Quantitative EEG in frontal lobe dementia

  • C. Besthorn
  • H. Sattel
  • F. Hentschel
  • S. Daniel
  • R. Zerfaβ
  • H. Förstl
Part of the Journal of Neural Transmission Supplement book series (NEURAL SUPPL, volume 47)


A study on quantitative EEG in 14 patients with frontal lobe dementia (FLD), 14 patients with Alzheimer’s disease (AD), and 14 healthy controls was conducted using a complete set of EEG parameters: band power, coherence and fractal dimension. Contrary to earlier studies, we observed higher theta power and sagittal interactions in higher frequency bands in the FLD than in the control group. Lateral interactions of coherence and two indices of fractal dimension were lower in FLD than in controls. There was greater electrophysiological resemblance between the control group and FLD than between any of these groups and AD. This was documented by the results of a discriminant analysis which led to a correct overall classification of 66% of the subjects with misclassifications occurring primarily between control and FLD group.


Fractal Dimension Clinical Dementia Rate High Frequency Band Band Power Theta Band 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Baldwin B, Förstl H (1993) “Pick’s disease” 101 years on: still there, but in need of reform. Br J Psychiatry 163: 100–104PubMedCrossRefGoogle Scholar
  2. Besthorn C (1992) Improving algorithms for Grassberger-Procaccia dimension calculations using Euclidian norms. EEG chaos newsletter 3: 21–24Google Scholar
  3. Besthorn C, Förstl H, Geiger-Kabisch C, Sattel H, Gasser T, Schreiter-Gasser U (1994) EEG coherences in Alzheimer disease. Electroencephalogr Clin Neurophysiol 90: 242–245PubMedCrossRefGoogle Scholar
  4. Besthorn C, Sattel H, Geiger-Kabisch C, Zerfaß R, Förstl H (1995) Parameters of EEG fractal dimension in Alzheimer’s disease. Electroencephalogr Clin Neurophysiol 95: 84–89PubMedCrossRefGoogle Scholar
  5. Bullock TW, McClune MC (1989) Lateral coherence of the electrocorticogram: a new measure of brain synchrony. Electroencephalogr Clin Neurophysiol 73: 479–488PubMedCrossRefGoogle Scholar
  6. Brenner RP, Reynolds CF, Ulrich RF (1988) Diagnostic efficacy of computerized spectral versus visual EEG analysis in elderly normal, demented and depressed subjects. Electroencephalogr Clin Neurophysiol 69: 110–117PubMedCrossRefGoogle Scholar
  7. Caputo JG, Malraison B, Atten P (1986) Determination of attractor dimensions and entropy for various flows: an experi-mentalists viewpoint. In: Mayer-Kress G (ed) Dimension and entropies in chaotic systems. Springer, New YorkGoogle Scholar
  8. Coben LA, Chi D, Snyder AZ, Storandt M (1990) Replication of a study of frequency analysis of the resting awake EEG in mild probable Alzheimer disease. Electroencephalogr Clin Neurophysiol 75: 148–154PubMedCrossRefGoogle Scholar
  9. DeKosky ST, Scheff SW (1990) Synapse loss in frontal cortex biopsies in Alzheimer’s disease: correlation with cognitive severity. Ann Neurol 27: 457–464PubMedCrossRefGoogle Scholar
  10. Dvorak I (1990) Takens versus multichannel reconstruction in EEG correlation exponent estimates. Phys Lett A 151: 225–233CrossRefGoogle Scholar
  11. Fenton, GW (1986) Electroenphysiology of Alzheimer’s disease. Br Med Bull 62: 29–33Google Scholar
  12. Folstein MF, Folstein SE, McHugh PR (1975) “Mini-Mental-State”: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 12: 189–198PubMedCrossRefGoogle Scholar
