ObjectiveTo elucidate the relationship between disease stage in amyotrophic lateral sclerosis (ALS), as measured with the King's Clinical Staging System, and cognitive and behavioral change, measured with the Edinburgh Cognitive and Behavioural ALS Screen (ECAS).MethodsA large multicenter observational cohort of 161 cross-sectional patients with ALS and 80 healthy matched controls were recruited across 3 research sites (Dublin, Edinburgh, and London). Participants were administered the ECAS and categorized into independent groups based on their King's clinical disease stage at time of testing.ResultsSignificant differences were observed between patients and controls on all subtests of the ECAS except for visuospatial functioning. A significant cross-sectional effect was observed across disease stages for ALS-specific functions (executive, language, letter fluency) and ECAS total score but not for ALS-nonspecific functions (memory, visuospatial). Rates of ALS-specific impairment and behavioral change were also related to disease stage. The relationship between cognitive function and disease stage may be due to letter fluency impairment, whereas higher rates of all behavioral domains were seen in later King's stage. The presence of bulbar signs, but not site of onset, was significantly related to ALS-specific, ECAS total, and behavioral scores.ConclusionALS-specific cognitive deficits and behavioral impairment are more frequent with more severe disease stage. By end-stage disease, only a small percentage of patients are free of neuropsychological impairment. The presence of bulbar symptoms exaggerates the differences observed between disease stages. These findings suggest that cognitive and behavioral change should be incorporated into ALS diagnostic criteria and should be included in future staging systems.

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease primarily affecting motor function, with additional evidence of extensive nonmotor involvement. Despite increasing recognition of the disease as a multisystem network disorder characterised by impaired connectivity, the precise neuroelectric characteristics of impaired cortical communication remain to be fully elucidated. Here, we characterise changes in functional connectivity using beamformer source analysis on resting‐state electroencephalography recordings from 74 ALS patients and 47 age‐matched healthy controls. Spatiospectral characteristics of network changes in the ALS patient group were quantified by spectral power, amplitude envelope correlation (co‐modulation) and imaginary coherence (synchrony). We show patterns of decreased spectral power in the occipital and temporal (δ‐ to β‐band), lateral/orbitofrontal (δ‐ to θ‐band) and sensorimotor (β‐band) regions of the brain in patients with ALS. Furthermore, we show increased co‐modulation of neural oscillations in the central and posterior (δ‐, θ‐ and γl‐band) and frontal (δ‐ and γl‐band) regions, as well as decreased synchrony in the temporal and frontal (δ‐ to β‐band) and sensorimotor (β‐band) regions. Factorisation of these complex connectivity patterns reveals a distinct disruption of both motor and nonmotor networks. The observed changes in connectivity correlated with structural MRI changes, functional motor scores and cognitive scores. Characteristic patterned changes of cortical function in ALS signify widespread disease‐associated network disruption, pointing to extensive dysfunction of both motor and cognitive networks. These statistically robust findings, that correlate with clinical scores, provide a strong rationale for further development as biomarkers of network disruption for future clinical trials.

BackgroundAmyotrophic Lateral Sclerosis (ALS) is heterogeneous and overlaps with frontotemporal dementia. Spectral EEG can predict damage in structural and functional networks in frontotemporal dementia but has never been applied to ALS.Methods18 incident ALS patients with normal cognition and 17 age matched controls underwent 128 channel EEG and neuropsychology assessment. The EEG data was analyzed using FieldTrip software in MATLAB to calculate simple connectivity measures and scalp network measures. sLORETA was used in nodal analysis for source localization and same methods were applied as above to calculate nodal network measures. Graph theory measures were used to assess network integrity.ResultsCross spectral density in alpha band was higher in patients. In ALS patients, increased degree values of the network nodes was noted in the central and frontal regions in the theta band across seven of the different connectivity maps (p<0.0005). Among patients, clustering coefficient in alpha and gamma bands was increased in all regions of the scalp and connectivity were significantly increased (p=0.02). Nodal network showed increased assortativity in alpha band in the patients group. The Clustering Coefficient in Partial Directed Connectivity (PDC) showed significantly higher values for patients in alpha, beta, gamma, theta and delta frequencies (p=0.05).DiscussionThere is increased connectivity in the fronto-central regions of the scalp and areas corresponding to Salience and Default Mode network in ALS, suggesting a pathologic disruption of neuronal networking in early disease states. Spectral EEG has potential utility as a biomarker in ALS.

Psychometric properties of the ECAS using age and education adjusted norms indicate that the ECAS, when used as an overall measure of cognitive decline, is highly sensitive. Further comprehensive assessment is required for patients that present as impaired on the ECAS.