Mesoscale dynamics underlying expectation bias in the orbitofrontal cortex

项目摘要 适应性行为关键取决于从心理模型或认知地图做出预测的能力。 这些使我们能够在预期事件发生时先发制人，例如通过转移我们的注意力，思想， 和行为。然而，当期望不正确时，这种偏见可能是不适当的，应该是 抑制无法克服期望的影响是精神障碍的一个共同特征， 例如，当固定的负面预测过度偏向思想和行为时，抑郁和焦虑。 为了帮助我们理解这些症状的神经基础，这个项目研究了期望如何影响 动机行为，并在不适当时被抑制。眶额皮质（OFC）是 使用心理模型来创造期望。虽然OFC中的神经元是众所周知的信号值， 预期的结果，这些期望如何与新的信息相平衡，以适应性地指导行为， 没有很好地理解。一个障碍是眶额皮层很大，功能上是异质的，特别是在灵长类动物中， 这使得很难全面了解该地区如何有助于实现预期， 结果行为。在这里，我们提出了一种新的方法，将提供一个前所未有的观点OFC活动 功能性组织。我们将使用定制设计的微皮层电图（µECoG）阵列， 几乎覆盖了猕猴大脑的整个眼眶表面这种中尺度的方法记录了上皮层的信号， 其具有高信噪比、覆盖大的解剖区域并且具有优异的时空分辨率。我们 将联合收割机µECoG技术与猴子的新行为任务相结合， 不同的奖励。期望的行为效应通过工具性的强度来量化 以获得预期的结果。我们已经证明，这种行为是有偏见的事先预期 当矛盾的信息积累时，它会慢慢调整。为了理解期望是如何 通过OFC的动态信号，我们将招募尖端的计算方法，利用大规模的 µECoG记录的性质。我们将研究OFC中的主导信号和次区域变化 产生偏见的期望，并用新的信息更新它们。总之，该项目将提供一个 OFC功能的独特整体视图。这样做，它将促进我们对期望和偏见的理解， 动机行为，并为未来研究OFC在更广泛的电路中的作用奠定基础， 整合感官、记忆和情绪处理，以创建指导适应性行为的心理模型。

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.