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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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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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Advancing Intelligent Neuromorphic Computing: Recent Progress in All-Optical-Controlled Artificial Synaptic Devices.

Jian Yao1,2, Yu Teng1,2, Qinan Wang2

  • 1School of Nano-Tech and Nano-Bionics, University of Science and Technology of China, Hefei 230026, China.

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|July 18, 2025
PubMed
Summary
This summary is machine-generated.

All-optical-controlled neuromorphic devices offer a solution to computational bottlenecks by integrating functions. This review highlights materials and mechanisms driving efficiency and scalability in optical neuromorphic computing.

Keywords:
all-optical-controlledartificial synapsebrain-inspired deviceslow-dimensional materialsneuromorphic computingneuromorphic vision sensorsoptical logic gatesvan der Waals heterostructures

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Area of Science:

  • Optoelectronics
  • Materials Science
  • Computer Science

Background:

  • Traditional von Neumann architecture faces performance limitations due to data transfer bottlenecks and high energy consumption.
  • Neuromorphic devices integrate perception, storage, and processing, offering a potential solution.
  • Current neuromorphic devices often use electronic or hybrid control, limiting speed and efficiency.

Purpose of the Study:

  • To review advancements in all-optical-controlled neuromorphic devices.
  • To focus on the role of materials and optical control mechanisms in enhancing device performance.
  • To analyze the physical principles behind all-optical neuromorphic computing.

Main Methods:

  • Comprehensive literature review of recent research in all-optical-controlled neuromorphic devices.
  • Analysis of material properties and their impact on device functionality.
  • Examination of physical mechanisms enabling all-optical control.

Main Results:

  • All-optical-controlled neuromorphic devices demonstrate superior speed, lower energy consumption, and enhanced scalability compared to electronic counterparts.
  • Specific materials and optical control mechanisms significantly improve device efficiency.
  • Diverse applications identified in optical logic gates, visual perception, and brain-inspired computing.

Conclusions:

  • All-optical-controlled neuromorphic devices represent a promising paradigm for future computing.
  • Materials innovation and understanding optical control mechanisms are crucial for advancing this technology.
  • These devices have the potential to revolutionize computational paradigms across various fields.