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

摘要 静止状态下的国家网络是一个令人着迷但又知之甚少的现象。空间集合 分离的区域在fMRI BOLD信号中显示出相关的缓慢波动，当 受试者休息。这些网络似乎具有临床重要性：脑损伤扰乱 静息状态网络和多种临床疾病，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，但很少有人知道如何 神经元活动产生这些网络。此外，尽管有很多猜测， 了解静息网络状态如何影响与任务相关的神经元活动。 理解静息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。 我们的知识存在差距的原因主要是因为很难 表征静息状态网络，而不在主动MRI扫描仪内，并且难以 在这样的环境中记录来自神经元的尖峰（并且甚至更难以从 在这样的环境中一次多个小区）。替代方法大多涉及串行记录 静息状态网络和神经元活动的记录， (LFP)，或在小鼠中使用光学方法，其提供了接近但不精确的替代物， 神经元活动（例如，钙信号）和仅进入皮质的最上层。 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 记录和氧极谱法使用碳纤维微丝广泛分散在整个 清醒的非人类灵长类动物的大脑皮层我们已经展示了 使用标准尺寸微电极上记录的氧极谱法的相关性， 标准单位记录电极。这些相关性类似于静息状态现象，但 为了捕获神经活动的动态并将其与静息状态的动态相关联 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.