Statistical approaches for understanding the brain through electrophysiological data: an overview

Speaker: Dr. Sara Sommariva (University of Genova)

When: 2 May 2024, h. 5:00 pm

Where: 1A150, Torre Archimede


Most brain functions are regulated by intercorrelated electrical currents flowing in few specific brain
areas. Magneto- and electro-encephalography (M/EEG) are two modern neuroimaging techniques
capable of non-invasively recording the electromagnetic field produced outside the scalp by these
neural currents with an outstanding temporal resolution. Interpreting the recorded M/EEG data is not
straightforward and advanced mathematical and statistical techniques are required to estimate the
dynamical brain activity that has generated the measured data. A typical workflow of analysis
consists of two steps: (i) first the active brain regions and their time-courses are estimated by
solving and ill-posed inverse problem (ii) then proper statistical metrics are compute to estimate
functional connectivity, i.e. to quantify the statistical dependencies between the time-courses
reconstructed at different brain locations.
The aim of this talk is to provide some insights on modern statistical tools for facing and optimizing
such a workflow.