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関連する概念動画

Propagation of Action Potentials01:23

Propagation of Action Potentials

8.7K
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...
8.7K
Parallel Processing01:20

Parallel Processing

597
The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
597
Action Potential01:14

Action Potential

10.5K
Neurons communicate by firing action potentials—the electrochemical signal that is propagated along the axon. The signal results in the release of neurotransmitters at axon terminals, thereby transmitting information to the nervous system. An action potential is a specific "all-or-none" change in membrane potential that results in a rapid spike in voltage.
Membrane potential in neurons
Neurons typically have a resting membrane potential of about -70 millivolts (mV). When they receive...
10.5K
Spinal Cord: Information Processing01:10

Spinal Cord: Information Processing

3.0K
The spinal cord is an integral hub for motor and sensory information that enables the brain to communicate with the peripheral nervous system (PNS). This communication consists of relaying sensory data and transmission of motor commands.
Sensory Information Processing
Sensory information processing begins at the sensory receptors located in the skin and other tissues, which detect somatic sensory stimuli such as touch, temperature, or pain. These receptors function as catalysts, initiating...
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Storage01:23

Storage

324
A schema is a mental framework that helps individuals organize and interpret information. Schemata, formed from previous experiences, influence how we process new information: how we encode it, the inferences we make, and how we retrieve it. For instance, a schema for what a typical classroom looks like might include desks, a teacher's desk, a whiteboard, and students in such an environment. This expectation helps us quickly understand and navigate new classrooms without needing to analyze...
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Neuroplasticity01:01

Neuroplasticity

1.5K
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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関連する実験動画

Updated: Jan 7, 2026

Neural Activity Propagation in an Unfolded Hippocampal Preparation with a Penetrating Micro-electrode Array
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Neural Activity Propagation in an Unfolded Hippocampal Preparation with a Penetrating Micro-electrode Array

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脳における空間、時間を通じた誤差逆伝播

Benjamin Ellenberger1, Paul Haider2, Federico Benitez1

  • 1Department of Physiology, University of Bern, Bern, Switzerland.

Nature communications
|December 26, 2025
PubMed
まとめ
この要約は機械生成です。

一般化潜在平衡(GLE)は、物理的なニューロンネットワークが効率的な信用割当を局所的に実行することを可能にする。このフレームワークは、深層ネットワークにおける誤差逆伝播のオンライン近似を可能にし、時空間的局所性の制約を克服する。

キーワード:
誤差逆伝播信用割当ニューロンネットワーク時空間的局所性見込みコーディング物理ニューロンネットワーク連続学習局所的シナプス可塑性計算論的神経科学人工知能

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Perspectives on Neuroscience
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Perspectives on Neuroscience

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Modeling the Functional Network for Spatial Navigation in the Human Brain
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Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

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関連する実験動画

Last Updated: Jan 7, 2026

Neural Activity Propagation in an Unfolded Hippocampal Preparation with a Penetrating Micro-electrode Array
09:48

Neural Activity Propagation in an Unfolded Hippocampal Preparation with a Penetrating Micro-electrode Array

Published on: March 27, 2015

8.8K
Perspectives on Neuroscience
26:41

Perspectives on Neuroscience

Published on: July 31, 2007

5.3K
Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

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Published on: October 13, 2023

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科学分野:

  • 計算論的神経科学
  • 人工知能

背景:

  • ニューロンネットワークは、時空間的局所性の制約により、信用割当において課題に直面している。
  • 既存の誤差逆伝播アルゴリズムは、これらの局所性の原則に違反することが多い。

研究 の 目的:

  • 完全局所的な時空間的信用割当のための一般化潜在平衡(GLE)を導入する。
  • 物理的、動的なニューロンネットワークにおける効率的な学習のためのフレームワークを開発する。

主な方法:

  • 局所的な不一致に基づくエネルギー関数からニューロンダイナミクスを導出した。
  • パラメータダイナミクスに定常性と勾配降下法を利用した。
  • 情報処理と見込みコーディングのために樹状形態を利用した。

主要な成果:

  • 空間および時間を通じた誤差逆伝播のオンライン近似を開発した。
  • 順方向における時空間的畳み込みの計算を実証した。
  • 後方ストリームにおける随伴変数の近似を示した。

結論:

  • GLEは、ニューロンネットワークにおける信用割当のための生物学的に妥当なメカニズムを提供する。
  • このフレームワークは、局所的なシナプス可塑性を伴う連続学習をサポートする。
  • 見込みコーディングは、単一ニューロン内での計算能力を強化する。