Prefrontal EEG slowing, synchronization, and ERP peak latency in association with predementia stages of Alzheimer’s disease

Abstract

BackgroundEarly screening of elderly individuals who are at risk of dementia allows timely medical interventions to prevent disease progression. The portable and low-cost electroencephalography (EEG) technique has the potential to serve it.ObjectiveWe examined prefrontal EEG and event-related potential (ERP) variables in association with the predementia stages of Alzheimer’s disease (AD).MethodsOne hundred elderly individuals were recruited from the GARD cohort. The participants were classified into four groups according to their amyloid beta deposition (A+ or A−) and neurodegeneration status (N+ or N−): cognitively normal (CN; A−N−, n = 27), asymptomatic AD (aAD; A + N−, n = 15), mild cognitive impairment (MCI) with AD pathology (pAD; A+N+, n = 16), and MCI with non-AD pathology (MCI(−); A−N+, n = 42). 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 slowing, temporal synchrony, and ERP latency, respectively.ResultsDecreasing prefrontal MDF and increasing PPL were observed in the MCI with AD pathology. Interestingly, after controlling for age, sex, and education, we found a significant negative association between MDF and the aAD and pAD stages with an odds ratio (OR) of 0.58. Similarly, PPL exhibited a significant positive association with these AD stages with an OR of 2.36. Additionally, compared with the MCI(-) group, significant negative associations were demonstrated by the aAD group with STI and those in the pAD group with MDF with ORs of 0.30 and 0.42, respectively.ConclusionSlow 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.SignificanceThe EEG/ERP variables obtained from prefrontal EEG techniques are associated with early cognitive impairment due to AD and non-AD pathology. This result suggests that prefrontal EEG/ERP metrics may serve as useful indicators to screen elderly individuals’ early stages on the AD continuum as well as overall cognitive impairment.

Machine learning based on event-related oscillations of working memory differentiates between preclinical Alzheimer’s disease and neurotypical aging

“…The outcomes of this study underscore the utilization of machine learning approaches, employing EEG spectral features from task-based data, to distinguish cognitively normal older adults with preclinical AD from cognitively normal controls. While a few studies have noted task-related EEG modifications in older adults with an elevated risk of AD (Arakaki et al, 2019; Choi et al, 2023), these investigations have not incorporated machine learning techniques for group classification. Our study addresses this gap by providing validation that memory-related EEG oscillations can signify neurocognitive changes preceding clinical diagnosis.…”

Resting-state prefrontal EEG biomarker in correlation with postoperative delirium in elderly patients

“…The rhythm of this DMN is intrinsic oscillation, and the functional and anatomical disconnection of DMN could represent a core feature of mild cognitive impairment and postoperative cognitive dysfunction ( Berger et al, 2019 ). Recent study has shown that decreasing of MDF was associated with the pre-dementia stage of Alzheimer’s disease ( Choi et al, 2023 ).…”

“…For a more explicit prediction of POD, a further study with additional EEG paradigms of event-related potential related to surgery would be useful. Nevertheless, a recent study revealed that eye-closed resting-state EEG features, MDF could be a good indicator of neuro-degeneration and which is advantageous to practicality in real clinical field ( Choi et al, 2023 ). Notwithstanding these limitations, the study suggests that the preoperative MDF is related to POD.…”

“…We reported the correlation of resting-state EEG slowing (measured using a two-channel prefrontal EEG system) with the mini-mental state exam (MMSE) global and cognitive domain scores, especially those for orientation to time and place ( Choi et al, 2019 ). Additionally, using the same two-channel prefrontal EEG system, we reported that slow intrinsic oscillation is associated with mild cognitive impairment due to Alzheimer’s disease ( Choi et al, 2023 ). This indicated that our two-channel pre-frontal EEG system could yield reliable data quality and be clinically useful to examine cognitive function ( Choi et al, 2019 , 2020 ; Yi et al, 2019 ; Doan et al, 2021 ).…”

EEG Data Analysis Techniques for Precision Removal and Enhanced Alzheimer’s Diagnosis: Focusing on Fuzzy and Intuitionistic Fuzzy Logic Techniques

“…These electrodes are positioned according to the 10-20 system map, which includes standard locations such as Fp1 and Fp2 (frontal polar); F3 and F4 (frontal); C3 and C4 (central); P3 and P4 (parietal); O1 and O2 (occipital); F7 and F8 (frontal lateral); T3 and T4 (temporal); T5 and T6 (temporal lateral); and Fz, Cz, and Pz (midline electrodes). To facilitate accurate and efficient electrode placement, an elastic cap embedded with electrodes aligned according to the 10-20 system is often employed [79,80]. This cap ensures consistent positioning and adjusts to different head sizes, significantly enhancing patient comfort during the procedure.…”