Using Neuronal Populations to Probe Perceptual Decisions

使用神经元群体探索感知决策

• 批准号: 8706153
• 负责人: Marlene Rochelle Cohen
• 金额: $ 35.35万
• 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/8706153
• 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

DESCRIPTION (provided by applicant): 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.

描述（由申请人提供）：系统神经科学的主要重点是了解如何编码感官信息并用于指导行为。人们认为，知觉决策几乎与神经系统的所有正常行为过程和疾病一样，都被认为涉及大量神经元的活性。但是，技术局限性迫使大多数生理学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感觉神经元和决策组之间关系的关键信息。例如，单个神经元反应无法告诉我们该神经元的活性如何相互作用，并与皮质区域内或皮质区域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，即使是受过良好训练的主题的认知状态也瞬间大幅波动，对感知任务的表现产生了巨大的影响。因此，在不同时间记录的单个神经元的信息组合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的过程 进步。我们的目标是了解来自来自不同皮质区域的不同生理，视觉和认知特性的神经元的反应，并以不同方式与附近神经元相互作用以提出决策。在特定的目标1中，我们将询问如何通过评估动物选择和神经元之间的关系来指导决策的神经元的响应如何指导决策，而神经元的活性在编码相关信息的能力上有所不同，或者通过视觉关注等认知因素对其进行了不同的调节。在AIM 2中，我们将通过确定共享（或相关）响应变异性对感知性能的影响来评估当前决策模型的有效性。几十个同时记录的神经元的响应将提供一种评估大种群的相关结构的方法，并将相关变异性的影响与伴随的发射速率变化隔离。 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.我们还将调整视觉刺激，以偏爱两个区域中每个区域中神经元的调整特性，以查看每个区域在决策中的作用是否取决于其神经元对特定感知任务的适用性。我们希望将决策的研究扩展到神经元的人群将提高我们对基本神经元机制的理解，并指导未来的实验和理论工作。