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相关概念视频

Trait Centrality01:21

Trait Centrality

171
Trait centrality refers to the degree to which a particular characteristic influences the overall impression of an individual. Some traits exert a disproportionately strong impact on perception, shaping how people interpret other attributes of a person. Solomon Asch first systematically studied this phenomenon in 1946.Asch’s Experiment on Trait CentralityAsch's seminal study demonstrated the centrality of certain traits through a controlled experiment. Participants were presented with a...
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Classification of Neurotransmitters01:30

Classification of Neurotransmitters

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Neurotransmitters play a crucial role in the communication between neurons in the autonomic nervous system. Neurons in the autonomic nervous system can be cholinergic or adrenergic depending on the neurotransmitters synthesized. Cholinergic neurons use acetylcholine as their primary neurotransmitter. This includes all the preganglionic fibers of the sympathetic and pre- and postganglionic fibers of the parasympathetic nervous systems. In addition, neurons of the somatic nervous system also use...
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Theory of Attribution I: Correspondent Inference Theory01:15

Theory of Attribution I: Correspondent Inference Theory

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Correspondent inference theory, proposed by Jones and Davis in 1965, seeks to explain how individuals infer stable personality traits from observed behaviors. It suggests that people attribute actions to underlying dispositions rather than external circumstances, particularly when the behavior appears intentional and socially significant.Voluntary Behavior and Dispositional AttributionAccording to this theory, individuals are more likely to attribute behavior to personal traits when it appears...
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Relationship Formation02:12

Relationship Formation

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What do you think is the single most influential factor in determining with whom you become friends and whom you form romantic relationships? You might be surprised to learn that the answer is simple: the people with whom you have the most contact. This most important factor is proximity. You are more likely to be friends with people you have regular contact with. For example, there are decades of research that shows that you are more likely to become friends with people who live in your dorm,...
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Functional Classification of Joints01:09

Functional Classification of Joints

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Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses  or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
An...
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Aggregates Classification01:29

Aggregates Classification

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Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
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相关实验视频

Updated: Jan 14, 2026

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
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Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

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用Shapley值描述叙事分类中的动态功能连接子网络贡献的特征.

Aurora Rossi1, Yanis Aeschlimann2, Emanuele Natale1

  • 1COATI, Université Côte d'Azur, INRIA, CNRS, I3S, Sophia Antipolis, France.

Network neuroscience (Cambridge, Mass.)
|October 27, 2025
PubMed
概括
此摘要是机器生成的。

这项研究使用机器学习在叙事任务中分析大脑网络,揭示了理解内容涉及自上而下的和自下而上的过程,特别是来自顶部子网络.

关键词:
卷积神经网络是一种卷积神经网络.动态功能连接的功能连接.机器学习 机器学习叙述 叙述 叙述 叙述沙普利的价值是什么意思功能磁力共振成像 (fMRI) 是一种

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Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
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Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

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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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相关实验视频

Last Updated: Jan 14, 2026

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
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Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

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Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
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Modeling the Functional Network for Spatial Navigation in the Human Brain
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科学领域:

  • 神经科学是一个神经科学.
  • 认知科学 认知科学
  • 机器学习在脑成像中的应用

背景情况:

  • 功能磁共振成像 (fMRI) 对于研究大脑活动至关重要.
  • 动态功能连接分析模型模拟时间大脑网络.
  • 了解叙事理解需要探索大脑网络动态.

研究的目的:

  • 在叙事任务中模拟动态功能连接,作为时间大脑网络.
  • 使用监督机器学习模型对叙事模式和内容进行分类.
  • 通过使用Shapley值来调查子网络对叙事理解的贡献.

主要方法:

  • 在叙事任务期间,从fMRI数据中建模动态功能连接.
  • 采用监督机器学习模型来对叙事特征进行分类.
  • 使用Shapley值来分析Yeo分片中的子网络贡献.

主要成果:

  • 通过机器学习模型成功分类叙事模式和内容.
  • 确定了特定的子网络对理解叙事模式和内容的贡献.
  • 证明了顶子网络在叙事理解中的参与.

结论:

  • 这项研究为叙事任务期间大脑的功能方面提供了新的见解.
  • 叙述的图表表现可以从由顶子网络驱动的自下而上的处理中出现.
  • 这些发现挑战了叙事理解仅仅依赖于自上而下的过程和事先存在的知识的观念.