Leonardo Bonetti

I am Research Fellow at the Center for Eudaimonia and Human Fluorishing, University of Oxford and Associate Professor at Center for Music in the Brain (MIB), Aarhus University. My research primarily focuses on the whole-brain mechanisms underlying the perception, encoding and recognition of temporal sequences, with a particular interest in how the brain processes and predicts information that unfolds over time. To this use, I employ a large array of neuroscientific techniques such as magnetoencephalography (MEG), (functional) magnetic resonance imaging (fMRI) and stereoelectroencephalography (SEEG) combined with temporally structured auditory and visual stimuli.

In addition to empirical research, I am deeply involved in developing analytical methods for neuroscience. I co-developed Network Estimation via Source Separation (NESS)—a framework for deriving functional brain networks from neuroimaging data using linear decomposition techniques. NESS includes BROAD-NESS and FREQ-NESS, which are particularly suited for MEG datasets and help reveal frequency-specific and broadband brain networks in task-based contexts.

Another strand of my research investigates the cognitive and personality profiles of elite individuals, such as professional football players, merging psychological testing with AI-driven analysis.

While my current work mostly focuses on healthy populations, a future goal is to apply our paradigms and analytic methods to clinical populations, such as individuals with Alzheimer's and Parkinson's diseases, to better understand how neurodegenerative conditions affect temporal cognition and brain network organisation.