Norman A. S. Farb

This study uses machine learning to distinguish interoceptive and exteroceptive attention in fMRI data, showing distinct neural networks and improved interoceptive attention after training.

This study uses fMRI to compare interoceptive and exteroceptive attention, finding that interoception reduces cortical activity but increases connectivity, with greater awareness linked to preserved activation in specific brain regions.

This paper uses MVPA on fMRI data to decode internal attention states during meditation, finding that participants spent more time on breath attention than other states.