Mechanisms of neural circuit dynamics in working memory anddecision-making

工作记忆和决策中的神经回路动力学机制

基本信息

  • 批准号:
    9983177
  • 负责人:
  • 金额:
    $ 306.24万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2017
  • 资助国家:
    美国
  • 起止时间:
    2017-09-28 至 2022-07-31
  • 项目状态:
    已结题

项目摘要

Project Summary Working memory, the ability to temporarily hold multiple pieces of information in mind for manipulation, is central to virtually all cognitive abilities. Recent technical advances have opened an unprecedented opportunity to comprehensively dissect the neural circuit mechanisms of this ability across multiple brain areas. The task to be studied is a common form of decision-making that is based on the gradual accumulation of sensory evidence and thus relies on working memory. A team of leading experts propose to investigate the neural basis of this behavior using the latest techniques, including virtual reality, high-throughput automated behavioral training, large-scale cellular-resolution imaging in behaving rodents, manipulation of neural activity in specific brain areas and cell types, and automated anatomical reconstruction. In particular, the researchers will identify key brain regions that are required for this decision task through systematic, temporally specific inactivations via optogenetics technology, across all of dorsal cortex and in key subcortical areas, and use quantitative model-fitting to evaluate the effects. They will use state-of-the-art two-photon calcium imaging methods and electrophysiology to characterize the information flow in many individual neurons within these brain areas during the task. In addition, they will use cutting-edge anatomical reconstructions and new functional connectivity methods, within and across brain regions, to evaluate the interactions of these physiologically characterized neurons. The long-term goal of this project is to arrive at a complete, brain-wide understanding of the cellular and circuit mechanisms of activity dynamics related to working memory. Finally, they will use sophisticated computational methods to incorporate this new understanding into a realistic circuit model that will support a tightly integrated process of model-guided experimental design, in which the model suggests the most informative experiments and their results are then fed back to improve the model’s fidelity. This process is expected to produce the most accurate and detailed multi-brain-region biophysical circuit model of a cognitive process in existence. In addition, the proposed research will enable researchers to generate and test a variety of hypotheses about the neural basis of evidence accumulation, working memory, and decision-making. Taken together, these achievements will represent a crucial step toward a mechanistic understanding of how the brain works with information.
项目摘要 工作记忆是一种在头脑中暂时保存多条信息以进行操作的能力, 对几乎所有认知能力都至关重要最近的技术进步开启了一个前所未有的 有机会全面剖析这种能力在多个大脑中的神经回路机制 地区要研究的任务是一种常见的决策形式,它是基于渐进的 感官证据的积累,因此依赖于工作记忆。一个由顶尖专家组成的团队建议, 使用最新的技术,包括虚拟现实, 高通量自动化行为训练,行为啮齿动物的大规模细胞分辨率成像, 操纵特定脑区和细胞类型中的神经活动,以及自动解剖 重建特别是,研究人员将确定做出这一决定所需的关键大脑区域。 任务通过系统的,时间特异性失活,通过光遗传学技术,在所有的背 皮质和关键皮质下区域,并使用定量模型拟合来评估效果。他们将使用 最先进的双光子钙成像方法和电生理学来表征信息 在这些大脑区域内的许多单个神经元中流动。此外,他们将使用 尖端的解剖重建和新的功能连接方法,在大脑内和跨大脑 区域,以评估这些生理特征的神经元的相互作用。的长期目标 这个项目是为了达到一个完整的,大脑范围内的细胞和电路机制的理解, 与工作记忆相关的活动动态。最后,他们将使用复杂的计算方法, 将这一新的理解纳入一个现实的电路模型,将支持紧密集成的 模型引导的实验设计过程,其中模型提供了最丰富的信息 然后反馈实验及其结果以提高模型的保真度。预计这一进程将 产生认知过程的最准确和详细的多脑区生物物理电路模型 存在。此外,拟议的研究将使研究人员能够生成和测试各种 关于证据积累、工作记忆和决策的神经基础的假设。 总的来说,这些成就将代表着朝着机械地理解如何做到这一点迈出了关键一步。 大脑处理信息

项目成果

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Carlos D Brody其他文献

Carlos D Brody的其他文献

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{{ truncateString('Carlos D Brody', 18)}}的其他基金

P2: Geometry of Neural Representations and Dynamics
P2:神经表征和动力学的几何
  • 批准号:
    10705964
  • 财政年份:
    2023
  • 资助金额:
    $ 306.24万
  • 项目类别:
Mechanisms of neural circuit dynamics in working memory and decision-making
工作记忆和决策中的神经回路动力学机制
  • 批准号:
    10705962
  • 财政年份:
    2023
  • 资助金额:
    $ 306.24万
  • 项目类别:
C3: Behavior Automation
C3:行为自动化
  • 批准号:
    10705970
  • 财政年份:
    2023
  • 资助金额:
    $ 306.24万
  • 项目类别:
C1: Administrative
C1:行政
  • 批准号:
    10705968
  • 财政年份:
    2023
  • 资助金额:
    $ 306.24万
  • 项目类别:
C2: Data Science
C2:数据科学
  • 批准号:
    10705969
  • 财政年份:
    2023
  • 资助金额:
    $ 306.24万
  • 项目类别:
An experimental platform to investigate the neural mechanisms underlying flexible decision-making
研究灵活决策神经机制的实验平台
  • 批准号:
    10366077
  • 财政年份:
    2021
  • 资助金额:
    $ 306.24万
  • 项目类别:
Behavior Automation
行为自动化
  • 批准号:
    9983196
  • 财政年份:
    2017
  • 资助金额:
    $ 306.24万
  • 项目类别:
Administrative Core
行政核心
  • 批准号:
    9983201
  • 财政年份:
    2017
  • 资助金额:
    $ 306.24万
  • 项目类别:
Perturbations and Behavior
扰动和行为
  • 批准号:
    10247575
  • 财政年份:
    2017
  • 资助金额:
    $ 306.24万
  • 项目类别:
Behavior Automation
行为自动化
  • 批准号:
    10247578
  • 财政年份:
    2017
  • 资助金额:
    $ 306.24万
  • 项目类别:
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