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The propagation of an action potential refers to the process by which a nerve impulse, or "action potential," travels along a neuron.
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Postsynaptic potential (PSP) refers to a change in the electrical potential of a neuron when neurotransmitters released by presynaptic neurons bind to postsynaptic receptors. This potential can either be excitatory, leading to depolarization and ultimately action potential generation, or inhibitory, leading to hyperpolarization and suppression of the postsynaptic neuron.
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The action potential is a complex electrical event that occurs in excitable cells, such as neurons and muscle cells. It consists of several distinct phases, each with specific characteristics.
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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.
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Pulse Shape and Voltage-Dependent Synchronization in Spiking Neuron Networks.

Bastian Pietras1

  • 1Department of Information and Communication Technologies, Universitat Pompeu Fabra, 08018, Barcelona, Spain bastian.pietras@upf.edu.

Neural Computation
|July 19, 2024
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Summary
This summary is machine-generated.

Finite pulse width in spiking neural networks is crucial for collective behavior. Skewed pulse shapes, not just narrow ones, effectively synchronize neurons via voltage coupling, offering a new mechanism complementary to synaptic transmission.

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Area of Science:

  • Computational Neuroscience
  • Neural Dynamics
  • Complex Systems

Background:

  • Spiking neural networks (SNNs) model neural self-organization and collective behavior.
  • Current models often use idealized, infinitely narrow spikes, neglecting biological realism.
  • The impact of finite pulse width and shape on SNN dynamics remains largely unexplored and debated.

Purpose of the Study:

  • To comprehensively investigate pulse coupling in quadratic integrate-and-fire (QIF) and theta-neuron networks.
  • To explore the role of finite pulse width and shape in emergent network dynamics.
  • To elucidate a voltage-dependent spike synchronization mechanism.

Main Methods:

  • Utilized an exact low-dimensional description for globally coupled spiking neuron networks.
  • Modeled interactions using smooth pulse functions of arbitrary finite width and shape (symmetric/asymmetric).
  • Implemented finite-width pulses in QIF neurons to activate voltage-dependent synaptic conductances.

Main Results:

  • Instantaneous interactions lead to collective oscillations via mean voltage coupling.
  • Symmetric finite-width pulses show limited synchronization effectiveness.
  • Asymmetric pulses, skewed to the post-spike phase, readily induce collective oscillations.
  • Demonstrated a voltage-dependent synchronization mechanism facilitated by finite pulse widths.

Conclusions:

  • Finite pulse width is essential for biologically plausible neural network dynamics.
  • Pulse shape significantly influences synchronization and emergent collective behavior.
  • This study reveals a novel synchronization mechanism complementary to traditional synaptic transmission.