Mesoscale dynamics underlying expectation bias in the orbitofrontal cortex

眶额皮层期望偏差的中尺度动力学

• 批准号: 10571994
• 负责人: Erin L Rich
• 金额: $ 25.27万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-12-01 至 2024-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10571994
• 关键词: Adaptive Behaviors; Address; Anatomy; Animals; Anterior; Anxiety; Area; Attention; Behavior; Behavioral; Belief; Brain; Code; Cognitive; Computing Methodologies; Custom; Electrocorticogram; Electrophysiology (science); Emotional; Equilibrium; Event; Functional Magnetic Resonance Imaging; Future; Glean; Goals; Human; Macaca; Macaca mulatta; Maps; Memory; Mental Depression; Mental disorders; Modeling; Monkeys; Nature; Neurons; Noise; Outcome; Pathology; Perception; Placebo Effect; Play; Primates; Psyche structure; Records; Resolution; Rewards; Role; Sampling; Sensory; Signal Transduction; Specificity; Surface; Symptoms; Taste Perception; Technology; Testing; Thinking; Update; Variant; awake; design; expectation; information processing; insight; miniaturize; motivated behavior; neural; neural circuit; neuromechanism; novel; novel strategies; psychiatric symptom; response; sensory input; sensory integration; spatiotemporal; temporal measurement; Adaptive Behaviors; Address; Anatomy; Animals; Anterior; Anxiety; Area; Attention; Behavior; Behavioral; Belief; Brain; Code; Cognitive; Computing Methodologies; Custom; Electrocorticogram; Electrophysiology (science); Emotional; Equilibrium; Event; Functional Magnetic Resonance Imaging; Future; Glean; Goals; Human; Macaca; Macaca mulatta; Maps; Memory; Mental Depression; Mental disorders; Modeling; Monkeys; Nature; Neurons; Noise; Outcome; Pathology; Perception; Placebo Effect; Play; Primates; Psyche structure; Records; Resolution; Rewards; Role; Sampling; Sensory; Signal Transduction; Specificity; Surface; Symptoms; Taste Perception; Technology; Testing; Thinking; Update; Variant; awake; design; expectation; information processing; insight; miniaturize; motivated behavior; neural; neural circuit; neuromechanism; novel; novel strategies; psychiatric symptom; response; sensory input; sensory integration; spatiotemporal; temporal measurement

Project Summary Adaptive behavior critically depends on the ability to make predictions from mental models, or cognitive maps. These allow us to act preemptively when events are expected, for instance by shifting our attention, thoughts, and behavior. However, when expectations are incorrect, such biases may be inappropriate and should be suppressed. An inability to override the effects of expectations is a common feature of psychiatric disorders such as depression and anxiety, for instance when fixed negative predictions excessively bias thoughts and behavior. To help us understand the neural basis for these symptoms, this project examines how expectations influence motivated behavior and are suppressed when they are not appropriate. The orbitofrontal cortex (OFC) is critical for using mental models to create expectations. Although neurons in OFC are well-known to signal the value of expected outcomes, how these expectations are balanced with new information to adaptively guide behavior is not well understood. One hurdle is that OFC is large and functionally heterogeneous, particularly in primates, making it difficult to glean a comprehensive understanding of how the region contributes to expectations and resulting behavior. Here, we propose a novel approach that will provide an unprecedented view of OFC activity and functional organization. We will use micro-electrocorticography (µECoG) arrays custom-designed to cover nearly the entire orbital surface in the macaque brain. This mesoscale approach records epicortical signals, which are high signal-to-noise, cover large anatomical areas, and have excellent spatiotemporal resolution. We will combine µECoG technology with a novel behavioral task for monkeys, in which they expect and choose between different rewards. Behavioral effects of expectations are quantified by the intensity of instrumental responses to obtain an expected outcome. We have shown that this behavior is biased by prior expectations and slowly adjusts when contradictory information accumulates. To understand how expectations are dynamically signaled by OFC, we will enlist cutting-edge computational methods that leverage the large-scale nature of the µECoG recordings. We will investigate both dominant signals in OFC and subregional variation that produce biasing expectations and update them with new information. Together, this project will provide a uniquely holistic view of OFC function. In doing so, it will advance our understanding of expectation and bias in motivated behavior, and lay the groundwork for future studies investigating OFC’s role in broader circuits that integrate sensory, memory, and emotional processing to create the mental models that guide adaptive behavior.

项目摘要 自适应行为在很大程度上取决于从心理模型或认知图做出预测的能力。 这些使我们能够在预期事件时先发行，例如，通过转移我们的注意力，思想， 和行为。但是，当期望不正确时，这种偏见可能是不合适的，应该是 被压制。无法覆盖期望的影响是精神疾病的共同特征 作为抑郁症和焦虑，例如，当固定负面预测极为偏见时，思想和行为。 为了帮助我们了解这些符号的神经基础，该项目考试期望如何影响 动机行为并在不合适的情况下被压制。眶额皮质（OFC）至关重要 用于使用心理模型创造期望。尽管OFC中的神经元是众所周知的，以表明 预期的结果，这些期望如何与新信息平衡以适应性指导行为是 不太了解。一个障碍是OFC很大且功能性异构，尤其是在初级中， 很难全面了解该地区如何对期望和期望的贡献 由此产生的行为。在这里，我们提出了一种新颖的方法，该方法将为OFC活动提供前所未有的观点 和功能组织。我们将使用自定义设计的微皮质学（µECOG）阵列覆盖 猕猴大脑中几乎整个轨道表面。这种中尺度方法记录了史上的信号， 高信号到噪声，覆盖大型解剖区域，并具有出色的时空分辨率。 将把µEcog技术与猴子的新型行为任务相结合，他们期望和选择 期望的行为效应通过工具的强度来量化 获得预期结果的回应。我们已经表明，这种行为是由先前期望的偏见 并在矛盾的信息积累时慢慢调整。了解期望的方式 通过OFC动态签名，我们将招募利用大规模的尖端计算方法 µecog记录的性质。我们将研究OFC和下区域变化中的主要信号 这会产生偏见的期望，并使用新信息更新它们。该项目在一起将提供一个 OFC功能的独特整体视图。这样，它将提高我们对期望和偏见的理解 动机行为，并为未来的研究奠定了基础，以调查CC在更广泛电路中的作用 集成感官，记忆和情感处理，以创建指导自适应行为的心理模型。