EEG findings in senile dementia and normal aging

Area of Science:

• Neuroscience
• Neurology
• Medical Imaging

Background:

• Dementia, including Alzheimer's disease (AD) and multi-infarct dementia (MID), significantly impacts cognitive function in the elderly.
• Electroencephalography (EEG) is a non-invasive neurophysiological technique used to assess brain activity.
• Distinguishing between different types of dementia and normal aging using EEG requires detailed analysis of specific brainwave patterns.

Purpose of the Study:

• To investigate and compare EEG findings in patients with senile dementia of Alzheimer type (SDA), multi-infarct dementia (MID), and age-matched healthy controls.
• To determine the utility of EEG in differentiating between SDA, MID, and normal aging.
• To identify specific EEG markers that may help distinguish between SDA and MID.

Main Methods:

• EEG recordings were obtained from 62 patients with SDA, 22 patients with MID, and 90 healthy elderly controls.
• Quantitative and qualitative EEG parameters were analyzed, including normality, overall disturbance, dominant occipital rhythm, theta and delta activity, alertness fluctuations, paroxysmal activity, H-reaction, and asymmetric findings.
• Statistical comparisons were performed between the patient groups and controls, as well as between the SDA and MID groups.

Main Results:

• SDA patients showed significant differences from controls across most EEG variables, including slower dominant occipital rhythm with increasing cognitive impairment.
• MID patients differed from controls in all EEG parameters, notably exhibiting more frequent asymmetric findings compared to SDA patients.
• While EEG effectively differentiates dementia patients from healthy controls, distinguishing between SDA and MID based solely on EEG findings was found to be unreliable.

Conclusions:

• EEG is a valuable tool for identifying cognitive impairment in elderly individuals and distinguishing them from healthy controls.
• Specific EEG abnormalities are associated with both Alzheimer's disease and multi-infarct dementia.
• EEG alone has limited reliability in differentiating between Alzheimer's disease and multi-infarct dementia.