Uncovering the neural architecture underlying decisions abstracted from movements

揭示从运动中抽象出来的决策背后的神经架构

• 批准号: 10558587
• 负责人: Stephan Bickel
• 金额: $ 41.09万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-13 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10558587
• 关键词: Address; Affect; Animals; Architecture; Area; Behavior; Binding; Biophysics; Brain; Brain Diseases; Brain region; Characteristics; Classification; Cognition; Cognitive deficits; Complex; Coupled; Data; Decision Making; Development; Diagnosis; Disease; Divorce; Electrocorticogram; Electrophysiology (science); Epilepsy; Event-Related Potentials; Exhibits; Eye Movements; Functional Magnetic Resonance Imaging; Future; Goals; Hand; Health; Homologous Gene; Human; Impaired cognition; Investigation; Joints; Knowledge; Lateral; Link; Macaca; Macaca mulatta; Maps; Mathematics; Measures; Medial; Methodology; Methods; Modality; Modeling; Monkeys; Motor; Movement; Neural Network Simulation; Neurons; Parietal; Patients; Physiological; Play; Population; Prefrontal Cortex; Preparation; Process; Reporting; Research; Response to stimulus physiology; Role; Saccades; Scalp structure; Sensory; Signal Transduction; Source; Techniques; Testing; Time; analog; biophysical model; cognitive capacity; cognitive function; encephalography; flexibility; forging; innovation; insight; intraparietal sulcus; mathematical model; multimodality; neural; neural circuit; neural network; neuroimaging; neuromechanism; neurophysiology; neurosurgery; neurotransmission; nonhuman primate; novel; response; temporal measurement

Project Abstract Decision making is a core component of normal and abnormal cognitive function. Understanding the neural mechanisms of decision-making will lead to advances in the diagnosis, classification and future treatments of disorders affecting thought and control. Mathematical models of the decision process, based on bounded evidence accumulation, have been developed over decades and are being increasingly leveraged to gain deeper insights into the origins of cognitive deficits arising from a range of brain disorders. However, major gaps remain in our understanding of the neural mechanisms responsible for decision-making, thereby limiting the validity and utility of the models. A successful line of research on perceptual decision-making has established that neurons in the parietal and prefrontal cortex of the rhesus monkey (Macaca mulatta) encode the accumulating evidence bearing on the alternatives. These observations are mainly from neurons in areas of the macaque cortex that are associated with preparation of the actions (e.g. hand or eye movements) for reporting the decision alternatives. However, decisions are often formed without knowledge of what actions they might call for, and under such conditions, effector-selective neural activity does not appear to reflect accumulation dynamics. Recent studies, have identified a novel ‘abstract’ decision signal in non-invasive electrophysiological (EEG) recordings from human decision makers. The signal, termed the central parietal positivity (CPP), represents the accumulation of evidence for decisions irrespective of the sensory or motor requirements of the task, hence the designation, abstract. The neural circuits that give rise to the CPP are likely to explain the capacity to flexibly link decisions to various actions depending on context and goals. However, because the signal has thus far only been observed in EEG recordings from humans, its neural basis is unknown. The proposed aims will (1) establish the neural underpinnings of the CPP by establishing its analogues in single-neuron, multi-neuron, local field potentials and EEG of the macaque and (2) localizing its source in humans through the use of neuroimaging, and electrocorticography (ECoG) from patients undergoing neurosurgery. Both aims draw on an integrated computational effort that combines biophysical modeling, neural networks, and mathematical characterization of the decision process. The knowledge gained through these investigations will increase our understanding of core cognitive capacities whose deficiency contributes to major brain disorders while bridging long-standing methodological gaps in human versus non-human animal investigations.

项目摘要 决策是正常和异常认知功能的核心组成部分。了解 决策的神经机制将导致诊断，分类和未来的进步 治疗影响思维和控制的疾病。决策过程的数学模型， 基于有界证据积累，已经发展了几十年， 越来越多地利用，以获得更深入的了解认知缺陷的起源， 大脑紊乱然而，我们对神经机制的理解仍然存在重大差距 负责决策，从而限制了模型的有效性和实用性。一条成功的线路 对知觉决策的研究已经证实，顶叶和前额叶的神经元 恒河猴（Macaca mulatta）的大脑皮层编码了越来越多的证据， 替代品.这些观察结果主要来自猕猴皮层区域的神经元， 与准备用于报告决策的动作（例如，手或眼睛运动）相关联 替代品.然而，决策往往是在不知道他们可能会采取什么行动的情况下形成的。 因为，在这样的条件下，效应选择性神经活动似乎并不反映积累 动力学最近的研究，已经确定了一种新的'抽象'的决定信号，在非侵入性 人类决策者的脑电生理（EEG）记录。信号，称为中央 顶叶积极性（CPP），代表了决策证据的积累，而不管决策者是否 任务的感觉或运动要求，因此命名为抽象。的神经回路 产生CPP可能解释了将决策与各种行动灵活联系起来的能力 取决于背景和目标。然而，由于迄今为止仅在EEG中观察到信号， 从人类的记录，其神经基础是未知的。建议的目标将（1）建立神经网络 通过在单神经元，多神经元，局部领域建立其类似物来巩固CPP 猕猴的电位和EEG，以及（2）通过使用 神经影像学和皮质电图（ECoG）。两个目标 利用结合生物物理建模、神经网络和 决策过程的数学描述。通过这些获得的知识 研究将增加我们对核心认知能力的理解，这些能力的缺乏导致了 同时弥合人类与非人类之间长期存在的方法学差距， 动物调查