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Integration of Synaptic Events

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...

Long-term Potentiation

Long-term Potentiation

Long-term potentiation, or LTP, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTP is the process of synaptic strengthening that occurs over time between pre and postsynaptic neuronal connections. The synaptic strengthening of LTP works in opposition to the synaptic weakening of long-term depression (LTD) and together are the main mechanisms that underlie learning and memory.
Hebbian LTP
LTP can occur when...

Long-term Potentiation

Long-term Potentiation

Long-term potentiation, or LTP, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTP is the process of synaptic strengthening that occurs over time between pre- and postsynaptic neuronal connections. The synaptic strengthening of LTP works in opposition to the synaptic weakening of long-term depression (LTD) and together are the main mechanisms that underlie learning and memory.

Chemical Synapses

Chemical Synapses

Chemical synapses are specialized sites between two neurons or between a neuron and a non-neuronal cell like a muscle, glandular or sensory cell.
Because chemical synapses depend on the release of neurotransmitter molecules from synaptic vesicles to pass on their signal, there is an approximately one millisecond delay between when the axon potential reaches the presynaptic terminal and when the neurotransmitter leads to opening of postsynaptic ion channels. Additionally, this signaling is...

Chemical Synapses

Chemical Synapses

Chemical synapses are specialized sites between two neurons or between a neuron and a non-neuronal cell like a muscle, glandular or sensory cell.
Because chemical synapses depend on the release of neurotransmitter molecules from synaptic vesicles to pass on their signal, there is an approximately one millisecond delay between when the axon potential reaches the presynaptic terminal and when the neurotransmitter leads to opening of postsynaptic ion channels. Additionally, this signaling is...

Synaptic Signaling

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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Related Experiment Video

Updated: Nov 1, 2025

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond

Published on: June 24, 2015

Event-Based Update of Synapses in Voltage-Based Learning Rules.

Jonas Stapmanns^1,2, Jan Hahne³, Moritz Helias^1,2

¹Institute of Neuroscience and Medicine (INM-6), Institute for Advanced Simulation (IAS-6), JARA Institute Brain Structure Function Relationship (INM-10), Jülich Research Centre, Jülich, Germany.

Frontiers in Neuroinformatics

|June 28, 2021

Summary

New event-based algorithms efficiently archive postsynaptic membrane potentials for synaptic plasticity. This enables large-scale neural network simulations by overcoming limitations of traditional time-driven approaches.

Keywords:

Clopath rule NEST Urbanczik-Senn rule event-based simulation spiking neural network simulator voltage-based plasticity rules

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Last Updated: Nov 1, 2025

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond

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Published on: June 24, 2015

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

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Published on: April 23, 2019

Slice Patch Clamp Technique for Analyzing Learning-Induced Plasticity

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Published on: November 11, 2017

Area of Science:

Computational neuroscience
Neural network simulation

Background:

Event-based simulation is efficient for neuronal spiking.
Synaptic plasticity often requires postsynaptic membrane potentials beyond spike times.
Time-driven updates for plasticity hinder large-scale simulations.

Purpose of the Study:

Develop efficient algorithms for archiving membrane potentials in event-based simulators.
Enable biologically realistic synaptic plasticity in large-scale neural networks.
Analyze computational and memory advantages over time-driven methods.

Main Methods:

Derived two novel algorithms for event-based membrane potential archiving.
Theoretically contrasted algorithms with time-driven schemes.
Implemented and tested algorithms in the NEST simulator for Clopath and Urbanczik-Senn rules.

Main Results:

Event-based algorithms significantly outperform time-driven schemes in efficiency.
Performance gains depend on plasticity rule data storage requirements.
Compressing or sampling membrane potential data further boosts performance.

Conclusions:

Developed efficient, event-based methods for membrane potential archiving in neural simulations.
These algorithms facilitate large-scale simulations of synaptic plasticity.
Guidelines provided for designing computationally feasible learning rules for large networks.