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: COLD SPRING HARBOR LABORATORY
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-07-01 至 2009-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6915046
• 关键词: alternatives to animals in research; animal data; behavior test; behavioral /social science research tag; biophysics; computational neuroscience; decision making; electrophysiology; electroporation; eye movements; goldfish; neural information processing; neurons; neurophysiology; noise; prefrontal lobe /cortex; psychophysics; sensation; sequential perception; short term memory; somesthetic sensory cortex; stimulus /response; visual stimulus

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.

描述（由申请人提供）：本申请旨在深入了解短期记忆的保存机制以及与感觉相互作用以产生决策的机制。来自执行体感顺序辨别任务的猴子的数据将通过计算进行分析和建模。该任务涉及短期记忆成分（受试者必须记住每次试验中的第一个刺激）和决策成分（每次试验中的第二个刺激必须与第一个刺激进行比较，并且必须根据该比较做出决定） 。 将解决三个具体目标：（1）我们将建立顺序判别任务的计算神经模型。使用这些模型，我们将探索将第一次刺激加载到短期记忆中的生物物理机制；保存在短期记忆中；并与第二个刺激相结合，从而根据两个刺激的比较形成决策。我们将探索如何在一个基于生物物理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保存在具有近似连续吸引子的动力学的网络中的想法，我们提出了神经元之间的噪声相关性模型。该模型从根本上协调了第一刺激记忆的神经生理学表征的精度与猴子受试者的行为精度（如心理物理学推断的那样）。我们将分析同时记录的 PFC 神经元之间的相关性，并寻找支持或反对该噪声模型的证据。 (3) 关于第一和第二刺激之间的比较的决定是在 PFC 和/或次级体感皮层 (S2) 中做出的假设，并且 PFC 在时间上领先于 S2，将通过分析从这些刺激记录的数据来检验任务期间的皮质区域。 我们的长期目标是了解记忆背景如何影响基于传入感官数据的决策；也就是说，我们寻求对上下文相关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。