas for magnetic reconnection research.

Physical review. E·2022
Same author

Author Correction: Direct observations of pure electron outflow in magnetic reconnection.

Scientific reports·2022
Same author

High-power laser experiment on developing supercritical shock propagating in homogeneously magnetized plasma of ambient gas origin.

Physical review. E·2022
Same author

Direct observations of pure electron outflow in magnetic reconnection.

Scientific reports·2022
Same author

High-power laser experiment forming a supercritical collisionless shock in a magnetized uniform plasma at rest.

Physical review. E·2022
Same author

Reconstructing bifurcation diagrams only from time-series data generated by electronic circuits in discrete-time dynamical systems.

Chaos (Woodbury, N.Y.)·2020
Same journal

Harmonic memory in phasor neural networks.

Biological cybernetics·2026
Same journal

Correction: Decreased spinal inhibition leads to undiversified locomotor patterns.

Biological cybernetics·2026
Same journal

Foundational issues of network models in biology.

Biological cybernetics·2026
Same journal

Dynamical mechanisms for coordinating long-term working memory based on the precision of spike-timing in cortical neurons.

Biological cybernetics·2026
Same journal

Distinct dopaminergic spike-timing-dependent plasticity rules are suited to different functional roles.

Biological cybernetics·2026
Same journal

Fluctuation-response relations for a two-stage population of spiking neurons stimulated by common noise.

Biological cybernetics·2026
See all related articles

A novel neural network model dynamically adjusts its pattern classification using program input. This temporal-coding network simulates neuron spike timing and functional connectivity, offering new insights into neural processing.

Area of Science:

  • Computational neuroscience
  • Artificial intelligence
  • Neural network modeling

Background:

  • Traditional neural networks often lack dynamic adaptability.
  • Understanding complex neural communication requires models that capture temporal dynamics.

Purpose of the Study:

  • To propose a novel neural network model with program-input-driven adaptive classification.
  • To investigate the role of temporal coding and dynamic functional connectivity in neural information processing.

Main Methods:

  • Developed a continuous-time, deterministic point process neural network.
  • Incorporated finite, normally distributed synaptic delays.
  • Utilized dynamic functional connectivity characteristic of temporal-coding networks.

Related Experiment Videos

Main Results:

  • Simulations demonstrated the model's ability to alter pattern classification based on program input.
  • The model's behavior aligns with recent experimental findings on correlated neuronal firing.

Conclusions:

  • The proposed model offers a new paradigm for adaptive neural computation.
  • This approach provides a framework for exploring temporal coding and dynamic connectivity in biological and artificial neural systems.