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Chaos (Woodbury, N.Y.)|March 2, 2020
Supervised chaotic source separation by a tank of waterZhixin Lu, Jason Z Kim, Danielle S BassettChaos (Woodbury, N.Y.)|July 3, 2020
Invertible generalized synchronization: A putative mechanism for implicit learning in neural systemsZhixin Lu, Danielle S BassettChaos (Woodbury, N.Y.)|August 3, 2017
Development of structural correlations and synchronization from adaptive rewiring in networks of Kuramoto oscillatorsLia Papadopoulos, Jason Z Kim, Jürgen Kurths, et al.Journal of Neural Engineering|October 9, 2020
Network structure of cascading neural systems predicts stimulus propagation and recoveryHarang Ju, Jason Z Kim, John M Beggs, et al.Network Neuroscience (Cambridge, Mass.)|November 16, 2020
Path-dependent connectivity, not modularity, consistently predicts controllability of structural brain networksShubhankar P Patankar, Jason Z Kim, Fabio Pasqualetti, et al.Chaos (Woodbury, N.Y.)|October 21, 2025
SIGMa-DS: System identification from the geometric manifold of dynamical synchronizationJason Z Kim, Ling-Wei Kong, Zhixin LuPlos One|September 19, 2022
External drivers of BOLD signal's non-stationarityArian Ashourvan, Sérgio Pequito, Maxwell Bertolero, et al.Chaos (Woodbury, N.Y.)|February 2, 2022
Learning continuous chaotic attractors with a reservoir computerLindsay M Smith, Jason Z Kim, Zhixin Lu, et al.Nature Physics|February 10, 2018
Role of Graph Architecture in Controlling Dynamical Networks with Applications to Neural SystemsJason Z Kim, Jonathan M Soffer, Ari E Kahn, et al.Journal of Neural Engineering|January 23, 2020
A practical guide to methodological considerations in the controllability of structural brain networksTeresa M Karrer, Jason Z Kim, Jennifer Stiso, et al.Pageof 33