Luca Turella

This study evaluates how different preprocessing pipelines affect static and dynamic functional connectivity metrics in healthy controls and Parkinson's disease patients, showing dynamic connectivity is highly sensitive to motion correction methods.

The paper shows that action intentions can be predicted from neural signals in both dorsal and ventral visual streams using visual, memory-based, and somato-motor information, even without direct visual input.

The paper shows that low-level visual features, shape, and category are processed in overlapping spatial locations early in time, suggesting parallel computations in visual processing.