Affordable Access

Publisher Website

Decrease of non-linear structure in the EEG of Alzheimer patients compared to healthy controls

Authors
Journal
Clinical Neurophysiology
1388-2457
Publisher
Elsevier
Publication Date
Volume
110
Issue
7
Identifiers
DOI: 10.1016/s1388-2457(99)00013-9
Keywords
  • Alzheimer’
  • S Disease
  • Electroencephalography
  • Non-Linear Dynamics
  • Chaos
  • Correlation Dimension
Disciplines
  • Computer Science
  • Mathematics
  • Medicine

Abstract

Abstract Objectives: Non-linear EEG analysis can provide information about the functioning of neural networks that cannot be obtained with linear analysis. The correlation dimension (D 2) is considered to be a reflection of the complexity of the cortical dynamics underlying the EEG signal. The presence of non-linear dynamics can be determined by comparing the D 2 calculated from original EEG data with the D 2 from phase-randomized surrogate data. Methods: In a prospective study, we used this method in order to investigate non-linear structure in the EEG of Alzheimer patients and controls. Twenty-four patients (mean age 75.6 years) with ‘probable Alzheimer's disease’ (NINCDS-ADRDA criteria) and 22 controls (mean age 70.3 years) were examined. D 2 was calculated from original and surrogate data at 16 electrodes and in three conditions: with eyes open, eyes closed and during mental arithmetic. Results: D 2 was significantly lower in the Alzheimer patients compared to controls ( P=0.023). The difference between original and surrogate data was significant in both groups, implicating that non-linear dynamics play a role in the D 2 value. Moreover, this difference between original and surrogate data was smaller in the patient group. D 2 increased with activation, but not significantly more in controls than in patients. Conclusions: In conclusion, we found decreased dimensional complexity in the EEG of Alzheimer patients. This decrease seems to be attributable at least partially to different non-linear EEG dynamics. Because of this, non-linear EEG analysis could be a useful tool to increase our insight into brain dysfunction in Alzheimer's disease.

There are no comments yet on this publication. Be the first to share your thoughts.