  13. Förstl H, Burns A, Levy R, Cairns N, Luthert P, Lantos, P (1992) Neurologic signs in Alzheimer’s disease. Arch Neurol 49: 1038–1042PubMedCrossRefGoogle Scholar
  14. Förstl H, Besthorn C, Geiger-Kabisch C, Sattel H, Schreiter-Gasser U (1993) Psychotic features and the course of Alzheimer’s disease: relationship to cognitive, electroencephalographic and computerized tomography findings. Acta Psychiatr Scand 87: 395–399PubMedCrossRefGoogle Scholar
  15. Förstl H, Besthorn C, Hentschel F, Geiger-Kabisch C, Sattel H, Schreiter-Gasser U (1996) Frontal lobe degeneration and Alzheimer’s disease: a controlled study on clinical findings, volumetric brain changes and quantitative electroencephalogry data. Dementia 7: 27–34PubMedGoogle Scholar
  16. Frank GW, Lookman T, Nerenberg MAH (1990) Recovering the attractor: a review of chaotic time series analysis. Can J Phys 68: 711–718CrossRefGoogle Scholar
  17. Gasser T, Bächer P, Möcks J (1982) Transformation toward the normal distribution of broad band spectral parameters of the EEG. Electroencephalogr Clin Neurophysiol 53: 119–124PubMedCrossRefGoogle Scholar
  18. Gasser T, Jennen-Steinmetz C, Verleger R (1985) EEG coherence at rest and during a visual task in two groups of children. Electroencephalogr Clin Neurophysiol 67: 151–158Google Scholar
  19. Giannitrapani D, Collins J (1988) EEG differentiation between Alzheimer’s and non-Alzheimer’s dementias. In: Giannitrapani D, Murri R (eds) The EEG of mental activities. Karger, Basel, pp 26–41Google Scholar
  20. Grassberger P, Procaccia I (1983) Measuring the strangeness of strange attractors. Physica D 9: 189–208CrossRefGoogle Scholar
  21. Gustafson L, Nilsson L (1982) Differential diagnosis of presenile dementia on clinical grounds. Acta Psychiatr Scand 65: 194–209PubMedCrossRefGoogle Scholar
  22. Hooijer C, Jonker C, Posthuma J, Visser SL (1990) Reliability, validity and follow-up of the EEG in senile dementia: sequelae of sequential measurement. Electroencephalogr Clin Neurophysiol 76: 400–412PubMedCrossRefGoogle Scholar
  23. Hughes CP, Berg L, Danziger WL, Coben LA, Martin RL (1982) A new clinical scale for the staging of dementia. Br J Psychiatry 140: 566–572PubMedCrossRefGoogle Scholar
  24. Jansen, BH (1992) “Is it?” and “so what?” — a critical review of EEG chaos. In: Duke DW, Pritchard WS (eds) Measuring chaos in the human brain. World Scientific, SingapureGoogle Scholar
  25. Katznelson RD (1981) EEG recording, electrode placement, and aspects of generator localization. In: Nunez PL (ed) Electrical fields of the brain. Oxford University Press, New York, pp 176–213Google Scholar
  26. Lachenbruch PA (1975) Discriminant analysis. Hafner, New YorkGoogle Scholar
  27. Lutzenberger W, Birbaumer N, Flor H, Rockstroh B, Elbert T (1992) Dimensional analysis of the human EEG and intelligence. Neurosci Lett 143: 10–14PubMedCrossRefGoogle Scholar
  28. Matousek M, Petersèn I (1973) Frequency analysis of the EEG in normal children (1–15 years) and in normal adolescents (16–21 years). In: Kellaway P, Peterson I (eds) Automation of clinical electroencephalography. Raven, New York, pp 75–102Google Scholar
  29. McKhann G, Drachmann D, Folstein M, Katzman R, Price D, Stadlan EM (1984) Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology 34: 939–944PubMedGoogle Scholar
