Mapping electroencephalographic changes in amyotrophic lateral sclerosis

Abstract

Background: Amyotrophic lateral sclerosis (ALS) is a rapidly progressing neurodegenerative disorder that predominantly affects the motor neurons, leading to muscle weakness and impairments in motor functions. Additionally, a significant proportion of patients exhibit cognitive and behavioural changes. To date, ALS remains an incurable disease, and the prediction of its onset and progression remains elusive. Hence, an unmet need exists for objective biomarkers that can facilitate early diagnosis, assess disease progression, and provide novel insights contributing to targeted treatment strategies. Objective: This thesis seeks to explore the utility of electroencephalography (EEG) as a tool for unravelling the intricacies of network disruption in ALS. Methods: Chapters 2, 3, and 4 employ resting-state EEG analysis of spectral power and connectivity to investigate ALS patients for potential biomarkers relevant to disease diagnosis and progression. Chapter 5 employs clustering analysis on EEG-derived measures from previous chapters to categorise ALS patients into subgroups with similar network impairments. Chapter 6 focuses on the sustained attention to response task (SART) and event-related analysis to study ALS patients, while Chapter 7 employs the same approach to study asymptomatic family members of individuals with familial C9orf72-associated ALS. Results: The thesis reveals changes in power and connectivity in ALS across multiple brain networks, not confined solely to motor functions. Some of these alterations correspond with disease severity and progression, suggesting potential objective biomarkers. Additionally, the thesis demonstrates the ability to categorise ALS patients into stable groups with distinct brain network alterations. Finally, the thesis identifies impaired SART networks in ALS patients and their asymptomatic family members, the latter potentially indicating early pathological changes in the course of ALS. Conclusions: The thesis maps uncharted territories of EEG changes in ALS. It underscores the value of EEG in advancing our understanding of ALS and it unveils promising avenues for the enhancement of diagnostic tools, innovative patient subgrouping strategies, and the early identification of prodromal signs of the disease