Normal and abnormal differences in sustained visual attention have long been of interest to scientists, educators, and clinicians. Still lacking, however, is a clear understanding of how sustained visual attention varies across the broad sweep of the human lifespan. Here, we fill this gap in two ways. First, powered by an unprecedentedly large, 10,430-person sample, we model age-related differences with substantially greater precision than prior efforts. Second, using the recently developed gradual-onset continuous performance test (gradCPT), we parse sustained attention performance over the lifespan into its ability and strategy components. We find that after age 15, the strategy and ability trajectories saliently diverge. Strategy becomes monotonically more conservative with age, whereas ability peaks in the early forties and is followed by a gradual decline in older adults. These observed lifespan trajectories for sustained attention are distinct from results of other lifespan studies focusing on fluid and crystallized intelligence.

Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease that has significant overlap with frontotemporal dementia (FTD). Mutations in specific genes have been identified that can cause and/or predispose patients to ALS. However, the clinical variability seen in ALS patients suggests that additional genes impact pathology, susceptibility, severity, and/or progression of the disease. To identify molecular pathways involved in ALS, we undertook a meta-analysis of published genetic modifiers both in patients and in model organisms, and undertook bioinformatic pathway analysis. From 72 published studies, we generated a list of 946 genes whose perturbation (1) impacted ALS in patient populations, (2) altered defects in laboratory models, or (3) modified defects caused by ALS gene ortholog loss of function. Herein, these are all called modifier genes. We found 727 modifier genes that encode proteins with human orthologs. Of these, 43 modifier genes were identified as modifiers of more than one ALS gene/model, consistent with the hypothesis that shared genes and pathways may underlie ALS. Further, we used a gene ontology-based bioinformatic analysis to identify pathways and associated genes that may be important in ALS. To our knowledge this is the first comprehensive survey of ALS modifier genes. This work suggests that shared molecular mechanisms may underlie pathology caused by different ALS disease genes. Surprisingly, few ALS modifier genes have been tested in more than one disease model. Understanding genes that modify ALS-associated defects will help to elucidate the molecular pathways that underlie ALS and provide additional targets for therapeutic intervention.