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相关概念视频

Translation01:31

Translation

133.6K
Lesson: Translation
Translation is the process of synthesizing proteins from the genetic information carried by messenger RNA (mRNA). Following transcription, it constitutes the final step in the expression of genes. This process is carried out by ribosomes, complexes of protein and specialized RNA molecules. Ribosomes, transfer RNA (tRNA), and other proteins produce a chain of amino acids—the polypeptide—as the end product of translation.
Translation Produces the Building Blocks of...
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Higher Mental Functions of the Brain: Language01:10

Higher Mental Functions of the Brain: Language

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Language is a system of communication that allows the expression of thoughts, ideas, and feelings. The brain processes language in both hemispheres.
Language formation and comprehension take place in the dominant hemisphere. The dominant hemisphere is responsible for understanding the meaning of spoken, written, or sign language, as well as the ability to communicate. For most people, the left hemisphere is the dominant one. The right hemisphere, then, gives tone and emotional context to the...
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相关实验视频

Updated: May 1, 2026

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
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闭环深度大脑刺激平台用于翻译研究

Yan Li1, Yingnan Nie1, Xiao Li1

  • 1Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China; Ministry of Education Frontiers Center for Brain Science, Fudan University, Shanghai, China.

Neuromodulation : journal of the International Neuromodulation Society
|December 15, 2024
PubMed
概括
此摘要是机器生成的。

一个新的研究平台加速了闭环深度大脑刺激 (DBS) 策略的翻译. 它可以实时删除文物和低延迟控制,以更快地开发新的DBS疗法.

关键词:
闭环深度大脑刺激 闭环深度大脑刺激深度大脑刺激 刺激大脑机器学习是机器学习.实时实时的时间.翻译研究是翻译研究.

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Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment
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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
  • 翻译研究是翻译研究.

背景情况:

  • 深度大脑刺激 (DBS) 是一种治疗神经障碍的治疗方法.
  • 将创新的闭环DBS策略从概念转化为临床应用面临重大技术障碍.
  • 目前的方法往往缺乏适应性刺激所需的实时处理和低延迟控制.

研究的目的:

  • 建立一个多功能研究平台,以促进闭环DBS策略的翻译.
  • 为应对实时刺激,人工物移除和低延迟反控制方面的挑战.
  • 为了弥合动物研究和先进的DBS技术的临床实施之间的差距.

主要方法:

  • 在动物和临床模型中开发用于神经传感和刺激的集成硬件.
  • 实现一个闭环软件框架,支持实时数据流,文物移除和控制.
  • 创建一个带有信号处理和机器学习工具的算法库,用于开发新的DBS策略.

主要成果:

  • 在动物和临床实验中实现了低延迟反控制,响应时间低于7毫秒.
  • 证明有效地去除刺激器件,在实施各种闭环DBS算法时具有高度的灵活性.
  • 成功集成多个先进的闭环协议,包括值适应和神经状态依赖的DBS.

结论:

  • 开发的平台是加速部署创新的闭环DBS策略的关键研究工具.
  • 它的实时数据处理和低延迟控制能力显著提升了翻译DBS研究.
  • 这个平台有可能为患者开发更有效和个性化的治疗干预措施.