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相关概念视频

Neural Circuits01:25

Neural Circuits

1.6K
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...
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Indirect Motor Pathways01:22

Indirect Motor Pathways

1.7K
The indirect motor or extrapyramidal pathways originate in the brainstem, the lower portion of the brain that connects it to the spinal cord. They consist of several distinct tracts, each with specialized functions. The four main tracts of the indirect motor pathways are the vestibulospinal tract, the reticulospinal tract, the tectospinal tract, and the rubrospinal tract.
The vestibulospinal tract originates in the vestibular nuclei of the brainstem. The vestibular system detects changes in...
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Associative Learning01:27

Associative Learning

597
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
597
Neural Regulation01:37

Neural Regulation

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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.
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Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

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A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
150
Propagation of Action Potentials01:23

Propagation of Action Potentials

7.0K
The propagation of an action potential refers to the process by which a nerve impulse, or "action potential," travels along a neuron.
Neurons (nerve cells) have a resting membrane potential, with a slightly negative charge inside compared to outside. This is maintained by ion channels, such as sodium (Na+) and potassium (K+) channels, which control the flow of ions. When a stimulus, like a touch or a signal from another neuron, triggers the neuron, sodium channels open, allowing sodium ions to...
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相关实验视频

Updated: Sep 17, 2025

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
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使用人工神经网络,对使用者一致的过渡路径进行代变化学习.

Alberto Megías1,2, Sergio Contreras Arredondo1, Cheng Giuseppe Chen1

  • 1Laboratoire International Associé Centre National de la Recherche Scientifique et University of Illinois at Urbana-Champaign, Unité Mixte de Recherche 7019, Université de Lorraine, Lorraine, France.

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概括

本研究介绍了一种新的神经网络策略,用于绘制复杂系统中罕见事件过渡途径的地图. 该方法同时学习了提交函数及其一致的字符串,对生物分子转换产生了前所未有的洞察力.

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Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
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Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

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相关实验视频

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科学领域:

  • 计算化学是一种计算化学.
  • 生物物理学的生物物理.
  • 统计力学就是统计力学.

背景情况:

  • 在复杂系统中研究罕见事件和过渡途径具有挑战性.
  • 现有的方法通常依赖于近似值,这限制了它们的适用性.

研究的目的:

  • 开发一种基于神经网络的新策略,以发现具有物理意义和与犯人一致的过渡途径.
  • 为复杂系统中的过渡过程提供了前所未有的视角.

主要方法:

  • 一个神经网络策略,同时学习提交器函数及其相关的提交器一致字符串.
  • 在各种动态模式中利用犯人时间相关函数.
  • 超越传统的无限小的时间延迟近似.

主要成果:

  • 该方法成功地重现了既定的动态,速率常数和过渡机制.
  • 它在复杂的生物分子转换中区分了多个相互竞争的途径.
  • 在基准潜力和生物系统 (如异体化和蛋白质折叠) 上表现出稳健性.

结论:

  • 这种方法为罕见事件的增强样本模拟提供了一个强大而通用的工具.
  • 它为生物分子系统的复杂景观提供了宝贵的见解.
  • 该方法可以适应集体变量,并且在神经架构中具有弹性.