Introduction
Dementia is a group of neurodegenerative disorders that affect human cognition and behaviors, like the decline in memory, changes in personality and behavior, and impairment in reasoning and language ability. Alzheimer’s disease (AD) is the main cause of dementia, accounting for approximately 60-80% of cases. The prevalence of AD dementia has been increasing continuously due to the aging of our society. To date, there is no cure for AD or any type of dementia. Therefore, detecting cognitive impairment due to AD at its early stages is an urgent requirement for treatment to slow or halt disease progression before major brand damage occurs.
Clinically, AD dementia is detected by comprehensive evaluation procedures, which may include history assessment, neurological examinations, brain imaging, and neuropsychological tests. In addition, cerebrospinal fluid (CSF) Aβ and tau have been considered as core biomarkers of AD in clinical diagnosis and research framework; the decrease of Aβ peptide and the increase of tau protein are generally reported as potential CSF indicators of AD dementia.
Electroencephalography is a method to record the electrical activities of cortical pyramidal neurons in the brain. When there is a large number of neurons fired synchronously, sufficient postsynaptic potentials can be produced and thus observable from the scalp of the brain. The examination of EEG data therefore can reflect the normal brain functions and abnormal neural activities such as in AD. This scalp EEG method is not only non-invasive, relatively safe, and fast but also inexpensive, widely available, and allows repeated measurements on a vast number of high-risk elderly individuals.
Multiple studies have validated the feasibility and reliability of resting-state EEG and ERP (event-related potential) in relation to cognitive impairment due to AD. Notably, EEG spectral measures, synchronization patterns, and ERP latencies have served as potential indicators to screen individuals with mild cognitive impairment (MCI) and AD dementia.
Objective
The objective of this study was to examine the prefrontal EEG and event-related potential (ERP) variables in association with the predementia stages of Alzheimer’s disease (AD).
Methods
- One hundred elderly individuals were recruited for this study.
- The participants were classified into four groups according to their amyloid-beta deposition and neurodegeneration status: cognitive normal, asymptomatic AD (aAD), mild cognitive impairment (MCI) with AD pathology (pAD), and MCI with non-AD pathology.
- Prefrontal resting-state eyes-closed EEG measurements were recorded for five minutes and auditory ERP measurements were recorded for 8 min.
- Three variables of median frequency (MDF), spectrum triangular index (STI), and positive-peak latency (PPL) were employed to reflect EEG indicating, temporal synchrony, and ERP latency respectively.
Results
- Decreasing prefrontal MDF and increasing PPL we’re observed in the MCI with AD pathology.
- Interestingly, after controlling for age and education, a substantial negative association was found between MDF and the aAD and pAD stages with an odds ratio (OR) of 0.58.
- Also, PPL displayed a substantial positive association with these AD stages with an OR of 2.36.
- Additionally, compared with the (MCI) group, significant negative associations were indicated by the aAD group with STI and those in the pAD group with MDF with its of 0.30 and 0.42 respectively.
Conclusion
Slow intrinsic EEG oscillation is associated with MCI due to AD, and a delayed ERP peak latency is likely associated with general cognitive impairment. MCI individuals without AD pathology exhibited better cortical temporal synchronization and faster EEG oscillations than those with aAD or pAD. These findings provided additional insight into how EEG/ERP features change in the very early stages of the AD continuum and suggested that prefrontal EEG/ERP variables can serve as potential markers for screening early stages of cognitive impairment due to AD.