Dehghani Nima, Hatsopoulos Nicholas G, Haga Zach D, Parker Rebecca A, Greger Bradley, Halgren Eric, Cash Sydney S, Destexhe Alain
Laboratory of Computational Neuroscience, Unité de Neurosciences, Information et Complexité, CNRS Gif-sur-Yvette, France.
Front Physiol. 2012 Aug 3;3:302. doi: 10.3389/fphys.2012.00302. eCollection 2012.
Self-organized critical states are found in many natural systems, from earthquakes to forest fires, they have also been observed in neural systems, particularly, in neuronal cultures. However, the presence of critical states in the awake brain remains controversial. Here, we compared avalanche analyses performed on different in vivo preparations during wakefulness, slow-wave sleep, and REM sleep, using high density electrode arrays in cat motor cortex (96 electrodes), monkey motor cortex and premotor cortex and human temporal cortex (96 electrodes) in epileptic patients. In neuronal avalanches defined from units (up to 160 single units), the size of avalanches never clearly scaled as power-law, but rather scaled exponentially or displayed intermediate scaling. We also analyzed the dynamics of local field potentials (LFPs) and in particular LFP negative peaks (nLFPs) among the different electrodes (up to 96 sites in temporal cortex or up to 128 sites in adjacent motor and premotor cortices). In this case, the avalanches defined from nLFPs displayed power-law scaling in double logarithmic representations, as reported previously in monkey. However, avalanche defined as positive LFP (pLFP) peaks, which are less directly related to neuronal firing, also displayed apparent power-law scaling. Closer examination of this scaling using the more reliable cumulative distribution function (CDF) and other rigorous statistical measures, did not confirm power-law scaling. The same pattern was seen for cats, monkey, and human, as well as for different brain states of wakefulness and sleep. We also tested other alternative distributions. Multiple exponential fitting yielded optimal fits of the avalanche dynamics with bi-exponential distributions. Collectively, these results show no clear evidence for power-law scaling or self-organized critical states in the awake and sleeping brain of mammals, from cat to man.
自组织临界状态在许多自然系统中都能发现，从地震到森林火灾，在神经系统中也有观察到，特别是在神经元培养物中。然而，清醒大脑中临界状态的存在仍存在争议。在此，我们使用猫运动皮层（96个电极）、猴子运动皮层和运动前皮层以及癫痫患者的人类颞叶皮层（96个电极）中的高密度电极阵列，比较了在清醒、慢波睡眠和快速眼动睡眠期间对不同体内准备进行的雪崩分析。在由单元（多达160个单个单元）定义的神经元雪崩中，雪崩大小从未明显按幂律缩放，而是呈指数缩放或显示中间缩放。我们还分析了不同电极（颞叶皮层多达96个位点，相邻运动和运动前皮层多达128个位点）之间局部场电位（LFP）的动力学，特别是LFP负峰（nLFP）。在这种情况下，由nLFP定义的雪崩在双对数表示中显示幂律缩放，如先前在猴子中报道的那样。然而，定义为正LFP（pLFP）峰的雪崩，其与神经元放电的直接关系较小，也显示出明显的幂律缩放。使用更可靠的累积分布函数（CDF）和其他严格统计方法对这种缩放进行更仔细的检查，并未证实幂律缩放。猫、猴子和人类以及清醒和睡眠的不同脑状态都呈现出相同的模式。我们还测试了其他替代分布。多重指数拟合产生了双指数分布对雪崩动力学的最佳拟合。总体而言，这些结果表明，从猫到人的哺乳动物清醒和睡眠大脑中，没有明确证据支持幂律缩放或自组织临界状态。
