Z. Cui and J. Stiso and G. L. Baum and J. Z. Kim and D. R. Roalf and R. F. Betzel and S. Gu and Z. Lu and C. H. Xia and R. Ciric and T. M. Moore and R. T. Shinohara and K. Ruparel and C. Davatzikos and F. Pasqualetti and R. E. Gur and R. C. Gur and D. S. Bassett and T. D. Satterthwaite, Optimization of Energy State Transition Trajectory Supports the Development of Executive Function During Youth. eLife, 9:e53060, 2020. [PDF]
U. Braun and A. Harneit and G. Pergola and T. Menara and A. Schaefer and R. F. Betzel and Z. Zang and J. I. Schweiger and K. Schwarz and J. Chen and G. Blasi and A. Bertolino and D. Durstewitz and F. Pasqualetti and E. Schwarz and A. Meyer-Lindenberg and D. S. Bassett and H. Tost, Brain state stability during working memory is explained by network control theory, modulated by dopamine D1/D2 receptor function, and diminished in schizophrenia. Nature Neuroscience, 2019. Submitted. [PDF]
E. Wu-Yan and R. F. Betzel and E. Tang and S. Gu and F. Pasqualetti and D. S. Bassett, Benchmarking measures of network controllability on canonical graph models. Journal of Nonlinear Science, 1-39, 2018. [PDF]
S. Gu and R. F. Betzel and M. G. Mattar and M. Cieslak and P. R. Delio and S. T. Grafton and F. Pasqualetti and D. S. Bassett, Optimal trajectories of brain state transitions. NeuroImage, 148:305-317, 2017.
R. F. Betzel and S. Gu and J. D. Medaglia and F. Pasqualetti and D. S. Bassett, Optimally controlling the human connectome: the role of network topology. Scientific Reports, 6:30770, 2016. [PDF]
Fabio Pasqualetti - University of California at