Neurophysiological signatures of Alzheimer's disease and frontotemporal lobar degeneration: pathology versus phenotype

Sami et al. identify characteristic neurophysiological signatures of five neurodegenerative diseases, including two variants of Alzheimer's disease and three forms of frontotemporal lobar degeneration. Disorders that share a common underlying pathology have a similar spectral signature of alter...

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Bibliographic Details
Published in:Brain (London, England : 1878) England : 1878), 2018-08, Vol.141 (8), p.2500-2510
Main Authors: Sami, Saber, Williams, Nitin, Hughes, Laura E, Cope, Thomas E, Rittman, Timothy, Coyle-Gilchrist, Ian T S, Henson, Richard N, Rowe, James B
Format: Article
Language:English
Subjects:
Aged
Alzheimer Disease - diagnosis
Alzheimer Disease - pathology
Biomarkers
Brain - pathology
Connectome
Diagnostic Techniques, Neurological
Female
Frontotemporal Dementia - pathology
Frontotemporal Lobar Degeneration - diagnosis
Frontotemporal Lobar Degeneration - pathology
Humans
Magnetic Resonance Imaging - methods
Magnetoencephalography - methods
Male
Middle Aged
Nerve Net - pathology
Neurodegenerative Diseases - pathology
Neurophysiology - methods
Original
Phenotype
Temporal Lobe - pathology
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Summary:Sami et al. identify characteristic neurophysiological signatures of five neurodegenerative diseases, including two variants of Alzheimer's disease and three forms of frontotemporal lobar degeneration. Disorders that share a common underlying pathology have a similar spectral signature of altered connectivity, regardless of phenotype. Abstract 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 from 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 localization 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 s
ISSN:0006-8950
1460-2156
DOI:10.1093/brain/awy180