Understanding the role of quantitative internal signals in behavioral flexibility

项目总结/摘要 这项资助的重点是最近的经验-在过去的几秒钟到几分钟-如何让大脑 更新对世界的期望，然后用这些期望来指导行为。灵活的能力 以这种方式调整自己的行动是适应性人类行为的标志。在神经层面， 在非人灵长类动物和其它脊椎动物模型中已经描述了相关的细胞活性相关物 系统.例如，在几百毫秒或几秒内， 导致行为决定，这些斜坡的上升速度跟踪逐渐积累的 与正在作出的决定有关的信息。因此，斜坡活动是一个相关的增加 预期需要做出重要决定，并且坡道到达的时刻 阈值水平通常表示何时做出最终决定。另一个显著的内部关联 期望是奖励预测错误信号：当动物接受到 意想不到的奖励或奖励令人惊讶地被省略。奖励预测误差信号似乎准备好了， 根据习得的期望调整动物和人类的行为。更清楚地了解量化的程度 内部信号--如斜坡和奖励预测错误活动--有助于行为灵活性， 认知神经科学的重要一步在这里，我们建议开发两个新的行为任务， 拴在果蝇身上，我们可以同时进行神经生理学研究。我们的第一个目标是利用其中一个 任务，以测试这一假设，斜坡神经信号是在形成行为决策的基础， 几十秒到几分钟的时间尺度，而不仅仅是更短的时间尺度， 时间尺度和实验室定义的任务（如迄今为止所示）。这一发现表明， 在现实世界条件下，在几分钟内建立的预期最终会被输入缓慢上升的神经元信号， 从而指导自然决策。我们的第二个目标是发现水果中的奖励预测误差信号 苍蝇积极地执行一个试验一个试验的条件反射任务，并定义一个电路机制，通过该机制， 信号使大脑能够形成定量的精确预期--在逐个试验的基础上进行更新-- 奖励在不久的将来到达或不到达的可能性。这些发现在一个遗传学上易于处理的模型中 将告诉我们，我们的大脑如何产生期望，允许灵活的，适应性的行为， 最终为灵活性受损的神经系统疾病提供新的治疗方法， 强迫症

Project Summary / Abstract This grant focuses on how very recent experiences––over the past few seconds to minutes––allow brains to update expectations about the world and then use these expectations to guide behavior. The ability to flexibly adjust one's course of action in this manner is a hallmark of adaptive human behavior. At the neural level, relevant cellular-activity correlates have been described in non-human primates and other vertebrate model systems. For example, ramping neural activity has been observed in the few hundred milliseconds, or seconds, leading up to behavioral decisions and the rate of rise of these ramps tracks the gradual accumulation of information relevant for the decision being made. Ramping activity is thus a correlate of an increasing expectation that an important decision needs to be made and the moment at which the ramp reaches a threshold level typically signifies when a final decision is taken. Another salient correlate of internal expectations are reward-prediction error signals: bursts of dopamine-neuron activity when an animal receives an unexpected reward or a reward is surprisingly omitted. Reward-prediction error signals seem well poised to adjust animal and human behavior based on learned expectations. A clearer picture of how quantitative internal signals––like ramping and reward-prediction error activity––contribute to behavioral flexibility would be an important step forward for cognitive neuroscience. Here, we propose to develop two new behavioral tasks in tethered Drosophila, where we can perform simultaneous neurophysiology. Our first aim is to use one of these tasks to test the hypothesis that ramping neural signals are fundamental in forming behavioral decisions over tens-of-seconds to minutes timescales in ethologically relevant contexts, rather than just on much shorter timescales and in laboratory defined tasks (as has been shown to date). Such a discovery would argue that expectations built over minutes in real-world conditions are ultimately fed into slowly ramping neuronal signals so as to guide natural decision-making. Our second aim is to discover reward-prediction error signals in fruit flies actively performing a trial-by-trial conditioning task and to define a circuit mechanism through which such signals allow brains to form quantitatively precise expectations––updated on a trial-by-trial basis––on the likelihood of rewards arriving or not arriving in the near future. Such discoveries in a genetically tractable model will inform our thinking on how our brains generate expectations that allow for flexible, adaptive behaviors, ultimately informing new therapeutic approaches to neurological conditions in which flexibility is impaired, such as obsessive-compulsive disorder.