EEG spectral profile to stage Alzheimer's disease

Guido Rodriguez, Francesco Copello, Paolo Vitali, Germana Perego, Flavio Nobili

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: The present study was undertaken to investigate whether a synoptic parameter of quantitative EEG (qEEG), such as the power spectral profile, may be used as a simple marker to stage Alzheimer's disease (AD) in the clinical setting. Methods: To this purpose, the qEEG spectral profile was examined in 48 patients (mean age: 73 years) with probable (NINCDS-ADRDA criteria) AD, who were divided into 4 groups, according to the Global Deterioration Scale (GDS; score: 3-6). The spectral profile of each patient was expressed by the relative power of seven frequency bands (2-3.5, 4-5.5, 6-7.5, 8-9.5, 10-11.5, 12-13.5, 14-22.5 Hz). Mean values in each of the four GDS groups as well as in a control group of 18 healthy elderly subjects underwent multivariate analysis of variance. Results: A normally shaped but shifted-to-the left spectral profile was found in GDS 3 group, whereas a reduced background rhythm with various increase in slow activity power characterized both GDS 4 and 5 groups. Finally, an 'exponential asymptotic' profile with the highest power in the lowest frequencies was the hallmark of GDS 6 group. Overall, the 4-5.5 Hz and the 10-11.5 Hz band powers showed the highest statistical significance in differentiating the patient groups between one another and from controls (P <0.0001). Conclusions: These data show that spectral profile is a very simple parameter which can be used to stage the disease on a pathophysiological basis.

Original languageEnglish
Pages (from-to)1831-1837
Number of pages7
JournalClinical Neurophysiology
Volume110
Issue number10
DOIs
Publication statusPublished - Oct 1 1999

Keywords

  • Alzheimer's disease
  • Quantitative electroencephalography
  • Spectral profile

ASJC Scopus subject areas

  • Clinical Neurology
  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Sensory Systems
  • Physiology (medical)

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