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

The Role of Ion Channels in Neuronal Computation01:19

The Role of Ion Channels in Neuronal Computation

4.2K
A postsynaptic neuron usually receives numerous impulses from several other presynaptic neurons. The axon hillock of the postsynaptic neuron integrates all these signals and determines the likelihood of firing an action potential.
Sometimes a single EPSP is strong enough to induce an action potential in the postsynaptic neuron. However, multiple presynaptic inputs must often create EPSPs around the same time for the postsynaptic neuron to be sufficiently depolarized to fire an action potential....
4.2K
Electrochemical Gradient and Channel Proteins: An Overview01:21

Electrochemical Gradient and Channel Proteins: An Overview

5.4K
An electrochemical gradient is a fundamental concept in biology and chemistry. It regulates the movement of ions across cell membranes. This movement is influenced by two factors:
The electrical gradient: The electrical gradient across cell membranes refers to the difference in electric charge between the inside and outside of a cell.  This difference drives the movement of ions towards or away from the cells. For instance, if the inside of the cell is more negatively charged relative to...
5.4K
Action Potential: Phases of Stimulation01:28

Action Potential: Phases of Stimulation

18.6K
The action potential is a complex electrical event that occurs in excitable cells, such as neurons and muscle cells. It consists of several distinct phases, each with specific characteristics.
Resting Phase:
In this phase, the cell's membrane is at its resting potential, typically around -70 millivolts (mV) for neurons. Inside the cell, there is a higher concentration of potassium ions (K+) and a lower concentration of sodium ions (Na+). Voltage-gated sodium channels are closed, and...
18.6K
Action Potential01:14

Action Potential

12.3K
Neurons communicate by firing action potentials—the electrochemical signal that is propagated along the axon. The signal results in the release of neurotransmitters at axon terminals, thereby transmitting information to the nervous system. An action potential is a specific "all-or-none" change in membrane potential that results in a rapid spike in voltage.
Membrane potential in neurons
Neurons typically have a resting membrane potential of about -70 millivolts (mV). When they receive...
12.3K
Action Potential01:31

Action Potential

8.3K
Neurons communicate by firing action potentials—the electrochemical signal that is propagated along the axon. The signal results in the release of neurotransmitters at axon terminals, thereby transmitting information to the nervous system. An action potential is a specific "all-or-none" change in membrane potential that results in a rapid spike in voltage.
Membrane potential in neurons
Neurons typically have a resting membrane potential of about -70 millivolts (mV). When they receive...
8.3K
Action Potentials01:41

Action Potentials

150.2K
Overview
150.2K

You might also read

Related Articles

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

Sort by
Same author

Fast reconstruction of degenerate populations of conductance-based neuron models from spike times.

PLoS computational biology·2026
Same author

Activity-dependent neuromodulation and calcium homeostasis cooperate to produce robust and modulable neuronal function.

PLoS computational biology·2026
Same author

Burst firing creates an attractor in synaptic weight dynamics.

PLoS computational biology·2026
Same author

Efficient and reliable spike sorting from neural recordings with UMAP-based unsupervised nonlinear dimensionality reduction.

PLoS biology·2025
Same author

Multistable bimodal perceptual coding within the ventral premotor cortex.

Science advances·2025
Same author

Dimensionality reduction of neuronal degeneracy reveals two interfering physiological mechanisms.

PNAS nexus·2024
Same journal

Translational profiling of Drd2-expressing populations reveals molecular heterogeneity of dentate gyrus mossy cells along the dorsoventral axis.

eNeuro·2026
Same journal

Movement Disorder Patients with Depression have Altered Corticostriatal Alpha-Beta Power Response to Reward and Loss.

eNeuro·2026
Same journal

Ocular speech tracking persists in blindness, but its dynamics and oculo-cerebral connectivity depend on visual status.

eNeuro·2026
Same journal

Emergent multidien cycles from partial circadian synchrony.

eNeuro·2026
Same journal

Adolescent social isolation induces persistent impairments in emotional discrimination and helping behavior.

eNeuro·2026
Same journal

Increased Ih Current Is Associated with Reduced Hippocampal CA1 Excitability in a Mouse Model of Multiple Sclerosis.

