Yu Shan, Klaus Andreas, Yang Hongdian, Plenz Dietmar
Section of Critical Brain Dynamics, National Institute of Mental Health, Bethesda, Maryland, United States of America.
Section of Critical Brain Dynamics, National Institute of Mental Health, Bethesda, Maryland, United States of America; Nobel Institute for Neurophysiology, Department of Neuroscience, Karolinska Institute, Stockholm, Sweden.
PLoS One. 2014 Jun 13;9(6):e99761. doi: 10.1371/journal.pone.0099761. eCollection 2014.
Identification of cortical dynamics strongly benefits from the simultaneous recording of as many neurons as possible. Yet current technologies provide only incomplete access to the mammalian cortex from which adequate conclusions about dynamics need to be derived. Here, we identify constraints introduced by sub-sampling with a limited number of electrodes, i.e. spatial 'windowing', for well-characterized critical dynamics-neuronal avalanches. The local field potential (LFP) was recorded from premotor and prefrontal cortices in two awake macaque monkeys during rest using chronically implanted 96-microelectrode arrays. Negative deflections in the LFP (nLFP) were identified on the full as well as compact sub-regions of the array quantified by the number of electrodes N (10-95), i.e., the window size. Spatiotemporal nLFP clusters organized as neuronal avalanches, i.e., the probability in cluster size, p(s), invariably followed a power law with exponent -1.5 up to N, beyond which p(s) declined more steeply producing a 'cut-off' that varied with N and the LFP filter parameters. Clusters of size s≤N consisted mainly of nLFPs from unique, non-repeated cortical sites, emerged from local propagation between nearby sites, and carried spatial information about cluster organization. In contrast, clusters of size s>N were dominated by repeated site activations and carried little spatial information, reflecting greatly distorted sampling conditions. Our findings were confirmed in a neuron-electrode network model. Thus, avalanche analysis needs to be constrained to the size of the observation window to reveal the underlying scale-invariant organization produced by locally unfolding, predominantly feed-forward neuronal cascades.
尽可能同时记录多个神经元，这对识别皮层动力学有很大帮助。然而，目前的技术只能不完全地接入哺乳动物皮层，而要从该皮层得出关于动力学的充分结论。在这里，我们确定了用有限数量的电极进行子采样（即空间“加窗”）对特征明确的关键动力学——神经元雪崩——所带来的限制。在两只清醒的猕猴休息期间，使用长期植入的96微电极阵列从前运动皮层和前额叶皮层记录局部场电位（LFP）。在整个电极阵列以及按电极数量N（10 - 95）量化的紧凑子区域上识别LFP中的负向偏转（nLFP），即窗口大小。时空nLFP簇组织成神经元雪崩，即簇大小的概率p(s)，在N之前始终遵循指数为 - 1.5的幂律，超过N后，p(s)下降得更陡峭，产生一个随N和LFP滤波参数变化的“截止”。大小s≤N的簇主要由来自独特的、非重复皮层位点的nLFP组成，由附近位点之间的局部传播产生，并携带关于簇组织的空间信息。相比之下，大小s > N的簇以重复的位点激活为主，携带的空间信息很少，反映出采样条件严重失真。我们的发现在神经元 - 电极网络模型中得到了证实。因此，雪崩分析需要限制在观察窗口的大小范围内，以揭示由局部展开的、主要是前馈神经元级联产生的潜在尺度不变组织。
