Nicolas Schweighofer - researchr alias

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Viewing Publication 1 - 22 from 22

2024

Theoretical limits on the speed of learning inverse models explain the rate of adaptation in arm reaching tasksVictor R. Barradas, Yasuharu Koike, Nicolas Schweighofer. NN, 170:376-389, 2024. [doi]

2021

Stochastic optimal feedforward-feedback control determines timing and variability of arm movements with or without visionBastien Berret, Adrien Conessa, Nicolas Schweighofer, Etienne Burdet. ploscb, 17(6), 2021. [doi]

Computational reproductions of external force field adaption without assuming desired trajectoriesHiroyuki Kambara, Atsushi Takagi, Haruka Shimizu, Toshihiro Kawase, Natsue Yoshimura, Nicolas Schweighofer, Yasuharu Koike. NN, 139:179-198, 2021. [doi]

2020

Electrical coupling controls dimensionality and chaotic firing of inferior olive neuronsHuu Hoang, Eric J. Lang, Yoshito Hirata, Isao T. Tokuda, Kazuyuki Aihara, Keisuke Toyama, Mitsuo Kawato, Nicolas Schweighofer. ploscb, 16(7), 2020. [doi]

2016

Optimal Schedules in Multitask Motor LearningJeong-Yoon Lee, Youngmin Oh, Sung Shin Kim, Robert A. Scheidt, Nicolas Schweighofer. neco, 28(4):667-685, 2016. [doi]

2013

Solution to the inverse problem of estimating gap-junctional and inhibitory conductance in inferior olive neurons from spike trains by network model simulationMiho Onizuka, Huu Hoang, Mitsuo Kawato, Isao T. Tokuda, Nicolas Schweighofer, Yuichi Katori, Kazuyuki Aihara, Eric J. Lang, Keisuke Toyama. NN, 47:51-63, 2013. [doi]

Adaptive coupling of inferior olive neurons in cerebellar learningIsao T. Tokuda, Huu Hoang, Nicolas Schweighofer, Mitsuo Kawato. NN, 47:42-50, 2013. [doi]

2012

Use It and Improve It or Lose It: Interactions between Arm Function and Use in Humans Post-strokeYukikazu Hidaka, Cheol E. Han, Steven L. Wolf, Carolee J. Winstein, Nicolas Schweighofer. ploscb, 8(2), 2012. [doi]

2010

The role of chaotic resonance in cerebellar learningIsao Tokuda, Cheol E. Han, Kazuyuki Aihara, Mitsuo Kawato, Nicolas Schweighofer. NN, 23(7):836-842, 2010. [doi]

2009

An Adaptive Automated Robotic Task-Practice System for Rehabilitation of Arm Functions After StrokeYounggeun Choi, James Gordon, Duckho Kim, Nicolas Schweighofer. trob, 25(3):556-568, 2009. [doi]

2008

ADAPT - adaptive automated robotic task practice system for stroke rehabilitationYounggeun Choi, James Gordon, Nicolas Schweighofer. icra 2008: 2471-2476 [doi]

Stroke Rehabilitation Reaches a ThresholdCheol E. Han, Michael A. Arbib, Nicolas Schweighofer. ploscb, 4(8), 2008. [doi]

2007

Multiple model-based reinforcement learning explains dopamine neuronal activityMathieu Bertin, Nicolas Schweighofer, Kenji Doya. NN, 20(6):668-675, 2007. [doi]

Local Online Support Vector Regression for Learning ControlYounggeun Choi, Shin-Young Cheong, Nicolas Schweighofer. icira 2007: 13-18 [doi]

2006

Humans Can Adopt Optimal Discounting Strategy under Real-Time ConstraintsNicolas Schweighofer, K. Shishida, Cheol E. Han, Yasumasa Okamoto, Saori C. Tanaka, Shigeto Yamawaki, Kenji Doya. ploscb, 2(11), 2006. [doi]

2003

Meta-learning in Reinforcement LearningNicolas Schweighofer, Kenji Doya. NN, 16(1):5-9, 2003. [doi]

2000

Cerebellar learning of accurate predictive control for fast-reaching movementsJacob Spoelstra, Nicolas Schweighofer, Michael A. Arbib. bc, 82(4):321-333, 2000. [doi]

1999

Cerebellar adaptive control of a biomimetic manipulatorJacob Spoelstra, Michael A. Arbib, Nicolas Schweighofer. ijon, 26-27:881-889, 1999. [doi]

1998

A model of activity-dependent formation of cerebellar microzonesNicolas Schweighofer. bc, 79(2):97-107, 1998. [doi]

A Model of the Electrophysiological Properties of the Inferior Olive NeuronsNicolas Schweighofer, Kenji Doya, Mitsuo Kawato. iconip 1998: 1525-1528

1996

A model of the cerebellum in adaptive control of saccadic gainNicolas Schweighofer, Michael A. Arbib, Peter Ford Dominey. bc, 75(1):29-36, 1996. [doi]

A model of the cerebellum in adaptive control of saccadic gainNicolas Schweighofer, Michael A. Arbib, Peter Ford Dominey. bc, 75(1):19-28, 1996. [doi]

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