CTN: Mehdi Azabou, ARNI Postdoctorate Research Scientist

Title: Building foundation models for neuroscience

Abstract: Current methodologies for recording brain activity often provide narrow views of the brain’s function. This fragmentation of datasets has hampered the development of robust and comprehensive computational models that generalize across diverse conditions, tasks, and individuals. Our work is motivated by the need for a large-scale foundation model in neuroscience–one that can go beyond the limitations of single-dataset approaches and offer a fuller, more comprehensive picture of brain function. We propose a novel, scalable and unified approach for training on diverse neural datasets. We test our model across two large collections of data: 1. on nonhuman primates performing diverse motor tasks, spanning over 158 different sessions from over 27,373 neural units, and 2. the entirety of the Allen Institute’s Brain Observatory dataset, containing responses from over 100,000 neurons in 6 areas of the brains of mice, observed with two-photon calcium imaging, recorded while the mice observed different types of visual stimuli.