Fractal dimension values of cerebral and cerebellar activity in rats loaded with aluminium

  • Goran Kekovic
  • Milka Culic
  • Ljiljana Martac
  • Gordana Stojadinovic
  • Ivan Capo
  • Dusan Lalosevic
  • Slobodan Sekulic
Original Article


Aluminium interferes with a variety of cellular metabolic processes in the mammalian nervous system and its intake might increase a risk of developing Alzheimer’s disease (AD). While cerebral involvement even at the early stages of intoxication is well known, the role of cerebellum is underestimated. Our aim was to investigate cerebral and cerebellar electrocortical activity in adult male rats exposed to chronic aluminium treatment by nonlinear analytic tools. The adult rats in an aluminium-treated group were injected by AlCl3, intraperitoneally (2 mg Al/kg, daily for 4 weeks). Fractal analysis of brain activity was performed off-line using Higuchi’s algorithm. The average fractal dimension of electrocortical activity in aluminium-treated animals was lower than the average fractal dimension of electrocortical activity in the control rats, at cerebral but not at cerebellar level. The changes in the stationary and nonlinear properties of time series were more expressed in cerebral electrocortical activity than in cerebellar activity. This can be useful for developing effective diagnostic and therapeutic strategies in neurodegenerative diseases.


Aluminium Cerebral and cerebellar electrocortical activity Fractal dimension Alzheimer’s disease 



This study was financed by the Serbian Ministry of Science and Technological Development (Project Grant No. 143021). The kindness of Dr. S. Spasic, from the Institute for Multidisciplinary Studies in Belgrade for ceding us the software for FD calculation, is appreciated.


