Electroencephalographic signatures of attentional and cognitive default modes in spontaneous brain activity fluctuations at rest
休息时自发脑活动波动的注意和认知默认模式的脑电图特征
We assessed the relation between hemodynamic and electrical indices of brain function by performing simultaneous functional MRI (fMRI) and electroencephalography (EEG) in awake subjects at rest with eyes closed. Spontaneous power fluctuations of electrical rhythms were determined for multiple discrete frequency bands,and associated fMRI signal modulations were mapped on a voxel-by-voxel basis. There was little positive correlation of localized brain activity with alpha power (8–12 Hz), but strong and widespread negative correlation in lateral frontal and parietal cortices that are known to support attentional processes. Power in a 17–23 Hz range of beta activity was positively correlated with activity in retrosplenial, temporo-parietal, and dorsomedial prefrontal cortices.This set of areas has previously been characterized by high but coupled metabolism and blood flow at rest that decrease whenever subjects engage in explicit perception or action. The distributed patterns of fMRI activity that were correlated with power in different EEG bands overlapped strongly with those of functional connectivity, i.e., intrinsic covariations of regional activity at rest.This result indicates that, during resting wakefulness, and hence the absence of a task, these areas constitute separable and dynamic functional networks, and that activity in these networks is associated with distinct EEG signatures. Taken together with studies that have explicitly characterized the response properties of these distributed cortical systems, our findings may suggest that alpha oscillations signal a neural baseline with lsquo;lsquo;inattentionrsquo;rsquo;whereas beta rhythms index spontaneous cognitive operations during conscious rest.
我们评估脑功能的血流动力学和电气指标关系的同时进行功能磁共振成像（fMRI）和脑电图（EEG）使受试者在清醒状态下闭眼休息。自发的电力波动的电节律被确定为多个离散的频带，相关的fMRI信号调制被映射在体素的基础上。alpha;电源大脑局部活动点呈正相关（8–12 Hz），但强大而广泛的负相关在外侧额叶和顶叶皮层支持注意的过程。休息时在17–23赫兹范围内测活动能力与活性呈正相关，扣带，背内侧前额叶皮层和颞顶叶，这套区域已被具有高耦合的代谢和血流，减少时，受试者进行明确的认知或行为。fMRI的活动，与不同的脑电频段功率与功能连接，即强烈重叠的分布模式，在休息区域活动的内在协同变化。本结果表明，在清醒的休息状态下，和不需要进行其他工作任务时，这些区域构成了分离和动态功能网络，在这些网络活动与不同的脑电特征相关。结合研究明确这些分布式皮质系统的响应特性,我们的发现可能表明，在清醒的静息状态下，alpha;振荡信号的神经底线突出注意力不集中而beta;节律指数自发的进行认知操作。
electroencephalography human brain spontaneous activity
functional magnetic resonance imaging blood oxygenation-leveldependent contrast
脑电图 人类大脑 自发活动 功能性磁共振成像 血氧水平依赖核磁造影
To lsquo;lsquo;do and think nothingrsquo;rsquo; is probably the hardest instruction to follow. By nature restless, we are driven toward activity when awake, and refraining from such activity is an efficient way of falling asleep. Despite its intrinsic instability, the lsquo;lsquo;awake resting statersquo;rsquo; has been the most widely used experimental condition in functional neuroimaging studies. It usually serves to define a lsquo;lsquo;baselinersquo;rsquo; of brain activity, and local task-related deviations from baseline values are interpreted as functionallsquo;lsquo;activationrsquo;rsquo; or lsquo;lsquo;deactivationrsquo;rsquo; in response to a precisely defined
experimental condition (1). Because any such difference is meaningful only if both conditions compared are well defined, there is continuing interest in better understanding brain processes during the resting state.From the earliest electrophysiological recordings, lsquo;lsquo;spontaneous activityrsquo;rsquo;has been observed in neuronal discharge patterns.Neurons fire not only in relation to a sensory or behavioral event but also variably and seemingly unpredictably including atlsquo;lsquo;rest.rsquo;rsquo;In the context of experiments that target stimulus-locked responses,such unpredictable activity has been consideredlsquo;lsquo;noise.rsquo;rsquo; However, recent evidence suggests that spontaneous activity is coherently expressed in larger neuronal populations and functionally meaningful (2–4). But how are spontaneous fluctuations in activity organized macroscopically across the brain? Answering this question could enable us to better understand their functional significance. If, for instance, neural activity fluctuated coherently in specific brain circuits, it might be related to fluctuations of specific mental activities, the nature of which might then be inferred from existing studies reporting explicit activation of these circuits. This result would corroborate the concept of a lsquo;lsquo;default modersquo;rsquo; of brain function as proposed by others (5). The underlying idea is that when one is awake and at lsquo;lsquo;rest,rsquo;rsquo; brain activity switches to default processes, which are suspended when one is engaged in a task. However, demonstrating that during rest neural activity spontaneously fluctuates in specific distributed spatial patterns would also modify this concept. In contrast to a static baseline, rest would appear as intrinsically dynamic and different from other functional states by virtue of preferential association with a distinct subset of the totality of neural (and cognitive) processes.
