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Related Concept Videos

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...
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...
Propagation of Action Potentials01:23

Propagation of Action Potentials

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

The Role of Ion Channels in Neuronal Computation

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.
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...

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Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

Efficiently passing messages in distributed spiking neural network simulation.

Corey M Thibeault1, Kirill Minkovich, Michael J O'Brien

  • 1Center for Neural and Emergent Systems, Information and System Sciences Laboratory, HRL Laboratories LLC. Malibu, CA, USA ; Department of Electrical and Biomedical Engineering, The University of Nevada Reno, NV, USA ; Department of Computer Science and Engineering, The University of Nevada Reno, NV, USA.

Frontiers in Computational Neuroscience
|June 18, 2013
PubMed
Summary
This summary is machine-generated.

Efficiently simulating large neural networks requires optimized spike message passing. This study benchmarks Message Passing Interface (MPI) mechanisms, including a novel hybrid method, for high-performance computing clusters.

Keywords:
distributed computingdistributed message passingneural networksparallel simulationparallel spiking neuron simulation

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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

Area of Science:

  • Computational Neuroscience
  • High-Performance Computing

Background:

  • Simulating large-scale neural networks demands efficient communication.
  • Inter-node communication is a performance bottleneck in high-performance computing (HPC) clusters.
  • Optimizing spike message passing is crucial for accurate and fast neural simulations.

Purpose of the Study:

  • To evaluate Message Passing Interface (MPI) mechanisms for spike message passing.
  • To assess the performance of MVAPICH, an MPI implementation optimized for InfiniBand hardware.
  • To introduce and benchmark a novel hybrid method for spike exchange in neural simulations.

Main Methods:

  • Benchmarking various Message Passing Interface (MPI) mechanisms for spike communication.
  • Utilizing the MVAPICH implementation on high-performance clusters with InfiniBand.
  • Implementing and evaluating a new hybrid approach for spike exchange.

Main Results:

  • Performance characteristics of different MPI communication patterns for spike data were analyzed.
  • MVAPICH demonstrated specific advantages for spike message passing on InfiniBand hardware.
  • The novel hybrid method showed competitive or improved performance compared to standard MPI approaches.

Conclusions:

  • MPI mechanisms offer viable options for optimizing spike message passing in large-scale neural simulations.
  • MVAPICH and the developed hybrid method provide valuable tools for enhancing simulation performance.
  • Further research into optimized communication strategies is essential for advancing computational neuroscience.