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Social Proof00:52

Social Proof

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Social proof is a form of persuasion based on comparison and conformity. People compare their behavior and actions to what others are doing and will change to conform to do what their peers do.
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The Evidence for Evolution02:55

The Evidence for Evolution

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Genetic variations accumulating within populations over generations give rise to biological evolution. Evolutionary changes can result in the formation of novel varieties and entire new species. These changes are responsible for the diverse forms of life inhabiting the planet. The evidence for evolution suggests that all living organisms descended from common ancestors.
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The Uncertainty Principle04:08

The Uncertainty Principle

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Werner Heisenberg considered the limits of how accurately one can measure properties of an electron or other microscopic particles. He determined that there is a fundamental limit to how accurately one can measure both a particle’s position and its momentum simultaneously. The more accurate the measurement of the momentum of a particle is known, the less accurate the position at that time is known and vice versa. This is what is now called the Heisenberg uncertainty principle. He...
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Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

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Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.
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The Pauli Exclusion Principle03:06

The Pauli Exclusion Principle

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The arrangement of electrons in the orbitals of an atom is called its electron configuration. We describe an electron configuration with a symbol that contains three pieces of information:
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The Aufbau Principle and Hund's Rule03:02

The Aufbau Principle and Hund's Rule

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To determine the electron configuration for any particular atom, we can build the structures in the order of atomic numbers. Beginning with hydrogen, and continuing across the periods of the periodic table, we add one proton at a time to the nucleus and one electron to the proper subshell until we have described the electron configurations of all the elements. This procedure is called the aufbau principle, from the German word aufbau (“to build up”). Each added electron occupies the...
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相关实验视频

Updated: Feb 7, 2026

A Protocol for the Administration of Real-Time fMRI Neurofeedback Training
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通过协同适应性培训增强fMRI解码的神经反:模拟和原则证明证据.

Najmeddine Abdennour1, Pedro Margolles2, David Soto3

  • 1Basque Center on Cognition, Brain and Language, Paseo Mikeletegi 69, 2nd Floor, 20009, San Sebastian, Spain. n.abdennour@bcbl.eu.

Neuroinformatics
|February 5, 2026
PubMed
概括

这项研究引入了一种共同适应方法,以改善实时fMRI神经反 (DecNef) 培训. 这种自适应解码器增强了参与者实现目标大脑状态的能力,提高了DecNef的精度和可靠性.

关键词:
同适应 同适应解码的神经反解码机器学习. 机器学习.实时功能磁共振成像实时功能磁共振成像

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科学领域:

  • 神经科学是一个神经科学.
  • 机器学习 机器学习
  • 生物医学工程 生物医学工程

背景情况:

  • 神经反训练,特别是基于fMRI的解码神经反 (DecNef),在参与者学习控制特定的大脑模式时面临挑战.
  • 解码器训练数据和实时神经反数据之间的差异,包括噪音和不同的环境,有助于学习困难.

研究的目的:

  • 开发和验证一个共同适应程序,以提高参与者在DecNef培训中的表现.
  • 提高DecNef协议的精度和可靠性,以准特定的大脑表示.

主要方法:

  • 使用标准机器学习算法与实时自适应解码器开发了协同适应程序.
  • 在以前的DecNef数据集上使用模拟测试了该程序.
  • 通过DecNef培训课程的实时fMRI数据验证了同适应方法.

主要成果:

  • 模拟表明解码器协同适应在神经反训练期间显著提高了性能.
  • 漂移分析证实了共适应解码器在整个培训期间的稳定性.
  • 实时fMRI数据提供了概念证明证据,即同适应增强了参与者诱导目标大脑状态的能力.

结论:

  • 通过共同适应创建的个性化解码器可以提高DecNef培训协议的有效性.
  • 这种方法为针对特定的大脑表示提供了更高的精度和可靠性,具有潜在的翻译研究应用.
  • 开发的工具是科学界公开使用的.