Using Neuronal Populations to Probe Perceptual Decisions

使用神经元群体探索感知决策

• 批准号: 8578677
• 负责人: Marlene Rochelle Cohen
• 金额: $ 35.79万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-01 至 2018-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8578677
• 关键词: Afferent Neurons; Animals; Area; Arousal; Attention; Attention deficit hyperactivity disorder; Behavior; Behavioral; Cells; Code; Cognitive; Controlled Study; Data; Decision Making; Diagnosis; Discrimination; Disease; Dorsal; Employee Strikes; Future; Goals; Individual; Measures; Mental Depression; Modeling; Monitor; Monkeys; Neurons; Neurosciences; Output; Performance; Pharmacotherapy; Physiological; Population; Primates; Process; Property; Relative (related person); Role; Schizophrenia; Sensory; Stimulus; Stream; Structure; System; Techniques; Testing; Theoretical model; Time; Training; Visual; Visual Cortex; Visual attention; Visual system structure; Weight; Work; area V4; base; extrastriate visual cortex; flexibility; improved; insight; nervous system disorder; public health relevance; research study; response; visual stimulus; Afferent Neurons; Animals; Area; Arousal; Attention; Attention deficit hyperactivity disorder; Behavior; Behavioral; Cells; Code; Cognitive; Controlled Study; Data; Decision Making; Diagnosis; Discrimination; Disease; Dorsal; Employee Strikes; Future; Goals; Individual; Measures; Mental Depression; Modeling; Monitor; Monkeys; Neurons; Neurosciences; Output; Performance; Pharmacotherapy; Physiological; Population; Primates; Process; Property; Relative (related person); Role; Schizophrenia; Sensory; Stimulus; Stream; Structure; System; Techniques; Testing; Theoretical model; Time; Training; Visual; Visual Cortex; Visual attention; Visual system structure; Weight; Work; area V4; base; extrastriate visual cortex; flexibility; improved; insight; nervous system disorder; public health relevance; research study; response; visual stimulus

Project summary/ Abstract A main focus of systems neuroscience is to understand how sensory information is encoded and used to guide behavior. Perceptual decision-making, like nearly all normal behavioral processes and disorders of the nervous system, is thought to involve the activity of large groups of neurons. Technical limitations, however, have forced most physiological studies to focus on single neurons. These studies have provided many important insights, but they necessarily miss key information about the relationship between groups of sensory neurons and decisions. For example, single neuron responses cannot tell us how that neuron's activity interacts and is combined with that of other neurons within or between cortical areas. Furthermore, my prior work showed that the cognitive state of even a well-trained subject fluctuates greatly from moment to moment, with striking consequences on performance on perceptual tasks. Therefore, combining information from single neurons recorded at different times produces an average over many behavioral states. The experiments in this proposal use the activity of many simultaneously recorded neurons while animals perform a visual discrimination task to track each perceptual decision while it is in progress. Our goal is to understand how the responses of neurons with different physiological, visual and cognitive properties who come from different cortical areas and interact with nearby neurons in different ways are combined to drive decisions. In Specific Aim 1, we will ask how the responses of neurons with different functional properties are combined to guide decisions by assessing the relationship between the animal's choices and the activity of neurons that differ in their ability to encode the relevant information or are modulated differently by cognitive factors such as visual attention. In Aim 2, we will assess the validity of current models of decision-making by determining the effect of shared (or correlated) response variability on perceptual performance. The responses from a few dozen simultaneously recorded neurons will provide a means of assessing the correlation structure of a large population and isolating the effects of correlated variability from accompanying changes in firing rates. In Aim 3, we will examine the role of neurons in different visual areas in decisions, ask whether there is complementary choice-related activity in different areas, and determine whether the role of each area is flexible. We will record simultaneously from groups of neurons in V4, a ventral stream area, and MT, a dorsal stream area, to determine whether we can better predict the animal's decisions from groups of neurons in the two areas together or from one area alone. We will also adjust the visual stimulus to favor the tuning properties of neurons in each of the two areas to see whether the role of each area in decisions depends on the suitability of its neurons for the particular perceptual task. We hope that extending the study of decision-making to populations of neurons will improve our understanding of the underlying neuronal mechanisms and guide future experimental and theoretical work.

项目摘要/摘要 系统神经科学的一个主要重点是了解感觉信息的编码和使用方式 指导行为。感知决策，就像几乎所有正常的行为过程和疾病一样 神经系统被认为涉及大量神经元的活性。技术限制， 但是，已经迫使大多数生理研究专注于单个神经元。这些研究提供了 许多重要的见解，但它们一定会错过有关群体之间关系的关键信息 感觉神经元和决定。例如，单个神经元的反应无法告诉我们该神经元如何 活性相互作用，并与皮质区域内或皮质之间的其他神经元的相互作用相互作用。此外， 我先前的工作表明，即使受过良好训练的主题的认知状态也从瞬间到 时刻，对感知任务的表现产生了巨大的后果。因此，结合信息 从不同时间记录的单个神经元中，在许多行为状态下会产生平均值。 该提案中的实验使用许多同时记录神经元的活动，而 动物执行视觉歧视任务，以跟踪每个感知决策。我们的目标 是了解具有不同生理，视觉和认知特性的神经元的反应 来自不同皮质区域并以不同方式与附近神经元互动的人被合并为 驱动决定。在特定目标1中，我们将询问具有不同功能的神经元的反应 通过评估动物的选择之间的关系，将属性合并为指导决策 神经元的活性在编码相关信息或对其进行不同调制的能力不同 通过认知因素，例如视觉注意力。在AIM 2中，我们将评估当前模型的有效性 通过确定共享（或相关）响应变异性对感知的影响来制定决策 表现。几十个同时记录的神经元的反应将提供一种方法 评估庞大的人群的相关结构，并隔离相关变异性的影响 伴随发射率变化。在AIM 3中，我们将检查神经元在不同视觉区域的作用 在决策中，询问在不同领域是否存在与选择相关的互补活动，并确定 每个区域的作用是否灵活。我们将同时从V4中的神经元组中记录 腹侧溪流区域和背面的MT，以确定我们是否可以更好地预测动物的 在两个区域或仅一个区域的神经元组中的决定。我们还将调整 视觉刺激有利于两个区域中每个区域中神经元的调谐特性，以查看是否作用 决策中的每个领域都取决于其神经元对特定感知任务的适用性。我们希望 将决策研究扩大到神经元人群的研究将提高我们对 基本的神经元机制，并指导未来的实验和理论工作。