Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

The Role of Ion Channels in Neuronal Computation

The Role of Ion Channels in Neuronal Computation

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....

Integration of Synaptic Events

Integration of Synaptic Events

Synaptic integration mainly includes the summation of graded potentials. Graded potentials, regardless of their type, cause subtle alterations in membrane voltage, resulting in either depolarization or hyperpolarization. These incremental changes, when combined or summed, can propel the neuron toward its threshold. Consider, for example, a membrane experiencing a +15 mV shift, causing it to depolarize from -70 mV to -55 mV. In this scenario, graded potentials govern the membrane's ability to...

Electrical Synapses

Electrical Synapses

Electrical synapses found in all nervous systems play important and unique roles. In these synapses, the presynaptic and postsynaptic membranes are very close together (3.5 nm) and are actually physically connected by channel proteins forming gap junctions.
Gap junctions allow the current to pass directly from one cell to the next. In contrast, in the chemical synapse, the neurotransmitters carry the information through the synaptic cleft from one neuron to the next. They consist of two...

Electrochemical Gradient and Channel Proteins: An Overview

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...

Synaptic Signaling

Synaptic Signaling

Neurons communicate at synapses, or junctions, to excite or inhibit the activity of other neurons or target cells, such as muscles. Synapses may be chemical or electrical.
Most synapses are chemical, meaning an electrical impulse or action potential spurs the release of chemical messengers called neurotransmitters. The neuron sending the signal is called the presynaptic neuron, and the neuron receiving the signal is the postsynaptic neuron.
The presynaptic neuron fires an action potential that...

Synaptic Signaling

Synaptic Signaling

Neurons communicate at synapses, or junctions, to excite or inhibit the activity of other neurons or target cells, such as muscles. Synapses may be chemical or electrical.

You might also read

Related Articles

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

Sort by

Same author

State-switching navigation strategies in <i>Caenorhabditis elegans</i> are beneficial for chemotaxis.

Proceedings of the National Academy of Sciences of the United States of America·2026

Same author

Compact deep neural network models of the visual cortex.

Nature·2026

Same author

Cone bipolar cell synapses generate transient versus sustained signals in parallel ON pathways of the mouse retina.

eLife·2025

Same author

Identifying the factors governing internal state switches during nonstationary sensory decision-making.

Nature communications·2025

Same author

Fast Optimization of Robust Transcriptomics Embeddings using Probabilistic Inference Autoencoder Networks for multi-Omics.

bioRxiv : the preprint server for biology·2025

Same author

Improved inference of latent neural states from calcium imaging data.

bioRxiv : the preprint server for biology·2025

Same journal

SqueakPose Studio, an end-to-end platform for pose estimation and real-time edge-AI deployment.

eLife·2026

Same journal

Mechanistic insights into transcriptional regulation of ARHGAP36 expression identify a factor predictive of neuroblastoma survival.

eLife·2026

Same journal

Activity-dependent CO<sub>2</sub> production in the axon triggers opening of Connexin32 in the Schwann cell paranode.

eLife·2026

Same journal

Lipid packing contributes to the confinement of caveolae to the plasma membrane.

eLife·2026

Same journal

A coma pattern-based autofocusing method resolves bacterial cold shock response at single-cell level.

eLife·2026

Same journal

Non-canonical amino acid incorporation enables minimally disruptive labeling of stress granule and TDP-43 proteinopathy.

eLife·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jan 1, 2026

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond

Published on: June 24, 2015

Inferring synaptic inputs from spikes with a conductance-based neural encoding model.

Kenneth W Latimer¹, Fred Rieke¹, Jonathan W Pillow²

¹Department of Physiology and Biophysics, University of Washington, Seattle, United States.

|December 19, 2019

Summary

This summary is machine-generated.

We introduce a conductance-based encoding model (CBEM) that links stimuli to synaptic conductances, predicting neural activity. This model offers a biophysical interpretation for statistical models like the Poisson generalized linear model (GLM).

Keywords:

neuroscience retinal circuitry rhesus macaque statistical modeling synaptic condutances

More Related Videos

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Published on: March 25, 2014

Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution

Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution

Published on: September 5, 2012

Related Experiment Videos

Last Updated: Jan 1, 2026

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond

Published on: June 24, 2015

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Published on: March 25, 2014

Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution

Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution

Published on: September 5, 2012

Area of Science:

Computational neuroscience
Systems neuroscience
Neural encoding

Background:

Statistical models of neural responses often overlook biophysical mechanisms.
Understanding the link between stimuli and neural firing requires integrating statistical and biophysical approaches.

Purpose of the Study:

To introduce the conductance-based encoding model (CBEM) for neural responses.
To demonstrate CBEM's ability to predict synaptic currents from spike data.
To provide a biophysical interpretation of statistical models.

Main Methods:

Developed the conductance-based encoding model (CBEM).
Fit CBEM to extracellular spike train data.
Validated predictions using intracellular recordings from macaque retinal ganglion cells.

Main Results:

CBEM successfully maps stimuli to synaptic conductances.
CBEM predictions of synaptic currents were validated by intracellular recordings.
A quasi-biophysical interpretation of the Poisson generalized linear model (GLM) was established.

Conclusions:

CBEM provides a novel link between statistical and biophysical models of neural encoding.
The model sheds light on biophysical variables influencing spiking in the early visual pathway.
This approach advances our understanding of neural information processing.