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

Integration of Synaptic Events01:28

Integration of Synaptic Events

1.4K
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...
1.4K
The Role of Ion Channels in Neuronal Computation01:19

The Role of Ion Channels in Neuronal Computation

3.1K
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....
3.1K
Graded Potential01:19

Graded Potential

3.5K
Graded potentials are localized fluctuations in the cell membrane's electrical charge, commonly found in the dendrites of neurons. The magnitude of these potential changes depends on the strength of the initiating stimulus. In a membrane at its resting potential, a graded potential signifies a voltage shift either above -70 mV or below -70 mV.
Graded potentials fall into two categories: depolarizing and hyperpolarizing. Depolarizing graded potentials typically occur when sodium (Na+) or...
3.5K

You might also read

Related Articles

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

Sort by
Same author

Optical linear systems framework for event sensing and computational neuromorphic imaging.

Frontiers in neuroscience·2026
Same author

Sequential analysis and its applications to neuromorphic engineering.

Frontiers in neuroscience·2026
Same author

Biomarkers.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025
Same author

Discrimination of ischemic versus hemorrhagic stroke type by presenting symptoms or signs: A systematic review and meta-analysis.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association·2025
Same author

Low-latency hierarchical routing of reconfigurable neuromorphic systems.

Frontiers in neuroscience·2025
Same author

Spiking neural networks on FPGA: A survey of methodologies and recent advancements.

Neural networks : the official journal of the International Neural Network Society·2025
Same journal

A Model-Free Reinforcement Learning Implementation of Decision Making Under Uncertainty by Sequential Sampling.

Neural computation·2026
Same journal

DROP: Distributional and Regular Optimism and Pessimism for Reinforcement Learning.

Neural computation·2026
Same journal

Hierarchical Active Inference Using Successor Representations.

Neural computation·2026
Same journal

W-Kernel and Its Principal Space for Frequentist Evaluation of Bayesian Estimators.

Neural computation·2026
Same journal

A Hidden Markov Model-Inspired Sequence Classification Method for Hyperdimensional Computing.

Neural computation·2026
Same journal

Sparse Graphical Modeling for Electrophysiological Phase-Based Connectivity Using Circular Statistics.

Neural computation·2026
See all related articles

Related Experiment Video

Updated: May 21, 2025

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond
08:08

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

Published on: June 24, 2015

11.4K

The Leaky Integrate-and-Fire Neuron Is a Change-Point Detector for Compound Poisson Processes.

Shivaram Mani1, Paul Hurley2, André van Schaik3

  • 1International Centre for Neuromorphic Systems, MARCS Institute, Western Sydney University, Sydney, Australia shivarammani@gmail.com.

Neural Computation
|March 20, 2025
PubMed
Summary
This summary is machine-generated.

Spiking neurons, like the leaky integrate-and-fire model, act as online change-point detectors. These neurons can rapidly identify subtle shifts in neural activity, challenging the view of neurons as merely noisy devices.

More Related Videos

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
07:34

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

Published on: March 25, 2014

9.8K
Studying the Integration of Adult-born Neurons
09:00

Studying the Integration of Adult-born Neurons

Published on: March 25, 2011

13.8K

Related Experiment Videos

Last Updated: May 21, 2025

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond
08:08

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

Published on: June 24, 2015

11.4K
A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
07:34

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

Published on: March 25, 2014

9.8K
Studying the Integration of Adult-born Neurons
09:00

Studying the Integration of Adult-born Neurons

Published on: March 25, 2011

13.8K

Area of Science:

  • Computational Neuroscience
  • Systems Neuroscience
  • Statistical Signal Processing

Background:

  • Animal nervous systems detect environmental changes via abrupt shifts in neural activity.
  • Change-point detection (CPD) algorithms are commonly used to analyze these shifts.
  • Few studies explore spiking neurons as inherent online CPD agents.

Purpose of the Study:

  • To demonstrate that a leaky integrate-and-fire (LIF) neuron implements an online CPD algorithm.
  • To analyze the performance of LIF neuron CPD across its parameter space.
  • To investigate if neural networks of LIF neurons can detect changes in spiking rates.

Main Methods:

  • Modeling a leaky integrate-and-fire (LIF) neuron as a CPD algorithm for compound Poisson processes.
  • Quantifying LIF neuron CPD performance across parameter variations.
  • Analyzing a feedforward network of LIF neurons for detecting input rate changes.

Main Results:

  • An LIF neuron was shown to implement an online CPD algorithm.
  • A feedforward network of LIF neurons detected a 5% change in input rates within 20 ms with rare false positives.
  • Key electrophysiological features of LIF neurons were statistically interpreted in the context of CPD.

Conclusions:

  • Spiking neurons, specifically LIF neurons, can function as sophisticated online statistical change-point detectors.
  • Neural networks of LIF neurons exhibit efficient and reliable detection of subtle input rate changes.
  • This suggests a re-evaluation of neurons not as noisy units but as implementers of optimal statistical algorithms.