Modeling the Molecular Networks that Underlie the Formation and Consolidation of Memory

模拟记忆形成和巩固的分子网络

基本信息

  • 批准号:
    10607560
  • 负责人:
  • 金额:
    $ 50.11万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2018
  • 资助国家:
    美国
  • 起止时间:
    2018-02-15 至 2027-12-31
  • 项目状态:
    未结题

项目摘要

PROJECT SUMMARY/ABSTRACT This proposal will test the hypothesis that learning and memory can be improved by using computationally designed training protocols that optimize the interactions among kinase cascades and transcription factors involved in the induction of long-term memory (LTM). Three model systems will be used: long-term sensitization, fear conditioning and extinction, and inhibitory avoidance learning. This hypothesis is based on our previous work demonstrating that computationally designed protocols maximizing the overlap of activities between protein kinase A (PKA) and the mitogen-activated protein kinase (MAPK) isoform termed extracellular signal-regulated kinase (ERK) enhance long-term synaptic facilitation (LTF) and LTM for sensitization, as well as the acquisition and extinction of fear learning. This proposal has two key innovative aspects. First, we utilize a novel, multi- disciplinary strategy to enhance learning and improve different types of memory retrieval. Pharmacological interventions to improve learning and memory, and rescue memory deficits, have been ongoing for many decades, but these approaches rely on trial-and-error and are highly nonspecific. In contrast, the strategy we have developed, combining biologically realistic computational models with empirical approaches, enables us to efficiently and systematically explore the molecular processes that underlie different types of long-term synaptic plasticity, and predict individual training protocols to optimize learning and memory. Second, to our knowledge, our groups are the first to develop a computational model describing the possible mechanism underlying infantile learning and the apparent rapid forgetting associated with infantile amnesia. Our simulations suggest that altered regulation of basal activities of kinases and transcription factors in infant animals contributes to fast forgetting of infantile memory. Specific hypotheses to be tested by simulation and in vivo experiments include: Aim 1) LTF and LTM for sensitization can be prolonged up to 7 days by novel computationally designed training protocols; Aim 2) Computationally designed protocols based on the dynamics of amygdala kinases can enhance the acquisition and extinction of conditioned fear memories; and Aim 3) The apparent rapid forgetting of infantile memory observed in an inhibitory avoidance paradigm can be overcome by computationally designed protocols based on the dynamics of hippocampal kinases. We believe that these predictions, combined with concurrent empirical tests, will provide a proof of principle for an efficient strategy to enhance learning and improve memory retrieval. Our study may have clinical relevance for interventions aiming at facilitating memory formation in a series of psychiatric disorders associated with cognitive impairment in humans, as well as for improving extinction-based therapies in patients suffering from anxiety-related disorders.
项目总结/文摘

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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John H Byrne其他文献

John H Byrne的其他文献

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{{ truncateString('John H Byrne', 18)}}的其他基金

A novel approach to analyzing functional connectomics and combinatorial control in a tractable small-brain closed-loop system
一种在易处理的小脑闭环系统中分析功能连接组学和组合控制的新方法
  • 批准号:
    10700737
  • 财政年份:
    2020
  • 资助金额:
    $ 50.11万
  • 项目类别:
A novel approach to analyzing functional connectomics and combinatorial control in a tractable small-brain closed-loop system
一种在易处理的小脑闭环系统中分析功能连接组学和组合控制的新方法
  • 批准号:
    10058915
  • 财政年份:
    2020
  • 资助金额:
    $ 50.11万
  • 项目类别:
Modeling the Molecular Networks that Underlie the Formation and Consolidation of Memory
模拟记忆形成和巩固的分子网络
  • 批准号:
    10083237
  • 财政年份:
    2018
  • 资助金额:
    $ 50.11万
  • 项目类别:
Analyses of the Distributed Representation of Associative-Learning in an Identified Circuit Using a Combination of Single-Cell Electrophysiology and Multicellular Voltage-Sensitive Dye Recordings
结合单细胞电生理学和多细胞电压敏感染料记录分析已识别电路中联想学习的分布式表示
  • 批准号:
    10083235
  • 财政年份:
    2018
  • 资助金额:
    $ 50.11万
  • 项目类别:
Modeling the Molecular Networks that Underlie the Formation and Consolidation of Memory
模拟记忆形成和巩固的分子网络
  • 批准号:
    10317000
  • 财政年份:
    2018
  • 资助金额:
    $ 50.11万
  • 项目类别:
Analyses of the Distributed Representation of Associative-Learning in an Identified Circuit Using a Combination of Single-Cell Electrophysiology and Multicellular Voltage-Sensitive Dye Recordings
结合单细胞电生理学和多细胞电压敏感染料记录分析已识别电路中联想学习的分布式表示
  • 批准号:
    10317049
  • 财政年份:
    2018
  • 资助金额:
    $ 50.11万
  • 项目类别:
Analyses of the Distributed Representation of Associative-Learning in an Identified Circuit Using a Combination of Single-Cell Electrophysiology and Multicellular Voltage-Sensitive Dye Recordings
结合单细胞电生理学和多细胞电压敏感染料记录分析已识别电路中联想学习的分布式表示
  • 批准号:
    10539225
  • 财政年份:
    2018
  • 资助金额:
    $ 50.11万
  • 项目类别:
Modeling Gene Regulation Essential for Long-Term Plasticity
对长期可塑性至关重要的基因调控建模
  • 批准号:
    8652842
  • 财政年份:
    2011
  • 资助金额:
    $ 50.11万
  • 项目类别:
Modeling Gene Regulation Essential for Long-Term Plasticity
对长期可塑性至关重要的基因调控建模
  • 批准号:
    8185497
  • 财政年份:
    2011
  • 资助金额:
    $ 50.11万
  • 项目类别:
Modeling Gene Regulation Essential for Long-Term Plasticity
对长期可塑性至关重要的基因调控建模
  • 批准号:
    8464817
  • 财政年份:
    2011
  • 资助金额:
    $ 50.11万
  • 项目类别:

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