在“想什么”可能是最难的指令跟踪。自然的不安，我们赶往活动时清醒，避免这样的活动是睡着了的一种有效方法。尽管有其内在的不稳定性，“唤醒状态静息状态”一直是最广泛使用的实验条件在功能神经影像学研究。它通常用来定义一个基准的大脑活动，和当地的任务相关的偏离基线值解释为功能激活”或“失活”回应一个精确的定义实验条件（1）。因为任何这样的差异是有意义的只有在条件比较明确，有在静息状态下更好的理解大脑持续利益的过程。从最早的电生理记录，“自发活动”被观察到神经元的神经元放电模式，不仅关系到一个感觉或行为事件也多变，看似不可预知的包括在休息”语境下的实验，目标刺激锁定反应，这种不可预知的活动被认为是噪声”然而，最近的证据表明，自发活动是在较大的神经元群连贯表达和功能上有意义的（2–4）。但是，如何活动的自发波动组织宏观上整个大脑？回答这个问题可以使我们更好地了解他们的功能意义。如果，例如，神经活动变化一致的特定的大脑，它可能是具体的心理活动的波动有关，它的性质就可以从现有的研究报告明确推断这些电路的激活。这一结果也证实了概念的“默认模式”提出的其他脑功能（5）。其基本思想是，当一个人清醒，在“休息”的大脑活动，切换到默认的过程，这是暂停时，一位从事一项任务。然而，表明在休息神经活动自发波动在特定的分布式空间格局也将修改这个概念。相反，静态基线，休息会出现本质上是动态的，不同于其他的功能状态，凭借优惠的神经（认知）过程的一个独特的子集的关联。
Surprisingly, few studies have addressed this issue so far, despite the implications for interpreting functional neuroimaging studies. Here, we explored the neuroanatomical patterns of resting state fluctuations of human brain activity by simultaneously applying two neurophysiological recording techniques, functional MRI (fMRI) and electroencephalography (EEG). The contrast used in most fMRI studies, including the present one, is blood oxygenation-level-dependent (BOLD) (6). In recent visual stimulation studies combining microelectrode recordings and fMRI in anaesthetized monkeys, a linear correlation was found between the BOLD response and the stimulus driven modulation of the local field potential, a measure of local synaptic activity (7). In relation to this electrical signal, the BOLD response is convolved with a spatio-temporal low-pass filter that reflects the properties of neurovascular coupling. In surface EEG, electrical signals arise from synchronization of postsynaptic potentials across large populations of cortical neurons (8). We used recent methodological developments that allow for continuous acquisition of EEG despite the artifacts generated by fMRI (9). Our starting hypothesis was that the dynamics of EEG activity at rest hold information about the functional state of subjects and can be used to dissociate different brain networks spontaneously engaged and disengaged in the absence of any explicit instruction or task.
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