Researchers from the Computer Vision Data Science Team at Sano and the Institute of Mathematics at the University of Warsaw have successfully applied quantum computing techniques to discover structure in brain networks.
The study, which was recently published in Scientific Reports, explored the potential of quantum computing for brain-wide community detection. Analysis showed that quantum computers are capable of rendering highly efficient community structures with modularity indices superior to classical algorithms. One of the most noteworthy results was that the community structure can be obtained “all at once”. The approach described enables the computation of any number of clusters, in contrast to previous methods that were limited to computing clusters in powers of 2.
Community detection is a pivotal issue in computational neuroscience since recent advancements in network neuroscience showed that brain as a small-world system with an efficient integration-segregation balance that facilitates different cognitive tasks and functions, as well as potential disfunctions.
The paper “Community detection in brain connectomes with hybrid quantum computing” is available here: https://www.nature.com/articles/s41598-023-30579-y