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）：系统神经科学的一个主要焦点是了解感官信息如何编码并用于指导行为。感知决策，就像几乎所有正常的行为过程和神经系统疾病一样，被认为涉及大量神经元的活动。然而，技术限制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，但它们必然错过了有关感觉神经元群体和决策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动如何与皮质区域内或之间的其他神经元的活动相互作用并结合。此外，我之前的工作表明，即使是训练有素的受试者的认知状态也会随时发生很大的波动，这会对感知任务的表现产生显着的影响。因此，结合不同时间记录的单个神经元的信息可以产生许多行为状态的平均值。 该提案中的实验使用许多同时记录的神经元的活动，同时动物执行视觉辨别任务来跟踪每个感知决策。 进步。我们的目标是了解来自不同皮质区域并以不同方式与附近神经元相互作用的具有不同生理、视觉和认知特性的神经元的反应如何结合起来以驱动决策。在具体目标 1 中，我们将询问如何将具有不同功能特性的神经元的反应结合起来，通过评估动物的选择与神经元的活动之间的关系来指导决策，这些神经元的编码相关信息的能力不同或受到不同的调节认知因素，例如视觉注意力。在目标 2 中，我们将通过确定共享（或相关）响应变异性对感知表现的影响来评估当前决策模型的有效性。来自几十个同时记录的神经元的反应将提供一种评估大量群体的相关结构的方法，并将相关变异的影响与伴随的放电率变化分开。在目标3中，我们将检查不同视觉区域的神经元在决策中的作用，询问不同区域是否存在互补的选择相关活动，并确定每个区域的作用是否灵活。 V4（腹侧流区域）和 MT（背侧流区域），以确定我们是否可以从两个区域中的神经元组一起或单独从一个区域更好地预测动物的决策。我们还将调整视觉刺激，以有利于两个区域中神经元的调节特性，看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。我们希望将决策研究扩展到神经元群体，将提高我们对潜在神经元机制的理解，并指导未来的实验和理论工作。