Within the framework of a predictive brain, hierarchical generative models continuously compare sensoric input with top-down predictions of the to-be-expected percepts (a process coined predictive coding), thereby minimising the predicition error (Mumford, 1992; Friston, 2010). As a basis for the modification of internal forward models, the prediction error is subject to many imaging studies, especially with regard to neuroanatomical correlates allowing for conclusions concerning the fundamental functional networks of cortical processing. In paradigms exploring abstract rule violations, activations have been reported for dorsolateral prefrontal cortex (Fletcher et al., 2001), intraparietal sulcus (Gläscher, Daw, & O'Doherty, 2010) and premotor cortex (den Ouden, Daunizeau, Roiser, Friston, & Stephan, 2010). With an emphasis on prediction errors in sequential stimuli, Bubic, von Cramon, Jacobsen, Schröger, and Schubotz (2009) were able to show a distinguished funtional network comprising premotor and prefrontal involvement, which provided an insight into error detection, model updating, and error evaluation.
Via functional magnetic resonance imaging (fMRI), my work focusses on different types of abstract rule violations and the qualitatively different, associated neuronal correlates. Furthermore, the stability of predictions based on forward models is studied across varying statistical contexts, making rule violations more or less probable.
Prof. Dr. Ricarda Schubotz
Prof. Dr. Pienie Zwitserlood
Dr. Moritz Wurm
|2009–2014||Studies in Psychology at the University of Münster|
|2014||Beginning of PhD research project, Department for Biological Psychology, Institute for Psychology, University of Münster|