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Computational Intelligence and Neuroscience
Volume 2010, Article ID 785919, 9 pages
Research Article

Quantitative Estimation of the Nonstationary Behavior of Neural Spontaneous Activity

1Biomedical Engineering Laboratory (BioLab), School of Electronic Engineering (FEELT), Federal University of Uberlândia (UFU), Av. João Naves de Avila 2121, Santa Mônica, 38400-902 Uberlândia, MG, Brazil
2Physics Department, FFCLH, São Paulo University (USP), Av. Bandeirantes 3900.14040-901 Ribeirão Preto, Brazil
3Neuroengineering & Bio-Nano Technology Group, Department of Biophysical and Electronic Engineering, University of Genova, Via Opera Pia 11A, 16145 Genova, Italy

Received 2 November 2008; Revised 20 May 2009; Accepted 10 September 2009

Academic Editor: Rodrigo Quian Quiroga

Copyright © 2010 João-Batista Destro-Filho et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.