Cortical circuit dynamics underlying multisensory decision making

多感官决策背后的皮层回路动力学

• 批准号: 10721255
• 负责人: CHRISTOPHER R FETSCH
• 金额: $ 149.02万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10721255
• 关键词: 3-Dimensional; Acceleration; Address; Affect; Animal Model; Animals; Area; Associate Degree; Behavior; Belief; Binding; Brain; Brain region; Cells; Cognitive; Communication; Complex; Computer Models; Conflict (Psychology); Coupling; Cues; Decentralization; Decision Making; Discrimination; Disease; Environment; Esthesia; Feedback; Foundations; Future; Goals; Human; Individual; Investigation; Joints; Judgment; Kinesthesis; Link; Locomotion; Measures; Mediating; Methods; Modality; Modeling; Monkeys; Motion; Motor; Neurons; Parietal; Pattern; Perception; Population; Population Dynamics; Process; Property; Psychologist; Reaction Time; Recurrence; Reporting; Saccades; Self Direction; Self Perception; Sensory; Sensory Process; Shapes; Signal Transduction; Source; Stimulus; Structure; System; Task Performances; Testing; Time; Training; Uncertainty; Visual; Visuospatial; analytical tool; area MST; behavior prediction; cognitive ability; cognitive function; density; experimental study; improved; insight; lateral intraparietal area; multisensory; neural; neurophysiology; novel; sensory cortex; sensory integration; spatiotemporal; success; visual-vestibular

Project Summary To navigate and guide locomotion in a complex 3D environment, humans and animals must make countless judgments of their direction of self-motion, or heading. Each of these is a multisensory perceptual decision, able to achieve greater accuracy and precision by combining signals from the visual, vestibular, and kinesthetic senses. At the same time, the brain must decide when to commit to a course of action (e.g., to quickly change direction to avoid an obstacle), and make predictions of the likelihood of success in that action. These features of a decision—choice accuracy, response time (RT), and confidence—have been studied by psychologists for over a century, but primarily for only a single modality, instead of the more natural case of integrating multiple sources of sensory evidence. Moreover, the neural basis of multisensory integration is largely studied at the level of individual cells or brain regions, whereas nearly all perceptual and cognitive functions depend on population-level computations and communication between areas. To address these gaps, we trained monkeys to perform a visual-vestibular heading discrimination task which measures choice, RT, and confidence via a post-decision wager (PDW). During performance of the task, we will record ensemble activity simultaneously from two key nodes in the sensory cortical network representing visual and vestibular self-motion cues (MST and PIVC, respectively), as well as one node (lateral intraparietal area, LIP) in the downstream decision network that converts sensory evidence into a motor plan. These regions have individually been linked to heading perception, but little is known about how their coordinated activity patterns, observable only though population recordings, support multisensory decision making. In Aim 1 of the proposal, we will quantify the coordinated activity across sensory neural populations and test whether the perceptual improvement from multisensory integration depend on the strength of coupling between them, beyond what can be explained by their activity considered independently. When visual and vestibular cues are artificially placed in conflict, we will ask whether and how the relative precision of heading estimates decoded from these sensory populations predicts choice and confidence, guided by predictions of a multisensory evidence accumulation model. In Aim 2, we will extend our investigation of inter-areal interactions to the decision stage, quantifying the strength and timing of functional coupling between LIP and each of the two sensory areas. The relative timing of this coordinated activity can indicate feedforward versus feedback processes, revealing how perceptual decisions evolve via recurrent loops between sensation and degree of belief in a proposition (or commitment to a plan of action). The results will yield new insights into the representation and readout of sensory evidence and its associated degree of (un)certainty, and will advance a population- and circuit-level understanding of decision computations in a multisensory task.

项目概要 为了在复杂的 3D 环境中导航和引导运动，人类和动物必须做出无数的动作 对自身运动方向或航向的判断。每一个都是多感官的感知决定， 能够通过结合来自视觉、前庭和大脑的信号来实现更高的准确性和精确度 动觉。同时，大脑必须决定何时采取一系列行动（例如， 快速改变方向以避免障碍），并预测成功的可能性 行动。决策的这些特征——选择准确性、响应时间 (RT) 和置信度——已被 心理学家研究了一个多世纪，但主要只针对单一模式，而不是更多 整合多种感官证据来源的自然案例。此外，多感觉的神经基础 整合主要在单个细胞或大脑区域的水平上进行研究，而几乎所有的感知和 认知功能取决于人口水平的计算和区域之间的交流。致地址 这些差距，我们训练猴子执行视觉前庭方向辨别任务，该任务测量 通过决策后投注 (PDW) 实现的选择、RT 和置信度。在执行任务的过程中，我们会记录 感觉皮层网络中两个关键节点同时进行整体活动，代表视觉和视觉 前庭自我运动线索（分别为 MST 和 PIVC），以及一个节点（侧顶叶区，LIP） 将感官证据转化为运动计划的下游决策网络。这些地区有 个体与航向感知有关，但人们对它们的协调活动如何进行知之甚少 只有通过人口记录才能观察到的模式支持多感官决策。目标 1 该提案中，我们将量化感觉神经群体之间的协调活动，并测试是否 多感官整合的感知改善取决于它们之间的耦合强度， 超出了他们独立考虑的活动所能解释的范围。当视觉和前庭提示时 人为地将其置于冲突中，我们将询问航向估计的相对精度是否以及如何 从这些感官群体中解码出来的信息可以预测选择和信心，并受到以下预测的指导 多感官证据积累模型。在目标 2 中，我们将扩大跨区域调查 决策阶段的交互，量化 LIP 和 LIP 之间功能耦合的强度和时间 两个感觉区域中的每一个。这种协调活动的相对时间可以表明前馈与 反馈过程，揭示感知决策如何通过感觉和感觉之间的循环进行演变 对某个主张（或对行动计划的承诺）的信念程度。研究结果将为我们带来新的见解 感官证据的表示和读出及其相关的（不）确定性程度，并将推进 对多感官任务中决策计算的总体和电路级理解。