Differences between memory encoding and retrieval failure in mild cognitive impairment: results from quantitative electroencephalography and magnetic resonance volumetry

Abstract

Background The memory impairments in mild cognitive impairment (MCI) can be classified into encoding (EF) and retrieval (RF) failure, which can be affected by underlying pathomechanism. We explored the differences structurally and functionally. Methods We compared quantitative electroencephalography (qEEG) power spectra and connectivity between 87 MCI patients with EF and 78 MCI with RF using iSyncBrain® (iMediSync Inc., Republic of Korea) (https://isyncbrain.com/). Voxel-based morphometric analysis of the gray matter (GM) in the MCI groups and 71 cognitive normal controls was also done using the Computational Anatomy Toolbox 12 (http://www.neuro.uni-jena.de/cat/). Results qEEG showed higher frontal theta and lower beta2 band power, and higher theta connectivity in the EF. There was no statistically significant difference in GM volume between the EF and RF. However, when compared to normal control, GM volume reductions due to EF in the left thalamus and bilateral hippocampi and reductions due to RF in the left thalamus, right superior frontal lobe, right superior temporal lobe, and right middle cingulum were observed (p < 0.05, family-wise error correction). Conclusions MCI differs functionally and structurally according to their specific memory impairments. The EF findings are structurally and functionally more consistent with the prodromal Alzheimer’s disease stage than the RF findings. Since this study is a cross-sectional study, prospective follow-up studies are needed to investigate whether different types of memory impairments can predict the underlying pathology of amnestic MCI. Additionally, insufficient sample size may lead to ambiguous statistical findings in direct comparisons, and a larger patient cohort could more robustly identify differences in GM volume reductions between the EF and the RF group.

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“…This result is coherent with previous studies that reported a higher risk of AD in women [ 49 , 50 ]. As expected, the AD-MCI group showed lower scores both at the MMSE and at all the sub-scores of the FWT; suggesting that AD-MCI patients present higher overall cognitive impairment and episodic memory failure in encoding [ 51 , 52 ] and retrieval [ 52 ] with lower sensibility to semantic cue facilitation [ 22 , 26 ].…”

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“…The platform on the cloud comprised of AI-guided EEG denoising process (Kang et al, 2018) trained through 1800 normative EEG data collected during last 7 years, sex classified healthy normative qEEG database, standardized qEEG feature extraction process from adaptive mixture ICA (AMICA) dipole source information to sLORETA-based ROI connectivity, normative library and group statistics for researchers (Kim et al, 2018;D. Lee et al, 2018;Min et al, 2020), and a series of qEEG discriminant biomarker has been implemented, such as early screening of Alzheimer dementia, prognosis of coma patients, and brain age for development disorder (Han et al, 2021;Shim & Shin, 2020;Thapa et al, 2020). Biomarkers for stroke rehabilitation, Parkinson's disease, and early screening and intervention prediction for depression are under development (Baik et al, 2021;Lee et al, 2018Lee et al, , 2020Min et al, 2020).…”