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2006; 16 (7): 916 - 28. 16 Radakovic R, Abrahams S. Developing a new apathy measurement scale: Dimensional Apathy Scale, Psychiatry Res. 2014; 219 (3): 658 - 63. 17 Huynh W, Ahmed R, Mahoney CJ, et al. Measurement of Social Cognition in Amyotrophic Lateral Sclerosis: A Population Based Study. 7 Girardi A, MacPherson SE, Abrahams S, Deficits in emotional and social cognition in amyotrophic lateral sclerosis, Neuropsychology. [Extracted from the article]

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., (© 2024. The Author(s).)

Objective: To establish if induced current direction across the motor cortex alters the sensitivity of transcranial magnetic stimulation (TMS)-evoked short-interval intracortical inhibition (SICI) as an ALS biomarker., Methods: Threshold tracking-TMS was undertaken in 35 people with ALS and 39 controls. Using a coil orientation which induces posterior-anterior (PA)-directed current across the motor cortex, SICI (1 ms and 3 ms interstimulus intervals) and intracortical facilitation (ICF, 10 ms interstimulus interval) were recorded. SICI 3ms was also recorded using a coil orientation which induces anterior-posterior (AP)-directed current across the motor cortex., Results: At group level, SICI 3ms-PA (AUROC = 0.7), SICI 3ms-AP (AUROC = 0.8) and SICI 1ms (AUROC = 0.66) were substantially lower in those with ALS, although there was considerable interindividual heterogeneity. Averaging across interstimulus intervals (ISIs) marginally improved SICI PA sensitivity (AUROC = 0.76). Averaging SICI values across ISIs and orientations into a single SICI measure did not substantially improve sensitivity (AUROC = 0.81) compared to SICI 3ms-AP alone. SICI 3ms-AP and SICI 3ms-PA did not significantly correlate (rho = 0.19, p = 0.313), while SICI 1ms-PA and SICI 3ms-PA did (rho = 0.37, p = 0.006). Further, those with ALS with the lowest SICI 3ms-PA were not those with the lowest SICI 3ms-AP . ICF was similar between groups (AUROC = 0.50)., Conclusions: SICI PA and SICI AP are uncorrelated measures of motor cortical inhibitory functions which are useful as distinct, unequally affected, measures of disinhibition in ALS., Significance: Examining both SICI PA and SICI AP may facilitate more comprehensive characterisation of motor cortical disinhibition in ALS., (© 2024 International Federation of Clinical Neurophysiology. Published by Elsevier B.V.)

Recent electroencephalography (EEG) studies have shown that patterns of brain activity can be used to differentiate amyotrophic lateral sclerosis (ALS) and control groups. These differences can be interrogated by examining EEG microstates, which are distinct, reoccurring topographies of the scalp's electrical potentials. Quantifying the temporal properties of the four canonical microstates can elucidate how the dynamics of functional brain networks are altered in neurological conditions. Here we have analysed the properties of microstates to detect and quantify signal-based abnormality in ALS. High-density resting-state EEG data from 129 people with ALS and 78 HC were recorded longitudinally over a 24-month period. EEG topographies were extracted at instances of peak global field power to identify four microstate classes (labelled A-D) using K-means clustering. Each EEG topography was retrospectively associated with a microstate class based on global map dissimilarity. Changes in microstate properties over the course of the disease were assessed in people with ALS and compared with changes in clinical scores. The topographies of microstate classes remained consistent across participants and conditions. Differences were observed in coverage, occurrence, duration, and transition probabilities between ALS and control groups. The duration of microstate class B and coverage of microstate class C correlated with lower limb functional decline. The transition probabilities A to D, C to B and C to B also correlated with cognitive decline (total ECAS) in those with cognitive and behavioural impairments. Microstate characteristics also significantly changed over the course of the disease. Examining the temporal dependencies in the sequences of microstates revealed that the symmetry and stationarity of transition matrices were increased in people with late-stage ALS. These alterations in the properties of EEG microstates in ALS may reflect abnormalities within the sensory network and higher-order networks. Microstate properties could also prospectively predict symptom progression in those with cognitive impairments., (© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)