Using Neuronal Populations to Probe Perceptual Decisions

描述(申请人提供)：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用于指导行为的。知觉决策，就像几乎所有正常的行为过程和神经系统的紊乱一样，被认为涉及到大群神经元的活动。然而，技术限制迫使大多数生理学研究将重点放在单个神经元上。这些研究提供了许多重要的见解，但它们必然遗漏了有关感觉神经元组和决策之间关系的关键信息。例如，单个神经元的反应不能告诉我们该神经元的活动如何相互作用，以及如何与皮质内或皮层之间的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，其认知状态也会随时间而变化很大，对知觉任务的表现会产生显著的影响。因此，将不同时间记录的单个神经元的信息结合在一起，可以得出多种行为状态的平均值。在这个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来跟踪每个感知决定，当它是在 进步。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是如何组合在一起的，这些神经元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，以推动决策。在具体目标1中，我们将询问具有不同功能特性的神经元的反应是如何结合起来的，通过评估动物的选择与神经元活动之间的关系来指导决策，这些神经元的活动在编码相关信息的能力上不同，或者受到视觉注意等认知因素的不同调制。在目标2中，我们将通过确定共享(或相关)反应变异性对知觉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手段，评估大量人群的相关结构，并将相关变异性的影响与伴随着放电率变化的影响分开。在目标3中，我们将研究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。我们将同时记录V4(腹侧流区)和MT(背流区)的神经元组，以确定我们是否可以更好地预测这两个区域的神经元组一起或仅从一个区域预测动物的决定。我们还将调整视觉刺激，以有利于这两个区域中每一个神经元的调谐特性，以了解每个区域在决策中的作用是否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，将提高我们对潜在神经机制的理解，并指导未来的实验和理论工作。

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.