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Related Concept Videos

Electrical Synapses01:28

Electrical Synapses

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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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Intrinsic semiconductors are highly pure materials with no impurities. At absolute zero, these semiconductors behave as perfect insulators because all the valence electrons are bound, and the conduction band is empty, disallowing electrical conduction. The Fermi level is a concept used to describe the probability of occupancy of energy levels by electrons at thermal equilibrium. In intrinsic semiconductors, the Fermi level is positioned at the midpoint of the energy gap at absolute zero. When...
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A postsynaptic neuron usually receives numerous impulses from several other presynaptic neurons. The axon hillock of the postsynaptic neuron integrates all these signals and determines the likelihood of firing an action potential.
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Chemical Synapses01:26

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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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Chemical Synapses01:26

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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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There is variation in the electrical conductivity of materials - metals, semiconductors, and insulators that are showcased with the help of the energy band diagrams.
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Translating Extracellular Electron Transfer Activities with Organic Electrochemical Transistors
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Electret-Based Organic Synaptic Transistor for Neuromorphic Computing.

Rengjian Yu1, Enlong Li1, Xiaomin Wu1

  • 1Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou 350002, China.

ACS Applied Materials & Interfaces
|March 11, 2020
PubMed
Summary
This summary is machine-generated.

Researchers developed a novel electret-based synaptic transistor (EST) that mimics brain functions for neuromorphic computing. This artificial synapse demonstrates key synaptic behaviors and achieves high accuracy in neural network simulations.

Keywords:
charge trappingelectret-based synaptic transistorneuromorphic computingnonlinearitypattern recognitionsynaptic weight update

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Area of Science:

  • Materials Science
  • Neuroscience
  • Computer Engineering

Background:

  • Neuromorphic computing aims to mimic the brain's efficiency by integrating processing and memory.
  • Artificial synaptic devices are crucial for low-power, brain-inspired computing systems.
  • Exploring diverse synaptic transistor types is vital for advancing artificial intelligence.

Purpose of the Study:

  • To introduce and characterize a novel electret-based synaptic transistor (EST).
  • To evaluate the synaptic behaviors and performance of the EST in neuromorphic applications.

Main Methods:

  • Fabrication and characterization of an electret-based synaptic transistor.
  • Demonstration of synaptic behaviors: postsynaptic current, paired-pulse modulation, and memory effects.
  • Implementation of a neuromorphic computing simulation using a handwritten artificial neural network with the EST.

Main Results:

  • The EST successfully exhibited excitatory/inhibitory postsynaptic current, paired-pulse facilitation/depression, and long-term memory.
  • The device demonstrated high-pass filtering capabilities.
  • Neuromorphic simulations achieved 85.88% recognition accuracy, outperforming many organic synaptic transistors.

Conclusions:

  • The novel EST enriches the diversity of artificial synaptic devices.
  • This development lays the groundwork for next-generation, diversified neuromorphic computing systems.
  • The EST shows significant potential for low-power, high-performance artificial intelligence applications.