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Related Concept Videos

Chemical Synapses01:26

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.
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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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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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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The Role of Ion Channels in Neuronal Computation01:19

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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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Overview of Synapses01:25

Overview of Synapses

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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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Integration of Synaptic Events01:28

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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...
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Related Experiment Video

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Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
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Artificial Synapse Based on van der Waals Heterostructures with Tunable Synaptic Functions for Neuromorphic

Congli He1, Jian Tang2,3, Da-Shan Shang4

  • 1Institute of Advanced Materials, Beijing Normal University, Beijing 100875, China.

ACS Applied Materials & Interfaces
|February 14, 2020
PubMed
Summary

Researchers developed a novel dual-gate device using 2D van der Waals heterostructures. This device demonstrates high-speed, low-energy artificial synapse functionality for neuromorphic computing applications.

Keywords:
2D materialsMoS2artificial synapsedual-gateneuromorphic computingvan der Waals heterostructures

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Area of Science:

  • Materials Science
  • Condensed Matter Physics
  • Nanotechnology

Background:

  • Two-dimensional (2D) materials and van der Waals heterostructures offer unique electronic and optoelectronic properties.
  • These materials are crucial for developing advanced functionalities in electronic devices.
  • Neuromorphic computing aims to mimic the human brain's structure and function.

Purpose of the Study:

  • To fabricate a novel multiterminal device using 2D van der Waals heterostructures.
  • To investigate the nonvolatile multilevel resistance switching performance of the device.
  • To demonstrate the potential of this device as an artificial synapse for neuromorphic computing.

Main Methods:

  • Fabrication of a multiterminal device with dual-gate configuration based on 2D van der Waals heterostructures.
  • Characterization of nonvolatile multilevel resistance switching controlled by source-drain and back-gate voltages.
  • Mimicking heterosynaptic plasticity by tuning synaptic weight.

Main Results:

  • The fabricated device exhibited excellent nonvolatile multilevel resistance switching performance.
  • Achieved tunable analog weight updates with a high on/off ratio and controllable nonlinearity.
  • Demonstrated high-speed (50 ns) and low-energy (∼7.3 fJ) programming for synaptic operations.

Conclusions:

  • The developed 2D van der Waals heterostructure device shows great potential for artificial synapse applications.
  • The device's properties are suitable for mimicking synaptic plasticity, crucial for neuromorphic computing.
  • This work paves the way for advanced neuromorphic computing hardware.