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相关概念视频

Timing and Consequences on Behavior01:08

Timing and Consequences on Behavior

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In operant conditioning, the timing of reinforcement is crucial. For animals like rats and cats, immediate reinforcement (within a few seconds) is much more effective than delayed reinforcement. For example, a food reward for a rat needs to follow within 30 seconds of pressing a bar to be effective. 
Humans, however, can respond to delayed reinforcers. We often make decisions between immediate small rewards and delayed larger rewards. This ability to delay gratification is a significant...
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Reason and Intuition01:37

Reason and Intuition

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The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
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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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Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

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Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
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Purposive Learning01:22

Purposive Learning

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E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...
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In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. However, sometimes, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the...
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相关实验视频

Updated: Jan 14, 2026

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
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人类大脑整合了无条件和有条件的时间统计数据,以指导期望和行为.

Yiyuan Teresa Huang1,2,3, Zenas C Chao1

  • 1International Research Center for Neurointelligence (WPI-IRCN), UTIAS, The University of Tokyo, Tokyo, Japan.

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|October 23, 2025
PubMed
概括

我们的大脑整合了事件的多个时间预测,结合了一般和特定的时间统计数据. 这个过程涉及不同的大脑区域来编码和整合这些预测,揭示了层次化的时间感知网络.

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科学领域:

  • 认知神经科学 认知神经科学
  • 计算神经科学是一种神经科学.

背景情况:

  • 大脑使用基于概率分布的危险函数预测即将发生的事件时间.
  • 整合多个时间概率分布进行连贯预测仍然不清楚.

研究的目的:

  • 研究大脑如何整合无条件和条件时间预测.
  • 确定基层时间预测的基础的神经机制.

主要方法:

  • 开发了一个前期序列范式,并配对试验.
  • 使用危险函数表示无条件和有条件预测的模拟反应时间.
  • 分析了电脑电图 (EEG) 源信号.

主要成果:

  • 整合两种预测类型的行为模型最能解释反应时间.
  • 通过整合两个预测来最好地重建EEG源信号.
  • 无条件和条件预测分别被编码在后部和前部区域.
  • 右后带带皮带区域整合了这些预测.

结论:

  • 大脑整合多层次的时间信息进行预测.
  • 不同的神经网络支持对时间的层次预测编码.
  • 这为大脑的时间处理能力提供了洞察力.