Extract and translate detailed information about neural connectivity and function across different species to create the next generation of robust, efficient intelligent systems operating in the real world.
Connectomics-Derived Neural Networks
Matelsky, J.K., Reilly, E.P., Johnson, E.C., Stiso, J., Bassett, D.S., Wester, B.A. and Gray-Roncal, W., 2021 "DotMotif: an open-source tool for connectome subgraph isomorphism search and graph queries." Scientific reports 11, no. 1 (2021): 1-14.
Developing increasingly complex autonomous agents with neurally-inspired control policies.
Monaco, J.D., Hwang, G.M., Schultz, K.M. and Zhang, K., 2020. Cognitive swarming in complex environments with attractor dynamics and oscillatory computing. Biological cybernetics, 114(2), pp.269-284.
Robinson, B.S., Norman-Tenazas, R., Cervantes, M., Symonette, D., Johnson, E.C., Joyce, J., Rivlin, P.K., Hwang, G., Zhang, K. and Gray-Roncal, W., 2022. Online learning for orientation estimation during translation in an insect ring attractor network. Scientific reports, 12(1), pp. 1-15.