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Related Concept Videos

Integration of Synaptic Events01:28

Integration of Synaptic Events

Synaptic integration mainly includes the summation of graded potentials. Graded potentials, regardless of their type, cause subtle alterations in membrane voltage, resulting in either depolarization or hyperpolarization. These incremental changes, when combined or summed, can propel the neuron toward its threshold. Consider, for example, a membrane experiencing a +15 mV shift, causing it to depolarize from -70 mV to -55 mV. In this scenario, graded potentials govern the membrane's ability to...
Action Potential01:14

Action Potential

Neurons communicate by firing action potentials—the electrochemical signal that is propagated along the axon. The signal results in the release of neurotransmitters at axon terminals, thereby transmitting information to the nervous system. An action potential is a specific "all-or-none" change in membrane potential that results in a rapid spike in voltage.
Membrane potential in neurons
Neurons typically have a resting membrane potential of about -70 millivolts (mV). When they receive...
Action Potential01:14

Action Potential

Neurons communicate by firing action potentials—the electrochemical signal that is propagated along the axon. The signal results in the release of neurotransmitters at axon terminals, thereby transmitting information to the nervous system. An action potential is a specific "all-or-none" change in membrane potential that results in a rapid spike in voltage.
Membrane potential in neurons
Neurons typically have a resting membrane potential of about -70 millivolts (mV). When they receive...
Postsynaptic Potential (PSP)01:32

Postsynaptic Potential (PSP)

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.
There are two types of receptors: ionotropic and metabotropic.
The ionotropic receptor is the membrane protein that has an...
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.
Excitatory and Inhibitory Effects of Neurotransmitters01:29

Excitatory and Inhibitory Effects of Neurotransmitters

When an action potential reaches the presynaptic axon terminal, it releases neurotransmitters from the neuron into the synaptic cleft at a chemical synapse. The released neurotransmitter can be excitatory or inhibitory. The critical criteria commonly used to determine whether a molecule is a neurotransmitter at a chemical synapse are the molecule's presence in the presynaptic neuron. Second, its release is in response to strong presynaptic depolarization. And lastly, the presence of specific...

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Related Experiment Video

Updated: Jun 3, 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

Finite post synaptic potentials cause a fast neuronal response.

Moritz Helias1, Moritz Deger, Stefan Rotter

  • 1RIKEN Brain Science Institute Wako City, Japan.

Frontiers in Neuroscience
|March 24, 2011
PubMed
Summary
This summary is machine-generated.

Spiking neuronal network models reveal that neural responses to transient inputs are instantaneous, not low-pass. This finding, driven by synaptic impulse characteristics and background noise, resolves discrepancies between theory and experiments.

Keywords:
diffusion approximationleaky integrate-and-fire modelnon-linear responseperfect integratorshot noise

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Vibrodissociation of Neurons from Rodent Brain Slices to Study Synaptic Transmission and Image Presynaptic Terminals
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Published on: May 25, 2011

Evaluation of Synaptic Multiplicity Using Whole-cell Patch-clamp Electrophysiology
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Evaluation of Synaptic Multiplicity Using Whole-cell Patch-clamp Electrophysiology

Published on: April 23, 2019

Related Experiment Videos

Last Updated: Jun 3, 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

Vibrodissociation of Neurons from Rodent Brain Slices to Study Synaptic Transmission and Image Presynaptic Terminals
08:38

Vibrodissociation of Neurons from Rodent Brain Slices to Study Synaptic Transmission and Image Presynaptic Terminals

Published on: May 25, 2011

Evaluation of Synaptic Multiplicity Using Whole-cell Patch-clamp Electrophysiology
10:52

Evaluation of Synaptic Multiplicity Using Whole-cell Patch-clamp Electrophysiology

Published on: April 23, 2019

Area of Science:

  • Computational neuroscience
  • Neuronal dynamics
  • Spiking neural networks

Background:

  • Current integrate-and-fire models approximate synaptic input as Gaussian white noise.
  • Linearization is commonly used to analyze signal transfer in neurons.
  • These approximations limit the accuracy of existing neuronal network theories.

Purpose of the Study:

  • To challenge the assumptions of Gaussian white noise and linearization in spiking neuronal network models.
  • To investigate the impact of synaptic impulse characteristics on neural responses.
  • To reconcile theoretical predictions with experimental observations.

Main Methods:

  • Developed a theoretical framework beyond Gaussian white noise and linearization approximations.
  • Analyzed the response of neurons to transient synaptic inputs.
  • Investigated the role of synaptic impulse amplitude, excitation-inhibition asymmetry, and background noise.

Main Results:

  • Neural responses to transient inputs are instantaneous, not low-pass, deviating from previous predictions.
  • Response characteristics are non-linearly dependent on impulse amplitude.
  • Excitation and inhibition exhibit asymmetric responses.
  • A specific level of synaptic background noise promotes neural responses.

Conclusions:

  • The study provides a more accurate model for neuronal communication, resolving contradictions with experimental data.
  • Membrane potential near threshold is sensitive to afferent noise properties, shaping neural responses.
  • Extended theory quantifies simulation artifacts and offers improved validation methods.