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

Oscillations In An LC Circuit01:30

Oscillations In An LC Circuit

3.3K
An idealized LC circuit of zero resistance can oscillate without any source of emf by shifting the energy stored in the circuit between the electric and magnetic fields. In such an LC circuit, if the capacitor contains a charge q before the switch is closed, then all the energy of the circuit is initially stored in the electric field of the capacitor. This energy is given by
3.3K
¹H NMR Signal Multiplicity: Splitting Patterns01:13

¹H NMR Signal Multiplicity: Splitting Patterns

7.2K
When protons A and X are coupled, their nuclear spin energy levels are slightly modified. This is because the energy required to excite proton A to a spin state parallel to proton X is slightly different from the energy required for it to become anti-parallel to spin X. Consequently, there are two possible excitation frequencies for A (A1 and A2), depending on the spin state of X, and vice versa. The mutual nature of coupling implies that the difference between frequencies A1 and A2, indicated...
7.2K
Forced Oscillations01:06

Forced Oscillations

8.1K
When an oscillator is forced with a periodic driving force, the motion may seem chaotic. The motions of such oscillators are known as transients. After the transients die out, the oscillator reaches a steady state, where the motion is periodic, and the displacement is determined.
8.1K
¹H NMR: Long-Range Coupling01:27

¹H NMR: Long-Range Coupling

2.8K
The coupling interactions of nuclei across four or more bonds are usually weak, with J values less than 1 Hz. While these are usually not observed in spectra, the presence of multiple bonds along the coupling pathway can result in observable long-range coupling.
In alkenes, spin information is communicated via σ–π overlap, as seen in allylic (four-bond) and homoallylic (five-bond) couplings. These coupling interactions are stronger when the σ bond is parallel to the alkene...
2.8K
Linear time-invariant Systems01:23

Linear time-invariant Systems

1.0K
A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
1.0K
Oscillations about an Equilibrium Position01:04

Oscillations about an Equilibrium Position

7.1K
Stability is an important concept in oscillation. If an equilibrium point is stable, a slight disturbance of an object that is initially at the stable equilibrium point will cause the object to oscillate around that point. For an unstable equilibrium point, if the object is disturbed slightly, it will not return to the equilibrium point. There are three conditions for equilibrium points—stable, unstable, and half-stable. A half-stable equilibrium point is also unstable, but is named so...
7.1K

You might also read

Related Articles

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

Sort by
Same author

Y-Polyp: research on devices for detecting colorectal polyps with limited samples.

BMC medical imaging·2026
Same author

Resource diversity and supply drive colonization resistance.

PLoS computational biology·2025
Same author

Single-cell sequencing reveals that AK5 inhibits apoptosis in AD oligodendrocytes by regulating the AMPK signaling pathway.

Molecular biology reports·2025
Same author

Improvement of the accuracy in measuring cryogenic hot spot mix by multi-channel Ross filter pairs through a two-temperature model of hot spot electron temperature.

The Review of scientific instruments·2025
Same author

CRH-YOLO for precise and efficient detection of gastrointestinal polyps.

Scientific reports·2024
Same author

Single-cell and bulk transcriptomic datasets enable the development of prognostic models based on dynamic changes in the tumor immune microenvironment in patients with hepatocellular carcinoma and portal vein tumor thrombus.

Frontiers in immunology·2024

Related Experiment Video

Updated: Mar 6, 2026

Optogenetic Entrainment of Hippocampal Theta Oscillations in Behaving Mice
07:33

Optogenetic Entrainment of Hippocampal Theta Oscillations in Behaving Mice

Published on: June 29, 2018

12.4K

Cluster synchronization in networks of identical oscillators with α-function pulse coupling.

Bolun Chen1, Jan R Engelbrecht1, Renato Mirollo2

  • 1Department of Physics, Boston College, Chestnut Hill, Massachusetts 02467, USA.

Physical Review. E
|March 17, 2017
PubMed
Summary

This study reveals novel attracting states in coupled neuron networks, including clustered and splay states, beyond simple synchronization. These findings enhance our understanding of neural dynamics and model classification.

More Related Videos

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

2.0K
Generation of Local CA1 γ Oscillations by Tetanic Stimulation
08:02

Generation of Local CA1 γ Oscillations by Tetanic Stimulation

Published on: August 14, 2015

9.6K

Related Experiment Videos

Last Updated: Mar 6, 2026

Optogenetic Entrainment of Hippocampal Theta Oscillations in Behaving Mice
07:33

Optogenetic Entrainment of Hippocampal Theta Oscillations in Behaving Mice

Published on: June 29, 2018

12.4K
Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

2.0K
Generation of Local CA1 γ Oscillations by Tetanic Stimulation
08:02

Generation of Local CA1 γ Oscillations by Tetanic Stimulation

Published on: August 14, 2015

9.6K

Area of Science:

  • Computational Neuroscience
  • Complex Systems Dynamics
  • Mathematical Biology

Background:

  • Neural networks exhibit complex dynamics, with focus on synchronized and asynchronous states.
  • Coupling parameters (K) dictate network behavior, distinguishing excitation from inhibition.
  • Previous studies concentrated on fully synchronized or asynchronous states.

Purpose of the Study:

  • To uncover and characterize a broader range of attracting states in networks of identical leaky integrate-and-fire neurons.
  • To investigate the stability and bifurcations of these newly identified partially synchronized states.
  • To develop a framework for distinguishing neuron models based on their attractor sets.

Main Methods:

  • Utilized a dimensional reduction strategy exploiting K=0 dynamics.
  • Analyzed a simplified continuous flow on a codimension 3 subspace.
  • Employed high-precision numerical simulations for N=2-4 neurons.
  • Investigated bifurcations and stability of fixed points and limit cycles.

Main Results:

  • Identified a rich set of attractors including (N-1,1) fixed states and equal-sized splay states.
  • Discovered limit cycles clarifying previously observed quasiperiodic behavior.
  • Demonstrated that the sign of K determines the direction of the simplified flow.
  • Characterized the complete bifurcation sequence and stability for small N.

Conclusions:

  • The identified attracting states offer a new perspective on neural network dynamics.
  • Partially synchronized states, beyond (N-1,1), are possible in integrate-and-fire networks but not Kuramoto models.
  • The framework provides a method for classifying different neuron models.
  • Generalization to non-identical neurons shows attracting fixed points where neurons need not fire simultaneously.