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Related Concept Videos

Neural Circuits01:25

Neural Circuits

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...
Neuronal Communication01:28

Neuronal Communication

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...
The Synapse02:47

The Synapse

Neurons communicate with one another by passing on their electrical signals to other neurons. A synapse is the location where two neurons meet to exchange signals. At the synapse, the neuron that sends the signal is called the presynaptic cell, while the neuron that receives the message is called the postsynaptic cell. Note that most neurons can be both presynaptic and postsynaptic, as they both transmit and receive information.
Synaptic Signaling01:09

Synaptic Signaling

Neurons communicate at synapses, or junctions, to excite or inhibit the activity of other neurons or target cells, such as muscles. Synapses may be chemical or electrical.
Most synapses are chemical, meaning an electrical impulse or action potential spurs the release of chemical messengers called neurotransmitters. The neuron sending the signal is called the presynaptic neuron, and the neuron receiving the signal is the postsynaptic neuron.
The presynaptic neuron fires an action potential that...
Synaptic Signaling01:12

Synaptic Signaling

Neurons communicate at synapses, or junctions, to excite or inhibit the activity of other neurons or target cells, such as muscles. Synapses may be chemical or electrical.
Neurons: The Axon01:21

Neurons: The Axon

Axons are long, cytoplasmic processes of nerve cells capable of propagating electrical impulses known as action potentials. The cytoplasm or axoplasm of an axon contains neurofibrils, neurotubules, small vesicles, lysosomes, mitochondria, and various enzymes, all encased within the axolemma, the plasma membrane of the axon.
The axon attaches to the cell body at a cone-shaped elevation called the axon hillock. The initial part of the axon, closest to the hillock, is known as the initial segment.

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Related Experiment Video

Updated: Jul 16, 2026

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

Synchronization in a network of model neurons.

Maruthi Pradeep Kanth Jampa1, Abhijeet R Sonawane, Prashant M Gade

  • 1The Institute of Mathematical Sciences, CIT Campus, Taramani, Chennai 600 113, India.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|March 16, 2007
PubMed
Summary

We investigated neuronal network dynamics, finding that increased random connections stabilize chaotic activity. Spatial synchronization emerges with random links, enhancing network stability even with noise.

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Area of Science:

  • Computational Neuroscience
  • Complex Systems Dynamics
  • Network Science

Background:

  • Neuronal networks exhibit complex spatiotemporal dynamics.
  • Understanding the impact of coupling strength and randomness on network stability is crucial.
  • Chaotic maps are used to model neuronal activity.

Purpose of the Study:

  • To investigate the spatiotemporal dynamics of coupled chaotic maps modeling neuronal activity.
  • To analyze the effects of coupling strength (epsilon) and coupling randomness (p) on network stability and synchronization.
  • To examine the robustness of observed phenomena in the presence of noise and different neuronal dynamics.

Main Methods:

  • Simulations of coupled chaotic maps with varying coupling strength and randomness.
  • Analysis of stability of fixed points and transition to chaotic regimes.
  • Quantification of spatial synchronization and its dependence on the fraction of random links.
  • Testing robustness against parametric noise and non-identical neuronal maps.

Main Results:

  • A critical coupling strength (epsilon_fixed) stabilizes the network's fixed point, invariant to coupling randomness (p).
  • Below epsilon_fixed, networks exhibit chaos with regular coupling (p=0) but spatial synchronization with random coupling (p>0).
  • Synchronization range increases exponentially with p and occurs at a finite p, robust to noise and applicable to spiking/bursting neurons.

Conclusions:

  • Randomness in neuronal connections can induce stable spatiotemporal patterns and synchronization.
  • The degree of randomness is a key factor in controlling network dynamics, shifting from chaos to synchronization.
  • Findings offer insights into how network structure influences neuronal information processing and stability.