  1. 1.
    Accardo A, Affinito M, Carozzi M, Bouquiet F (1997) Use of fractal dimension for the analysis of electroencephalographic time series. Biol Cybern 77:339–350CrossRefPubMedGoogle Scholar
  2. 2.
    Adler G, Brassen S, Jajcevic A (2003) EEG coherence in Alzheimer’s dementia. J Neural Trans 110:1051–1058CrossRefGoogle Scholar
  3. 3.
    Baikun W, Dong M, Xiaomeng F, Chunmei J, Hongzhi H, Binjin C (2006) Study on a quantitative electroencephalography power spectrum typical of Chinese Han Alzheimer’s disease patients by using wavelet transforms. J Neural Eng 3:71–77CrossRefGoogle Scholar
  4. 4.
    Banakar Z, Nazardad S, Rakhshan M (1996) Chronic aluminium toxicity and its relation to Alzheimer disease in male rats. Toxicol Lett (Suppl. 1) 88: 60–61Google Scholar
  5. 5.
    Becaria A, Campbell A, Bondy SC (2002) Aluminum as a toxicant. Toxicol Ind Health 18:309–320CrossRefPubMedGoogle Scholar
  6. 6.
    Bendat JS, Piersol AG, Random Data (2000) Analysis and measurement procedures, 3nd ed. Wiley-Interscience, New York, p. 594Google Scholar
  7. 7.
    Besthorn C, Sattel H, Geiger-Kabisch C, Zerfass R, Forstl H (1995) Parameters of EEG dimensional complexity in Alzheimer’s disease. Electroencephalogr Clin Neurophysiol 95:84–89CrossRefPubMedGoogle Scholar
  8. 8.
    Chau T, Chau D, Casas M, Berall G, Kenny DJ (2005) Investigating the stationarity of pediatric aspiration signals. IEEE Trans Neural Syst Rehab Eng 13:99–105CrossRefGoogle Scholar
  9. 9.
    Culic M, Martac Blanusa L, Grbic G, Spasic S, Jankovic B, Kalauzi A (2005) Spectral analysis of cerebellar activity after acute brain injury in anesthetized rats. Acta Neurobiol Exp 65:11–17Google Scholar
  10. 10.
    Culic M, Martac L, Grbic G, Kesic S, Spasic S, Lalosevic D, Sekulic S (2007) Fractal analysis of brain activity in the rat model of cognitive disfunction. In: Proceedings of poster sessions: neuroscience today: neuronal functional diversity and collective behaviors. Firenze, March 26–28, pp. 10–13Google Scholar
  11. 11.
    Culic M, Martac L, Grbic G, Kesic S, Spasic S, Sekulic S, Lalosevic D, Capo I (2007) Aluminium toxicity in rat brain: electrophysiological, histological and behavioral evidence. In: Gantchev N (ed) From basic motor to functional recovery V. Sofia Publ House, Sofia, pp. 224–230Google Scholar
  12. 12.
    Culic M, Kekovic G, Grbic G, Lj Martac, Sokovc M, Podgorac J, Sekulic S (2009) Wavelet and fractal analysis of rat brain activity in seizures evoked by camphor essential oil and 1,8-cineole. Gen Physiol Biophys (Special issue) 28:33–40Google Scholar
  13. 13.
    Daud MS, Yunus J (2005) Relative wavelet energy as a tool to select suitable wavelet for artifact removal in EEG. In: Proceeding of 1st conference on computers, communication, and signal processing, Kuala LumpurGoogle Scholar
  14. 14.
    Escudero J, Abásolo D, Hornero R, Espino P, López M (2006) Analysis of electroencephalograms in Alzheimer’s disease patients with multiscale entropy. Physiol Meas 27:1091–1106CrossRefPubMedGoogle Scholar
  15. 15.
    Exley C, (ed) (2001) Aluminium and Alzheimer’s disease. In: The science that describes the link. Elsevier Science, AmsterdamGoogle Scholar
  16. 16.
    Garcia T, Ribes D, Colomina MT, Cabre M, Domingo H, Gomez M (2009) Evaluation of effects of protective role of melatonin on the behavioral effects of aluminium in a mouse model of Alzheimer’s disease. Toxicology 265:49–55CrossRefPubMedGoogle Scholar
  17. 17.
    Golub MS, Keen CL (1999) Effects of dietary aluminium on pubertal mice. Neurotoxicol Teratol 21:595–602CrossRefPubMedGoogle Scholar
  18. 18.
    Gómez C, Madiavilla A, Hornero R, Abásalo D, Fernández A (2009) Use of Higuchi’s fractal dimension for the analysis of MEG recordings from Alzheimer’s disease patients. Med Eng Phys 31:306–313CrossRefPubMedGoogle Scholar
  19. 19.
    Higuchi T (1988) Approach to an irregular time series on the basis of the fractal theory. Physica D 31:277–283CrossRefGoogle Scholar
  20. 20.
    Jeong J (2004) EEG dynamics in patients with Alzheimer’s disease. Clin Neurophysiol 115:1490–1505CrossRefPubMedGoogle Scholar
  21. 21.
    Jeong J, Chae JH, Kim SY, Han SH (2001) Nonlinear dynamic analysis of EEG in patients with Alzheimer’s disease and vascular dementia. J Clin Neurophysiol 18:58–67CrossRefPubMedGoogle Scholar
  22. 22.
    Kwak YT (2006) Quantitative EEG findings in different stages of Alzheimer’s disease. J Clin Neurophysiol 23:457–462CrossRefGoogle Scholar
  23. 23.
    Lehmann C, Koenig T, Jelic V, Prichep L, John RE, Wahlund LO, Dodge Y, Dierks T (2007) Application and comparison of classification algorithms for recognition of Alzheimer’s disease in electrical brain activity (EEG). J Neurosci Methods 161:342–350CrossRefPubMedGoogle Scholar
  24. 24.
    Lessard SC (2006) Signal processing of random physiological signals. Morgan & Claypool, USAGoogle Scholar
  25. 25.
