UCR

Fabio Pasqualetti

Associate Professor, University of California at Riverside

Home | Research | Publications | Research Group | Teaching
Curriculum Vitae | Google Scholar | ORCID

Menu

  Year
2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011 | 2010 | 2009 | 2008 | 2007 | View all

  Topic
Learning for control
Cyber-physical security
Network analysis and design
Distributed control/estimation
Network neuroscience
Smart power grid
Robotic patrolling/surveillance

  Co-author
R. Anguluri
G. Baggio
D. S. Bassett
R. Betzel
G. Bianchin
A. Bicchi
F. Bullo
R. Carli
F. Celi
J. Cortés
F. Dörfler
A. Franchi
P. Frasca
A. Gasparri
S. Grafton
A. A. Al Makdah
S. Gu
V. Gupta
V. Katewa
V. Krishnan
J. D. Medaglia
T. Menara
S. F. Muldoon
H. Mohsenian-Rad
Y. Qin
S. Zampieri
S. Zhao
Q. Zhu

Journal Articles

  1. Y. Qin and T. Menara and D. S. Bassett and F. Pasqualetti, Phase-Amplitude Coupling in Neuronal Oscillator Networks. Physical Review Research, 3(2):2021. [PDF]
  2. B. H. Scheid and A. Ashourvan and J. Stiso and K. A. Davis and F. Mikhail and F. Pasqualetti and B. Litt and D. S. Bassett, Time-evolving controllability of effective connectivity networks during seizure progression. Proceedings of the National Academy of Sciences, 2021. [PDF]
  3. G. Baggio and D. S. Bassett and F. Pasqualetti, Data-Driven Control of Complex Networks. Nature Communications, 12(1429):2021. [PDF]
  4. X. He and L. Caciagli and L. Parkes and J. Stiso and T. M Karrer and J. Z. Kim and Z. Lu and T. Menara and F. Pasqualetti and M. R. Sperling and J. I. Tracy and D. S. Bassett, Pathological and metabolic underpinnings of energetic inefficiency in temporal lobe epilepsy. bioRxiv, 2021.
  5. P. Srivastava and P. Mucha and K. Ochsner and E. Falk and F. Pasqualetti and D. S. Bassett, Structural underpinnings of control in multiplex networks. Nature Communications, 2021.
  6. T. Menara and Y. Qin and D. S. Bassett and F. Pasqualetti, Relay Interactions Enable Remote Synchronization in Networks of Phase Oscillators. IEEE Control Systems Letters, 6:500-505, 2021.
  7. 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 X. Zhang 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 network dynamics during working memory are modulated by dopamine and diminished in schizophrenia. Nature Communications, 3478, 2021. [PDF]
  8. E. Tang and G. L. Baum and D. R. Roalf and T. D. Satterthwaite and F. Pasqualetti and D. S. Bassett, Control of brain network dynamics across diverse scales of space and time. Physical Review E, 101(6):2020.
  9. T. Menara and G. Baggio and D. S. Bassett and F. Pasqualetti, Stability Conditions for Cluster Synchronization in Networks of Heterogeneous Kuramoto Oscillators. IEEE Transactions on Control of Network Systems, 7(1):302 - 314, 2020. [PDF]
  10. 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]
  11. T. M. Karrer and J. Z. Kim and J. Stiso and A. E. Kahn and F. Pasqualetti and U. Habel and D. S. Bassett, A practical guide to methodological considerations in the controllability of structural brain networks. Journal of Neural Engineering, 17(026031):2020. [PDF]
  12. T. Menara and G. Baggio and D. S. Bassett and F. Pasqualetti, Conditions for Feedback Linearization of Network Systems. IEEE Control Systems Letters, 4(3):578-583, 2020. [PDF]
  13. K. P. Szymula and F. Pasqualetti and A. M. Graybiel and T. M. Desrochers and D. S. Bassett, Habit learning supported by efficiently controlled network dynamics in naive macaque monkeys. Nature Neuroscience, 2020. Submitted. [PDF]
  14. J. Stiso and M.-C. Corsi and J. Vettel and J. Garcia and F. Pasqualetti and F. de Vico-Fallani and T. Lucas and D. S. Bassett, Learning in brain-computer interface control evidenced by joint decomposition of brain and behavior. Journal of Neural Engineering, 17(4):2020. [PDF]
  15. J. K. Brynildsen and K. D. Mace and E. J. Cornblath and C. Weidler and F. Pasqualetti and D. S. Bassett and J. A. Blendy, Gene coexpression patterns predict opiate-induced brain state transitions. Proceedings of the National Academy of Sciences, 2020. [PDF]
  16. Y. Qin and M. Cao and B. D. O. Anderson and D. S. Bassett and F. Pasqualetti, Mediated Remote Synchronization: the Number of Mediators Matters. IEEE Control Systems Letters, 5(3):767-772, 2020. [PDF]
  17. P. Srivastava and E. Nozari and J. Z. Kim and H. Ju and D. Zhou and C. Becker and F. Pasqualetti and D. S. Bassett, Models of communication and control for brain networks: distinctions, convergence, and future outlook. Network Neuroscience, 4(4):2020. [PDF]
  18. S. P. Patankar and J. Z. Kim and F. Pasqualetti and D. S. Bassett, Path-dependent connectivity, not modularity, consistently predicts controllability of structural brain networks. Network Neuroscience, 2020. In press. [PDF]
  19. T. Menara and D. S. Bassett and F. Pasqualetti, Structural Controllability of Symmetric Networks. IEEE Transactions on Automatic Control, 64(9):3740-3747, 2019. [PDF]
  20. E. J. Cornblath and E. Tang and G. L. Baum and T. M. Moore and A. Abedimpe and D. R. Roalf and R. C. Gur and R. E. Gur and F. Pasqualetti and T. D. Satterthwaite and D. S. Bassett, Sex differences in network controllability as a predictor of executive function in youth. Neuroimage, 122-134, 2019. [PDF]
  21. F. Pasqualetti and S. Gu and D. S. Bassett, RE: Warnings and caveats in brain controllability. NeuroImage, 197:586-588, 2019.
  22. J. Stiso and A. N. Khambhati and T. Menara and A. E. Kahn and J. M. Stein and S. R. Das and R. Gorniak and J. Tracy and B. Litt and K. A. Davis and F. Pasqualetti and T. H. Lucas and D. S. Bassett, White Matter Network Architecture Guides Direct Electrical Stimulation through Optimal State Transitions. Cell Reports, 28(10):2554 - 2566.e7, 2019. [PDF]
  23. S. Gu and M. Cieslak and B. Baird and S. F. Muldoon and S. T. Grafton and F. Pasqualetti and D. S. Bassett, The Energy Landscape of Neurophysiological Activity Implicit in Brain Network Structure. Scientific Reports, 8(2507):2018. [PDF]
  24. 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]
  25. J. Kim and J. M. Soffer and A. E. Kahn and J. M. Vettel and F. Pasqualetti and D. S. Bassett, Role of graph architecture in controlling dynamical networks with applications to neural systems. Nature Physics, 14:91-98, 2018. [PDF]
  26. J. D. Medaglia and F. Pasqualetti and R. H. Hamilton and S. L. Thompson-Schill and D. S. Bassett, Brain and cognitive reserve: Translation via network control theory. Neuroscience and Biobehavioral Reviews, 75(2017):53-64, 2017. [PDF]
  27. L. Wiles and S. Gu and F. Pasqualetti and D. S Bassett and D. F. Meaney, Autaptic Connections Shift Network Excitability and Bursting. Scientific Reports, 7(44006):2017. [PDF]
  28. J. D. Medaglia and S. Gu and F. Pasqualetti and R. L. Ashare and C. Lerman and J. Kable and D. S. Bassett, Cognitive Control in the Controllable Connectome. Journal of Neuroscience, 2017. Submitted.
  29. 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.
  30. 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]
  31. S. F. Muldoon and F. Pasqualetti and S. Gu and M. Cieslak and S. T. Grafton and J. M. Vettel and D. S. Bassett, Stimulation-based control of dynamic brain networks. PLoS Computational Biology, 12(9):e1005076, 2016. [PDF]
  32. S. Gu and F. Pasqualetti and M. Cieslak and Q. K. Telesford and B. Y. Alfred and A. E. Kahn and J. D. Medaglia and J. M. Vettel and M. B. Miller and S. T. Grafton and D. S. Bassett, Controllability of structural brain networks. Nature Communications, 6:2015. [PDF]

