Nicolas Schweighofer

University of Southern California, Los Angeles, CA, United States 
Computational Neuroscience
"Nicolas Schweighofer"
Mean distance: 14.44 (cluster 29)
Cross-listing: Computational Biology Tree


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Cheol E. Han grad student 2004-2009 USC
Feng Qi grad student 2010 USC
Young Geun G. Choi grad student 2004-2010 USC
Jeong-Yoon Lee grad student 2005-2011 USC
Yukikazu Hidaka grad student 2013 USC


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Jun Izawa collaborator
Saori Tanaka collaborator ATR
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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
Oh Y, Schweighofer N. (2019) Minimizing Precision-Weighted Sensory Prediction Errors via Memory Formation and Switching in Motor Adaptation. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience
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