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Amyotrophic lateral sclerosis (ALS) is increasingly recognized as a multisystem disorder accompanied by cognitive changes. To date, no effective therapy is available for ALS patients, partly due to disease heterogeneity and an imperfect understanding of the underlying pathophysiological processes. Reliable models that can predict cognitive and motor de ficits are needed to improve symptomatic treatment and slow down disease progression. This study aimed to identify individualized functionaldoi:10.1162/netn_a_00217 pmid:35356196 pmcid:PMC8959121 fatcat:sphkqs72dvepjdystvrscgyzpi