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Distinct Longitudinal Changes in EEG Measures Reflecting Functional Network Disruption in ALS Cognitive Phenotypes

Abstract

Amyotrophic lateral sclerosis (ALS) is characterised primarily by motor system degeneration, with clinical evidence of cognitive and behavioural change in up to 50% of cases. We have shown previously that resting-state EEG captures dysfunction in motor and cognitive networks in ALS. However, the longitudinal development of these dysfunctional patterns, especially in networks linked with cognitive-behavioural functions, remains unclear. Longitudinal studies on non-motor changes in ALS are essential to further develop our understanding of disease progression, improve care and enhance the evaluation of new treatments. To address this gap, we examined 124 ALS individuals with 128-channel resting-state EEG recordings, categorised by cognitive impairment (ALSci, n = 25), behavioural impairment (ALSbi, n = 58), or non-impaired (ALSncbi, n = 53), with 12 participants meeting the criteria for both ALSci and ALSbi. Using linear mixed-effects models, we characterised the general and phenotype-specific longitudinal changes in brain network, and their association with cognitive performance, behaviour changes, fine motor symptoms, and survival. Our findings revealed a significant decline in [Formula: see text]-band spectral power over time in the temporal region along with increased [Formula: see text]-band power in the fronto-temporal region in the ALS group. ALSncbi participants showed widespread β-band synchrony decrease, while ALSci participants exhibited increased co-modulation correlated with verbal fluency decline. Longitudinal network-level changes were specific of ALS subgroups and correlated with motor, cognitive, and behavioural decline, as well as with survival. Spectral EEG measures can longitudinally track abnormal network patterns, serving as a candidate stratification tool for clinical trials and personalised treatments in ALS.

Citing Articles

Resting-State EEG Oscillations in Amyotrophic Lateral Sclerosis (ALS): Toward Mechanistic Insights and Clinical Markers.

Chmiel J, Stepien-Slodkowska M J Clin Med. 2025; 14(2).

PMID: 39860557 PMC: 11766307. DOI: 10.3390/jcm14020545.

References
1.
Bigdely-Shamlo N, Mullen T, Kothe C, Su K, Robbins K . The PREP pipeline: standardized preprocessing for large-scale EEG analysis. Front Neuroinform. 2015; 9:16. PMC: 4471356. DOI: 10.3389/fninf.2015.00016. View

2.
Cedarbaum J, Stambler N, Malta E, Fuller C, Hilt D, Thurmond B . The ALSFRS-R: a revised ALS functional rating scale that incorporates assessments of respiratory function. BDNF ALS Study Group (Phase III). J Neurol Sci. 1999; 169(1-2):13-21. DOI: 10.1016/s0022-510x(99)00210-5. View

3.
Abrahams S, Leigh P, Harvey A, Vythelingum G, Grise D, Goldstein L . Verbal fluency and executive dysfunction in amyotrophic lateral sclerosis (ALS). Neuropsychologia. 2000; 38(6):734-47. DOI: 10.1016/s0028-3932(99)00146-3. View

4.
Engel A, Gerloff C, Hilgetag C, Nolte G . Intrinsic coupling modes: multiscale interactions in ongoing brain activity. Neuron. 2013; 80(4):867-86. DOI: 10.1016/j.neuron.2013.09.038. View

5.
McMackin R, Muthuraman M, Groppa S, Babiloni C, Taylor J, Kiernan M . Measuring network disruption in neurodegenerative diseases: New approaches using signal analysis. J Neurol Neurosurg Psychiatry. 2019; 90(9):1011-1020. PMC: 6820156. DOI: 10.1136/jnnp-2018-319581. View