Ai+ Training

Brain science is at an inflection point: while previous generations of researchers relied mostly on small datasets collected in individual labs, the field is transitioning to analyze large data sets that are collected and openly released by large research consortia, such as the Allen Institute for Brain Science or the Human Connectome Project. These large datasets promise to provide new and important information about the brain, and through data-driven approaches, help us understand and cure brain diseases. However, because of the scale and dimensionality of these datasets, researchers are meanwhile struggling to store, manage, analyze, and understand the data. In this talk, I will present some of the challenges that neuroscience is facing in tackling these large open datasets and discuss the ecosystem of open-source software tools that aims to address these challenges. I will demonstrate this with a set of tools that I have developed to analyze human MRI data that sheds light on networks of brain connections.