Department of Molecular & Cell Biology, University of California at Berkeley, Berkeley, CA, 94720-3206, USA,
Cogn Neurodyn. 2009 Mar;3(1):97-103. doi: 10.1007/s11571-008-9064-y. Epub 2008 Oct 2.
The ECoG background activity of cerebral cortex in states of rest and slow wave sleep resembles broadband noise. The power spectral density (PSD) then may often conform to a power-law distribution: a straight line in coordinates of log power vs. log frequency. The exponent, x, of the distribution, 1/f(x), ranges between 2 and 4. These findings are explained with a model of the neural source of the background activity in mutual excitation among pyramidal cells. The dendritic response of a population of interactive excitatory neurons to an impulse input is a rapid exponential rise and a slow exponential decay, which can be fitted with the sum of two exponential terms. When that function is convolved as the kernel with pulses from a Poisson process and summed, the resulting "brown" or "black noise conforms to the ECoG time series and the PSD in rest and sleep. The PSD slope is dependent on the rate of rise. The variation in the observed slope is attributed to variation in the level of the background activity that is homeostatically regulated by the refractory periods of the excitatory neurons. Departures in behavior from rest and sleep to action are accompanied by local peaks in the PSD, which manifest emergent nonrandom structure in the ECoG, and which prevent reliable estimation of the 1/f(x) exponents in active states. We conclude that the resting ECoG truly is low-dimensional noise, and that the resting state is an optimal starting point for defining and measuring both artifactual and physiological structures emergent in the activated ECoG.
大脑皮层在静息和慢波睡眠状态下的脑电图背景活动类似于宽带噪声。此时,功率谱密度(PSD)可能经常符合幂律分布:对数功率与对数频率的坐标中的一条直线。分布的指数,1/f(x),范围在 2 到 4 之间。这些发现可以用背景活动的神经源模型来解释,该模型是在锥体细胞之间的相互兴奋中。一群相互兴奋的神经元的树突反应对脉冲输入是一个快速指数上升和缓慢指数衰减,可以用两个指数项的和来拟合。当该函数作为核函数与泊松过程的脉冲卷积并求和时,产生的“棕色”或“黑色”噪声符合静息和睡眠时的脑电图时间序列和 PSD。PSD 斜率取决于上升率。观察到的斜率变化归因于背景活动水平的变化,背景活动通过兴奋性神经元的不应期进行自我调节。从静息和睡眠到活动的行为变化伴随着 PSD 中的局部峰值,这在脑电图中表现出突发的非随机结构,并阻止在活动状态下可靠地估计 1/f(x)指数。我们得出结论,静息脑电图确实是低维噪声,静息状态是定义和测量激活脑电图中突发的人为和生理结构的最佳起点。