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 影响思想和控制的疾病的治疗。决策过程的数学模型， 基于有限的证据积累，已经开发了数十年，并且正在 越来越多的杠杆来深入了解范围引起的认知缺陷的起源 脑疾病。但是，我们对神经机制的理解仍然存在主要差距 负责决策，从而限制了模型的有效性和实用性。成功的线 关于感知决策的研究确定了顶叶和前额叶的神经元 恒河猴的皮质（Macaca Mulatta）编码有关累积的证据 替代方案。这些观察结果主要来自猕猴皮质区域的神经元 与准备决定的动作（例如手或眼动）有关 替代方案。但是，通常在不知道他们可能称之为行动的情况下制定决定 对于在这种情况下，效应子选择性神经活性似乎并不反映积累 动力学。最近的研究已经确定了非侵入性的新型“抽象”决策信号 电生理（EEG）记录了人类决策者。信号称为中央 顶阳性阳性（CPP）代表了决策的积累 任务的感官或电机要求，因此设计，抽象。神经回路 引起CPP可能会解释能够灵活地将决策与各种行动联系起来的能力 取决于上下文和目标。但是，因为到目前为止，该信号仅在脑电图中观察到 人类的录音，其神经基础尚不清楚。拟议的目标将（1）建立神经 CPP的基础通过在单神经，多神经，本地领域建立类似物。 猕猴的潜力和脑电图以及（2）通过使用将其来源定位在人类中 来自接受神经外科的患者的神经影像学和电皮质学（ECOG）。两个目标 利用结合生物物理建模，神经网络和 决策过程的数学表征。这些知识通过这些知识 调查将增加我们对核心认知能力的理解 在人类与非人类的长期方法论上弥合长期的方法论差距，以使主要的脑部疾病与非人类疾病 动物投资。