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Neuroplasticity

Neuroplasticity

Neuroplasticity reflects the brain's remarkable capacity to adapt and evolve, responding dynamically to learning, experiences, or injury by reorganizing its neural circuitry. This reorganization involves creating new neural connections and refining old ones through a series of biological processes that contribute to the brain's lifelong development and adaptability.

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Memory is categorized into three major systems: sensory memory, short-term memory (STM), and long-term memory (LTM). These systems differ in their capacity and the duration for which they can hold information. Sensory memory captures raw sensory input from the environment, holding it for just a few seconds or less. For example, on hearing a brief, loud sound, like a car horn honking, the sound seems to linger in the mind for a moment even after it stops. This is an instance of sensory memory...

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Updated: May 21, 2026

Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits

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Published on: April 15, 2015

通过缺陷工程实现的2D可重新配置的记忆设备,用于多功能神经形态计算.

Yunpeng Xia¹, Ning Lin², Jiajia Zha²

¹Department of Electrical Engineering, City University of Hong Kong, Hong Kong SAR, 999077, China.

Advanced materials (Deerfield Beach, Fla.)

|July 15, 2024

概括

此摘要是机器生成的。

本研究介绍了一种使用MoS2/CuInP2S6异构的新型可重新配置存储器 (RMD). 这种多功能设备集成了传感,内存和计算,用于先进的AI应用.

关键词:

缺陷工程是什么?缺陷工程是什么?铁电极化的电极化神经形态计算是一种神经形态计算.可重新配置的存储器设备.范德瓦尔斯异构结构的异构结构

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Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits

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A Method for Growing Bio-memristors from Slime Mold

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Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Published on: March 9, 2019

科学领域:

材料科学材料科学材料科学
纳米技术纳米技术
设备物理设备物理

背景情况:

新兴的计算范式,如传感器和内存计算,需要简单的多功能内存设备.
现有的二维 (2D) 存储器设备往往缺乏多功能性或具有结构复杂性.
需要先进的内存解决方案来支持人工智能 (AI) 和物联网 (IoT).

研究的目的:

开发一个结构简化的多功能记忆装置.
将传感,内存和计算能力集成到一个单一的设备中.
探索缺陷工程和铁电特性,以提高设备性能.

主要方法:

制造一个MoS2/CuInP2S6异构结构.
使用等离子处理在CuInP2S6纳米片中进行缺陷工程,以增加层间缺陷.
利用CuInP2S6中的铁电极化来实现设备的重新配置.

主要成果:

可重新配置的内存设备 (RMD) 展示了集成的传感,内存和计算功能.
缺陷工程显著提高了电荷捕获能力,并与铁电特性协同作用.
该设备可以在非挥发性电子存储器,光电子存储器和突触模式之间重新配置.
通过视网膜血管细分来诊断眼科疾病是在光电子记忆模式下实现的.
展示了用于手势识别的传感器内容器计算,使用高能效的光电子突触模式进行了展示.

结论:

开发的MoS2/CuInP2S6 RMD为多功能应用提供了简化的结构.
该设备的重新配置可实现各种功能,包括传感,记忆和神经形态计算.
这项工作为节能AI和物联网应用提供了一个有前途的平台.