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Estimation of Parameter k max in Fractal Analysis of Rat Brain Activity
Author(s) -
SPASIĆ SLADJANA,
KALAUZI ALEKSANDAR,
ĆULIĆ MILKA,
GRBIĆ GORDANA,
MARTAĆ LJILJANA
Publication year - 2005
Publication title -
annals of the new york academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.712
H-Index - 248
eISSN - 1749-6632
pISSN - 0077-8923
DOI - 10.1196/annals.1342.054
Subject(s) - fractal dimension , mathematics , biosignal , measure (data warehouse) , fractal , mathematical analysis , computer science , data mining , telecommunications , wireless
A bstract : We recorded electrocortical activity in anesthetized rats and constructed k max new self‐similar time series, applying Higuchi's algorithm. The aim of this study was to estimate value of the parameter k max in order to obtain fractal dimension values as an optimum measure of biosignal change. After our analysis, electrocortical activity recordings resulted in a family of curves f(k max ). Three regions could be distinguished 2 ≤ k max < 8, with a U‐shape; 8 ≤ k max ≤ 30, with a steeper quasilinear increase; and k max ≥ 30, with a smaller slope quasilinear increase. We suggest the optimum region for k max : 8 < k max < 18, specifically k max = 8.