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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.

Synaptic Signaling

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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.
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...

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...

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

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Chemical synapses are specialized sites between two neurons or between a neuron and a non-neuronal cell like a muscle, glandular or sensory cell.
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Multiprotein signaling complexes are formed in a dynamic process involving protein-protein interactions at the cytoplasmic domain of transmembrane receptors or enzymatic and non-enzymatic proteins associated with the receptor. These complexes ensure the activation and propagation of intracellular signals that regulate cell functions.
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Related Experiment Video

Updated: Jun 30, 2026

3D Modeling of Dendritic Spines with Synaptic Plasticity

3D Modeling of Dendritic Spines with Synaptic Plasticity

Published on: May 18, 2020

Synaptic clustering by dendritic signalling mechanisms.

Matthew E Larkum¹, Thomas Nevian

¹Department of Physiology, University of Berne, Bern, Switzerland.

Current Opinion in Neurobiology

|September 23, 2008

Summary

This summary is machine-generated.

Neurons process information through dendritic signal integration. Input clustering on dendrites allows neurons to act as multiple integrate-and-fire units, enhancing computational power.

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Area of Science:

Neuroscience
Computational Neuroscience
Cellular Neuroscience

Background:

Dendrites are crucial for neural information processing.
Nonlinear summation of synaptic inputs generates regenerative dendritic events like sodium, NMDA, and calcium spikes.
These events depend on specific spatio-temporal input patterns.

Purpose of the Study:

To investigate the functional implications of dendritic spike generation.
To explore how local synaptic plasticity and dendritic spikes might lead to input clustering.
To propose a model where input clusters enable neurons to function as multiple independent processing units.

Main Methods:

Theoretical modeling of dendritic integration.
Analysis of existing literature on dendritic spikes and synaptic plasticity.
Hypothesizing functional consequences of observed dendritic mechanisms.

Main Results:

Dendritic spikes and local plasticity rules suggest input clustering along dendritic branches.
Input clusters can allow dendrites to independently threshold groups of similar inputs.
This mechanism supports the idea of neurons acting as a superposition of integrate-and-fire units.

Conclusions:

Input clustering on dendrites is a plausible mechanism for enhancing neuronal computation.
This organization expands the computational capacity of single neurons.
Understanding dendritic integration advances our knowledge of neural network computational power.