Neural time-integration underlying higher cognitive function

描述(申请人提供)：本研究的长期目标是了解将感觉信号转换为支持认知过程并指导后续行动的表征的基本神经计算。这里提出的这项研究测试了信号如何流经外侧顶叶内区(LIP)，在积累和记忆感觉证据的过程中引导眼球运动。我们通过采用来自以前工作的计算框架来处理这个问题，使用方向辨别范式，并将其扩展到更广泛的行为任务、实验现象和理论方法。我们的主要目标是测试嘴唇持续和倾斜的活动反映神经时间整合的程度，以及这种计算与感觉刺激、工作记忆和眼动规划的关系。我们的第二个目标是更好地将方向辨别范式和时间整合假说中的定量推断整合到眼动计算的其他工作中。我们以前已经证明，唇区的神经活动反映了运动方向决策任务执行过程中噪声感觉证据的时间积累。因为嘴唇的活动强烈地受到这种视觉目标的启动，所以有必要测试嘴唇的时间整合是否依赖于响应场中视觉刺激的存在。我们还将评估持续活动在嘴唇中的认知作用。如果嘴唇的持续活动支持在不同时间获得的多个证据的组合，那么刺激观看和工作记忆交错期间的嘴唇活动应该反映感觉证据的时间积分。我们将通过在感官证据的连续时期之间加入空白记忆延迟期来检验这一假设，并评估延迟期内的活动是否反映了证据的积累和维持水平。我们将通过执行一个类似的任务来进一步研究嘴唇活动和认知功能之间的关系，在这个任务中，两个刺激必须进行比较，而不是合并。简而言之，我们将操纵感觉、认知和运动变量，以评估在以下情况下嘴唇活动似乎支持时间整合的程度：(1)对响应场的视觉刺激被操纵；(2)感觉证据的连续积累和保持；以及(3)在决策形成期间，特定的眼动是未知的。这些测量还将提供几个机会，以欣赏细胞在感觉、记忆、决策和运动反应方面的多样性。与公共健康相关的灵长类动物的行为是聪明、灵活和复杂的。这些行为优势通常来自人类和非人类灵长类动物将在不同时间获得的多个证据结合在一起的能力。彻底了解大脑是如何执行这种“时间整合”的，将有助于神经治疗，并为智能假肢和机器人的控制和设计中涉及的技术应用提供信息。

DESCRIPTION (provided by applicant): The long-term goal of this research is to understand the basic neural computations that transform sensory signals into representations that support cognitive processes and guide subsequent actions. The research proposed here tests how signals flowing through the lateral intraparietal area (LIP) underlie processes of accumulating and remembering sensory evidence for the purposes of guiding eye-movements. We approach this topic by adapting a computational framework derived from previous work using a direction-discrimination paradigm, and extending it to a wider range of behavioral tasks, experimental phenomena, and theoretical approaches. Our primary goal is to test the degree to which the persistent and ramping activity in LIP reflects neural time-integration, and how this computation relates to sensory stimulation, working memory, and oculomotor planning. Our secondary goal is to better integrate the quantitative inferences available from the direction-discrimination paradigm and time-integration hypothesis to other work on oculomotor computations. We have previously demonstrated that neural activity in area LIP reflects the temporal accumulation of noisy sensory evidence during the performance of a motion direction decision- making task. Because LIP activity is driven strongly by the onset of such a visual target, it is necessary to test whether temporal integration in LIP depends on the presence of a visual stimulus within the response field. We will also assess the cognitive role of persistent activity in LIP. If the persistent activity in LIP supports the combination of multiple pieces of evidence acquired at different times, LIP activity during interleaved periods of stimulus viewing and working memory should reflect the time integral of the sensory evidence. We will test this hypothesis by incorporating a blank memory delay period between successive periods of sensory evidence, and evaluating whether activity during the delay period reflects the accumulated and maintained level of evidence. We will further investigate the relationship between LIP activity and cognitive function by performing a similar task in which two stimuli must be compared, instead of combined. In short, we will manipulate sensory, cognitive, and motor variables to assess the degree to which LIP activity appears to support time integration when: (1) visual stimulation of the response field is manipulated; (2) successive periods of accumulation and maintenance of sensory evidence occur; and (3) the specific eye-movement is not known during the formation of a decision. These measurements will also provide several opportunities to appreciate cell-by- cell diversity in sensory, memory, decision, and motor responses. PUBLIC HEALTH RELEVANCE Primate behavior is intelligent, flexible, and complex. These behavioral strengths often derive from the ability of human and nonhuman primates to combine multiple pieces of evidence acquired at different times. A thorough understanding of how the brain performs this "temporal integration" will benefit neurological treatments, as well as inform technical applications involved in the control and design of intelligent prosthetics and robotics.