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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

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.

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...

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.
Gap junctions allow the current to pass directly from one cell to the next. In contrast, in the chemical synapse, the neurotransmitters carry the information through the synaptic cleft from one neuron to the next. They consist of two...

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.

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...

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Bidirectional Electrical and Optoelectronic Interfaces in Healthy and Ischemic Ex Vivo Rat Hearts

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Synaptic electronics: materials, devices and applications.

Duygu Kuzum¹, Shimeng Yu, H-S Philip Wong

¹Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA. duygu@stanford.edu

|September 4, 2013

Summary

This summary is machine-generated.

This review covers synaptic electronics, detailing biological synaptic plasticity and learning. It explores synaptic devices for brain-inspired computing, discussing material properties, performance metrics, and applications.

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Area of Science:

Materials Science
Neuroscience
Computer Engineering

Background:

Biological synapses exhibit plasticity and learning, fundamental to brain function.
Synaptic electronics aim to mimic these biological processes using artificial devices.

Purpose of the Study:

To review recent advancements in synaptic electronics.
To discuss the application of synaptic devices in neuromorphic computing.
To highlight performance metrics and target applications.

Main Methods:

Review of existing literature on synaptic plasticity and learning.
Analysis of material properties and electrical characteristics of various synaptic devices.
Discussion of performance metrics and computational applications.

Main Results:

Synaptic devices show promise for brain-inspired computing.
Material properties and device characteristics are crucial for performance.
Specific applications demonstrate the potential of these devices.

Conclusions:

Synaptic electronics is a rapidly advancing field with significant potential.
Further research is needed to optimize devices for large-scale neuromorphic systems.
Synaptic devices offer a pathway towards more efficient and intelligent computing architectures.