Estimation of Parameter k max  in Fractal Analysis of Rat Brain Activity | Zendy

SPASIĆ SLADJANA | Zendy; KALAUZI ALEKSANDAR | Zendy; ĆULIĆ MILKA | Zendy; GRBIĆ GORDANA | Zendy; MARTAĆ LJILJANA | Zendy

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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.

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