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

Action Potential: Phases of Stimulation01:28

Action Potential: Phases of Stimulation

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...
Postsynaptic Potential (PSP)01:32

Postsynaptic Potential (PSP)

Postsynaptic potential (PSP) refers to a change in the electrical potential of a neuron when neurotransmitters released by presynaptic neurons bind to postsynaptic receptors. This potential can either be excitatory, leading to depolarization and ultimately action potential generation, or inhibitory, leading to hyperpolarization and suppression of the postsynaptic neuron.
There are two types of receptors: ionotropic and metabotropic.
The ionotropic receptor is the membrane protein that has an...

You might also read

Related Articles

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

Sort by
Same author

Three-population connectivity scheme for inhibitory control from the locus coeruleus governing the development of power law wake bouts through early infancy.

Mathematical biosciences·2026
Same author

Bifunctional enzyme action as a source of robustness in biochemical reaction networks: a novel hypergraph approach.

Journal of the Royal Society, Interface·2026
Same author

Bifunctional enzyme provides absolute concentration robustness in multisite covalent modification networks.

Journal of mathematical biology·2024
Same author

Development of the sleep-wake switch in rats during the P2-P21 early infancy period.

Frontiers in network physiology·2024
Same author

Experimental and theoretical probe on mechano- and chemosensory integration in the insect antennal lobe.

Frontiers in physiology·2022
Same author

Foundations of static and dynamic absolute concentration robustness.

Journal of mathematical biology·2022

Related Experiment Video

Updated: May 13, 2026

The Power of Interstimulus Interval for the Assessment of Temporal Processing in Rodents
10:27

The Power of Interstimulus Interval for the Assessment of Temporal Processing in Rodents

Published on: April 19, 2019

Encoding with synchrony: phase-delayed inhibition allows for reliable and specific stimulus detection.

Badal Joshi1, Mainak Patel

  • 1School of Mathematics, University of Minnesota, 127 Vincent Hall, 206 Church St. SE, Minneapolis, MN 55455, USA.

Journal of Theoretical Biology
|March 26, 2013
PubMed
Summary

Phase-delayed inhibition, unlike high spike thresholds, allows neural decoders to reliably and specifically interpret stimuli encoded through neuronal synchrony, even with noisy inputs.

More Related Videos

Automated Multimodal Stimulation and Simultaneous Neuronal Recording from Multiple Small Organisms
08:28

Automated Multimodal Stimulation and Simultaneous Neuronal Recording from Multiple Small Organisms

Published on: March 3, 2023

DetectSyn: A Rapid, Unbiased Fluorescent Method to Detect Changes in Synapse Density
09:10

DetectSyn: A Rapid, Unbiased Fluorescent Method to Detect Changes in Synapse Density

Published on: July 22, 2022

Related Experiment Videos

Last Updated: May 13, 2026

The Power of Interstimulus Interval for the Assessment of Temporal Processing in Rodents
10:27

The Power of Interstimulus Interval for the Assessment of Temporal Processing in Rodents

Published on: April 19, 2019

Automated Multimodal Stimulation and Simultaneous Neuronal Recording from Multiple Small Organisms
08:28

Automated Multimodal Stimulation and Simultaneous Neuronal Recording from Multiple Small Organisms

Published on: March 3, 2023

DetectSyn: A Rapid, Unbiased Fluorescent Method to Detect Changes in Synapse Density
09:10

DetectSyn: A Rapid, Unbiased Fluorescent Method to Detect Changes in Synapse Density

Published on: July 22, 2022

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Systems Neuroscience

Background:

  • Synchronized neuronal oscillations are prevalent in the brain, suggesting a key role in information processing.
  • Neuronal synchrony can be decoded by mechanisms like high spike thresholds or phase-delayed inhibition.
  • These decoding mechanisms differ in their reliance on absolute versus relative synchrony.

Purpose of the Study:

  • To investigate the effectiveness of phase-delayed inhibition versus high spike thresholds in decoding noisy neuronal synchrony.
  • To determine which mechanism enables more reliable and specific stimulus representation.

Main Methods:

  • Simulated noisy neuronal encoders transmitting stimuli via synchrony.
  • Implemented two decoder types: high spike threshold (absolute synchrony) and phase-delayed inhibition (relative synchrony).
  • Compared decoder reliability and specificity in response to stimuli.

Main Results:

  • Phase-delayed inhibition demonstrated reliable and specific stimulus detection.
  • High spike threshold decoders failed to achieve reliable or specific stimulus detection.
  • Noisy encoders encoding stimuli through synchrony were effectively decoded by phase-delayed inhibition.

Conclusions:

  • Phase-delayed inhibition is a superior mechanism for decoding stimuli encoded by neuronal synchrony in noisy systems.
  • This finding highlights the importance of relative synchrony detection for robust neural computation.
  • The study provides insights into how the brain may effectively process information despite neural noise.