Javascript must be enabled to continue!
Spatially resolved neural slowing predicts impairment and amyloid burden in Alzheimer’s disease
View through CrossRef
AbstractAn extensive electrophysiological literature has proposed a pathological ‘slowing’ of neuronal activity in patients on the Alzheimer’s disease 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 from 38 biomarker-confirmed patients on the Alzheimer’s disease spectrum and 20 cognitively normal biomarker-negative older adults. From these data, we compute and validate a new metric of spatially resolved oscillatory deviations from healthy ageing for each patient on the Alzheimer’s disease spectrum.Using this Pathological Oscillatory Slowing Index, we show that patients on the Alzheimer’s disease 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. Montreal Cognitive Assessment scores) and domain-specific (i.e. attention, language and processing speed) cognitive function. Further, regional amyloid-β accumulation, as measured by quantitative 18F florbetapir PET, robustly predicted the magnitude of this pathological neural slowing effect, and the strength of this relationship between amyloid-β 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 Alzheimer’s disease spectrum, and link this effect to both regional proteinopathy and cognitive outcomes in a spatially resolved manner. The Pathological Oscillatory Slowing Index 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.
Title: Spatially resolved neural slowing predicts impairment and amyloid burden in Alzheimer’s disease
Description:
AbstractAn extensive electrophysiological literature has proposed a pathological ‘slowing’ of neuronal activity in patients on the Alzheimer’s disease 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 from 38 biomarker-confirmed patients on the Alzheimer’s disease spectrum and 20 cognitively normal biomarker-negative older adults.
From these data, we compute and validate a new metric of spatially resolved oscillatory deviations from healthy ageing for each patient on the Alzheimer’s disease spectrum.
Using this Pathological Oscillatory Slowing Index, we show that patients on the Alzheimer’s disease 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.
Montreal Cognitive Assessment scores) and domain-specific (i.
e.
attention, language and processing speed) cognitive function.
Further, regional amyloid-β accumulation, as measured by quantitative 18F florbetapir PET, robustly predicted the magnitude of this pathological neural slowing effect, and the strength of this relationship between amyloid-β 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 Alzheimer’s disease spectrum, and link this effect to both regional proteinopathy and cognitive outcomes in a spatially resolved manner.
The Pathological Oscillatory Slowing Index 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.
Related Results
Leveraging speech and artificial intelligence to screen for early Alzheimer’s disease and amyloid beta positivity
Leveraging speech and artificial intelligence to screen for early Alzheimer’s disease and amyloid beta positivity
Abstract
Early detection of Alzheimer’s disease is required to identify patients suitable for disease-modifying medications and to improve access to non-pharmacologi...
Brain MRI signatures across sex and CSF Alzheimer’s disease biomarkers
Brain MRI signatures across sex and CSF Alzheimer’s disease biomarkers
Abstract
The relationship between cerebrospinal fluid (CSF) biomarkers of Alzheimer’s disease and neurodegenerative effects is not fully understood. This study inves...
ATN status in amnestic and non-amnestic Alzheimer’s disease and frontotemporal lobar degeneration
ATN status in amnestic and non-amnestic Alzheimer’s disease and frontotemporal lobar degeneration
AbstractUnder the ATN framework, cerebrospinal fluid analytes provide evidence of the presence or absence of Alzheimer’s disease pathological hallmarks: amyloid plaques (A), phosph...
Clinical characteristics and biomarker profile in early- and late-onset Alzheimer’s disease: the Shanghai Memory Study
Clinical characteristics and biomarker profile in early- and late-onset Alzheimer’s disease: the Shanghai Memory Study
Abstract
Early-onset Alzheimer’s disease constitutes ∼5–10% of Alzheimer’s disease. Its clinical characteristics and biomarker profiles are not well documented. To c...
Penerapan Metode Convolutional Neural Network untuk Diagnosa Penyakit Alzheimer
Penerapan Metode Convolutional Neural Network untuk Diagnosa Penyakit Alzheimer
Abstract— Alzheimer's disease is a neurodegenerative disease that develops gradually, and is associated with cardiovascular and cerebrovascular problems. Alzheimer's is a serious d...
Reasons for undergoing amyloid imaging among cognitively unimpaired older adults
Reasons for undergoing amyloid imaging among cognitively unimpaired older adults
AbstractObjectivesPreclinical Alzheimer’s disease (AD) clinical trials screen cognitively unimpaired older adults for biomarker criteria and disclose their results. We examined whe...
A glycan biomarker predicts cognitive decline in amyloid- and tau-negative patients
A glycan biomarker predicts cognitive decline in amyloid- and tau-negative patients
Abstract
Early detection of Alzheimer’s disease is vital for timely treatment. Existing biomarkers for Alzheimer’s disease reflect amyloid- and tau-related pathology...
Pathological and neurophysiological outcomes of seeding human-derived tau pathology in the APP-KI NL-G-F and NL-NL mouse models of Alzheimer’s Disease
Pathological and neurophysiological outcomes of seeding human-derived tau pathology in the APP-KI NL-G-F and NL-NL mouse models of Alzheimer’s Disease
AbstractThe two main histopathological hallmarks that characterize Alzheimer’s Disease are the presence of amyloid plaques and neurofibrillary tangles. One of the current approache...

