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The Value of Quantitative EEG Measures in the Early Diagnosis of Alzheimer’s Disease

The Value of Quantitative EEG Measures in the Early Diagnosis of Alzheimer’s Disease

Hideaki Tanaka
Copyright: © 2012 |Volume: 3 |Issue: 4 |Pages: 10
ISSN: 1947-3133|EISSN: 1947-3141|EISBN13: 9781466611245|DOI: 10.4018/ijcmam.2012100101
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MLA

Tanaka, Hideaki. "The Value of Quantitative EEG Measures in the Early Diagnosis of Alzheimer’s Disease." IJCMAM vol.3, no.4 2012: pp.1-10. http://doi.org/10.4018/ijcmam.2012100101

APA

Tanaka, H. (2012). The Value of Quantitative EEG Measures in the Early Diagnosis of Alzheimer’s Disease. International Journal of Computational Models and Algorithms in Medicine (IJCMAM), 3(4), 1-10. http://doi.org/10.4018/ijcmam.2012100101

Chicago

Tanaka, Hideaki. "The Value of Quantitative EEG Measures in the Early Diagnosis of Alzheimer’s Disease," International Journal of Computational Models and Algorithms in Medicine (IJCMAM) 3, no.4: 1-10. http://doi.org/10.4018/ijcmam.2012100101

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Abstract

There is growing interest in the discovery of clinically useful, robust biomarkers for Alzheimer’s disease (AD) and pre-AD; the ability to accurately diagnose AD or to predict conversion from a preclinical state to AD would aid in both prevention and early intervention. This study aimed to evaluate the usefulness of a statistical assessment of cortical activity using electroencephalograms (EEGs) with normative data and the ability of such an assessment to contribute to the diagnosis of AD. 15 patients with AD and 8 patients with mild cognitive impairment (MCI) were studied. Eyes-closed resting EEGs were digitally recorded at 200 Hz from 20 electrodes placed according to the international 10/20 system on the scalp, and 20 artifact-free EEG epochs lasting 2.56 ms were selected. Each EEG epoch was down-sampled to 100 Hz and matched to the normal data sets. The selected EEGs from each subject were analyzed by standardized Low Resolution Electromagnetic Tomography (sLORETA) and statistically compared with the age-matched normal data sets at all frequencies. This procedure resulted in cortical z values for each EEG frequency with 0.39 Hz frequency resolution for each subject. Some of the AD and MCI patients presented a peak of negative z value around 20 Hz, revealing hypoactivity of the parahippocampal gyrus and the insula in the sLORETA cortical image. In addition, severe cases of AD showed decreased parietal activation. These results were in agreement with evidence from statistical neuroimaging using MRI/SPECT. Submission of normal EEG data sets to sLORETA might be useful for the detection of diagnostic and predictive markers of AD and MCI in individual patients.

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