课题基金 / 基金详情

Neurocomputational models of sequential discrimination

Neurocomputational models of sequential discrimination
顺序辨别的神经计算模型
批准号:
6915046
负责人:
Carlos D Brody
金额:
$30.51万
依托单位国家:
美国
项目类别:
财政年份:
2004
资助国家:
美国
项目状态:
已结题
起止时间:
2004-07-01 至 2009-04-30

项目摘要

项目成果

Carlos D Brody的其他基金

相似基金

相关文献

中文摘要
翻译
描述(由申请人提供):本申请旨在深入了解短期记忆的机制,并与感觉相互作用以产生决策。将对执行体感顺序辨别任务的猴子的数据进行分析并进行计算建模。这项任务涉及短期记忆部分(受试者必须记住每次试验中的第一个刺激)和决策部分(每次试验中的第二个刺激必须与第一个刺激进行比较,并且必须根据比较做出决定)。 本研究的主要目的有三:(1)建立序列辨别任务的计算神经模型。使用这些模型,我们将探索生物物理机制,通过该机制,第一刺激可以加载到短期记忆中,保存在短期记忆中,并与第二刺激相结合,从而形成基于两个刺激的比较的决定。我们将探索如何在一个基于生物制药学的神经网络中组合和理解所有三个任务组件(加载,记忆和比较/决策)。(2)基于连续变量的短期记忆被保持在具有近似连续吸引子的动态网络中的思想,我们提出了一个神经元之间的噪声相关性模型。这个模型从根本上调和了第一刺激记忆的神经生理表征的精确性与猴子受试者的行为精确性,正如精神病学推断的那样。我们将分析同时记录的PFC神经元之间的相关性,并寻求支持或反对这种噪声模型的证据。(3)关于第一和第二刺激之间的比较的决定是在PFC和/或次级躯体感觉皮层(S2)中做出的,其中PFC在时间上领先于S2,这一假设将通过分析在任务期间从这些皮层区域记录的数据来检验。 我们的长期目标是了解记忆背景如何影响基于传入的感觉数据的决策;也就是说,我们寻求对背景依赖性决策的神经生理学基础的理解。从长远来看,这项研究可能会对心理健康的理解产生重大影响。
英文摘要
DESCRIPTION (provided by applicant): This application seeks to gain insight into the mechanisms by which short-term memories are held and interact with sensations in order to produce decisions. Data from monkeys performing a somatosensory sequential discrimination task will be analyzed and modeled computationally. This task involves both a short-term memory component (subjects must remember the first stimulus in each trial) and a decision component (the second stimulus in each trial must be compared to the first, and a decision must be made based on that comparison). Three specific aims will be addressed: (1) We will build computational neural models of the sequential discrimination task. Using these models, we will explore biophysical mechanisms by which the first stimulus may be loaded into short-term memory; preserved in short-term memory; and combined with the second stimulus, so as to form a decision based on the comparison of the two stimuli. We will explore how all three task components (loading, memory, and comparison/decision-making) may be combined and understood in a single biophysically-based neural network. (2) Based on the idea that the short-term memory of continuous variables is held in networks with dynamics that approximate a continuous attractor, we propose a model of noise correlations between neurons. This model fundamentally reconciles the precision of the neurophysiological representation of the memory of the first stimulus with the behavioral precision of the monkey subjects, as inferred psychophysically. We will analyze correlations between simultaneously recorded PFC neurons and seek evidence for, or against, this noise model. (3) The hypothesis that a decision regarding the comparison between the first and second stimulus is made in the PFC and/or the secondary somatosensory cortex (S2), with the PFC leading S2 in time, will be tested by analyzing data recorded from these cortical areas during the task. Our long-term goal is to understand how memory context can affect decisions based on incoming sensory data; that is, we seek an understanding of the neurophysiological basis of context-dependent decisions. In the long term, this research could potentially have significant impact on the understanding of mental health.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
P2: Geometry of Neural Representations and Dynamics
  • 批准号:
    10705964
  • 项目类别:
  • 资助金额:
    $35.6万
  • 财政年份:
    2023
  • 负责人:
    Carlos D Brody
  • 依托单位:
Mechanisms of neural circuit dynamics in working memory and decision-making
  • 批准号:
    10705962
  • 项目类别:
  • 资助金额:
    $468.67万
  • 财政年份:
    2023
  • 负责人:
    Carlos D Brody
  • 依托单位:
C3: Behavior Automation
  • 批准号:
    10705970
  • 项目类别:
  • 资助金额:
    $32.13万
  • 财政年份:
    2023
  • 负责人:
    Carlos D Brody
  • 依托单位:
C1: Administrative
  • 批准号:
    10705968
  • 项目类别:
  • 资助金额:
    $13.26万
  • 财政年份:
    2023
  • 负责人:
    Carlos D Brody
  • 依托单位:
海外基金