Simulated power spectral density (PSD) of background electrocorticogram (ECoG)

被引:145
作者
Freeman, Walter J. [1 ]
Zhai, Jian [2 ]
机构
[1] Univ Calif Berkeley, Dept Mol & Cell Biol, Berkeley, CA 94720 USA
[2] Zhejiang Univ, Dept Math, Hangzhou 310027, Peoples R China
关键词
Cortex; Background activity; Black noise; Electrocorticogram ECoG; Power-law distribution; Power spectral density PSD; EEG ACTIVITY; ORIGIN;
D O I
10.1007/s11571-008-9064-y
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
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.
引用
收藏
页码:97 / 103
页数:7
相关论文
共 19 条
[1]  
Abeles M., 1991, CORTICONICS
[2]   Spatiotemporal analysis of prepyriform, visual, auditory, and somesthetic surface EEGs in trained rabbits [J].
Barrie, JM ;
Freeman, WJ ;
Lenhart, MD .
JOURNAL OF NEUROPHYSIOLOGY, 1996, 76 (01) :520-539
[3]  
Elul R, 1971, Int Rev Neurobiol, V15, P227
[4]  
Freeman W. J., 1975, MASS ACTION NERVOUS
[5]   Fine spatiotemporal structure of phase in human intracranial EEG [J].
Freeman, Walter J. ;
Holmes, Mark D. ;
West, G. Alexander ;
Vanhatalo, Sampsa .
CLINICAL NEUROPHYSIOLOGY, 2006, 117 (06) :1228-1243
[6]  
Freeman WJ, 2007, COGN NEURODYNAMICS, V1, P85, DOI [10.1007/s11571-006-9002-9, 10.1007/S11571-006-9002-9]
[7]   Definitions of state variables and state space for brain-computer interface Part 1. Multiple hierarchical levels of brain function [J].
Freeman, Walter J. .
COGNITIVE NEURODYNAMICS, 2007, 1 (01) :3-14
[8]   Proposed Renormalization Group Analysis of Nonlinear Brain Dynamics at Criticality [J].
Freeman, Walter J. ;
Cao, Tian Yu .
ADVANCES IN COGNITIVE NEURODYNAMICS, PROCEEDINGS, 2008, :145-+
[9]   Origin, structure, and role of background EEG activity. Part 4: Neural frame simulation [J].
Freeman, WJ .
CLINICAL NEUROPHYSIOLOGY, 2006, 117 (03) :572-589
[10]   Origin, structure, and role of background EEG activity. Part 3. Neural frame classification [J].
Freeman, WJ .
CLINICAL NEUROPHYSIOLOGY, 2005, 116 (05) :1118-1129