Neurophysiological signatures of Alzheimer's disease and frontotemporal lobar degeneration: pathology versus phenotype.
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Brain : a journal of neurology
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Sami, S., Williams, N., Hughes, L., Cope, T., Rittman, T., Coyle-Gilchrist, I. T., Henson, R., & et al. (2018). Neurophysiological signatures of Alzheimer's disease and frontotemporal lobar degeneration: pathology versus phenotype.. Brain : a journal of neurology, 141 (8), 2500-2510. https://doi.org/10.1093/brain/awy180
The disruption of brain networks is characteristic of neurodegenerative dementias. However, it is controversial whether changes in connectivity reflect only the functional anatomy of disease, with selective vulnerability of brain networks, or the specific neurophysiological consequences of different neuropathologies within brain networks. We proposed that the oscillatory dynamics of cortical circuits reflect the tuning of local neural interactions, such that different pathologies are selective in their impact on the frequency spectrum of oscillations, whereas clinical syndromes reflect the anatomical distribution of pathology and physiological change. To test this hypothesis, we used magnetoencephalography of five patient groups, representing dissociated pathological subtypes and distributions across frontal, parietal and temporal lobes: amnestic Alzheimer's disease, posterior cortical atrophy, and three syndromes associated with frontotemporal lobar degeneration. We measured effective connectivity with graph theory-based measures of local efficiency, using partial directed coherence between sensors. As expected, each disease caused large-scale changes of neurophysiological brain networks, with reductions in local efficiency compared to controls. Critically however, the frequency range of altered connectivity was consistent across clinical syndromes that shared a likely underlying pathology, whilst the localisation of changes differed between clinical syndromes. Multivariate pattern analysis of the frequency-specific topographies of local efficiency separated the disorders from each other and from controls (accuracy 62% to 100%, according to the groups’ differences in likely pathology and clinical syndrome). The data indicate that magnetoencephalography has the potential to reveal specific changes in neurophysiology resulting from neurodegenerative disease. Our findings confirm that while clinical syndromes have characteristic anatomical patterns of abnormal connectivity that may be identified with other methods like structural brain imaging, the different mechanisms of neurodegeneration also cause characteristic spectral signatures of physiological coupling that are not accessible with structural imaging nor confounded by the neurovascular signalling of functional magnetic resonance imaging. We suggest that these spectral characteristics of altered connectivity are the result of differential disruption of neuronal microstructure and synaptic physiology by Alzheimer’s disease versus frontotemporal lobar degeneration.
Brain, Temporal Lobe, Nerve Net, Humans, Alzheimer Disease, Neurodegenerative Diseases, Magnetic Resonance Imaging, Diagnostic Techniques, Neurological, Magnetoencephalography, Neurophysiology, Phenotype, Aged, Middle Aged, Female, Male, Frontotemporal Lobar Degeneration, Frontotemporal Dementia, Connectome, Biomarkers
Medical Research Council (G1100464)
Medical Research Council (MC_UU_00005/8)
Alzheimer's Research UK (ARUK-PPG2016B-10)
Association of British Neurologists (ABN) (unknown)
Cambridge University Hospitals NHS Foundation Trust (CUH) (146281)
WELLCOME TRUST (103838/Z/14/Z)
James S McDonnell Foundation (220020289)
External DOI: https://doi.org/10.1093/brain/awy180
This record's URL: https://www.repository.cam.ac.uk/handle/1810/280433