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Experimental and modeling investigations into microcircuit, cellular and subcellular determinants of hippocampal ensemble recruitment to contextual representations

Experimental and modeling investigations into microcircuit, cellular and subcellular determinants of hippocampal ensemble recruitment to contextual representations
对海马体集合招募到情境表征的微电路、细胞和亚细胞决定因素的实验和建模研究
批准号:
10535439
负责人:
Attila Losonczy
金额:
$64.71万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-01-01 至 2025-11-30

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中文摘要
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英文摘要
Although neuroscience has recently provided a great deal of information about how neurons represent and encode behaviorally relevant information at the population level, the fundamental question of how individual neurons are selected and recruited to memory coding ensembles has been difficult to address. Our group has been at the forefront of developing experimental methods that allow high-resolution monitoring of identified neurons, monitoring subcellular events in dendrites and axons, all of which can now be done in awake behaving animals. We propose to use these experimental methods in combination with circuit modeling to provide a deep understanding of how the neurons in the mouse hippocampus are recruited to neural ensembles during contextual memory encoding. Because much is known about the excitatory and inhibitory cell types involved and their network connections at the main CA1 output node of the rodent hippocampus, this circuit represents a tractable target for the first major effort to elucidate the microcircuit/cellular/subcellular mechanisms of cell- selection at a mechanistic level comparable to that achieved in the study of simple invertebrate systems. Aim 1 is aimed at characterizing collective inhibitory dynamics in CA1 during contextual learning. Aim 2 deals with the events that occur in cell bodies and dendrites of CA1 pyramidal cells during contextual leaning, including targeted manipulation in identified inhibitory cells types and understanding the fundamental network architecture by which cellular activity patterns conducive to memory encoding are regulated. Aim 3 deals with how the information that is encoded during contextual learning converges onto individual CA1 pyramidal cells during contextual learning. Finally, Aim 4 builds upon recent work indicating that CA1 pyramidal cells can be reliably recruited to memory coding ensembles through a plasticity mechanism that requires dendritic spikes and somatic bursting activity. We will use optogenetic means to create artificial firing fields in neurons and determine whether these cells can encode context-related and reinforcement related signals; we will also interfere with local circuit inhibition to determine whether cell selection through plasticity is regulated by inhibition. Throughout the proposal we will leverage unprecedentedly close interplay between experiment and computation by using a biophysically detailed model of the hippocampal CA1 microcircuit. To the extent that the model can account for the experimental observations, we can use it to understand underlying network principles and design interventional experiments to validate this understanding. To the extent that the model cannot explain results, it will help point us to aspects of network function that require further elucidation. Taken together, Aims 1-4 provide a tractable path to a major breakthrough in understanding how cognitively important neural activity dynamics are generated at the microcircuit-, cellular- and subcellular-levels.
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Activity-dependent endocannabinoid control in epilepsy
  • 批准号:
    10639147
  • 项目类别:
  • 资助金额:
    $59.93万
  • 财政年份:
    2023
  • 负责人:
    Attila Losonczy
  • 依托单位:
2023 NINDS Landis Mentorship Award - Administrative Supplement to NS121106 Control of Axon Initial Segment in Epilepsy
  • 批准号:
    10896844
  • 项目类别:
  • 资助金额:
    $15.66万
  • 财政年份:
    2023
  • 负责人:
    Attila Losonczy
  • 依托单位:
Local Circuit Control of Rapid Plasticity and Tunable Ensemble Formation in the Hippocampus
Control of Axon Initial Segment in Epilepsy
  • 批准号:
    10383771
  • 项目类别:
  • 资助金额:
    $64.62万
  • 财政年份:
    2021
  • 负责人:
    Attila Losonczy
  • 依托单位:
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