The failure of over 40 large-scale MND/ALS clinical trials reflects the limitations in direct translation of treatment from animal models to human disease. The emerging evidence indicates impairments beyond the traditional pathology in the upper/lower motor neurons (UMN/LMN), including degeneration in brain pathways and disruptions in broader motor and non-motor networks. Clinical trials of next-generation therapeutics need to target this heterogenous network dysfunction; however, the existing biomarkers do not capture these impairments. The aim of this proposal is to recalibrate MND/ALS as a disorder of networks, by developing a novel set of neurophysiology-based markers that will quantify specific patterns of network disruption. As the neurons in each affected circuit have specific biological signatures, these neurophysiology-based markers will also serve as proxies for the underlying pathobiological processes. We hypothesise that a set of network-specific biomarkers better capture the heterogenous disease progression than a single score of degeneration in UMN/LMN. This study capitalizes on our exciting findings derived from extensive multimodal datasets from MND/ALS patients and controls, including clinical/behavioural sub-phenotyping, MRI and EEG. We will characterize brain network disruption using 3 experimental paradigms (resting-state, cognitive tasks, and motor tasks). We will use the EEG-based spectral source-connectivity analyses of the resting-state recordings, cognitive event response potentials and cortico-muscular coherence; as well as transcranial magnetic stimulation (TMS)-based assessment of cortical connectivity. These techniques will provide non-invasive measures that profile the patterns of disruption in motor and non-motor networks, which we will study longitudinally in more than 100 new MND/ALS patients. These measures will be validated and refined against the results of clinical neurological assessment, detailed neuropsychological, and quantitative structural MRI. Subsequently, these cost-effective EEG/TMS measures can be used independently as neurophysiological biomarkers that quantify the disease progression in the disease sub-phenotypes. These biomarkers can serve as outcome measures in future clinical trial settings.
