How does the human brain process sensory information from our natural environment and how does it represent meaningful information about it? How does the complexity of realistic tasks and emotions influence our cognitive performance and decision making (e.g. in multitasking). How can we improve our (group-) analysis methods by better understanding and accommodating the functional organization of human brains? Will this improve our understanding of brain function at the group and individual level? How can we make neuroscience research more open and FAIR? These are the questions motivating the research in the lab. Addressing such such questions requires innovative research approaches and methods development. In one research focus we investigate speech processing in realistic soundscapes with relatively realistic movie soundtracks. In another research focus we investigate cognition and decision making in custom made driving simulators in fMRI, MEG, and fNIRS. In these empirical research foci we use symbolic and data-driven subsymbolic AI-methods to model brain function and analyze brain data obtained while people performed realistic tasks. In a methodological focus we develop tools and procedures for Open Science, to make neurodata FAIR and interoperable. Moreover we develop methods that better accommodate to the functional organization of human brains to improve the combination of brain activation measurements across individuals e.g. in big data research applications and to “warm start” brain computer interfaces with pre-recorded data. More detailed information can be found in our publications below and our project page.
Applied Neurocognitive Psychology Lab University Oldenburg
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