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

3.2K
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....
3.2K
Neural Circuits01:25

Neural Circuits

3.0K
Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
3.0K
Neuronal Communication01:28

Neuronal Communication

5.5K
Neurons, the fundamental units of the brain and nervous system, communicate through complex electrochemical signals that underpin all cognitive and bodily functions. This communication is primarily facilitated by a process involving the generation and propagation of an action potential along the axon of the neuron. When the internal electrical charge of a neuron surpasses a certain threshold, an action potential is triggered. This rapid change in voltage travels swiftly along the axon to the...
5.5K
Propagation of Action Potentials01:23

Propagation of Action Potentials

15.4K
The propagation of an action potential refers to the process by which a nerve impulse, or "action potential," travels along a neuron.
Neurons (nerve cells) have a resting membrane potential, with a slightly negative charge inside compared to outside. This is maintained by ion channels, such as sodium (Na+) and potassium (K+) channels, which control the flow of ions. When a stimulus, like a touch or a signal from another neuron, triggers the neuron, sodium channels open, allowing sodium ions to...
15.4K
Ligand-Gated Ion Channel Receptor: Gating Mechanism01:30

Ligand-Gated Ion Channel Receptor: Gating Mechanism

4.6K
Ligand-gated ion channels are transmembrane proteins that play a vital role in intercellular communication and functions of the nervous system. They allow the influx of ions across the membrane once the neurotransmitter binds, allowing the subsequent transmission of electrical excitation across the neurons. Other ligand-gated ion channels, like the γ-aminobutyric acid (GABA) receptor, permit anions like chloride into the cells on the binding of the GABA molecule. Their entry into the cell...
4.6K
Electrical Synapses01:28

Electrical Synapses

10.1K
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...
10.1K

You might also read

Related Articles

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

Sort by
Same author

Advanced deep architecture pruning using single-filter performance.

Physical review. E·2025
Same author

Towards a universal mechanism for successful deep learning.

Scientific reports·2024
Same author

Hebbian dreaming for small datasets.

Neural networks : the official journal of the International Neural Network Society·2024
Same author

Enhancing the accuracies by performing pooling decisions adjacent to the output layer.

Scientific reports·2023
Same author

Efficient shallow learning as an alternative to deep learning.

Scientific reports·2023
Same author

Learning on tree architectures outperforms a convolutional feedforward network.

Scientific reports·2023

Related Experiment Video

Updated: Apr 30, 2026

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments
05:19

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

Published on: November 12, 2019

6.1K

A computational paradigm for dynamic logic-gates in neuronal activity.

Amir Goldental1, Shoshana Guberman2, Roni Vardi3

  • 1Department of Physics, Bar-Ilan University Ramat-Gan, Israel.

Frontiers in Computational Neuroscience
|May 9, 2014
PubMed
Summary

Neurons function as dynamic logic-gates (DLGs) with time-dependent truth tables, unlike traditional computer logic. This new paradigm, based on increasing neuronal response latencies, offers insights into brain computation.

Keywords:
Boolean algebrain vitro modular networkslogic-gatesneuronal circuitneuronal response latency

More Related Videos

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

11.1K
Dynamic Clamp Methods to Investigate Impaired Neuronal Excitability Associated with Autism
08:44

Dynamic Clamp Methods to Investigate Impaired Neuronal Excitability Associated with Autism

Published on: October 17, 2025

853

Related Experiment Videos

Last Updated: Apr 30, 2026

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments
05:19

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

Published on: November 12, 2019

6.1K
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

11.1K
Dynamic Clamp Methods to Investigate Impaired Neuronal Excitability Associated with Autism
08:44

Dynamic Clamp Methods to Investigate Impaired Neuronal Excitability Associated with Autism

Published on: October 17, 2025

853

Area of Science:

  • Computational Neuroscience
  • Neuroscience
  • Artificial Intelligence

Background:

  • The McCulloch-Pitts model proposed brain logic-gates similar to computer logic, but failed to capture the complex dynamics of biological neurons.
  • Traditional Boolean algebra is insufficient for modeling the brain's rich neuronal dynamics.

Purpose of the Study:

  • To introduce and experimentally validate a new computational paradigm: dynamic logic-gates (DLGs).
  • To demonstrate that DLG truth tables are time-dependent, influenced by activity history and input stimulation frequencies.
  • To explore the implications of this paradigm for understanding brain functionality.

Main Methods:

  • In-vitro experiments on cortical cell networks subjected to conditioned stimulations.
  • Simulations and theoretical analysis using models of identical neurons with fixed increases in response latency per spike.
  • Investigating the impact of increasing neuronal response latencies on network delays.

Main Results:

  • Experimental evidence confirms that neuronal response latencies increase during ongoing stimulation, causing network delays to stretch non-uniformly.
  • This mechanism underlies the time-dependent nature of dynamic logic-gates (DLGs).
  • Simulations and theoretical arguments support the experimental findings.

Conclusions:

  • The dynamic logic-gate (DLG) paradigm, accounting for time-dependent truth tables, offers a more biologically plausible model of brain computation.
  • Understanding DLGs requires new mathematical frameworks beyond traditional Boolean algebra.
  • This research advances the computational understanding of brain functionalities.