Multi-scale Orbitofrontal Networks Underlying Reward Processing

奖励处理背后的多尺度眶额网络

• 批准号: 8868828
• 负责人: Erin L Rich
• 金额: $ 13.05万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-04-15 至 2020-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8868828
• 关键词: Abstinence; Accounting; Acute; Affective; Anterior; Area; Brain; Brain Mapping; Characteristics; Choice Behavior; Code; Communication; Cues; Decision Making; Dimensions; Disease; Drug Addiction; Electrocorticogram; Epilepsy; Goals; Human; Individual; Language; Lead; Learning; Lesion; Link; Measures; Memory; Mentors; Monitor; Monkeys; Neurons; Neurosurgeon; Operative Surgical Procedures; Output; Patients; Pharmaceutical Preparations; Phonetics; Play; Population; Positioning Attribute; Prefrontal Cortex; Preparation; Process; Property; Psychological reinforcement; Relapse; Research; Research Personnel; Rewards; Role; Sensory; Sensory Process; Series; Signal Transduction; Site; Stimulus; Structure; Substance abuse problem; Superior temporal gyrus; Temporal Lobe; Testing; Therapeutic; Time; Training; Work; abstracting; addiction; awake; base; cognitive ability; cognitive process; craving; drug addict; drug craving; experience; insight; neuromechanism; neurophysiology; neuroregulation; neurotransmission; nonhuman primate; novel; novel therapeutic intervention; preference; programs; public health relevance; relating to nervous system; research study; reward processing; sensory cortex; sensory stimulus; spatiotemporal; stimulus processing; theories; translational approach

 DESCRIPTION (provided by applicant): In substance abuse disorders, cravings and relapses can occur even after long periods of abstinence, posing a key challenge for successful long-term treatment. These phenomena arise when brain circuits that support reward-based learning and decision-making associate arbitrary cues with behaviorally reinforcing effects of drugs. The orbitofrontal cortex is a region crucial to reward-based decision-making, and has been strongly implicated in addiction. To date, it is known that the orbitofrontal cortex encodes the subjective value of predicted rewards, but the precise mechanism by which orbitofrontal networks use value information to inform learning and choice remains unclear. One theory suggests that orbitofrontal neurons combine multiple inputs, including sensory information to compute an abstract value, so that stimulus information contributes to orbitofrontal value coding in a bottom-up fashion. Another view holds that orbitofrontal cortex makes value-related predictions that influences downstream stimulus representations in a top-down fashion. Crucially, both accounts predict that orbitofrontal neurons encode value information; the distinction lies in how that information is used at a network level. Here, we will investigate how stimulus values are processed in both local orbitofrontal networks and broader functional circuits. To assess local network properties, we will use acute neurophysiology approaches in awake, behaving monkeys as they perform a reward preference task. We will record both single neurons and local field potentials, signals believed to reflect underlying network-level function, and focus on spatiotemporal dynamics in local field potentials, and their relationship to value-encoding neurons. To assess large-scale functional networks, we will record electrocorticography (ECoG) signals from the brains of human patients undergoing intracranial monitoring in preparation for epilepsy surgery. Patients will be tested in a reinforcement-learning task, while we simultaneously record from orbitofrontal cortex and anatomically linked sensory areas that process the stimuli used in the learning task. Over the course of learning, we will determine how orbitofrontal value representations interact with sensory stimulus representations. Overall, this work will use translational approaches to determine how orbitofrontal value coding relates to network-level activity at multiple scales, which could lead to novel therapeutic approaches for conditions of aberrant reward processing, such as addiction disorders. In addition, this proposal offers outstanding training potential. I will benefit from the expertise of two established mentors Dr. Wallis who specializes in non-human primate neurophysiology, and Dr. Chang, a neurosurgeon and researcher specializing in functional brain mapping and ECoG in human patients. Their training will help me build an independent research program that combines multiple approaches to understand how reward processing impacts higher cognitive abilities such as learning, memory and decision-making.

 描述（由申请人提供）：在物质滥用障碍中，即使在长期禁欲后也可能发生渴望和复发，这对成功的长期治疗构成了关键挑战。当支持基于奖励的学习和决策的大脑回路将任意线索与药物的行为强化效应联系起来时，就会出现这些现象。眶额皮层是一个对基于奖励的决策至关重要的区域，并且与成瘾密切相关。到目前为止，我们已经知道眶额皮层对预测奖励的主观价值进行编码，但是眶额网络使用价值信息来告知学习和选择的确切机制仍然不清楚。一种理论认为，眶额神经元联合收割机将多种输入（包括感觉信息）结合起来计算抽象值，因此刺激信息以自下而上的方式有助于眶额值编码。另一种观点认为，眶额皮层做出与价值相关的预测，以自上而下的方式影响下游的刺激表征。至关重要的是，这两种解释都预测眶额神经元编码价值信息;区别在于如何在网络层面使用这些信息。在这里，我们将研究如何刺激值处理在本地orbitofrontal网络和更广泛的功能电路。为了评估局部网络特性，我们将在清醒的行为猴子执行奖励偏好任务时使用急性神经生理学方法。我们将记录单个神经元和局部场电位，这些信号被认为反映了潜在的网络级功能，并专注于局部场电位的时空动态，以及它们与编码值的神经元的关系。为了评估大规模的功能网络，我们将记录来自接受颅内监测的人类患者大脑的皮层电图（ECoG）信号，为癫痫手术做准备。患者将在一个学习任务中进行测试，同时我们从眶额皮层和解剖学上相关的感觉区域记录学习任务中使用的刺激。在学习过程中，我们将确定眶额值表征如何与感官刺激表征相互作用。总的来说，这项工作将使用翻译方法来确定眶额值编码如何在多个尺度上与网络水平活动相关，这可能会导致异常奖励处理条件的新治疗方法，如成瘾症。此外，这项建议提供了出色的培训潜力。我将受益于两位知名导师的专业知识，一位是专门研究非人类灵长类动物神经生理学的沃利斯博士，另一位是专门研究人类患者功能性脑映射和皮层脑电图的神经外科医生和研究人员张博士。他们的培训将帮助我建立一个独立的研究计划，结合多种方法来了解奖励处理如何影响更高的认知能力，如学习，记忆和决策。