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相关概念视频

Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
Brain Imaging01:14

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic Stimulation (TMS).

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相关实验视频

Updated: Jul 2, 2026

Surgical Training for the Implantation of Neocortical Microelectrode Arrays Using a Formaldehyde-fixed Human Cadaver Model
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在体内用于神经科学的微电极阵列.

Nathaniel P Williams1,2, Mihaly Voroslakos3, Delin Shi1,2

  • 1Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.

Nature reviews. Methods primers
|February 23, 2026
PubMed
概括
此摘要是机器生成的。

微电极阵列 (MEAs) 能够同时记录神经活动. 本书详细介绍了用于体内神经科学研究的MEA技术,涵盖了设计,植入和数据分析.

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Interfacing Microfluidics with Microelectrode Arrays for Studying Neuronal Communication and Axonal Signal Propagation
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Construction and Implementation of Carbon Fiber Microelectrode Arrays for Chronic and Acute In Vivo Recordings
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相关实验视频

Last Updated: Jul 2, 2026

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科学领域:

  • 神经科学是一个神经科学.
  • 生物医学工程 生物医学工程
  • 电力生理学 电力生理学

背景情况:

  • 微电极阵列 (MEAs) 对于高分辨率的同时神经记录至关重要.
  • 了解神经网络是解读感官,运动和决策过程的关键.

研究的目的:

  • 为了提供一个全面的概述体内微电极阵列 (MEA) 技术.
  • 为MEA构建,植入,数据采集和分析的研究人员提供指导.

主要方法:

  • 对各种体内MEA设计及其制造的审查.
  • 植入技术和行为实验集成的描述.
  • 高质量的电生理记录和尖峰分类的策略.

主要成果:

  • 详细解释MEA的构造,表征和应用.
  • 关于减轻异物反应的指导,用于稳定的记录.
  • 介绍用于高通道计数数据的半自动尖端分类.

结论:

  • 在体内MEA技术是神经科学研究的宝贵工具.
  • 这本手册为读者提供了利用MEA技术的基础知识.
  • 未来的趋势集中在仿生和多功能MEA上,以提高能力.