In everyday life, we are immersed in a multitude of sounds. Sound waves convey language, emotion, and other vital information on events in the environment. To recognize sounds, we effortlessly analyze and combine their elementary features. For example, we recognize a high and fast fluctuating sound as birdsong. Alternatively, a low and more slowly fluctuating sound is recognized as the voice of a colleague. Previous research in animals suggested several neuronal mechanisms for the analysis and combination of sound features. However, insufficient spatial resolution of non-invasive methods precluded investigating if these mechanisms are present and relevant for human listening in natural environments. In this project, I will use 7 Tesla functional magnetic resonance imaging (fMRI) and a novel analysis method to study the neural mechanisms underlying feature processing of natural sounds in the human brain. My results will provide a detailed view on the neural basis of human audition, bridging the gap with findings from animal research. Furthermore, they may provide the methodological basis for similar investigations throughout the brain. I will perform this research at the Center for Magnetic Resonance Research (CMRR) in Minneapolis (USA), which provides unique facilities and immense technical expertise in MRI at ultra-high magnetic fields.

Our daily environment is filled with sounds. Sound processing in our brain ensures that we can hear, recognize, and understand incoming sounds. Sound processing is extremely flexible: brain processes change depending on which sounds - and what context - is currently relevant. This project uses strong MRI scanners to study how flexibility in the part of the brain that processes sounds ensures that relevant sounds - such as the ringtone of your own phone - are recognized and comprehended.