We have analyzed the presence of persistence properties in rabbit brain electrical signals by means of non-equilibrium statistical physics tools. To measure long-memory properties of these experimental signals, we have first determined whether the data are fractional Gaussian noise (fGn) or fractional Brownian motion (fBm) by calculating the slope of the power spectral density plot of the series. The results show that the series correspond to fBm. Then, the data were studied by means of the bridge detrended scaled windowed variance analysis, detecting long-term correlation. Three different types of experimental signals have been studied: neural basal activity without stimulation, the response induced by a single flash light stimulus and the average of the activity evoked by 200 flash light stimulations. Analysis of the series revealed the existence of persistent behavior in all cases. Moreover, the results also exhibited an increasing correlation in the level of long-term memory from recordings without stimulation, to one sweep recording or 200 sweeps averaged recordings. Thus, brain neural electrical activity is affected not only by its most recent states, but also by previous states much more distant in the past.
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This work has been supported by the Grant Nos. MC y T BFM2001-0201, UPV 13665/2001, UPV 00127.312-E-15280/2003, FISS PI041234, MTM 2005-01504 and SAF 2004-06949. The authors appreciate the valuable help of I. Arostegui and also express their thanks to the agency ACTS (Academic Consulting and Translating Services; http://www.euskalnet.net/acts) for having improved the English of this paper.
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de la Fuente, I.M., Perez-Samartin, A.L., Martínez, L. et al. Long-Range Correlations in Rabbit Brain Neural Activity. Ann Biomed Eng 34, 295–299 (2006). https://doi.org/10.1007/s10439-005-9026-z
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DOI: https://doi.org/10.1007/s10439-005-9026-z