Adolescents are most often described as being reward seeking. However, adolescence is also a period in life where one has to flexibly adjust and adapt one’s beliefs. Thus, we studied the neural mechanisms underlying cognitive flexibility by means of reward prediction errors and computational modelling. We found that adolescents had an increased learning from negative prediction errors. We furthermore associated these differences with increased responses to prediction errors in the anterior insula in adolescents.
Hauser TU, Iannaccone R, Walitza S, Brandeis D & Brem S (2015). Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development. NeuroImage 104: 347-354.
Children and adults suffering from Attention Deficit Hyperactivity Disorder (ADHD) have previously been found to struggle in making decisions and learning from feedback. In this study, we investigated the neural mechanisms underlying these impaired mechanisms. Using computational modelling, we found that subjects with ADHD make more stochastic and exploratory choices. Using simultaneous EEG-fMRI, we determined the impaired neural signals by means of reward prediction errors. We found prediction error impairments in the medial frontal cortex. Moreover, we could determine the exact timing of this impairments, as it was reflected by an impaired Feedback-Related Negativity (FRN) in the EEG.
Hauser TU, Iannaccone R, Ball J, Mathys C, Brandeis D, Walitza S & Brem S (2014). Role of the Medial Prefrontal Cortex in Impaired Decision Making in Juvenile Attention-Deficit/Hyperactivity Disorder. JAMA Psychiatry (formerly Arch Gen Psychiatry) 71(10):1165-1173.
Although we know a lot about the neural regions which are involved in decision making, little is known about the temporal signatures of decision making and learning. In this study, we investigated the Feedback-Related Negativity, an event-related response of the EEG which has been proposed to reflect reward prediction errors. We used simultaneous EEG-fMRI to study the FRN in more detail. We investigated whether the FRN reflected prediction errors or saliency signals, determined the neural source of the FRN using the concurrently aquired data, and studied the organisation of the network using dynamic causal modelling (DCM).
Hauser TU, Iannaccone R, Stämpfli P, Drechsler R, Brandeis D, Walitza S & Brem S (2014). The Feedback-Related Negativity (FRN) revisited: New insights into the localization, meaning and network organization. NeuroImage 84:159-168.