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Related Concept Videos

Integration of Synaptic Events01:28

Integration of Synaptic Events

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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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Field Effect Transistor01:29

Field Effect Transistor

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Field-effect transistors (FETs) are integral to electronic circuits and distinguished by their three-terminal setup: the gate, drain, and source. These transistors operate as unipolar devices, which utilize either electrons or holes as charge carriers, in contrast to bipolar transistors, which use both types of carriers. The primary function of the FET is to modulate the flow of these carriers from the source to the drain through a channel. The voltage difference between the gate and source...
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Bipolar Junction Transistor01:22

Bipolar Junction Transistor

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Bipolar Junction Transistors (BJTs) are essential elements in electronic circuits, playing a crucial role in the functionality of amplifiers, memories, and microprocessors. These transistors can be designed as NPN or PNP based on their doping patterns. They consist of three layers: the emitter, base, and collector. The configuration of these layers and their respective doping levels—with N-type or P-type impurities—define the transistor's type and its operational...
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Transduction01:16

Transduction

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Among the three main modes of HGT—transformation, conjugation, and transduction—transduction is unique in that it is mediated by bacteriophages, or bacterial viruses.Transduction occurs in two ways. Generalized transduction occurs during the lytic cycle of a bacteriophage infection. In this process, bacteriophages infect bacterial cells, replicate within them, and ultimately cause cell lysis, releasing newly assembled virions. Occasionally, random fragments of the bacterial genome...
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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.
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...
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Synaptic Signaling01:09

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.
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The presynaptic neuron fires an action potential that...
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Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
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Bio-inspired artificial synaptic transistors: evolution from innovative basic units to system integration.

Xin Wang1, Yixin Ran1, Xiaoqian Li2

  • 1Frontier Institute of Science and Technology, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an 710054, P. R. China. guanghao.lu@mail.xjtu.edu.cn.

Materials Horizons
|June 14, 2023
PubMed
Summary
This summary is machine-generated.

Artificial synapses using transistors are key for brain-like computing. This review highlights novel device designs and material advancements for improved synaptic transistor performance and system integration in neuromorphic engineering.

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Area of Science:

  • Neuromorphic Engineering
  • Materials Science
  • Artificial Intelligence Hardware

Background:

  • The von Neumann architecture faces limitations in processing explosive information due to separate storage and computing.
  • Transistor-based artificial synapses are crucial building blocks for brain-inspired computing, mimicking biological neural functions.
  • Existing research shows promise in simulating neural functions but lacks a clear link between semiconductor properties, device structure, and synaptic performance.

Purpose of the Study:

  • To review recent advancements in novel structure designs of semiconductor materials and devices for synaptic transistors.
  • To explore the influence of semiconductor choice and device architecture on synaptic transistor properties.
  • To discuss system-level applications and interconnected working mechanisms of synaptic transistors.

Main Methods:

  • Comprehensive literature review focusing on recent developments in synaptic transistor design.
  • Analysis of structure-property relationships in semiconductor materials for artificial synapses.
  • Examination of multi-device system integration and operational mechanisms.

Main Results:

  • Significant progress in designing novel structures for synaptic transistors, enhancing their functionality.
  • Demonstration of multifunction synaptic devices and their integration into larger interconnected systems.
  • Identification of key relationships between material properties, device architecture, and synaptic behavior.

Conclusions:

  • Novel structural designs and material innovations are crucial for advancing transistor-based artificial synapses.
  • Bridging hardware design with software simulation is critical for efficient neuromorphic computing.
  • Future research should address challenges and opportunities in synaptic interconnection for robust brain-like computing systems.