Backdoor attacks are serious security threats to machine learning models where an
adversary can inject poisoned samples into the training set, causing a backdoored model …

Through harmonized procedures and by sharing site-specific brain metrics (for example,
cortical thickness) or aggregated statistical maps, ENIGMA has set the stage for large-scale …

We propose a patch-based singular value shrinkage method for diffusion magnetic
resonance image estimation targeted at low signal to noise ratio and accelerated …

Diffusion MRI (dMRI) provides invaluable information for the study of tissue microstructure
and brain connectivity, but suffers from a range of imaging artifacts that greatly challenge the …

Backdoor defense, which aims to detect or mitigate the effect of malicious triggers introduced
by attackers, is becoming increasingly critical for machine learning security and integrity …

Diffusion MRI‐based tractography is the most commonly‐used technique when inferring the
structural brain connectome, ie, the comprehensive map of the connections in the brain. The …

A growing number of studies have used stylized network models of communication to predict
brain function from structure. Most have focused on a small set of models applied globally …

Network neuroscience has emerged as a leading method to study brain connectivity. The
success of these investigations is dependent not only on approaches to accurately map …

The intrinsic dynamics of neuronal populations are shaped by both microscale attributes and
macroscale connectome architecture. Here we comprehensively characterize the rich …

Implications of structural connections within and between brain regions for their functional
counterpart are timely points of discussion. White matter microstructural organization and …