Psychiatric disorders encompass complex aberrations of cognition and affect and are
among the most debilitating and poorly understood of any medical condition. Current …

Relating individual brain patterns to behaviour is fundamental in system neuroscience.
Recently, the predictive modelling approach has become increasingly popular, largely due …

Algorithmic biases that favor majority populations pose a key challenge to the application of
machine learning for precision medicine. Here, we assessed such bias in prediction models …

The transition from childhood to adolescence is marked by pronounced shifts in brain
structure and function that coincide with the development of physical, cognitive, and social …

Resting-state functional magnetic resonance imaging (rs-fMRI) allows estimation of
individual-specific cortical parcellations. We have previously developed a multi-session …

Magnetic resonance imaging (MRI) continues to drive many important neuroscientific
advances. However, progress in uncovering reproducible associations between individual …

Characterizing the optimal fMRI paradigms for detecting behaviorally relevant functional
connectivity (FC) patterns is a critical step to furthering our knowledge of the neural basis of …

Cognitive performance can be predicted from an individual's functional brain connectivity
with modest accuracy using machine learning approaches. As yet, however, predictive …

A fundamental goal across the neurosciences is the characterization of relationships linking
brain anatomy, functioning, and behavior. Although various MRI modalities have been …

Resting-state fMRI is commonly used to derive brain parcellations, which are widely used for
dimensionality reduction and interpreting human neuroscience studies. We previously …