The central goal of the BRAIN Initiative is to understand the structure and function of human brain circuits. Functional magnetic resonance imaging (fMRI) has great potential to achieve this goal, however fMRI is fundamentally an indirect measure of neuronal activity—it assesses brain function through the measurement of changes in blood flow and oxygenation driven by local neuronal activity, and is also influenced by regional differences in tissue anatomy including vascular density. The cerebral cortex consists of layers that are well- known to serve as inputs or outputs for the connections across brain regions, and so localizing fMRI signals to individual layers will be key to deciphering brain circuitry in humans. However, the cortical microanatomy varies dramatically across layers, introducing biases that have been demonstrated to confound our ability to detect and localize activity within layers with fMRI, and therefore to hinder the interpretation and use of laminar fMRI. Our aim is to characterize and remove these fMRI signal biases due to local differences in microanatomy, in order to address this fundamental limitation of fMRI and to more accurately relate fMRI to neuronal activity. We will achieve this goal by combining histology of human brain specimens with advanced ex vivo and in vivo imaging to develop a framework for enhancing fMRI neuronal specificity—through deriving a mapping between tissue microarchitecture and quantitative MRI, and then correcting fMRI signal bias related to tissue microstructure. The candidate is trained in physics and computer science; has experience in high-resolution structural MRI and in correlating in vivo and ex vivo MRI with histology; and seeks training in experimental neuroscience in order to become an independent researcher in this field. During the mentored phase, she will develop a model of intracortical microstructure using ex vivo data from regions of visual cortex. She will measure vascular density in vivo to map out this additional source of fMRI signal bias, then develop a model to derive predictions of cortical microstructure and fMRI responses in vivo, and validate it through an fMRI experiment using a wide range of acquisition parameters. To achieve these goals, the candidate—with guidance from the experienced mentors, the pioneers of laminar microanatomy and fMRI—will extend her knowledge, gain new skills in advanced ultra- high-field fMRI acquisition and data analysis. Building on this, in the independent phase she will apply the model to laminar fMRI experiments designed to validate the bias correction. This project will prepare the candidate for her long-term career goal of establishing a research program applying non-invasive functional imaging techniques, with aid of quantitative tissue property analyses, to study the circuitry of the human brain. The mentored phase will be carried out at the Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard ...