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

Signal delay and input synchronization in passive dendritic structures

H Agmon-Snir1, I Segev

  • 1Department of Neurobiology, Hebrew University, Jerusalem, Israel.

Journal of Neurophysiology
|November 1, 1993
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

Dynamic and spatial features of the inhibitory pallidal GABAergic synapses.

Neuroscience·2005
Same author

Synaptic scaling in vitro and in vivo.

Nature neuroscience·2001
Same author

The role of single neurons in information processing.

Nature neuroscience·2000
Same author

Untangling dendrites with quantitative models.

Science (New York, N.Y.)·2000
Same author

Subthreshold voltage noise due to channel fluctuations in active neuronal membranes.

Journal of computational neuroscience·2000
Same author

Taming time in the olfactory bulb.

Nature neuroscience·1999
Same journal

Comprehensive Analysis of Auditory Nerve Fiber Responses using Fiber-Specific Modeling.

Journal of neurophysiology·2026
Same journal

HCN channels modulate the medium afterhyperpolarization and adjust the firing gain of fast alpha motoneurons in mice.

Journal of neurophysiology·2026
Same journal

Targeting intracranial electrical stimulation to network regions defined within individuals causes network-level effects.

Journal of neurophysiology·2026
Same journal

When "Noise" Isn't Simply Noise: Deterministic Postural Drive During Noisy Galvanic Vestibular Stimulation (nGVS).

Journal of neurophysiology·2026
Same journal

Abrupt Scene Onsets and Gradually Emerging Scene Information Produce Distinct EEG Decoding Dynamics.

Journal of neurophysiology·2026
Same journal

From discovery to translation: charting a course for the <i>Journal of Neurophysiology</i>.

Journal of neurophysiology·2026
See all related articles

A novel method of moments analyzes electrical signal propagation in passive dendritic trees, offering an analytic solution for time delay and speed without simulations. This method reveals key properties of dendritic delay, independent of input signals and tree morphology.

Area of Science:

  • Computational Neuroscience
  • Biophysics
  • Electrical Engineering

Background:

  • Analyzing transient electrical signal propagation in complex neuronal structures like dendritic trees is crucial for understanding neural computation.
  • Existing methods often rely on numerical simulations, which can be computationally intensive and time-consuming.
  • Developing analytical approaches can provide deeper insights and more efficient calculations.

Purpose of the Study:

  • To introduce a novel analytical method, the method of moments, for calculating signal propagation delays in passive dendritic trees.
  • To define and analyze key delay parameters: Total Dendritic Delay (TD), Local Delay (LD), Propagation Delay (PD), and Net Dendritic Delay (NDD).
  • To establish fundamental properties of dendritic delays and develop efficient calculation strategies.

Related Experiment Videos

Main Methods:

  • Introduced the "method of moments" as an analytic approach for transient analysis.
  • Defined Total Dendritic Delay (TD) based on the centroid of input current and voltage response.
  • Defined Local Delay (LD), Propagation Delay (PD), and Net Dendritic Delay (NDD) relative to specific points in the dendritic tree.
  • Derived signal velocity (θ) from the voltage response derivative.
  • Utilized lumping of subtrees into equivalent R-C compartments for efficient calculation.

Main Results:

  • The method provides an analytic solution for time delay and signal propagation speed in any passive dendritic tree, eliminating the need for numerical simulations.
  • Dendritic delay is independent of the input signal's properties (shape, duration).
  • Signal velocity at a point is independent of the tree's morphology "behind" the signal and the input location.
  • Total Dendritic Delay (TD) is symmetric: TD(y, x) = TD(x, y).
  • Subtrees can be lumped into equivalent R-C compartments, and local delay is a weighted mean of subtree local delays.

Conclusions:

  • The method of moments offers a powerful, simulation-free analytical tool for studying signal propagation in passive dendritic structures.
  • Defined delays (LD, TD) provide a measure of the time window for synaptic input integration.
  • Net Dendritic Delay (NDD) quantifies the delay cost associated with synapse location relative to the target point.
  • The derived properties and calculation methods facilitate efficient analysis of complex dendritic architectures.