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Related Concept Videos

Action Potentials01:41

Action Potentials

Overview
Action Potential01:14

Action Potential

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...
Action Potential01:14

Action Potential

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...
Electrochemical Gradient and Channel Proteins: An Overview01:21

Electrochemical Gradient and Channel Proteins: An Overview

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 the...
Resting Potential Decay01:15

Resting Potential Decay

The resting membrane potential of a neuron (-70mV) is sustained due to the selective ion permeability of the membrane. At the resting potential, the membrane is slightly permeable to ions like sodium (Na+) and chloride (Cl−) and highly permeable to potassium ions (K+). Differences in the ions' concentration inside the cell compared to the outside are maintained by membrane transport proteins like channels and pumps.
At rest, the K+ is the main ion that moves across the membrane through...
Resting Potential Decay01:15

Resting Potential Decay

The resting membrane potential of a neuron (-70mV) is sustained due to the selective ion permeability of the membrane. At the resting potential, the membrane is slightly permeable to ions like sodium (Na+) and chloride (Cl−) and highly permeable to potassium ions (K+). Differences in the ions' concentration inside the cell compared to the outside are maintained by membrane transport proteins like channels and pumps.
At rest, the K+ is the main ion that moves across the membrane through...

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Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
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Characterizing neuronal activity by describing the membrane potential as a stochastic process.

Martin Pospischil1, Zuzanna Piwkowska, Thierry Bal

  • 1Integrative and Computational Neuroscience Unit, UPR, CNRS, Gif-sur-Yvette, France.

Journal of Physiology, Paris
|June 9, 2009
PubMed
Summary

Cortical neurons exhibit stochastic activity, modeled as stochastic processes. New methods like the VmT method analyze membrane potential (V(m)) single traces to estimate synaptic conductances, advancing neuronal activity analysis.

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Area of Science:

  • Computational Neuroscience
  • Systems Neuroscience
  • Biophysics

Background:

  • Cortical neurons display irregular firing patterns and dense connectivity, resembling stochastic processes.
  • Neuronal membrane potential (V(m)) can be characterized as colored noise and analyzed using stochastic process theory.
  • Understanding neuronal activity requires extracting statistical signatures from V(m) dynamics.

Purpose of the Study:

  • To review and compare methods for characterizing neuronal activity using stochastic processes.
  • To introduce and evaluate the VmT method for analyzing single V(m) traces.
  • To assess the utility of VmD, STA, and VmT methods in estimating synaptic conductances.

Main Methods:

  • Review of the VmD method, fitting V(m) distributions to stochastic process models.
  • Discussion of single-trial analysis techniques: power spectral analysis and spike-triggered average (STA) method.
  • Introduction and application of the VmT method, a maximum-likelihood approach for single-trial V(m) analysis.

Main Results:

  • The VmD method requires multiple V(m) levels, limiting its use in single-trial analysis.
  • The STA method and power spectral analysis offer insights into single V(m) traces.
  • The VmT method successfully estimates mean excitatory/inhibitory conductances and variances from single V(m) traces.

Conclusions:

  • Stochastic process modeling provides a framework for understanding cortical neuron activity.
  • The VmT method offers a powerful, single-trial approach to estimating synaptic conductances.
  • These methods, validated in dynamic-clamp experiments, enhance the analysis of neuronal network function.