eNeuro·2026
See all related articles

Related Experiment Video

Updated: Mar 31, 2026

Induction of an Isoelectric Brain State to Investigate the Impact of Endogenous Synaptic Activity on Neuronal Excitability In Vivo
10:19

Induction of an Isoelectric Brain State to Investigate the Impact of Endogenous Synaptic Activity on Neuronal Excitability In Vivo

Published on: March 31, 2016

8.7K

Dynamic Input Conductances Shape Neuronal Spiking

Guillaume Drion1, Alessio Franci2, Julie Dethier3

  • 1Systems and Modeling, Department of Electrical Engineering and Computer Science, University of Liège , Liège, B-4000, Belgium ; Laboratory of Pharmacology and GIGA Neurosciences, University of Liège , Liège, B-4000, Belgium ; Volen Center and Biology Department, Brandeis University , Waltham, Massachussetts 02454.

Eneuro
|October 15, 2015
PubMed
Summary
This summary is machine-generated.

This study introduces dynamic input conductances as a method to understand neuronal signaling. Analyzing these conductances reveals how biophysical parameter changes affect neuronal activity and stability.

Keywords:
compensationfiring patternion channelsneuromodulation

More Related Videos

Implementing Dynamic Clamp with Synaptic and Artificial Conductances in Mouse Retinal Ganglion Cells
11:46

Implementing Dynamic Clamp with Synaptic and Artificial Conductances in Mouse Retinal Ganglion Cells

Published on: May 16, 2013

12.9K
Application of a NMDA Receptor Conductance in Rat Midbrain Dopaminergic Neurons Using the Dynamic Clamp Technique
06:42

Application of a NMDA Receptor Conductance in Rat Midbrain Dopaminergic Neurons Using the Dynamic Clamp Technique

Published on: December 21, 2010

12.5K

Related Experiment Videos

Last Updated: Mar 31, 2026

Induction of an Isoelectric Brain State to Investigate the Impact of Endogenous Synaptic Activity on Neuronal Excitability In Vivo
10:19

Induction of an Isoelectric Brain State to Investigate the Impact of Endogenous Synaptic Activity on Neuronal Excitability In Vivo

Published on: March 31, 2016

8.7K
Implementing Dynamic Clamp with Synaptic and Artificial Conductances in Mouse Retinal Ganglion Cells
11:46

Implementing Dynamic Clamp with Synaptic and Artificial Conductances in Mouse Retinal Ganglion Cells

Published on: May 16, 2013

12.9K
Application of a NMDA Receptor Conductance in Rat Midbrain Dopaminergic Neurons Using the Dynamic Clamp Technique
06:42

Application of a NMDA Receptor Conductance in Rat Midbrain Dopaminergic Neurons Using the Dynamic Clamp Technique

Published on: December 21, 2010

12.5K

Area of Science:

  • Neuroscience
  • Computational Biology
  • Biophysics

Background:

  • Understanding neuronal signaling modulation, robustness, and homeostasis requires assessing biophysical parameter variations.
  • Dynamic input conductances integrate ion channel activity across timescales, influencing neuronal spiking.
  • Current-voltage relationships are shaped by these dynamic conductances.

Purpose of the Study:

  • To propose and validate a method for analyzing dynamic input conductances in neurons.
  • To investigate the role of biophysical parameter variations in neuronal activity.
  • To provide tools for experimental measurement and computational analysis of dynamic input conductances.

Main Methods:

  • Development of an experimental protocol for measuring dynamic input conductances.
  • Creation of a computational method to extract dynamic input conductances from models.
  • Sensitivity analysis of dynamic input conductances to arbitrary parameters.

Main Results:

  • Dynamic input conductances effectively aggregate ion channel activity.
  • These conductances shape the current-voltage dynamical relationships determining neuronal spiking.
  • The approach is demonstrated for modulation, compensation, and robustness studies.

Conclusions:

  • Dynamic input conductances offer a powerful framework for analyzing neuronal signaling.
  • The proposed methods facilitate experimental and computational investigations into neuronal function.
  • This approach enhances understanding of neuronal robustness and homeostasis.