Title
Quantitative estimation of the nonstationary behavior of neural spontaneous activity.
Abstract
The "stationarity time" (ST) of neuronal spontaneous activity signals of rat embryonic cortical cells, measured by means of a planar Multielectrode Array (MEA), was estimated based on the "Detrended Fluctuation Analysis" (DFA). The ST is defined as the mean time interval during which the signal under analysis keeps its statistical characteristics constant. An upgrade on the DFA method is proposed, leading to a more accurate procedure. Strong statistical correlation between the ST, estimated from the Absolute Amplitude of Neural Spontaneous Activity (AANSA) signals and the Mean Interburst Interval (MIB), calculated by classical spike sorting methods applied to the interspike interval time series, was obtained. In consequence, the MIB may be estimated by means of the ST, which further includes relevant biological information arising from basal activity. The results point out that the average ST of MEA signals lies between 2-3 seconds. Furthermore, it was shown that a neural culture presents signals that lead to different statistical behaviors, depending on the relative geometric position of each electrode and the cells. Such behaviors may disclose physiological phenomena, which are possibly associated with different adaptation/facilitation mechanisms.
Year
DOI
Venue
2010
10.1155/2010/785919
Comp. Int. and Neurosc.
Keywords
Field
DocType
interspike interval time series,stationarity time,statistical characteristic,different statistical behavior,quantitative estimation,nonstationary behavior,dfa method,basal activity,mean time interval,neural spontaneous activity,mea signal,strong statistical correlation,average st
Spike sorting,Pattern recognition,Computer science,Detrended fluctuation analysis,Artificial intelligence,Statistical correlation,Multielectrode array,Amplitude,Machine learning,Physiological Phenomenon
Journal
Volume
ISSN
Citations 
2010,
1687-5273
0
PageRank 
References 
Authors
0.34
5
7