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Related Concept Videos

Neuronal Communication01:28

Neuronal Communication

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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...
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Neurons as Communicators of the Brain01:22

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Neurons, the fundamental units of the brain and nervous system, function as the primary transmitters of information throughout the body. Their ability to communicate through electrical and chemical signals is vital for every bodily function, from regulating the heartbeat to processing complex thoughts. Each neuron has three main components: the cell body (soma), dendrites, and an axon, each specialized to facilitate swift and efficient neural communication.
Cell Body
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Synaptic Signaling01:09

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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.
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Synaptic Signaling01:12

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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.
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Communication01:03

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Communication between two animals occurs when one animal transmits an information signal that causes a change in the animal that receives the information. Organisms communicate with one another in a host of different ways. Signals can be auditory, chemical, visual, tactile, or a combination of these. Communication is a critical behavioral adaptation that promotes survival, growth, and reproduction.
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The Synapse02:47

The Synapse

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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.
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Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments
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Evolution-Communication Spiking Neural P Systems.

Tingfang Wu1,2, Qiang Lyu1,2, Linqiang Pan3,4

  • 1School of Computer Science and Technology, Soochow University, Suzhou 215006, P. R. China.

International Journal of Neural Systems
|November 9, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces evolution-communication spiking neural P systems (ECSNP systems), a novel computational model. ECSNP systems demonstrate Turing universality, but neuron spike capacity critically impacts their computational power.

Keywords:
Membrane computingcomputational powerneural computationspiking neural P systemspiking neural network

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Area of Science:

  • Theoretical Computer Science
  • Computational Neuroscience
  • Biologically Inspired Computing

Background:

  • Spiking neural P systems (SNP systems) model neuronal computation using spikes.
  • Existing models integrate neuron behavior and spike distribution within spiking rules.

Purpose of the Study:

  • To propose a novel variant of SNP systems, termed evolution-communication SNP (ECSNP) systems.
  • To separately model neuron integrate-and-fire behavior and spike distribution.
  • To analyze the computational power of ECSNP systems.

Main Methods:

  • Introducing spike-evolution rules for neuron integrate-and-fire behavior.
  • Implementing spike-communication rules for spike distribution.
  • Examining the computational power of standard and restricted ECSNP systems.

Main Results:

  • ECSNP systems are proven to be Turing universal as number-generating devices.
  • Restricted ECSNP systems, with limited neuron spike capacity, characterize semilinear number sets.
  • Neuron information storage capacity significantly influences ECSNP system computational power.

Conclusions:

  • The proposed ECSNP systems offer a refined model for spiking neural computation.
  • The study highlights the critical role of neuron spike capacity in determining computational capabilities.
  • ECSNP systems provide a new framework for exploring biologically plausible computation.