Fractal analysis of rat brain activity after injury

With application of the Higuchi algorithm, fractal dimension (FD) values of the electrocortical activity of the rat parietal cerebral and paravermal cerebellar cortex were calculated, before and after unilateral discrete injury of the left parietal cortex. Immediately following the first acute injury, in a group of six rats, a reversible increase in mean FD was found at the left (ipsilateral side to the injury) cerebral cortex, from 1.38 to 1.59, and at the left cerebellar cortex from 1.51 to 1.73. In addition, an indication of plastic changes after repeated (third) injury was found as an irreversible increase in mean FD: 1.54 on the left and 1.48 on the right side of parietal cortex.

[1]  L. J. Leon,et al.  Electrophysiological basis of mono-phasic action potential recordings , 1999, Medical & Biological Engineering & Computing.

[2]  Wlodzimierz Klonowski,et al.  New methods of nonlinear and symbolic dynamics in sleep EEG-signal analysis , 2003 .

[3]  N. Thakor,et al.  Time-Dependent Entropy Estimation of EEG Rhythm Changes Following Brain Ischemia , 2003, Annals of Biomedical Engineering.

[4]  Comité Científico,et al.  TOWARDS THE ESTIMATION OF THE FRACTAL DIMENSION OF HEART RATE VARIABILITY DATA. , 2004 .

[5]  P. Agostino Accardo,et al.  Use of the fractal dimension for the analysis of electroencephalographic time series , 1997, Biological Cybernetics.

[6]  A. Babloyantz,et al.  Low-dimensional chaos in an instance of epilepsy. , 1986, Proceedings of the National Academy of Sciences of the United States of America.

[7]  Metin Akay,et al.  Fractal Analysis of Heart Rate Variability , 1998 .

[8]  Piotr J. Franaszczuk,et al.  Epileptic seizures are characterized by changing signal complexity , 2001, Clinical Neurophysiology.

[9]  H. Huikuri,et al.  Fractal analysis of heart rate variability and mortality after an acute myocardial infarction. , 2002, The American journal of cardiology.

[10]  N Janakiramiah,et al.  Post-seizure EEG fractal dimension and spectral power predict antidepressant response to unilateral ECT , 2003, Indian journal of psychiatry.

[11]  T. Higuchi.  Approach to an irregular time series on the basis of the fractal theory , 1988 .

[12]  Wlodzimierz Klonowski,et al.  Application of Chaos Theory for EEG-signal Analysis in Patients with Seasonal Affective Disorder , 2000 .

[13]  Aleksandar Kalauzi,et al.  Spectral analysis of cerebellar activity after acute brain injury in anesthetized rats. , 2005, Acta neurobiologiae experimentalis.

[14]  C. King.  Fractal and chaotic dynamics in nervous systems , 1991, Progress in Neurobiology.

[15]  George J. Vachtsevanos,et al.  A comparison of fractal dimension algorithms using synthetic and experimental data , 1999, ISCAS'99. Proceedings of the 1999 IEEE International Symposium on Circuits and Systems VLSI (Cat. No.99CH36349).

[16]  J. Echauz,et al.  Fractal dimension characterizes seizure onset in epileptic patients , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).