Integrated multimodal brain imaging for neuroscience research and clinical practice.

Advances in neuroimaging have given unprecedented access to in vivo measurements of brain function, structure and connectivity, but the full potential is not being realized due to a lack of suitable analysis tools to explore relationships between, and integrate across, modalities. Our overall goal is to bring multimodal imaging to the forefront of neuroscience and clinical research in order to provide new biomarkers and insights into disease mechanisms, explore aging and developmental processes, increase the scope for large neuroimaging studies and improve clinical decision-support for patients. We will generate new methodology, algorithms and software tools for integrated modelling and analysis of multimodal neuroimaging data: specifically, structural MRI, diffusion MRI, resting/task functional MRI and MEG. Key technical goals are: parcellation of the brain into functional and structural units, and alignment of brain structure and function across multiple subjects, in both cases ut ilizing all modalities simultaneously; modelling of structural and functional networks in the brain that mediate information flow; developing multivariate classification and probabilisitic parametric atlases using structural, functional and network information, to develop biomarkers and investigate disease mechanisms. To maximize practical impact we will be translating these methods into user-accessible, well-supported software tools for both basic and clinical neuroimaging scientists worldwide.