2024
Barradas, V. R., Koike, Y., & Schweighofer, N. (2024).Theoretical limits on the speed of learning inverse models explain the rate of adaptation in arm reaching tasks.Neural Networks, 170, 376-389.
Magnard, J., Macaulay, T. R., Schroeder, E. T., Laine, C., Gordon, J., & Schweighofer, N. (2024).Initial development of skill with a reversed bicycle and a case series of experienced riders.Scientific Reports, 14(1), 4334.
2023
Kettlety, S. A., Finley, J. M., Reisman, D. S., Schweighofer, N., & Leech, K. A. (2023).Speed-dependent biomechanical changes vary across individual gait metrics post-stroke relative to neurotypical adults.Journal of NeuroEngineering and Rehabilitation, 20(1), 1-13.
Sugiyama, T., Schweighofer, N., & Izawa, J. (2023).Reinforcement learning establishes a minimal metacognitive process to monitor and control motor learning performance.Nature Communications, 14(1), 3988.
Schweighofer, N., Ye, D., Luo, H., D’Argenio, D. Z., & Winstein, C. (2023).Long-term forecasting of a motor outcome following rehabilitation in chronic stroke via a hierarchical bayesian dynamic model.Journal of NeuroEngineering and Rehabilitation, 20(1), 83.
Bonilla Yanez, M., Kettlety, S. A., Finley, J. M., Schweighofer, N., & Leech, K. A. (2023).Gait speed and individual characteristics are related to specific gait metrics in neurotypical adults.Scientific Reports, 13(1), 8069.
Liew, S. L., Schweighofer, N., Cole, J. H., Zavaliangos-Petropulu, A., Lo, B. P., Han, L. K., … & Thompson, P. M. (2023).Association of Brain Age, Lesion Volume, and Functional Outcome in Patients With Stroke.Neurology, 100(20), e2103-e2113.
Chen, Y. A., Lewthwaite, R., Schweighofer, N., Monterosso, J. R., Fisher, B. E., & Winstein, C. (2023).Essential role of social context and self-efficacy in daily paretic arm/hand use after stroke: an ecological momentary assessment study with accelerometry.Archives of Physical Medicine and Rehabilitation, 104(3), 390-402.
Sanchez, N., Schweighofer, N., Mulroy, S., Roemmich, R. T., Kesar, T. M., Torres-Oviedo, G., … & Winstein, C. J. (2023).Multi-site identification and generalization of clusters of walking impairment in individuals with chronic stroke.bioRxiv, 2023-05.
Varghese, R., Gordon, J., Sainburg, R. L., Winstein, C. J., & Schweighofer, N. (2023).Adaptive control is reversed between hands after left hemisphere stroke and lost following right hemisphere stroke.Proceedings of the National Academy of Sciences, 120(6), e2212726120.
Juliano, J. M., Schweighofer, N., & Liew, S. L. (2022).Increased cognitive load in immersive virtual reality during visuomotor adaptation is associated with decreased long-term retention and context transfer.Journal of NeuroEngineering and Rehabilitation, 19(1), 1-14.
Varghese, R., Chang, B., Kim, B., Liew, S. L., Schweighofer, N., & Winstein, C. J. (2023).Corpus callosal microstructure predicts bimanual motor performance in chronic stroke survivors: A preliminary cross-sectional study.Topics in Stroke Rehabilitation, 30(6), 626-634.
2022
Zavaliangos‐Petropulu, A., Lo, B., Donnelly, M. R., Schweighofer, N., Lohse, K., Jahanshad, N., … & Liew, S. L. (2022).Chronic stroke sensorimotor impairment is related to smaller hippocampal volumes: An ENIGMA analysis.Journal of the American Heart Association, 11(10), e025109.
Ito, K. L., Kim, B., Liu, J., Soekadar, S. R., Winstein, C., Yu, C., … & Liew, S. L. (2022).Corticospinal tract lesion load originating from both ventral premotor and primary motor cortices are associated with post-stroke motor severity.Neurorehabilitation and neural repair, 36(3), 179-182.
Schweighofer, N. (2022).Computational Neurorehabilitation.In Neurorehabilitation Technology(pp. 345-355). Cham: Springer International Publishing.
Cho, W., Barradas, V. R., Schweighofer, N., & Koike, Y. (2022).Design of an isometric end-point force control task for electromyography normalization and muscle synergy extraction from the upper limb without maximum voluntary contraction.Frontiers in Human Neuroscience, 16, 805452.
