Coordinate-based meta-analysis (CBMA) is a statistical technique allowing to perform meta-analyses of neuroimaging data, either structural or functional. Its main peculiarity is the possibility to estimate whole-brain 3D effects starting from stereotactic coordinates rather than full spatial maps. In the last 20 years, CBMA took hold as a fundamental tool to assess convergence among multiple experiments while solving the issue of high results variability in MRI. While standard CBMAs produce patterns of effect measured across the brain, recent advancements allowed to move from patterns to nodes-and-edges networks, therefore assessing more informative dependencies among brain regions involved. Moreover, while CBMAs were originally based on the logic of forward inference, it is now possible to leverage on this technique to address reverse inference as well. The aim of this seminar is to explain and practice the whole pipe-line to perform CBMA, from the definition of research hypotheses to advanced interpretation of results. Several tools will be presented and used to cover each necessary step, including network computation and Bayesian reverse inference implementation.
Please find here the link to join the meeting https://www.google.com/url?q=https://dott-neuroscienze.campusnet.unito.it/do/corsi.pl/Show?_id%3Durww&sa=D&source=calendar&ust=1651558286235899&usg=AOvVaw0bQnURf_jaXnce02uExjf7