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相关概念视频

Introduction to Cognitive Psychology01:20

Introduction to Cognitive Psychology

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Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem-solving, as well as other cognitive processes. Cognitive psychology studies how information is processed and manipulated in remembering, thinking, and knowing.
This field emerged in the mid-20th century, following a period dominated by behaviorism, which...
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Cognitive Enhancers: Cholinesterase Inhibitors and NMDA Receptor Antagonists01:30

Cognitive Enhancers: Cholinesterase Inhibitors and NMDA Receptor Antagonists

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Cognitive enhancers, also known as "smart drugs," are substances used to enhance memory, mental alertness, and concentration. These can be natural or synthetic and improve cognition in conditions like Alzheimer's disease (AD) and other neurodegenerative diseases. Some common examples include caffeine, amphetamines, methylphenidate, modafinil, arecoline, donepezil, vortioxetine, and piracetam. These enhancers work on the principle of synaptic plasticity and altered circuit function.
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Cognitive Learning01:21

Cognitive Learning

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Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
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Survival Tree01:19

Survival Tree

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Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
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Role of Cerebellum and Prefrontal Cortex in Memory01:14

Role of Cerebellum and Prefrontal Cortex in Memory

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The cerebellum, while traditionally associated with motor control, also plays a crucial role in memory, particularly in procedural memory, which involves learning motor tasks that become automatic through repetition. For example, studies have shown that when the cerebellum is damaged, individuals or animals lose the ability to learn conditioned motor responses, such as the conditioned eye-blink response in classical conditioning experiments with rabbits. This study demonstrates the...
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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

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使用ML来预测认知功能的性能使用ML的陷

Gianna Kuhles1,2, Sami Hamdan3,4, Stefan Heim5,6,7

  • 1Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany. g.kuhles@fz-juelich.de.

Scientific reports
|October 30, 2025
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概括
此摘要是机器生成的。

机器学习对认知能力的预测可能会因混变量而有缺陷. 这项研究表明,年龄,性别和教育如何膨胀执行职能预测的准确性,突出了需要仔细控制ML管道的需要.

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Assessment of Age-related Changes in Cognitive Functions Using EmoCogMeter, a Novel Tablet-computer Based Approach
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科学领域:

  • 认知神经科学 认知神经科学
  • 计算语言学 计算语言学
  • 心理测量 心理测量 心理测量

背景情况:

  • 机器学习 (ML) 经常用于预测认知能力.
  • 机器学习模型的实施和解释带有风险,特别是来自混变量.

研究的目的:

  • 为了说明由于混变量导致的ML预测错误结论的风险.
  • 为了证明潜在的错误漏洞在预测执行功能 (EF) 使用prosodic特征.

主要方法:

  • 健康的参与者 (n=231) 完成了语言任务和EF测试.
  • ML模型预测了使用264个体特征的EF性能,控制年龄,性别和教育.
  • 深入分析检查了预测准确度的潜在漏洞.

主要成果:

  • ML模型最初显示了执行功能 (EF) 变量 (Trail Making Test) 的合理预测性能.
  • 深入分析显示,由于混杂因素 (年龄,性别,教育) 和目标EF性能之间的显著关系,预测准确度被膨胀.
  • 确定了"混泄漏"的证据,扭曲了体特征的真正预测能力.

结论:

  • 混变量在ML驱动的认知能力预测中存在重大风险.
  • 在ML管道中,严格控制混变量至关重要,以避免错误的结论.
  • 研究人员必须小心潜在的陷,并仔细解释ML预测结果.