Resting-State EEG Power Spectral Density Analysis Between Healthy and Cognitively Impaired Subjects

Area of Science:

• Neuroscience
• Medical Technology
• Cognitive Science

Background:

• Distinguishing between healthy cognition, mild cognitive impairment (MCI), and dementia is crucial for timely intervention.
• Current diagnostic methods can be invasive or costly.
• Electroencephalography (EEG) offers a potential noninvasive approach to assess cognitive status.

Purpose of the Study:

• To evaluate the efficacy of electroencephalography (EEG) in differentiating individuals with dementia, MCI, and healthy controls.
• To explore EEG as a noninvasive, cost-effective diagnostic tool for cognitive decline.

Main Methods:

• Utilized a 14-channel Emotiv EPOC-X headset for EEG data acquisition.
• Analyzed power spectral density during a 2-minute eyes-closed resting state.
• Compared EEG findings across three groups: healthy controls (n=79), MCI (n=36), and dementia (n=7).

Main Results:

• EEG successfully differentiated dementia patients from healthy individuals.
• No significant EEG differences were found between individuals with MCI and healthy controls.
• EEG shows promise for detecting advanced cognitive decline but struggles with early-stage detection.

Conclusions:

• EEG is a potential cost-effective, noninvasive alternative for diagnosing advanced cognitive impairment.
• Further research with larger sample sizes and task-based paradigms is needed to enhance EEG's diagnostic precision for MCI.
• EEG's utility in early cognitive decline detection requires further investigation.