Neurocognitive mechanisms for implicit learning of crossmodal predictions (B03)

• Subject Area: Human Cognitive and Systems Neuroscience ; General, Cognitive and Mathematical Psychology
• Term: since 2016
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 261402652

The Project will extend current findings on implicit learning of crossmodal information. The main goal is to examine how generalization of implicit knowledge to more complex, life-like environments in serial prediction tasks differs from current models. To this end, neuronal correlates and computational foundations of implicit crossmodal learning are examined in virtual reality (VR) with concurrent EEG measurements in crossmodal prediction contexts. Secondly, the mechanisms of transfer learning of implicitly learned rules will be studied between modalities as well as across different crossmodal configurations. Here, neuronal correlates will be identified by employing a combination of fMRI and EEG. Lastly, the influence of emotion and culture are tested for their modulation of crossmodal transfer learning effects.

• DFG Programme: CRC/Transregios
• Subproject of: TRR 169: Crossmodal Learning: Adaptivity, Prediction and Interaction
• International Connection: China
• Applicant Institution: Universität Hamburg
• Project Heads: Dr. Qiufang Fu; Professor Dr. Xiaorong Gao, until 12/2019; Professor Dr. Michael Rose