Moving beyond the mean: Subgroups and dimensions of brain activity and cognitive performance across domains

Human neuroimaging during cognitive tasks has provided unique and important insights into the neurobiology of cognition. However, the vast majority of research relies upon group aggregate or average statistical maps of activity, which do not fully capture the rich variability which exists across individuals. To better characterize individual variability, hierarchical clustering was performed separately on six fMRI tasks in 822 participants from the Human Connectome Project. Across all tasks, clusters ranged from a predominantly ‘deactivating’ pattern towards a more ‘activating’ pattern of brain activity, with differences in out-of-scanner cognitive test scores between clusters. Cluster stability was assessed via bootstrapping approach. Cluster probability did not indicate distinct/clear clustering. However, when participants were plotted in a dimensionally reduced ‘similarity space’ derived from bootstrapping, variability in brain activity among participants was best represented multidimensionally. A ‘positive to negative’ axis of activity was the strongest driver of individual differences.