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Cognitive and Molecular Challenges to Statistical Inference Across Healthy Aging.

Cognitive and Molecular Challenges to Statistical Inference Across Healthy Aging.
健康老龄化过程中统计推断的认知和分子挑战。
批准号:
10171740
负责人:
Matthew Nassar
金额:
$24.74万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-01 至 2023-05-31

项目摘要

项目成果

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中文摘要
翻译
考虑到寿命延长的趋势和年龄的增长,与糖尿病相关的认知能力下降是一个越来越重要的问题。 认知功能在确定神经退行性疾病风险中的重要性。尽管这很重要 尽管存在这个问题,但对介导它的认知和分子变化仍然知之甚少。虽然有竞争 在心理和分子水平上的认知老化介质理论,关于衰老的理论和 支持它们的研究通常集中在单一层次的分析上。我们对生物学基础的理解 随着行为的增长,这种划分变得不那么合理。相反,心理学理论应该受到限制, 已知的生物学,而生物学反过来又应该为心理学理论提供信息。这里我提出学习神经网络建模 和磁共振波谱(MRS)技术,以弥合人类心理学理论,一直是 我最近工作的重点是分子水平的理论,这是我在NIA的学士后培训的重点。我 我将以我最近的工作为基础,强调大脑面临的一个关键统计问题:如何选择性地汇集 信息跨相关源,但划分信息跨不相关的。我将仔细研究 和分子机制,允许有效的汇集和分区,以测试总体理论,由于 受损的谷氨酸和多巴胺信号,老年人在汇集相关来源的选择性缺陷, 信息.我将在两个独立的范式中检验这一理论:视觉工作记忆(K99)和学习与知觉 推理(R00)。在K99阶段的奖励,我将研究如何汇集信息,从视觉目标, 类似的特征可以1)提高有效记忆能力,2)通过神经网络模型实现,以及3)被削弱 通过模拟分子缺陷(谷氨酸,多巴胺,去甲肾上腺素)。这座认知和分子之间的桥梁 分析水平将用于测试年龄相关的记忆缺陷是否是由于效率低下的汇集和介导的 谷氨酸和多巴胺的分子缺陷(分别通过MRS和行为代理测量)。期间 R00阶段的奖励我将使用在K99阶段提供的神经网络和MRS中的训练来研究如何1) 汇集连续的信息片段会影响学习和感知偏差,2)有效的汇集和划分可以 通过神经网络模型实现,以及3)这些过程被特定的分子缺陷破坏。的 建立了统计特性(顺序合并和划分)、心理测量 (学习和感知偏差)和分子因素(谷氨酸,多巴胺和去甲肾上腺素信号水平)将被 用于测试学习和感知偏差中与年龄相关的差异是否反映了由局部 谷氨酸缺乏症(通过MRS测量)。总的来说,这项工作将有助于更深入,更详细的 了解心理和分子因素相互作用,以介导与年龄相关的认知能力下降。在 此外,K99培训将为我提供必要的工具,将心理和分子水平的分析联系起来, R00阶段将为我的独立研究实验室奠定基础,使我能够成功地开发出一种 科学生涯由实验驱动,建立和完善认知老化的统一理解。
英文摘要
Age-related cognitive decline is a problem of growing importance given the trend toward increased lifespan and the importance of cognitive function in determining risk for neurodegenerative disease. Despite the importance of this problem, the cognitive and molecular changes that mediate it are still poorly understood. While there are competing theories for the mediators of cognitive aging at both psychological and molecular levels, theories on aging and the research supporting them have typically focused on a single level of analysis. As our understanding of the biological basis for behavior grows, this divide becomes less sensible. Instead, psychological theory should be constrained according to its known biology, and biology should in turn inform psychological theory. Here I propose to learn neural network modeling and magnetic resonance spectroscopy (MRS) techniques in order to bridge human psychological theory that has been the focus of my recent work to the molecular level theory that was the focus of my post-baccalaureate training at the NIA. I will build from my recent work that highlights a key statistical problem faced by the brain: how to selectively pool information across relevant sources but partition information across irrelevant ones. I will closely examine the cognitive and molecular mechanisms that allow for efficient pooling and partitioning to test the overarching theory that, due to impaired glutamate and dopamine signaling, older adults develop a selective deficit in pooling relevant sources of information. I will test this theory in two separate paradigms: visual working memory (K99) and learning and perceptual inference (R00). During the K99 phase of the award I will examine how pooling information from visual targets with similar features can 1) improve