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

Neural Circuits01:25

Neural Circuits

3.2K
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...
3.2K
State Space Representation01:27

State Space Representation

677
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
677
Atomic Nuclei: Nuclear Relaxation Processes01:23

Atomic Nuclei: Nuclear Relaxation Processes

1.4K
In the absence of an external magnetic field, nuclear spin states are degenerate and randomly oriented. When a magnetic field is applied, the spins begin to precess and orient themselves along (lower energy) or against (higher energy) the direction of the field. At equilibrium, a slight excess population of spins exists in the lower energy state. Because the direction of the magnetic field is fixed as the z-axis,  the precessing magnetic moments are randomly oriented around the z-axis.
1.4K
Propagation of Action Potentials01:23

Propagation of Action Potentials

12.7K
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...
12.7K
Action Potential01:14

Action Potential

12.0K
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...
12.0K
Instinctive Drift01:05

Instinctive Drift

1.1K
Instinctive drift refers to the tendency of animals to revert to their innate behaviors despite repeated reinforcement. Breland and Breland demonstrated this concept in an experiment with a raccoon. The raccoon was trained to pick up two coins and place them in a container in exchange for food. Initially, the raccoon learned to associate the coins with food, making them a conditioned stimulus or a substitute for food. However, over time, the raccoon became less willing to put the coins into the...
1.1K

You might also read

Related Articles

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

Sort by
Same author

Utilization and Metrics Associated with Paramedic Treat and Discharge Medical Directives for Paramedic Services and Emergency Departments: A Retrospective Cohort Study.

Prehospital emergency care·2026
Same author

When Is the Right Time? A Qualitative Study of Timing of Specialty Palliative Care in Patients With Brain Tumors.

JCO oncology practice·2026
Same author

Chemoselective Reduction of Nitroarenes to Anilines Using a Nickel Foam.

Journal of the American Chemical Society·2026
Same author

Inhibitory-stabilization is sufficient for history-dependent computation in a randomly connected attractor network.

Journal of computational neuroscience·2026
Same author

Too aroused to be attractive.

Neuron·2026
Same author

A qualitative study with patients, care-partners, clinicians, and bioethicists to identify ethical considerations of artificial intelligence tools in palliative care.

Palliative medicine·2026

Related Experiment Video

Updated: Mar 19, 2026

Induction of an Isoelectric Brain State to Investigate the Impact of Endogenous Synaptic Activity on Neuronal Excitability In Vivo
10:19

Induction of an Isoelectric Brain State to Investigate the Impact of Endogenous Synaptic Activity on Neuronal Excitability In Vivo

Published on: March 31, 2016

8.7K

Itinerancy between attractor states in neural systems.

Paul Miller1

  • 1Volen National Center for Complex Systems, Brandeis University, Waltham, MA 02454-9110, USA.

Current Opinion in Neurobiology
|June 20, 2016
PubMed
Summary
This summary is machine-generated.

Neural circuits form discrete attractor states. Analyzing state transitions without averaging data, using methods like hidden Markov modeling, reveals computational benefits for stimulus processing.

More Related Videos

Ex Utero Electroporation and Organotypic Slice Cultures of Embryonic Mouse Brains for Live-Imaging of Migrating GABAergic Interneurons
09:50

Ex Utero Electroporation and Organotypic Slice Cultures of Embryonic Mouse Brains for Live-Imaging of Migrating GABAergic Interneurons

Published on: April 20, 2018

10.6K
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

1.8K

Related Experiment Videos

Last Updated: Mar 19, 2026

Induction of an Isoelectric Brain State to Investigate the Impact of Endogenous Synaptic Activity on Neuronal Excitability In Vivo
10:19

Induction of an Isoelectric Brain State to Investigate the Impact of Endogenous Synaptic Activity on Neuronal Excitability In Vivo

Published on: March 31, 2016

8.7K
Ex Utero Electroporation and Organotypic Slice Cultures of Embryonic Mouse Brains for Live-Imaging of Migrating GABAergic Interneurons
09:50

Ex Utero Electroporation and Organotypic Slice Cultures of Embryonic Mouse Brains for Live-Imaging of Migrating GABAergic Interneurons

Published on: April 20, 2018

10.6K
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

1.8K

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Cognitive Science

Background:

  • Neural circuits develop discrete attractor states through learning.
  • External stimuli can influence or shift neural activity between these states.

Purpose of the Study:

  • To review the current understanding of attractor state transitions in neural circuits.
  • To highlight the computational advantages of processing stimuli via state transitions.
  • To address perceived limitations in the field.

Main Methods:

  • Analysis of neural, perceptual, and simulated data.
  • Utilizing methods that avoid trial-averaging, such as hidden Markov modeling.
  • Reviewing existing literature and modeling efforts.

Main Results:

  • Evidence suggests discrete attractor states are fundamental to neural processing.
  • Hidden Markov modeling effectively identifies state transitions in various neural circuits and tasks.
  • Stimulus processing through attractor state transitions offers computational benefits.

Conclusions:

  • Attractor state transitions are a key mechanism in neural computation.
  • Non-trial-averaged analyses are crucial for understanding dynamic neural processes.
  • The field is advancing, with methods addressing previous limitations.