Nicolas Schweighofer
Affiliations: | University of Southern California, Los Angeles, CA, United States |
Area:
Computational NeuroscienceWebsite:
http://pt.usc.edu/labs/cnrlGoogle:
"Nicolas Schweighofer"Cross-listing: Neurotree
Parents
Sign in to add mentor| Michael A. Arbib | grad student | USC (Neurotree) | |
| Mitsuo Kawato | post-doc | ATR (Neurotree) |
Children
Sign in to add trainee| Cheol E. Han | grad student | 2004-2009 | USC (Neurotree) |
| Feng Qi | grad student | 2010 | USC (Neurotree) |
| Young Geun G. Choi | grad student | 2004-2010 | USC (Neurotree) |
| Jeong-Yoon Lee | grad student | 2005-2011 | USC |
| Yukikazu Hidaka | grad student | 2013 | USC (Neurotree) |
Collaborators
Sign in to add collaborator| Jun Izawa | collaborator | (Neurotree) | |
| Saori Tanaka | collaborator | ATR (Neurotree) |
BETA: Related publications
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Publications
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| Barradas VR, Koike Y, Schweighofer N. (2023) Theoretical limits on the speed of learning inverse models explain the rate of adaptation in arm reaching tasks. Neural Networks : the Official Journal of the International Neural Network Society. 170: 376-389 |
| Sugiyama T, Schweighofer N, Izawa J. (2023) Reinforcement learning establishes a minimal metacognitive process to monitor and control motor learning performance. Nature Communications. 14: 3988 |
| Varghese R, Gordon J, Sainburg RL, et al. (2023) Adaptive control is reversed between hands after left hemisphere stroke and lost following right hemisphere stroke. Proceedings of the National Academy of Sciences of the United States of America. 120: e2212726120 |
| Kim S, Han CE, Kim B, et al. (2021) Effort, success, and side of lesion determine arm choice in chronic stroke survivors with mild-to-moderate impairment. Journal of Neurophysiology |
| Berret B, Conessa A, Schweighofer N, et al. (2021) Stochastic optimal feedforward-feedback control determines timing and variability of arm movements with or without vision. Plos Computational Biology. 17: e1009047 |
| Kambara H, Takagi A, Shimizu H, et al. (2021) Computational reproductions of external force field adaption without assuming desired trajectories. Neural Networks : the Official Journal of the International Neural Network Society. 139: 179-198 |
| Varghese R, Kutch JJ, Schweighofer N, et al. (2020) The probability of choosing both hands depends on an interaction between motor capacity and limb-specific control in chronic stroke. Experimental Brain Research |
| Wang C, Winstein C, D'Argenio DZ, et al. (2020) The Efficiency, Efficacy, and Retention of Task Practice in Chronic Stroke. Neurorehabilitation and Neural Repair. 1545968320948609 |
| Hoang H, Lang EJ, Hirata Y, et al. (2020) Electrical coupling controls dimensionality and chaotic firing of inferior olive neurons. Plos Computational Biology. 16: e1008075 |
| Lefebvre S, Jann K, Schmiesing A, et al. (2019) Differences in high-definition transcranial direct current stimulation over the motor hotspot versus the premotor cortex on motor network excitability. Scientific Reports. 9: 17605 |