Cortical Dynamics and Neural/Behavioral Performance

最佳神经和行为表现的细胞和网络皮层机制是什么？ 大脑皮层清醒状态下的自发变化和诱发变化是通过什么机制影响大脑皮层的活动的 感觉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，到丘脑皮层网络， 调制和行为。理解这些问题不仅是理解正常的 大脑的运作，而且它的运作在各种疾病，从精神分裂症，多动症，自闭症， 他人我们的建议雄心勃勃，但并非不合理或没有重点。我们已经取得了重大进展， 我们正在朝着拼图的重要部分的大致轮廓取得进展，因此相信我们将取得进展， 在资助期间，在详细澄清这两个基本问题方面取得了非常重大的进展 期 一百多年前，两位研究人员耶基斯和多德森指出， 在困难的检测任务，相关的唤醒水平在一个“倒U”形的方式。较低水平增加 唤醒到中等唤醒会提高困难任务的表现，而唤醒的进一步增加 从中间到高将降低性能。这一结果表明，存在一个“最佳状态”， 大脑和行为。令人惊讶的是，直到我们最近的研究在行为小鼠执行一个困难的听觉 检测任务中，最佳状态的皮层活动或回路表征尚未被研究。我们 一项研究表明，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，并与抑制缓慢的皮质和 丘脑皮质活动，锥体细胞膜电位的超极化和低变异性，以及大 振幅和高度可靠的诱发听觉皮层突触反应。这表明了 在这些效应中，我们观察到我们可以预测皮质神经元膜中超过一半的方差， 电位、动作电位，甚至行为表现，只需通过测量瞳孔直径-一个容易的方法， 行为状态快速（秒到秒）波动的测量。通过解释大部分的 神经元和行为的变化，我们已经证明，大脑是更精确和可靠的， 以前认为。在这里，我们建议揭示详细的细胞，调节和网络机制， 解释了状态变化对神经和行为表现的显著影响。通过 结合了最先进的成像、全细胞记录、光遗传学操作和高质量的 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/行为反应的最佳状态的途径。

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.