fMRI has considerable potential as a translational tool for understanding risk, prioritizing
interventions, and improving the treatment of brain disorders. However, recent studies have …

Extensive sampling of neural activity during rich cognitive phenomena is critical for robust
understanding of brain function. Here we present the Natural Scenes Dataset (NSD), in …

Electroencephalographic (EEG) methods have great potential to serve both basic and
clinical science approaches to understand individual differences in human neural function …

How individual differences in brain network organization track behavioral variability is a
fundamental question in systems neuroscience. Recent work suggests that resting-state and …

Multimodal evidence suggests that brain regions accumulate information over timescales
that vary according to anatomical hierarchy. Thus, these experimentally defined “temporal …

We regularly infer other people's thoughts and feelings from observing their actions, but how
this ability contributes to successful social behavior and interactions remains unknown. We …

Human brain connectivity yields significant potential as a noninvasive biomarker. Several
studies have used fMRI-based connectivity fingerprinting to characterize individual patterns …

There is significant interest in using neuroimaging data to predict behavior. The predictive
models are often interpreted by the computation of feature importance, which quantifies the …

Functional magnetic resonance imaging (fMRI) is increasingly used to non-invasively study
the acute impact of psychedelics on the human brain. While fMRI is a promising tool for …

Recent work has demonstrated that individual-specific variations in functional networks
(termed “network variants”) can be identified in individuals using resting state functional …