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

Extending cable theory to heterogeneous dendrites.

Claude Meunier1, Boris Lamotte d'Incamps

  • 1Laboratoire de Neurophysique et Physiologie (UMR CNRS 8119), Université Paris Descartes, 75006 Paris, France. claude.meunier@univ-paris5.fr

Neural Computation
|February 8, 2008
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

The alpha7 nicotinic acetylcholine receptor mediates network dysfunction in a mouse model of local amyloid pathology.

Molecular psychiatry·2025
Same author

Renshaw cells, corelease and nicotinic receptors: The last journey in synaptic transmission.

Neuroscience·2024
Same author

Neurofilament accumulations in amyotrophic lateral sclerosis patients' motor neurons impair axonal initial segment integrity.

Cellular and molecular life sciences : CMLS·2023
Same author

Two opposite voltage-dependent currents control the unusual early development pattern of embryonic Renshaw cell electrical activity.

eLife·2021
Same author

Stoichiometry of the Heteromeric Nicotinic Receptors of the Renshaw Cell.

The Journal of neuroscience : the official journal of the Society for Neuroscience·2018
Same author

Force encoding in muscle spindles during stretch of passive muscle.

PLoS computational biology·2017
Same journal

A Model-Free Reinforcement Learning Implementation of Decision Making Under Uncertainty by Sequential Sampling.

Neural computation·2026
Same journal

DROP: Distributional and Regular Optimism and Pessimism for Reinforcement Learning.

Neural computation·2026
Same journal

Hierarchical Active Inference Using Successor Representations.

Neural computation·2026
Same journal

W-Kernel and Its Principal Space for Frequentist Evaluation of Bayesian Estimators.

Neural computation·2026
Same journal

A Hidden Markov Model-Inspired Sequence Classification Method for Hyperdimensional Computing.

Neural computation·2026
Same journal

Sparse Graphical Modeling for Electrophysiological Phase-Based Connectivity Using Circular Statistics.

Neural computation·2026
See all related articles

Detailed neuron models can simplify complex dendritic structures. This study uses homogenization to approximate heterogeneous dendrites as homogeneous cables, justifying common modeling assumptions for synaptic integration.

Area of Science:

  • Computational neuroscience
  • Biophysics
  • Mathematical modeling

Background:

  • Neuron models often oversimplify dendritic complexity, neglecting small-scale electrical and morphological heterogeneities.
  • Existing models rarely account for variations in membrane conductances, diameter, or spine structures.

Discussion:

  • This research employs the homogenization method to derive averaged cable equations for heterogeneous dendrites.
  • It rigorously determines conditions under which simplified homogeneous cable models accurately represent complex dendritic structures.
  • The study analyzes synaptic distributions and their impact on voltage fluctuations in passive and active dendrites.

Key Insights:

  • A new regime is identified where spiny dendrites effectively behave as smooth dendrites, simplifying their modeling.

Related Experiment Videos

  • Spine neck conductance relative to synaptic conductance determines if spines can be modeled as an effective excitatory current.
  • Varicosities' impact on voltage diffusion and spatiotemporal integration in dendrites is examined.

    • Outlook:

    • These findings provide a rigorous basis for simplifying complex dendritic structures in computational neuroscience models.
    • The results offer guidance on the validity of approximations used in compartmental modeling of neurons.
    • Understanding dendritic integration in heterogeneous structures can advance theories of neural computation and information processing.