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相关概念视频

Working Memory01:24

Working Memory

137
Working memory refers to a combination of components, including short-term memory and attention, that allow an individual to hold information temporarily as we perform cognitive tasks. It is an essential cognitive function that enables the execution of complex tasks such as problem-solving, comprehension, and reasoning. Unlike short-term memory, which simply involves the storage of information for a brief period, working memory involves the active manipulation and processing of this...
137
Chunking and Rehearsal in Sensory Memory01:22

Chunking and Rehearsal in Sensory Memory

165
Improving short-term memory can be achieved through techniques like chunking and rehearsal. Chunking involves organizing information into larger, more manageable units. This technique is particularly useful for information that exceeds the typical memory span of between five and nine items. For instance, logging into an online account with a password like "ta89vq0179gz" involves grouping letters and numbers into three chunks—ta89, vq01, and 79gz. It makes large amounts of...
165
Higher Mental Functions of Brain: Learning and Memory01:26

Higher Mental Functions of Brain: Learning and Memory

679
Memory is one of the most vital higher mental functions of the brain. Memory is closely related to learning because it enables us to retain information and experiences from our past to use them in our present life. It also helps us to remember facts, events, and skills, such as riding a bike or swimming. There are two types of memory — declarative memory, which involves memorizing facts or events, and procedural memory, which enables us to remember how to do something like writing or...
679
Storage01:23

Storage

71
A schema is a mental framework that helps individuals organize and interpret information. Schemata, formed from previous experiences, influence how we process new information: how we encode it, the inferences we make, and how we retrieve it. For instance, a schema for what a typical classroom looks like might include desks, a teacher's desk, a whiteboard, and students in such an environment. This expectation helps us quickly understand and navigate new classrooms without needing to analyze...
71
Interference and Decay01:16

Interference and Decay

110
Forgetting is a complex cognitive phenomenon influenced by several factors, among which interference and decay are particularly prominent. These processes explain why individuals often struggle to retrieve specific information from memory, leading to lapses in recall that can be observed in everyday situations.
Interference occurs when competing memories hinder the retrieval of particular information. It can be classified into two types: proactive and retroactive interference. Proactive...
110
Elaborative Rehearsals01:07

Elaborative Rehearsals

80
Elaborative rehearsal is a crucial cognitive strategy that strengthens information encoding in long-term memory by making meaningful connections between new data and pre-existing knowledge. This approach contrasts with maintenance rehearsal, which involves simple repetition without delving into the significance of the information. While maintenance rehearsal might temporarily keep information active in short-term memory, it is less effective for long-term retention.
The effectiveness of...
80

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相关实验视频

Updated: Jun 7, 2025

A Lateralized Odor Learning Model in Neonatal Rats for Dissecting Neural Circuitry Underpinning Memory Formation
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一个基于循环神经网络的工作记忆模型,使用强化学习.

Mengyuan Wang1, Yihong Wang1, Xuying Xu1

  • 1Institute for Cognitive Neurodynamics, Center for Intelligent Computing, School of Mathematics, East China University of Science and Technology, 130 Meilong Road, Shanghai, 200237 China.

Cognitive neurodynamics
|November 18, 2024
PubMed
概括

这项研究使用一个使用强化学习训练的循环神经网络来建模空间工作记忆. 模型 模型的模型

科学领域:

  • 计算神经科学是一种计算神经科学.
  • 认知神经科学是一种认知神经科学.
  • 机器学习 机器学习

背景情况:

  • 前额叶皮层 (PFC) 神经元表现出动态的单个单元活动,但稳定的人口编码工作记忆.
  • 在工作记忆中这种PFC活动背后的神经计算机制仍然不清楚.
  • 了解神经网络动态对于破译工作记忆过程至关重要.

研究的目的:

  • 通过一种新的计算方法探索工作记忆的神经计算机制.
  • 使用循环神经网络 (RNN) 模型模拟空间工作记忆任务.
  • 研究RNN活动模式与前额叶皮层神经元活动的关系.

主要方法:

  • 使用强化学习训练了一种具有决策和基线网络的循环神经网络模型.
  • 该模型学习了一个空间工作记忆任务,涉及刺激信息维护.
  • 分析单位和人口活动动态,包括时间动态和低维编码.

主要成果:

  • RNN模型成功地执行了空间工作记忆任务.
  • 模型单元活动显示时间动态和偏好的方向选择性,反映了PFC神经元活动.
  • 人口活动稳定地在低维子空间中编码了刺激信息,随着学习而改善.
关键词:
人口编码的编码.前额叶皮层前额叶皮层.经常性的神经网络.强化学习是一种强化学习.空间工作记忆空间工作记忆

更多相关视频

Working Memory Training for Older Participants: A Control Group Training Regimen and Initial Intellectual Functioning Assessment
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Working Memory Training for Older Participants: A Control Group Training Regimen and Initial Intellectual Functioning Assessment

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Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
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相关实验视频

Last Updated: Jun 7, 2025

A Lateralized Odor Learning Model in Neonatal Rats for Dissecting Neural Circuitry Underpinning Memory Formation
10:42

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Published on: August 18, 2014

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Working Memory Training for Older Participants: A Control Group Training Regimen and Initial Intellectual Functioning Assessment
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Working Memory Training for Older Participants: A Control Group Training Regimen and Initial Intellectual Functioning Assessment

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Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
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Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

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结论:

  • 开发的RNN模型为空间工作记忆任务提供了可行的模拟.
  • 该模型提供了关于PFC神经元如何通过人口动态实现稳定的信息表示的见解.
  • 这种方法增强了对工作记忆和PFC功能的神经计算的理解.