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

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焦点是了解感觉信息是如何编码和使用的。 引导人们的行为。知觉决策，就像几乎所有正常的行为过程和精神障碍 神经系统，被认为涉及大群神经元的活动。技术限制， 然而，这迫使大多数生理学研究集中在单个神经元上。这些研究提供了 许多重要的见解，但它们必然会遗漏关于 感觉神经元和决策。例如，单个神经元的反应不能告诉我们该神经元如何 皮层内或皮层之间的活动相互作用，并与其他神经元的活动相结合。此外， 我之前的工作表明，即使是训练有素的受试者，认知状态也会随着时间的推移而变化很大 瞬间，对知觉任务的表现有显著影响。因此，结合信息 在不同时间记录的单个神经元产生了许多行为状态的平均值。 这一方案中的实验使用了许多同时记录的神经元的活动，而 动物执行视觉辨别任务，以跟踪每个正在进行的知觉决定。我们的目标 是为了了解具有不同生理、视觉和认知特性的神经元的反应 它们来自不同的皮质区域，并以不同的方式与附近的神经元相互作用 推动决策。在特定的目标1中，我们将询问不同功能的神经元的反应是如何 通过评估动物的选择和选择之间的关系，结合属性来指导决策 编码相关信息的能力不同或调制方式不同的神经元的活动 受视觉注意力等认知因素的影响。在目标2中，我们将评估当前模型的有效性 通过确定共享(或相关)反应的可变性对知觉的影响来进行决策 性能。来自几十个同时记录的神经元的反应将提供一种手段 评估大种群的相关结构，并将相关变异性的影响与 随之而来的是射击速度的变化。在目标3中，我们将研究神经元在不同视觉区域中的作用 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 每个领域的角色是否灵活。我们将同时记录V4中的一组神经元， 腹流区和MT，背流区，以确定我们是否可以更好地预测动物的 来自两个区域的神经元组的共同决定或单独来自一个区域的决定。我们还将调整 视觉刺激有利于神经元的调谐特性，分别观察这两个区域是否起作用 决策中的每个区域都取决于其神经元对特定知觉任务的适应性。我们希望 将决策研究扩展到神经元群体将提高我们对 并指导未来的实验和理论工作。