  30. Möcks J, Gasser T (1984) How to select epochs of the EEG at rest for quantitative analysis. Electroencephalogr Clin Neurophysiol 58: 89–92PubMedCrossRefGoogle Scholar
  31. Möcks J, Gasser T, Sroka L (1989) Approaches to correcting EOG artifacts. J Psychophysiol 3: 21–26Google Scholar
  32. Neary D, Snowden JS, Northen B, Goulding P (1988) Dementia of frontal lobe type. J Neurol Neurosurg Psychiatry 51: 353–361PubMedCrossRefGoogle Scholar
  33. Nunez P (1991) Comments on the paper by Miller, Lutzenberger, Elbert. J Psychophysiol 5: 279–280Google Scholar
  34. O’Donnel RD, Berkhout J, Adey RW (1974) Contamination of scalp EEG spectrum during contraction of cranio-facial muscles. Electroencephalogr Clin Neurophysiol 37: 145–151CrossRefGoogle Scholar
  35. Peitgen HO, Jürgens H, Saupe D (1992) Chaos and fractals. New frontiers of science. Springer, New YorkGoogle Scholar
  36. Penttilä M, Partanen JV, Soininen H, Riekkinen PJ (1985) Quantitative analysis of occipital EEG in different stages of Alzheimer’s disease. Electroencephalogr Clin Neurophysiol 60: 1–6PubMedCrossRefGoogle Scholar
  37. Pritchard WS, Duke DW, Coburn KL (1991) Altered EEG dynamical responsivity associated with normal aging and propable Alzheimer’s disease. Dementia 2: 102–105Google Scholar
  38. Pritchard WS, Duke DW (1992) Dimensional analysis of no-task human EEG using the Grassberger Procaccia method. Psychophysiology 29: 182–192PubMedCrossRefGoogle Scholar
  39. Pritchard WS, Duke DW, Coburn KL, Moore NC, Tucker KA, Jann MW, Hostetler RM (1994) EEG based, neural-net predictive classification of Alzheimer’s disease versus control subjects is augmented by non-linear EEG measures. Electroencephalogr Clin Neurophysiol 91: 118–130PubMedCrossRefGoogle Scholar
  40. Röschke J, Aldenhoff J (1991) The dimensionality of human’s electroencephalogram during sleep. Biol Cybernet 64: 307–313CrossRefGoogle Scholar
  41. Schellberg D, Besthorn C, Pfleger W, Gasser T (1993) Emotional activation and topographic EEG band power. J Psychophysiol 7: 24–33Google Scholar
  42. Soininen H, Partanen J, Laulumaa V, Helkala EL, Laakso M Riekkinen PJ (1991) Longitudinal EEG spectral analysis in early stage of Alzheimers disease. Electroencephalogr Clin Neurophysiol 72: 290–297Google Scholar
  43. Stigsby B, Johannesson G, Ingvar DM (1981) Regional EEG analysis and regional cerebral blood flow in Alzheimer’s and Pick’s disease. Electroencephalogr Clin Neurophysiol 51: 537–547PubMedCrossRefGoogle Scholar
  44. Szelies B, Mielke R, Herholz K, Heiss WD (1994) Quantitative topographical EEG compared to FDG PET for classification of vascular and degenerative dementia. Electroencephalogr Clin Neurophysiol 91: 131–139PubMedCrossRefGoogle Scholar
  45. Takens F (1981) Detecting strange attractors in turbulence. In: Rand DA, Young LS (eds) Lecture notes in mathematics, vol 898. Springer, New YorkGoogle Scholar
  46. Theiler J (1991) Some comments on the correlation dimension of 1/f**a noise. Phys Lett A 155: 480–493CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 1996

Authors and Affiliations

  • C. Besthorn
    • 1
  • H. Sattel
    • 1
  • F. Hentschel
    • 1
  • S. Daniel
    • 1
  • R. Zerfaβ
    • 1
  • H. Förstl
    • 1
  1. 1.Zentralinstitut für Seelische GesundheitMannheimFederal Republic of Germany

Personalised recommendations