NMR (Nuclear Magnetic Resonance)-based approaches have affirmed as extremely valuable for applications in neurosciences. Nonetheless, the exquisite flexibility of tissue contrast in magnetic resonance imaging (MRI) that can be obtained by proper manipulation of nuclear spins still offers room for technological improvements which can be quickly expanded to clinical routine. In particular, there is extreme need of imaging methods that allow a correct assessment of microstructural damage in many brain diseases, including – but not limited to – neurodegenerative diseases. Indeed, current MRI techniques suffer from poor specificity and ultimately lack the ability to identify the microscopic biophysical and biological mechanisms related to the specific features of the pathology.
This project aims at expanding the set of MR based techniques available to neuroscientists to characterize microstructural damage, assessing the usefulness of these approaches in some specific pathologies where they offer more promise. Notably, this project aims also at establishing the increased specificity and sensitivity of newly developed and current techniques when merged in a truly multiparametric analysis approach.
This project is heavily based on networking activities for exchanging the complimentary knowledge available at the different world-class academic and commercial EU and third country sites. The novel MRI pulse sequences and data analysis approaches tested and validated during the course of the project will be available at each site of the consortium, and will be made available to the scientific community as well.



The MICROBRADAM consortium includes several partners from Europe and USA. The Consortium members share a long history of collaboration in MR research projects, broadly related to human brain diseases and function, and to preclinical research on animal models.

This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 691110