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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.
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...

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.

Electrical Synapses

Electrical Synapses

Electrical synapses found in all nervous systems play important and unique roles. In these synapses, the presynaptic and postsynaptic membranes are very close together (3.5 nm) and are actually physically connected by channel proteins forming gap junctions.
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The Synapse

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.

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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A synapse is a specialized structure where two neurons connect, allowing them to pass an electrical or chemical signal to another neuron. It is the point of communication between neurons. The term "synapse" is derived from the Greek word "synapsis," which means "conjunction." The entire process of neural communication revolves around the synapse. When activated, a neuron releases chemicals known as neurotransmitters into the synapse. These neurotransmitters cross the synapse and bind to...

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Related Experiment Video

Updated: Jul 4, 2026

Electrophysiological and Morphological Characterization of Neuronal Microcircuits in Acute Brain Slices Using Paired Patch-Clamp Recordings

Electrophysiological and Morphological Characterization of Neuronal Microcircuits in Acute Brain Slices Using Paired Patch-Clamp Recordings

Published on: January 10, 2015

Geometric constraints on neuronal connectivity facilitate a concise synaptic adhesive code.

Shalev Itzkovitz¹, Leehod Baruch, Ehud Shapiro

¹Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 76100, Israel. shalev.itzkovitz@weizmann.ac.il

Proceedings of the National Academy of Sciences of the United States of America

|June 28, 2008

Summary

This summary is machine-generated.

The nervous system uses a limited number of "neuronal addresses" to wire its trillions of neurons. Geometric networks, with repeating patterns, efficiently encode complex neuronal connections, saving genetic resources.

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Last Updated: Jul 4, 2026

Electrophysiological and Morphological Characterization of Neuronal Microcircuits in Acute Brain Slices Using Paired Patch-Clamp Recordings

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Published on: January 10, 2015

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Published on: June 13, 2017

Area of Science:

Neuroscience
Computational Biology
Systems Biology

Background:

The nervous system's complexity arises from trillions of neurons forming numerous synaptic connections.
A proposed 'adhesive code' uses cell surface proteins to form neuronal addresses, dictating connectivity.
The number of unique neuronal addresses is significantly smaller than the total number of neurons.

Purpose of the Study:

To investigate how a limited set of neuronal addresses constrains and enables the encoding of neuronal network topologies.
To compare the address requirements for arbitrary versus geometric neuronal networks.
To explore the evolutionary and genetic encoding advantages of geometric network structures.

Main Methods:

Development of computational models to simulate neuronal network formation.
Analysis of address scaling with network size for arbitrary and geometric topologies.
Validation using simulated networks and the well-characterized neuronal network of *C. elegans*.

Main Results:

Encoding arbitrary networks requires addresses scaling linearly with network size.
Geometric networks require addresses scaling with the square root of network size due to address reutilization.
Ordered geometric networks with iterated patterns further minimize address requirements.

Conclusions:

A limited number of neuronal addresses imposes constraints on network topology.
Geometric and ordered geometric network structures offer highly efficient genetic encoding strategies.
These topological features provide an evolutionary advantage by facilitating genetic encoding and conserving resources.