Silvio Ionta

The paper reanalyzes passive finger movement fMRI data using univariate and multivariate methods to show that multivariate analysis better identifies brain regions encoding kinesthesia and proprioception, with larger neural representation for amplitude and direction than velocity.

This paper analyzes fMRI neurofeedback data to identify brain regions and networks involved in feedback processing and regulation recalibration during training.

The paper identifies a sustained decrease in corticomotor excitability as a neural marker of proactive inhibitory control during error correction.

This study evaluates the long-term effects of network-based fMRI neurofeedback training on sustained attention, finding lasting neural changes but transient behavioral improvements.