An extensive electrophysiological literature has proposed a pathological “slowing” of neuronal activity in patients on the Alzheimer’s disease (AD) spectrum. Supported by numerous studies reporting increases in low frequency and decreases in high frequency neural oscillations, this pattern has been suggested as a stable biomarker with potential clinical utility. However, no spatially-resolved metric of such slowing exists, stymieing efforts to understand its relation to proteinopathy and clinical outcomes. Further, the assumption that this slowing is occurring in spatially overlapping populations of neurons has not been empirically validated. In the current study, we collected cross-sectional resting state measures of neuronal activity using magnetoencephalography (MEG) from 38 biomarker-confirmed patients on the AD spectrum and 20 cognitively-normal (CN) biomarker-negative older adults. From these data, we compute and validate a new metric of spatially resolved oscillatory deviations from healthy aging for each patient on the AD spectrum. Using this Pathological Oscillatory Slowing Index (POSI), we show that patients on the AD spectrum exhibit robust neuronal slowing across a network of temporal, parietal, cerebellar, and prefrontal cortices. This slowing effect is shown to be directly relevant to clinical outcomes, as oscillatory slowing in temporal and parietal cortices significantly predicted both general (i.e. MoCA scores) and domain-specific (i.e. attention, language, and processing speed) cognitive function. Further, regional amyloid-beta (Aβ) accumulation, as measured by quantitative 18F florbetapir PET, robustly predicted the strength of this pathological neural slowing effect, and the strength of this relationship between Aβ burden and neural slowing also predicted attentional impairments across patients. These findings provide empirical support for a spatially overlapping effect of oscillatory neural slowing in biomarker-confirmed patients on the AD spectrum, and link this effect to both regional proteinopathy and cognitive outcomes in a spatially resolved manner. The POSI also represents a novel metric that is of potentially high utility across a number of clinical neuroimaging applications, as oscillatory slowing has also been extensively documented in other patient populations, most notably Parkinson’s disease, with divergent spectral and spatial features.

Introduction Numerous studies have described aberrant patterns of rhythmic neural activity in patients along the Alzheimer's disease (AD) spectrum, yet the relationships between these pathological features and cognitive decline are uncertain. Methods We acquired magnetoencephalography (MEG) data from 38 amyloid‐PET biomarker‐confirmed patients on the AD spectrum and a comparison group of biomarker‐negative cognitively normal (CN) healthy adults, alongside an extensive neuropsychological battery. Results By modeling whole‐brain rhythmic neural activity with an extensive neuropsychological profile in patients on the AD spectrum, we show that the spectral and spatial features of deviations from healthy adults in neural population‐level activity inform their relevance to domain‐specific neurocognitive declines. Discussion Regional oscillatory activity represents a sensitive metric of neuronal pathology in patients on the AD spectrum. By considering not only the spatial, but also the spectral, definitions of cortical neuronal activity, we show that domain‐specific cognitive declines can be better modeled in these individuals.