At the CPP lab (https://cpplab.be/), headed by Olivier Collignon, the team aims to understand the functional organization of the brain and how different brain networks interact to perform a specific perceptual/cognitive function.
Recently, the groundbreaking combination of functional magnetic resonance imaging (fMRI) -or other neuroimaging methods- with advanced machine learning (ML) or artificial intelligence (AI) techniques has opened unprecedented avenues to understand brain functions in healthy people and patients. The CPP lab uses classification algorithms from ML applied to multivariate neural data to predict the perceptual state of a participant or a patient while perceiving different visual, auditory or tactile stimuli.
Moreover, by combining ML with representational similarity analyses they can understand the format a brain region is using to represent information.
Finally, the laboratory is interested in contrasting the representation implemented in deep neural network (DNN) with the one implemented in brain regions to further understand brain organization.
They recently applied these techniques to understand how brain networks reorganise in the absence of one sensory input (eg. Blindness, Deafness). For instance, they discovered that occipital regions deprived of their native visual input reorganise to process information from the remaining senses (eg audition). Importantly, such crossmodal plasticity in blind people follows a computational organisation similar to the one typically observed in sighted people. These results highlight important principles in the development of brain functional networks.