Cortical Dynamics and Neural/Behavioral Performance

最佳神经和行为表现的细胞和网络皮质机制是什么？ 大脑皮层觉醒状态的自发和诱发变化通过什么机制产生影响 感官处理和行为？我的实验室的目标是回答这些广泛而重要的问题 从细胞和突触特性，到局部回路，再到丘脑皮质网络， 调制和行为。回答这些问题不仅是理解常态的基础 大脑的运作，以及它在各种疾病中的运作，从精神分裂症，到ADHD，自闭症，以及 其他。我们的建议是雄心勃勃的，但不是不合理的或不集中的。我们已经取得了重大进展 在为拼图的重要部分勾勒出大致轮廓方面取得了进展，因此相信我们将取得 在供资期间在详细澄清这两个基本问题方面取得了非常重大的进展 句号。 一百多年前，两位研究人员耶克斯和多德森注意到，最佳性能 难度检测任务与觉醒水平呈倒U形相关。从低到高 唤醒到中等程度的唤醒将提高在困难任务中的表现，同时进一步提高唤醒 从中到高会降低性能。这一结果表明，存在一个“最佳状态” 大脑和行为都是如此。令人惊讶的是，直到我们最近对行为正常的小鼠进行了一项困难的听觉测试 检测任务中，最佳状态的大脑皮层活动或回路表征尚未被研究。我们的 研究表明，执行困难的听觉感觉检测任务的最佳状态 发生在中等水平的觉醒，并与抑制慢的皮质和 丘脑皮质活动，一种超极化和低变异性的锥体细胞膜电位，和大 波幅和高度可靠的诱发听觉皮质突触反应。在广泛的性质的指示中 在这些影响中，我们观察到，我们可以预测大脑皮层神经元膜的一半以上的变异。 只需通过测量瞳孔直径，就可以轻松地获得电位、动作电位，甚至行为表现 获得行为状态快速(秒至秒)波动的测量结果。通过解释很大一部分 神经元和行为的差异，我们已经证明大脑比 之前的想法是。在这里，我们打算揭示详细的细胞、调制和网络机制， 解释了状态变化对神经和行为表现的这些显著影响。通过一个 结合最先进的成像、全细胞记录、光遗传操作和高质量 行为监测，我们将能够详细说明多个神经元和神经调节的贡献 确定神经/行为反应最佳状态的途径。

What are the cellular and network cortical mechanisms of optimal neural and behavioral performance? Through what mechanisms do spontaneous and evoked changes in the waking state of the cortex influence sensory processing and behavior? The goal of my laboratory is to answer these broad and important questions at levels extending from cellular and synaptic properties, to local circuits, to thalamocortical networks, modulation, and behavior. Answering these questions are fundamental not only to understanding the normal operation of the brain, but also its operation in a variety of disorders, from schizophrenia, to ADHD, autism, and others. Our proposal is ambitious, but not unreasonable or unfocused. We have already made significant progress towards a broad outline of important pieces of the puzzle, and therefore are confident that we will make very significant progress towards a detailed clarification of these two fundamental questions during the funding period. More than a hundred years ago, two investigators, Yerkes and Dodson, noted that optimal performance on difficult detection tasks was related to arousal level in an “inverted-U” shaped fashion. Increases from low arousal to intermediate arousal would enhance performance on difficult tasks, while further increases in arousal from intermediate to high would decrease performance. This result suggests that there is an “optimal state” for both the brain and behavior. Surprisingly, until our recent study in behaving mice performing a difficult auditory detection task, the cortical activity or circuit representation of optimal state had not been investigated. Our investigation revealed that the optimal state for performance of a difficult auditory sensory detection task occurred at intermediate levels of arousal and was associated with the suppression of slow corticocortical and thalamocortical activity, a hyperpolarized and low variability of pyramidal cell membrane potential, and large amplitude and highly reliable evoked auditory cortical synaptic responses. In an indication of the broad nature of these effects, we observed that we could predict more than half of the variance in cortical neuronal membrane potential, action potential, and even behavioral performance simply by measuring the pupil diameter – an easily obtained measure of rapid (second to second) fluctuations in behavioral state. By explaining a large fraction of neuronal and behavioral variance, we have demonstrated that the brain is much more precise and reliable than previously thought. Here we propose to reveal the detailed cellular, modulatory, and network mechanisms that account for these prominent effects of state variation on neural and behavioral performance. Through a combination of state-of-the-art imaging, whole cell recording, optogenetic manipulation, and high quality behavioral monitoring, we will be able to detail the contribution of multiple neuronal and neuromodulatory pathways to the determination of optimal state for neural/behavioral responses.