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相关概念视频

Uncertainty: Overview00:59

Uncertainty: Overview

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In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
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Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

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An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
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Cerebral Hemispheres01:05

Cerebral Hemispheres

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The human brain, a complex organ, is functionally divided into two cerebral hemispheres—left and right. These hemispheres are interconnected by a structure of paramount importance, the corpus callosum. This substantial bundle of neural fibers is not just a bridge between the hemispheres but a crucial element for the brain's comprehensive functioning. It enables efficient communication between the two hemispheres, allowing each side of the brain to control and receive sensory and motor...
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Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

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The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
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Cognitivism01:17

Cognitivism

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Cognitive psychology emerged as a significant field in the mid-20th century. It focused on understanding humans' internal mental processes. This approach emphasizes how people perceive, remember, think, and solve problems—elements critical to human cognition.
Previously dominated by behaviorism, which prioritized observable behaviors and largely ignored mental processes, psychology transformed in the 1950s. Cognitive psychologists argue that understanding how we think and process...
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Uncertainty: Confidence Intervals00:54

Uncertainty: Confidence Intervals

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The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor...
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相关实验视频

Updated: Sep 9, 2025

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
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面对面的枢纽利用概率表达和集成的不确定性来引导认知灵活性

Stephanie C Leach, Hannah Hollow, Jiefeng Jiang

    bioRxiv : the preprint server for biology
    |September 5, 2025
    PubMed
    概括

    大脑使用不同的神经区域来整合内部的信念和外部的线索. 通过动态调整大脑连接, 实现灵活的行为.

    科学领域:

    • 神经科学
    • 认知科学
    • 计算模型

    背景情况:

    • 适应性行为依赖于从多个来源整合信息,通常是随机和不确定的.
    • 整合内部和外部噪音信息的神经和计算机制在很大程度上是未知的.

    研究的目的:

    • 解释大脑系统如何整合内部维护和外部提示的随机信息来指导行为.
    • 为分析信息整合引入计算神经成像框架.

    主要方法:

    • 收集了健康成年人的神经成像数据.
    • 开发了一个计算模型来估计试验对试验的信念,并将其整合到联合概率分布中.
    • 使用联合分布的来追踪信念,预测错误和更新动态的量化不确定性.

    主要成果:

    • 不同的大脑区域编码潜伏状态的信念 (前部中额头,中背丘脑,下叶) 和感知信念 (侧侧角部区域,内角部,前中心部).
    • 整合的信息和它的汇聚在前侧侧 (中间前侧,内侧).
    • 用感觉,运动,前运动和预测错误电路进行适应性重新配置的连接.

    结论:

    • 面对面的中心集成并解决分布式不确定性以指导灵活的行为.

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  • 这些发现揭示了前端对象系统如何实现多个噪音输入的认知集成.
  • 不同的神经群体对内部和外部信息进行编码,然后由前端平行网络集成.