| Literature DB >> 29136131 |
Bahman Nasseroleslami1, Stefan Dukic1, Michael Broderick1, Kieran Mohr1, Christina Schuster1, Brighid Gavin1, Russell McLaughlin1,2, Mark Heverin1, Alice Vajda1, Parameswaran M Iyer1, Niall Pender1,3, Peter Bede1,3, Edmund C Lalor4,5,6, Orla Hardiman1,3,4.
Abstract
Amyotrophic lateral sclerosis (ALS) is a terminal progressive adult-onset neurodegeneration of the motor system. Although originally considered a pure motor degeneration, there is increasing evidence of disease heterogeneity with varying degrees of extra-motor involvement. How the combined motor and nonmotor degeneration occurs in the context of broader disruption in neural communication across brain networks has not been well characterized. Here, we have performed high-density crossectional and longitudinal resting-state electroencephalography (EEG) recordings on 100 ALS patients and 34 matched controls, and have identified characteristic patterns of altered EEG connectivity that have persisted in longitudinal analyses. These include strongly increased EEG coherence between parietal-frontal scalp regions (in γ-band) and between bilateral regions over motor areas (in θ-band). Correlation with structural MRI from the same patients shows that disease-specific structural degeneration in motor areas and corticospinal tracts parallels a decrease in neural activity over scalp motor areas, while the EEG over the scalp regions associated with less extensively involved extra-motor regions on MRI exhibit significantly increased neural communication. Our findings demonstrate that EEG-based connectivity mapping can provide novel insights into progressive network decline in ALS. These data pave the way for development of validated cost-effective spectral EEG-based biomarkers that parallel changes in structural imaging.Entities:
Mesh:
Year: 2019 PMID: 29136131 DOI: 10.1093/cercor/bhx301
Source DB: PubMed Journal: Cereb Cortex ISSN: 1047-3211 Impact factor: 5.357