Influence of Value-based Decision-Making on Cross-Modal Integration

In this project we are changing cross-modal integration by endowing the constituting stimuli with different expected values through learning. We are using visual and auditory stimuli, which - after an initial measurement of cross-modal activity - will be associated with a reward, a punishment, or no outcome. During learning and afterwards, we will measure cross-modal BOLD activity again and determine, if the connectivity strength and the composition of cross-modal BOLD activity has changed. We intend to demonstrate this using model-based fMRI analysis (Gläscher & O'Doherty, 2010), connectivity analyses (non-linear Dynamic Causal Modeling, Stephan et al, 2008) and through Pattern Component Modeling (Diedrichsen et al., 2011), a novel form of multivariate pattern analysis for fMRI data.

Influence of Integration principles on Value-Based Decision-Making

Here, we investigate the reverse side of the interaction of learning and cross-modal integration. We are using the spatial and temporal rule to create stimuli that will be integrated more or less strongly and associate them with different rewards. We are testing whether reward associations between highly integrated cross-modal stimuli are learned more easily or quicker (estimated via a learning rate) than non-rewarded multi-sensory stimuli.