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関連する概念動画

Steady Flow of a Fluid Stream01:27

Steady Flow of a Fluid Stream

Consider a control volume, such as a pipe with solid boundaries, through which fluid flows and changes direction due to the impulse exerted by the resulting force from the pipe walls. In steady flow, the mass of fluid entering the control volume at a given time, t, with velocity v1, is equal to the mass leaving after infinitesimal time dt, with velocity v2.
During this process, the momentum of the fluid within the control volume remains constant over the time interval dt. By applying the...
Conservation of Mass in Moving, Nondeforming Control Volume01:14

Conservation of Mass in Moving, Nondeforming Control Volume

Stormwater detention basins are essential in managing runoff during heavy rainfall, particularly in urban areas where impervious surfaces increase the risk of flooding. Understanding the conservation of mass in these systems allows engineers to optimize basin performance, balancing inflow, outflow, and water storage.
In the context of a detention basin, the conservation of mass states that the total mass of water entering the basin must equal the mass leaving the basin plus any accumulation of...
Typical Model Studies01:30

Typical Model Studies

Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
Design Example: Creating a Hydraulic Model of a Dam Spillway01:21

Design Example: Creating a Hydraulic Model of a Dam Spillway

Scaled hydraulic models of dam spillways provide a practical way to replicate and study the intricate flow dynamics of these structures. Often built to a 1:15 ratio, these models allow for observing critical water behavior, such as velocity distribution, flow patterns, and energy dissipation.
Gradually Varying Flow01:29

Gradually Varying Flow

Gradually varying flow (GVF) in open channels describes situations where water depth changes slowly along the channel due to factors like non-uniform bed slope, channel shape variations, or obstructions. This flow type occurs when the depth adjusts gradually to balance gravitational forces, shear forces, and energy requirements, resulting in a low rate of depth change.Characteristics of Gradually Varying FlowGVF is commonly observed in natural streams, rivers, and canals, where flow depth...
Rapidly Varying Flow01:24

Rapidly Varying Flow

Rapidly varying flow (RVF) in open channels is characterized by abrupt changes in flow depth over a short distance, with the rate of depth change relative to distance often approaching unity. These flows are inherently complex due to their transient and multi-dimensional nature, making exact analysis difficult. However, approximate solutions using simplified models provide valuable insights into their behavior.Key Features of Rapidly Varying FlowRVF is commonly observed in scenarios involving...

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Updated: May 12, 2026

Examining Local Network Processing using Multi-contact Laminar Electrode Recording
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ローカル・フィールド・ポテンシャルを用いた猿の外層皮質における視覚信号処理のワーキング・メモリ・モジュレーションの調査のためのプロトコル

Majid Roshanaei1, Mohammad Reza Daliri1, Zahra Bahmani2

  • 1Neuroscience & Neuroengineering Research Lab, Biomedical Engineering Department, School of Electrical Engineering, Iran University of Science and Technology (IUST), Narmak, Tehran 16846-13114, Iran.

STAR protocols
|August 27, 2025
PubMed
まとめ

この研究では 作業記憶が脳の視覚処理に 影響する様子を調べるためのプロトコルの概要です 空間的な作業記憶のタスク中に 神経活動を記録する方法を詳細に説明しています

キーワード:
行動認知神経科学神経科学

さらに関連する動画

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Concurrent Recording of Co-localized Electroencephalography and Local Field Potential in Rodent
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Concurrent Recording of Co-localized Electroencephalography and Local Field Potential in Rodent

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関連する実験動画

Last Updated: May 12, 2026

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科学分野:

  • 神経科学
  • 認知神経科学
  • 霊長類の研究

背景:

  • 外層皮質は視覚信号処理に不可欠です
  • 作業記憶のような認知状態が 神経活動に与える影響を 理解することが重要です

研究 の 目的:

  • 視覚信号処理に対するワーキングメモリの影響を調査するための詳細なプロトコルを提示する.
  • 作業記憶の負荷下での視覚刺激に対する神経データの記録と分析のための方法論を確立する.

主な方法:

  • 空間的な作業記憶のタスクが 猿のために設計されました
  • ローカル・フィールド・ポテンシャル (LFP) とスパイキング・アクティビティは,中側側頭葉 (MT) のニューロンから記録された.
  • 視覚信号の到着時間を決定するために,試験間一貫性 (ITC) を使用してLFPデータの事前処理と分析が行われました.

主要な成果:

  • このプロトコルは,外層皮質に視覚信号の到着時間を測定することができます.
  • 作業記憶が神経の反応を どう調節するかを 調べることができます

結論:

  • このプロトコルは,作業記憶と視覚知覚の相互作用を研究するための枠組みを提供します.
  • 感覚処理の認知制御を支える 神経学的メカニズムに関する将来の研究を容易にする.