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Related Concept Videos

Neural Circuits01:25

Neural Circuits

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Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
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Overview of Synapses01:25

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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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The Synapse02:47

The Synapse

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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.
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Neuronal Communication01:28

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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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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.
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...
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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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Multimodal Artificial Synapses for Neuromorphic Application.

Runze Li1,2,3, Zengji Yue1, Haitao Luan1

  • 1School of Artificial Intelligence Science and Technology, University of Shanghai for Science and Technology, Shanghai 200093, China.

Research (Washington, D.C.)
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Summary
This summary is machine-generated.

Artificial synapses enable low-energy, fast artificial intelligence for robots. This review covers multimodal artificial synapses for multisensory robotic applications, crucial for developing anthropomorphic intelligent robots.

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Area of Science:

  • Neuromorphic Computing
  • Artificial Intelligence
  • Robotics
  • Neuroscience

Background:

  • Neuromorphic computing advances drive artificial synapse research for efficient AI.
  • Artificial synapses mimic biological functions for in-memory computing and signal transmission.
  • Robots represent a key application area for advanced artificial intelligence.

Purpose of the Study:

  • To review working mechanisms of artificial synapses across diverse stimulation and response modalities.
  • To present the application of artificial synapses in various neuromorphic tasks.
  • To provide a comprehensive understanding of multimodal artificial synapses for researchers.

Main Methods:

  • Review of scientific literature on artificial synapse mechanisms.
  • Analysis of multimodal artificial synapses for sensory input simulation.
  • Examination of applications in neuromorphic computing tasks.

Main Results:

  • Artificial synapses offer parallel in-memory computing and signal transmission for low-energy AI.
  • Multimodal artificial synapses are essential for multisensory capabilities in anthropomorphic robots.
  • Diverse artificial synapse modalities are being explored for various neuromorphic applications.

Conclusions:

  • Developing anthropomorphic intelligent robots necessitates integrating artificial intelligence with multimodal artificial synapses.
  • Understanding diverse artificial synapse mechanisms is key to advancing neuromorphic engineering.
  • This review consolidates knowledge on multimodal artificial synapses, guiding future research.