THE DYNAMICS OF LONG RANGE CORRELATIONS IN CORTEX: SINGLE UNITS AND OXYGEN

摘要 静止的国家网络是一个令人着迷但却鲜为人知的现象。空间上的集合 分离的区域在fMRI BOLD信号中显示相关的缓慢波动，在以下情况下最为明显 受试者都在休息。这些网络似乎具有临床重要性：脑损伤令人不安 休息状态网络，以及多种临床障碍，包括抑郁症、阅读障碍和 面孔失认症，与特定的静息状态网络异常有关。静息状态 数据被用来推断区域之间的功能联系，但人们对数据是如何推断的知之甚少 神经元活动导致了这些网络的形成。此外，尽管有很多猜测，但几乎没有 知道休息的网络状态可能如何影响与任务相关的神经元活动。 理解静息状态网络和神经活动之间的相互关系 有可能彻底改变我们对大脑功能的理解。 我们的知识之所以存在鸿沟，主要是因为我们很难 描述静止状态网络的特征，而不在活动的MRI扫描仪内，并且难以 在这样的环境中记录神经元的尖峰信号(更难记录 在这样的环境中一次多个小区)。大多数替代方法都涉及到连续录制 静息状态网络和神经元活动，记录较低频率的电信号 (LFP)，或在小鼠中使用光学方法，这提供了接近但不准确的替代 神经元活动(例如，钙信号)和只进入最上层的皮质。 我们建议开发一种创新的方法来解决这个问题：高密度并行 使用碳纤维微丝记录和氧极谱 清醒状态的非人类灵长类动物的皮层。我们已经展示了远距离飞行 用氧极谱记录在标准尺寸微电极上的关联，配对 标准单元记录电极。这些关联类似于静止态现象，但 为了捕捉神经活动的动力学并将其与静息状态的动力学联系起来 网络，需要更密集的空间采样。

ABSTRACT Resting state networks are a fascinating yet poorly understood phenomenon. Sets of spatially separated regions show correlated slow fluctuations in fMRI BOLD signals, most obvious when subjects are at rest. These networks appear to have clinical imporantance: brain injuries perturb resting state networks, and multiple clinical disorders, including depression, dyslexia and prosopagnosia, are associated with specific resting state network abnormalities. Resting state data are used to infer functional connections between regions, but little is known about how neuronal activity gives rise to these networks. Furthermore, despite much speculation, little is known about how resting network state might influence task-related neuronal activity. Understanding the reciprocal relationships between resting state networks and neural activity has the potential to revolutionize our understanding of brain function. The reason that a gap in our knowledge exists is primarily due to the fact that it is difficult to characterize resting state networks without being within an active MRI scanner, and difficult to record spikes from neurons in such an environment (and even more difficult to record from multiple cells at once in such an environment). Alternative methods most involve serial recording of resting state networks and neuronal activity, recording of lower frequency electrical signals (LFP), or the use of optical methods in mouse which provide a close but not exact surrogate of neuronal activity (e.g., calcium signals) and access only to the uppermost layers of cortex. We propose to develop an innovative method to address this issue: high density parallel recording and oxygen polarography using carbon fiber microwires widely dispersed across the cortex of an awake behaving non-human primate. We have already demonstrated long-range correlations using oxygen polarography recorded on standard size micro-electrodes, paired with standard unit-recording electrodes. These correlations resemble resting state phenomenon, but in order to capture and relate the dynamics of neural activity to the dynamics of resting state networks, much denser spatial sampling is required.