CRCNS: Stochastic Models of Executive Control in Monkeys and Humans

在美国国家科学基金会的支持下，洛根博士，帕尔梅里和沙尔将进行为期三年的执行控制过程的调查，猴子和人类的灵活反应的基础。灵长类智能的标志是能够灵活地做出反应，专注于同一情况的不同方面，以产生适合当前目标的任意反应。 这个项目的目标是指定执行过程的计算和神经，专注于控制的注意力，分类和反应准备。 为了实现这一目标，猴子和人类将执行任务，要求他们使扫视眼球运动朝向或远离出现在干扰物显示器中的目标。 实验变量将被操纵，以选择性地影响注意力的目标，分类的目标和干扰，并准备眼动反应。 将记录人类和猴子执行任务时眼球运动的时间和准确性，并记录猴子执行任务时额叶神经元集合的活动。 人类和猴子的明显眼球运动行为以及猴子的神经活动将根据具有三个不同组成部分的数学精确计算理论进行描述，如下所示。 (1)一个注意力组件，它从干扰物中选择行为相关的目标;（2）一个分类组件，它选择目标刺激的目标相关解释;（3）一个反应准备组件，它选择完成目标所需的反应。 该理论提供了一种共同语言，使人们有可能将人类的外显行为与猴子的外显行为联系起来，并将猴子的外显行为与其背后的神经活动联系起来。该研究在三个方面具有重要意义。 首先，它将通过具体说明它们在计算和神经过程方面，推进对执行控制过程的理解。 执行控制过程在工作场所，教育环境和心理健康环境中的各种环境中至关重要，这些环境要求人们处理相互竞争的目标并在各种活动之间切换，包括工作场所，教育和心理健康。 这项研究将对人的因素、人体工程学、教育和工业培训计划的设计以及精神疾病的诊断和治疗产生影响。 其次，这项研究将通过提供将单细胞行为与单细胞实现的认知过程的心理状态相关联的命题来促进对神经过程的理解。 单细胞行为只有在它所依据的行为的背景下才有意义，这项研究将提供这种关系。 第三，这项研究将促进对注意力、分类和反应准备等认知过程基础的计算的理解。 这些过程的计算模型受到无法“打开黑匣子”和观察它们背后的内部大脑过程的限制。 具有非常不同的内部过程的计算模型通常预测相同的明显行为。 该研究将识别具有神经行为的认知过程，从而区分人类和猴子认知的这些计算模型。

Stochastic Models of Executive Control in Monkeys and HumansAbstractWith National Science Foundation support, Drs. Logan, Palmeri, and Schall will conduct a three-year investigation of the executive control processes that underlie flexible responding in monkeys and humans. It is the hallmark of primate intelligence to be able to respond flexibly, focusing on different aspects of the same situation to produce arbitrary responses that are appropriate to current goals. The goal of this project is to specify executive processes computationally and neurally, focusing on the control of attention, categorization, and response preparation. To accomplish this goal, monkeys and humans will perform tasks that require them to make saccadic eye movements toward or away from targets that appear in displays of distractors. Experimental variables will be manipulated to selectively influence attention to the targets, categorization of targets and distractors, and preparation of eye movement responses. The timing and accuracy of eye movements will be recorded in both humans and monkeys performing the task, and the activity of ensembles of neurons in the frontal lobes of monkeys will be recorded while they are performing the task. The overt eye movement behavior of humans and monkeys and the neural activity of monkeys will be described in terms of a mathematically precise computational theory with three distinct components, as follows. (1) An attention component that selects behaviorally-relevant targets from a field of distractors; (2) a categorization component that selects goal-relevant interpretations of target stimuli; and (3) a response preparation component that selects responses necessary to accomplish the goals. The theory provides a common language that makes it possible to relate the overt behavior of humans to the overt behavior of monkeys and to relate the overt behavior of monkeys to the neural activity that underlies it.The research is significant in three respects. First, it will advance understanding of executive control processes by specifying them concretely in terms of computational and neural processes. Executive control processes are critical in a variety of contexts in the workplace, educational settings, and mental health settings that require people to deal with competing goals and switch between various activities, including the workplace, education, and mental health. The research will have implications for human factors, ergonomics, design of training programs in education and industry, and diagnosis and treatment of mental disorders. Second, the research will advance understanding of neural processes by providing linking propositions that relate single-cell behavior to psychological states of the cognitive processes that the single cells implement. Single-cell behavior makes sense only in the context of the behavior it underlies, and the research will provide that relation. Third, the research will advance understanding of the computations that underlie cognitive processes of attention, categorization, and response preparation. Computational models of these processes are limited by an inability to "open the black box" and observe the inner brain processes that underlie them. Computational models with very different internal processes often predict the same overt behavior. The research will identify cognitive processes with neural behavior, allowing distinctions between these computational models of human and monkey cognition.