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相关概念视频

Neural Regulation01:37

Neural Regulation

Digestion begins with a cephalic phase that prepares the digestive system to receive food. When our brain processes visual or olfactory information about food, it triggers impulses in the cranial nerves innervating the salivary glands and stomach to prepare for food.
Data Collection by Experiments01:13

Data Collection by Experiments

Data collection is a systematic method of obtaining, observing, measuring, and analyzing accurate information. An experimental study is a standard method of data collection that involves the manipulation of the samples by applying some form of treatment prior to data collection. It refers to manipulating one variable to determine its changes on another variable. The sample subjected to treatment is known as “experimental units.”
An example of the experimental method is a public clinical trial...
Crossover Experiments01:16

Crossover Experiments

Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in different periods. Crossover experiments are generally used in psychology, the pharmaceutical industry, agriculture, and medicine.
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.
Neural Circuits01:25

Neural Circuits

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.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
Open and closed-loop control systems01:17

Open and closed-loop control systems

Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal and...
Observational Learning01:12

Observational Learning

Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning because...

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相关实验视频

Updated: Jun 21, 2026

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
10:51

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

Published on: March 10, 2011

13.7K

品牌:一个与深度网络模型闭环实验的平台.

Yahia H Ali1, Kevin Bodkin2, Mattia Rigotti-Thompson1

  • 1Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, United States of America.

Journal of neural engineering
|April 5, 2024
PubMed
概括
此摘要是机器生成的。

实时异步神经解码 (BRAND) 的新后端使人工神经网络 (ANN) 的快速,语言无关的整合成为实时大脑-计算机接口. 该系统实现了低延迟,在闭环实验中促进了先进的神经科学和机器学习应用.

关键词:
人工神经网络的人工神经网络大脑 计算机接口封闭循环的封闭循环.实时实时的时间.

更多相关视频

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
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Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

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Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments
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Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

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相关实验视频

Last Updated: Jun 21, 2026

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
10:51

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

Published on: March 10, 2011

13.7K
Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

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Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments
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科学领域:

  • 神经科学是一个神经科学.
  • 计算机科学 计算机科学
  • 生物医学工程 生物医学工程

背景情况:

  • 人工神经网络 (ANN) 对神经解码具有强大作用,但在实时系统中面临部署挑战.
  • 现有的框架很难支持高层次的ANN (Python,Julia) 以及低延迟的获取语言 (C,C++).

研究的目的:

  • 介绍实时异步神经解码 (BRAND) 的后端,以弥合ANN和实时实验需求之间的差距.
  • 能够将先进的机器学习模型无整合到闭环神经科学研究中.

主要方法:

  • 品牌使用基于Linux流程的架构,节点通过图中的数据流进行通信.
  • 异步设计允许在不同的时间范围内并行执行采集,控制和分析.
  • 雷迪斯促进了快速的进程间通信,支持54种编程语言,以便灵活地部署ANN.

主要成果:

  • 对于高通量神经数据,BRAND证明了在600微秒以下的进程间延迟.
  • 使用BRAND的脑电脑接口实现了<8毫秒的延迟,用于递归神经网络 (RNN) 解码.
  • 在临床试验中成功运行了光标控制任务,集成了信号处理,RNN解码和任务控制.

结论:

  • 品牌为实时神经科学实验提供了一个快速,模块化和语言无关的框架.
  • 降低了尖端机器学习和神经科学工具的整合障碍.
  • 通过动态系统实现先进的应用,如实时推断,并使用复杂的模型,如通过动态系统进行潜伏因子分析.