Neural circuit mechanisms of affective probabilistic learning

项目摘要 病理性改变的情感学习是几乎所有精神障碍的主要原因，包括 抑郁症和焦虑症。在人类、非人类灵长类动物和啮齿动物中，准确地学习 我们环境中的刺激预测奖惩取决于额叶皮质、纹状体和 边缘系统，如杏仁核。我们已经知道了相当多的神经机制， 与连接这些区域的回路内的自适应学习模式相关联。这些东西怎么了？ 当学习被增强或减弱时，神经活动的模式和涉及的特定路径 心理过程远没有那么清楚。获得这种知识是很重要的，因为它将开始揭示 学习可以被改变的具体机制，是识别 学习病理性改变患者治疗中的生物标志物和辅助治疗。因此，我们的目标是 这里要开始建立自下而上和自上而下的过程如何在水平上影响刺激-奖励学习 单个神经元和电路级的相互作用。我们特别关注腹外侧额叶皮质(PFC) 和杏仁核作为对猕猴的先前研究表明，这些区域，而不是其他部分 额叶皮质和纹状体是有效的概率刺激-奖赏学习所必需的。这两个领域是 也是相互关联的，并且基于神经成像检查，在学习过程中进行功能交互 进一步表明，它们构成了刺激-奖赏学习所必需的功能回路的一部分。我们的假设 自下而上和自上而下对学习的影响会影响内部的神经活动和相互之间的交流 腹外侧丘脑核和杏仁核的基底外侧核，但自下而上和自上而下的学习是这样做的 通过不同的机制和途径。我们将通过记录腹外侧区的活动来检验我们的假设。 猕猴学习过程中前额叶和杏仁基底外侧核以及眶前叶和纹状体的相互联系 在概率刺激-奖励任务中。我们将使用再生神经来评估不同区域之间的功能相互作用 自下而上(目标1)或自上而下改变学习时的网络模型和一致性测量 (目标2)进程。为了测试连接杏仁核和PFC腹外侧部的通路的因果作用，我们还将使用 选择性地抑制这些回路中活性的化学发生方法。因此，使用一种创新的组合 关于行为任务、神经记录、化学发生神经调节和计算方法，我们将 建立PFC-杏仁核通路内神经活动模式及其自下而上的因果重要性 以及自上而下对学习的影响。完成这些实验将有助于了解特定的神经 与改变的学习相关的机制和途径，对确定过程至关重要的信息 在精神障碍方面出了差错。

Project Summary Pathologically altered affective learning is central to accounts of nearly every psychiatric disorder including depression and anxiety disorders. In humans, non-human primates, and rodents accurately learning which stimuli in our environment predict rewards or punishments is dependent on parts of frontal cortex, striatum, and limbic system, such as amygdala. A considerable amount is known about the neural mechanisms that are associated with adaptive patterns of learning within the circuits connecting these areas. What happens to these patterns of neural activity and the specific pathways involved when learning is enhanced or diminished by psychological processes is much less clear. Obtaining this knowledge is important as it would begin to reveal the specific mechanisms through which learning can be altered, information that is essential for identifying biomarkers in and aiding therapies for individuals with pathologically altered learning. Consequently, our aim here is to begin to establish how bottom-up and top-down processes impact stimulus-reward learning at the level of single neurons and circuit-level interactions. We specifically focus on the ventrolateral prefrontal cortex (PFC) and amygdala as prior work in macaque monkeys has shown that these areas, as opposed to other parts of frontal cortex and striatum, are required for efficient probabilistic stimulus-reward learning. These two areas are also reciprocally connected and, based on neuroimaging investigations functionally interact during learning further suggesting that they form part of a functional circuit essential for stimulus-reward learning. Our hypothesis is that bottom-up and top-down influences on learning impact neural activity within and communication between ventrolateral PFC and the basolateral nucleus of the amygdala but that bottom-up and top-down learning do so through different mechanisms and pathways. We will test our hypothesis by recording activity in ventrolateral PFC and basolateral amygdala as well as interconnected parts of orbital PFC and striatum in macaques learning in a probabilistic stimulus-reward task. We will assess functional interaction between areas using recurrent neural network models and measures of coherence when learning is altered by either bottom-up (aim 1) or top-down (aim 2) processes. To test the causal role of pathways linking amygdala and ventrolateral PFC we will also use chemogenetic approaches to selectively inhibit activity in these circuits. Thus, using an innovative combination of behavioral tasks, neural recordings, chemogenetic neuromodulation, and computational approaches we will establish the patterns of neural activity within and causal importance of PFC-amygdala pathways to bottom-up and top-down influences on learning. Completing these experiments will shed light on the specific neural mechanisms and pathways associated with altered learning, information essential for determining the processes that go awry in psychiatric disorders.