Characteristic Increases in EEG Connectivity Correlate With Changes of Structural MRI in Amyotrophic Lateral Sclerosis

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.

Patterned functional network disruption in amyotrophic lateral sclerosis

“…Characteristic patterned changes of cortical function in ALS signify widespread disease-associated network disruption, pointing to extensive dysfunction of both motor and cognitive networks. Clinical and neuroimaging evidence confirms extensive involvement of motor (Douaud et al, 2011;Nasseroleslami et al, 2019;Proudfoot, van Ede, et al, 2018) and cognitive (Iyer et al, 2015;McMackin, Dukic, et al, 2019) pathways and networks. (Hardiman, Van Den Berg, & Kiernan, 2011).…”

“…To assess the statistical significance and statistical power of the connectivity modules from the NMF analysis and the correlations between EEG connectivity and other measures, a null and non-null bootstrapping resampling (n = 10,000) approach was applied (Nasseroleslami, 2018;Nasseroleslami et al, 2019). In the former case, the resampling was applied on the NMF weights, whereas in the latter case, it was applied on the data used in the correlation analysis.…”

“…In addition to this, the observed changes have not discriminated between the traditionally defined clinical ALS subgroups (e.g., bulbar-vs. spinal-onset ALS or ALS with the presence or absence of the pathologic hexanucleotide expansion in the C9ORF72 gene) Nasseroleslami et al, 2019). In addition to this, the observed changes have not discriminated between the traditionally defined clinical ALS subgroups (e.g., bulbar-vs. spinal-onset ALS or ALS with the presence or absence of the pathologic hexanucleotide expansion in the C9ORF72 gene) Nasseroleslami et al, 2019).…”

“…Previous EEG studies have shown altered patterns, such as increased frontal-to-parietal connectivity in ALS (Blain-Moraes, Mashour, Lee, Huggins, & Lee, 2013;Iyer et al, 2015;Nasseroleslami et al, 2019). To date, however, there have been limited attempts to localise abnormal EEG patterns to specific brain regions.…”

Brain functional networks become more connected as amyotrophic lateral sclerosis progresses: a source level magnetoencephalographic study

“…In ALS, increased EEG coherence in the theta and gamma band was shown to correlate with structural MRI changes (Nasseroleslami et al, 2017) and EEG based network topological metrics related to disease burden (Fraschini et al, 2016b). …”