Conference Articles

  1. Y. Qin and D. S. Bassett and F. Pasqualetti, Flexible Information Propagation in Oscillator Networks. IEEE Conf. on Decision and Control, Cancún, Mexico, December 2022. Submitted.
  2. Y. Qin and D. S. Bassett and F. Pasqualetti, Vibrational Control of Cluster Synchronization: Connections with Deep Brain Stimulation. IEEE Conf. on Decision and Control, Cancún, Mexico, December 2022. Submitted. [PDF]
  3. T. Menara and G. Baggio and D. S. Bassett and F. Pasqualetti, Exact and Approximate Stability Conditions for Cluster Synchronization of Kuramoto Oscillators. American Control Conference, Philadelphia, PA, USA, pages 205 - 210, July 2019. [PDF]
  4. T. Menara and G. Baggio and D. S. Bassett and F. Pasqualetti, A Framework to Control Functional Connectivity in the Human Brain. IEEE Conf. on Decision and Control, Nice, France, pages 4697-4704, December 2019. [PDF]
  5. T. Menara and V. Katewa and D. S. Bassett and F. Pasqualetti, The Structured Controllability Radius of Symmetric (Brain) Networks. American Control Conference, Milwaukee, WI, USA, pages 2802-2807, June 2018. [PDF]
  6. C. Favaretto and D. S. Bassett and A. Cenedese and F. Pasqualetti, Bode meets Kuramoto: Synchronized Clusters in Oscillatory Networks. American Control Conference, Seattle, WA, pages 2378-5861, May 2017. [PDF]
  7. L. Tiberi and C. Favaretto and M. Innocenti and D. S. Bassett and F. Pasqualetti, Synchronization Patterns in Networks of Kuramoto Oscillators: A Geometric Approach for Analysis and Control. IEEE Conf. on Decision and Control, Melbourne, Australia, pages 481-486, December 2017. [PDF]

Book Chapters

  1. D. S. Bassett and F. Pasqualetti, Network-based approaches for understanding intrinsic control capacities of the human brain. The Cognitive Neurosciences VI. Ed. by M. S. Gazzaniga and G. R. Mangun and D. Poeppel. MIT Press, 2019. In press.

Fabio Pasqualetti - University of California at Riverside