ERPs may be sensitive to progressive cognitive changes due to MCI and AD. The P300 and N200 may help identify patients who are likely to progress from MCI to AD, and could be a valuable clinical tool.

Background People with subjective cognitive decline (SCD) may be at increased risk for Alzheimer’s disease (AD). However, not all studies have observed this increased risk. This project examined whether four common methods of defining SCD yields different patterns of atrophy and future cognitive decline between cognitively normal older adults with (SCD+ ) and without SCD (SCD−). Methods Data from 273 Alzheimer’s Disease Neuroimaging Initiative cognitively normal older adults were examined. To operationalize SCD we used four common methods: Cognitive Change Index (CCI), Everyday Cognition Scale (ECog), ECog + Worry, and Worry. Voxel-based logistic regressions were applied to deformation-based morphology results to determine if regional atrophy between SCD− and SCD+ differed by SCD definition. Linear mixed-effects models were used to evaluate differences in future cognitive decline. Results Results varied between the four methods of defining SCD. Left hippocampal grading was more similar to AD in SCD+ than SCD− when using the CCI ( p = .041) and Worry ( p = .021) definitions. The right ( p= .008) and left ( p= .003) superior temporal regions had smaller volumes in SCD+ than SCD−, but only with the ECog. SCD+ was associated with greater future cognitive decline measured by Alzheimer’s Disease Assessment Scale, but only with the CCI definition. In contrast, only the ECog definition of SCD was associated with future decline on the Montreal Cognitive Assessment. Conclusion These findings suggest that the various methods used to differentiate between SCD− and SCD+ influence whether volume differences and findings of cognitive decline are observed between groups in this retrospective analysis.

Background: Cognitive deficits are correlated with increasing age and become more pronounced for people with mild cognitive impairment (MCI) and dementia caused by Alzheimer’s disease (AD). Conventional methods to diagnose cognitive decline (i.e., neuropsychological testing and clinical judgment) can lead to false positives. Tools such as electroencephalography (EEG) offer more refined, objective measures that index electrophysiological changes associated with healthy aging, MCI, and AD. Objective: We sought to review the EEG literature to determine whether visual event-related potentials (ERPs) can distinguish between healthy aging, MCI, and AD. Method: We searched Medline and PyscInfo for articles published between January 2005 and April 2018. Articles were considered for review if they included participants aged 60+ who were healthy older adults or people with MCI and AD, and examined at least one visually elicited ERP component. Results: Our search revealed 880 records, of which 34 satisfied the inclusion criteria. All studies compared cognitive function between at least two of the three groups (healthy older adults, MCI, and AD). The most consistent findings related to the P100 and the P3b; while the P100 showed no differences between groups, the P3b showed declines in amplitude in MCI and AD. Conclusion: Visually elicited ERPs can offer insight into the cognitive processes that decline in MCI and AD. The P3b may be useful in identifying older adults who may develop MCI and AD, and more research should examine the sensitivity and specificity of this component when diagnosing MCI and AD.