Exploiting cross-modal integration for enhanced power and sensitivity, the recently emerged field of imaging genomics is at the frontline of available tools for identifying genes which influence the neurobiology of human behavior and psychiatric illness. Computational approaches are not, however, up to par with the complexity of the disparate data: there is an urgent need for integrative predictive modeling to overcome the interdisciplinary fragmentation between genomics and neuroimaging to harvest the full potential of the data. The methodological objective of this project is therefore to develop and implement integrative cross-modal algorithms for synergistic modeling of human genetic effects on brain responses patterns. To this end, the project will use tools from machine learning which allow powerful, multivariate, generic, data-driven, general purpose predictive modeling. Application side, the project will target the neurobiology of affective behavior and disorders through modeling gene-brain correlates in a population of individuals carrying a mutation resulting in atypical sense of affective touch and insensitivity to pain. Employing a cross-modal, multi-disciplinary approach, integrating genomics, neuroimaging and engineering at the frontier of neuroscience research, the project enables holistic modeling of genetic correlates of human behavior and psychiatric conditions revealing new therapeutic avenues. The project embodies the work program by providing excellent international, multi-disciplinary, cross-modal academic training, establishing a solid yet dynamic basis for a prolific long-term scientific career for the Fellow. The project will increase the attractiveness of the ERA through promoting the world-leading Swedish neurobiology research and facilitate mutually beneficial relations with Singapore; moreover, the project will aid the ERA in benefiting from rather than competing with the growing science and technology investments in Asia.
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