effective memory capacity, 2) be achieved by a neural network model, and 3) be impaired by simulated molecular deficiencies (glutamate, dopamine, norepinephrine). This bridge between cognitive and molecular levels of analysis will be used to test whether age-related memory deficits are due to inefficient pooling and mediated by molecular deficits in glutamate and dopamine (as measured through MRS and behavioral proxy, respectively). During the R00 phase of the award I will use the training in neural networks and MRS provided in the K99 phase to examine how 1) pooling sequential pieces of information affects learning and perceptual bias, 2) efficient pooling and partitioning can be achieved by a neural network model and 3) these processes are disrupted by specific molecular deficiencies. The established relationships between statistical properties (sequential pooling and partitioning), psychological measurements (learning and perceptual bias) and molecular factors (glutamate, dopamine, and norepinephrine signaling levels) will be used to test whether age-related differences in learning and perceptual bias reflect deficient pooling mediated by local glutamate deficiency (as measured through MRS). Overall, this work will contribute a deeper and more detailed understanding of the psychological and molecular factors that interact to mediate age-related cognitive decline. In addition, the K99 training will provide me the tools necessary to link psychological and molecular levels of analysis and the R00 phase will build the foundations of my independent research laboratory allowing me to develop a successful scientific career driven by experiments that build and refine a unified understanding of cognitive aging.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
Adaptive Learning through Temporal Dynamics of State Representation.
通过状态表示的时间动态进行自适应学习。
DOI: 10.1523/jneurosci.0387-21.2022
发表时间: 2022
期刊: The Journal of neuroscience : the official journal of the Society for Neuroscience
影响因子: --
作者: [Razmi,Niloufar, Nassar,MatthewR]
通讯作者: Nassar,MatthewR
DOI: 10.7554/elife.62825
发表时间: 2021-04-30
期刊: eLife
影响因子: 7.7
作者: [Frömer R, Nassar MR, Bruckner R, Stürmer B, Sommer W, Yeung N]
通讯作者: Yeung N
Noise Correlations for Faster and More Robust Learning.
噪声相关性可实现更快、更稳健的学习。
DOI: 10.1523/jneurosci.3045-20.2021
发表时间: 2021
期刊: The Journal of neuroscience : the official journal of the Society for Neuroscience
影响因子: --
作者: [Nassar,MatthewR, Scott,Daniel, Bhandari,Apoorva]
通讯作者: Bhandari,Apoorva
Representational dynamics for flexible learning in complex environments
  • 批准号:
    10674993
  • 项目类别:
  • 资助金额:
    $58.86万
  • 财政年份:
    2022
  • 负责人:
    Matthew Nassar
  • 依托单位:
Representational dynamics for flexible learning in complex environments
  • 批准号:
    10818994
  • 项目类别:
  • 资助金额:
    $8.55万
  • 财政年份:
    2022
  • 负责人:
    Matthew Nassar
  • 依托单位:
Representational dynamics for flexible learning in complex environments
  • 批准号:
    10522159
  • 项目类别:
  • 资助金额:
    $59.81万
  • 财政年份:
    2022
  • 负责人:
    Matthew Nassar
  • 依托单位:
Dissociating spatial and cognitive grid representations in the brain
  • 批准号:
    10655777
  • 项目类别:
  • 资助金额:
    $16.25万
  • 财政年份:
    2021
  • 负责人:
    Matthew Nassar
  • 依托单位:
海外基金