Blood oxygen-level-dependent functional magnetic resonance imaging (BOLD fMRI) has
rapidly become a popular technique for the investigation of brain function in healthy …

The development of human cognition results from the emergence of coordinated activity
between distant brain areas. Network science, combined with non-invasive functional …

It is typically assumed that large networks of neurons exhibit a large repertoire of nonlinear
behaviours. Here we challenge this assumption by leveraging mathematical models derived …

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 …

Estimates of functional connectivity derived from resting-state functional magnetic resonance
imaging (rs-fMRI) are sensitive to artefacts caused by in-scanner head motion. This …

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

Resting-state functional magnetic resonance imaging (rs-fMRI) offers the opportunity to
delineate individual-specific brain networks. A major question is whether individual-specific …

Global signal regression (GSR) is one of the most debated preprocessing strategies for
resting-state functional MRI. GSR effectively removes global artifacts driven by motion and …

Several lines of evidence support the link between maternal inflammation during pregnancy
and increased likelihood of neurodevelopmental and psychiatric disorders in offspring. This …

Resting-state functional connectivity is used throughout neuroscience to study brain
organization and to generate biomarkers of development, disease, and cognition. The …