Theory, modelling and data analysis

Mathematical symbols and formulae floating in an abstract swirling background.

Our research 

We develop theory and models of neural dynamics that might be associated with different states and contents of consciousness. On an abstract level of description, this involves work on the mathematics of information dynamics, complexity, causality and emergence (Barnett, Barrett, Rosas, Seth), and the tying of this to general features of conscious experience, e.g., integration (conscious scenes are unified) and differentiation (we each enjoy a vast repertoire of possible conscious experiences). This work involves a distinctively pragmatic flavour, for example as applied to integrated information theory (Barrett, Seth). At the cognitive level, we develop theories and models of predictive, active inference, relating these processes to perceptual experiences of the world and the self (Buckley, Clark, Roseboom, Seth). This research integrates philosophy with computational modelling and mathematics and physics. We also address philosophical questions concerning the nature and distribution of consciousness. For data analysis we derive practical quantities and measures from theory and modelling that can be applied to neuroimaging data. We analyse EEG/MEG datasets from diverse states of consciousness, from wakeful rest to sleep and anaesthesia, to psychedelic states induced by pharmacological and non-pharmacological (e.g. flicker light stimulation) interventions(Barnett, Barrett, Rosas, Seth).


Lionel Barnett; Adam Barrett; Romy Beauté; Chris Buckley; Fernando Rosas; Warrick Roseboom; Anil Seth; Nadine Spychala