    Lindau M, Jelic V, Johansson S-E, Andersen C, Wahlund L-O, Almkvist O (2003) Quantitative EEG abnormalities and cognitive dysfunctions in frontotemporal dementia and Alzheimer’s disease. Dement Geriatr Cogn Disord 15:106–114CrossRefPubMedGoogle Scholar
  26. 26.
    Magosso E, Ursino M, Provini F, Montagna P (2007) Wavelet analysis of electroencephalographic and electro-oculographic changes during the sleep onset period. Conf Proc IEEE Eng Med Biol Soc 1:4006–4010Google Scholar
  27. 27.
    Martac L, Kesic S, Culic M, Grbic G, Spasic S, Sekulic S, Lalosevic D (2006) Effect of aluminium neurotoxicity on the rat brain electrocortical activity. Acta Physiol Pharmacol Serb 42:219–225Google Scholar
  28. 28.
    Martac L, Grbic G, Kekovic G, Podgorac J, Culic M, Sekulic S, Lalosevic D, Capo I (2010) Spectral changes of brain activity in offspring of rats exposed to aluminium during gestation and lactation. Arch Biol Sci 62Google Scholar
  29. 29.
    Metin A (1997) Time-frequency and wavelets in biomedical signal processing. In: Fast algorithms for wavelet transform computation. IEEE Computer Society Press, pp 211–222Google Scholar
  30. 30.
    Mizoroki T, Meshitsuka S, Maeda S, Murayama M, Sahara N, Takashima A (2007) Aluminium induces tau aggregation in vitro but not in vivo. J Alzheimer’s Dis 11:419–427Google Scholar
  31. 31.
    Nayak P, Chatterjee AK (2002) Response of regional brain glutamate transaminases of rat to aluminium in protein malnutrition. BMC Neurosci 3:12CrossRefPubMedGoogle Scholar
  32. 32.
    Podgorac J, Sekulić S, Lalosević D, Čapo I, Grbić I, Martać L, Ćulić M (2008) Spectral characteristics of brain activity in off-springs whose mothers drank water solution of AlCl3. In: Abstract Book of the IV Congress of Serbian Society for Neuroscience, Kragujevac, pp. 372-373Google Scholar
  33. 33.
    Polizzi S, Pira E, Ferrara M, Bugiani M, Papaleo A, Albera R, Palmi S (2002) Neurotoxic effects of aluminium among foundry workers and Alzheimer’s disease. Neurotoxicology 23:761–774CrossRefPubMedGoogle Scholar
  34. 34.
    Rosso OA, Blanco S, Rabinowicz A (2003) Wavelet analysis of generalized tonic-clonic epileptic seizures. Signal Process 83:1275–1289CrossRefGoogle Scholar
  35. 35.
    Shena Y, Olbricha E, Achermannb P, Meiera FP (2003) Dimensional complexity and spectral properties of the human sleep. EEG Clin Neurophysiol 114:199–209Google Scholar
  36. 36.
    Sińczuk-Walczak H, Matczak W, Raźniewska G, Szymczak M (2005) Neurological and neurophysiological examinations of workers occupationally exposed to aluminium. Medycina Pracy 56:9–17Google Scholar
  37. 37.
    Spasić S, Kalauzi A, Ćulić M, Grbić G, Martać L (2005) Estimation of parameter kmax in fractal analysis of rat brain activity. Ann NY Acad Sci 1048:427–429CrossRefPubMedGoogle Scholar
  38. 38.
    Spasic S, Kalauzi A, Culic M, Grbic G, Martac L (2005) Fractal analysis of rat brain activity after injury. Med Biol Eng Comput 43:345–348CrossRefPubMedGoogle Scholar
  39. 39.
    Theiler J, Eubank S, Longtin A, Galdrikian B, Doyne Farmer J (1992) Testing for nonlinearity in time series: the method of surrogate data. Physica D 58:77–94CrossRefGoogle Scholar
  40. 40.
    Thuraisingham RA, Tran Y, Boord P, Craig A (2007) Analysis of eyes open, eye closed EEG signals using second-order difference plot. Med Biol Eng Comput 45:1243–1249CrossRefPubMedGoogle Scholar
  41. 41.
    Verner K, Erich M, Colleen M, Vadim I (2001) Quantitative electroencephalography in Alzheimer’s disease: comparison with a control group, population norms and mental status. J Psychiatry Neurosci 26:106–116Google Scholar
  42. 42.
    Walton J, Tuniz C, Fink D, Jacobsen G, Wilcox DU (1995) Uptake of trace amounts of aluminum into the brain from drinking water. Neurotoxicology 16:187–190PubMedGoogle Scholar
  43. 43.
    Woodruff-Pak DS, Agelan A, Del Valle L (2007) A rabbit model of Alzheimer’s disease. Valid at neuropathological, cognitive, and therapeutic levels. J Alzheimer’s Dis 11:371–383Google Scholar
  44. 44.
    Wu X, Jiang X, Marini AM, Lipsky RG (2005) Delineating and understanding cerebellarneuroprotective pathways: potential implication for protecting the cortex. Ann NY Acad Sci 1053:39–47CrossRefPubMedGoogle Scholar
  45. 45.
    Yokel RA (2000) The toxicology of aluminum in the brain: a review. Neurotoxicology 21:813–828PubMedGoogle Scholar
  46. 46.
    Yokel RA, MacNamara PJ (2001) Aluminium toxicokinetics: an updated microreview. Pharmacol Toxicol 88:157–167CrossRefGoogle Scholar

Copyright information

© International Federation for Medical and Biological Engineering 2010

Authors and Affiliations

  • Goran Kekovic
    • 1
  • Milka Culic
    • 1
  • Ljiljana Martac
    • 1
  • Gordana Stojadinovic
    • 1
  • Ivan Capo
    • 2
  • Dusan Lalosevic
    • 2
  • Slobodan Sekulic
    • 2
  1. 1.Institute for Biological Research “S. Stankovic”University of BelgradeBelgradeSerbia
  2. 2.Medical FacultyUniversity of Novi SadNovi SadSerbia

Personalised recommendations