Models of animal brains are increasingly common and mapped in increasing detail. To simplify analysis of their function, we consider subregions and show that they perform well as classifiers of overall activity, with only a fraction of the neurons. The uniqueness of such ''reliable'' regions seems to be related to the types of connections that pairs of neurons form in them. By focusing on topologically significant structures and reciprocally connected neurons we find even stronger classification results. This is ongoing work across several institutions, including EPFL, the Blue Brain Project, and the University of Aberdeen.
Jānis Lazovskis is an Assistant Professor at RTU Riga Business School in Riga, Latvia, working in algebraic topology and topological data analysis, in particular dynamic data. His research focuses on the intersection of topology and neuroscience, simplifying and classifying in silico activity with graph theoretic and topological tools. Previously Jānis worked as a postdoc in Ran Levi's group at Aberdeen, and completed his PhD under Ben Antieau at the University of Illinois at Chicago. As an instructor and administrator of undergraduate mathematics courses, Jānis pushes for more inclusion and equity through better teaching methods and modified assessments.