Liew, S. L., Zavaliangos‐Petropulu, A., Jahanshad, N., Lang, C. E., Hayward, K. S., Lohse, K. R., … & Thompson, P. M. (2022).The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke.Human brain mapping, 43(1), 129-148.
Ballester, B. R., Winstein, C., & Schweighofer, N. (2022).Virtuous and vicious cycles of arm use and function post-stroke.Frontiers in neurology, 13, 804211.
Kim, S., Han, C. E., Kim, B., Winstein, C. J., & Schweighofer, N. (2022).Effort, success, and side of lesion determine arm choice in individuals with chronic stroke.Journal of Neurophysiology, 127(1), 255-266.
2021
Liew, S. L., Zavaliangos-Petropulu, A., Schweighofer, N., Jahanshad, N., Lang, C. E., Lohse, K. R., … & Thompson, P. M. (2021).Smaller spared subcortical nuclei are associated with worse post-stroke sensorimotor outcomes in 28 cohorts worldwide.Brain communications, 3(4), fcab254.
Kim, B., Schweighofer, N., Haldar, J. P., Leahy, R. M., & Winstein, C. J. (2021).Corticospinal tract microstructure predicts distal arm motor improvements in chronic stroke.Journal of Neurologic Physical Therapy, 45(4), 273-281.
Kambara, H., Takagi, A., Shimizu, H., Kawase, T., Yoshimura, N., Schweighofer, N., & Koike, Y. (2021).Computational reproductions of external force field adaption without assuming desired trajectories.Neural Networks, 139, 179-198.
Ito, K. L., Cao, L., Reinberg, R., Keller, B., Monterosso, J., Schweighofer, N., & Liew, S. L. (2021).Validating habitual and goal-directed decision-making performance online in healthy older adults.Frontiers in aging neuroscience, 13, 702810.
Sánchez, N., Schweighofer, N., & Finley, J. M. (2021).Different biomechanical variables explain within-subjects versus between-subjects variance in step length asymmetry post-stroke.IEEE Transactions on Neural Systems and Rehabilitation Engineering, 29, 1188-1198.
Berret, B., Conessa, A., Schweighofer, N., & Burdet, E. (2021).Stochastic optimal feedforward-feedback control determines timing and variability of arm movements with or without vision.PLOS Computational Biology, 17(6), e1009047.
Nibras, N., Liu, C., Mottet, D., Wang, C., Reinkensmeyer, D., Remy-Neris, O., … & Schweighofer, N. (2021).Dissociating sensorimotor recovery and compensation during exoskeleton training following stroke.Frontiers in human neuroscience, 15, 645021.
Rossi, C., Roemmich, R. T., Schweighofer, N., Bastian, A. J., & Leech, K. A. (2021).Younger and Late Middle-Aged Adults Exhibit Different Patterns of Cognitive-Motor Interference During Locomotor Adaptation, With No Disruption of Savings.Frontiers in Aging Neuroscience, 13, 729284.
Chen, Y. A., Demers, M., Lewthwaite, R., Schweighofer, N., Monterosso, J. R., Fisher, B. E., & Winstein, C. (2021).A novel combination of accelerometry and ecological momentary assessment for post-stroke paretic arm/hand use: feasibility and validity.Journal of Clinical Medicine, 10(6), 1328.
2020
Wang, C.,* D’Argenio D., Winstein, C., Schweighofer, N. (2020) The Efficiency, Efficacy, and Retention of Task Practice in Chronic Stroke. Neurorehabilitation and Neural Repair. doi: 10.1177/1545968320948609
Varghese R., Kutch J., Schweighofer, N and Winstein C.J. (2020) The Probability of Choosing Both Hands Depends on an Interaction Between Motor Capacity and Limb-Specific Control in Chronic Stroke In Press, Experimental Brain Research doi: 10.1007/s00221-020-05909-5
Hoang, H., Lang, E.J., Hirata, Y., Tokuda, I.T., Aihara, K., Toyama, K., Kawato, M. and Schweighofer, N., (2020). Electrical coupling controls dimensionality and chaotic firing of inferior olive neurons. PLOS Computational Biology, 16(7), p.e1008075.
Barradas V.,* Kutch J., Kawase T., Koike Y., Schweighofer N. (2020) When 90% is not enough: impact of discarded muscle synergies on motor control, Journal of Neurophysiology, 123, 2180-2190
Liew, S.L, Zavaliangos-Petropulu A., … Schweighofer N., … Steven C. Cramer S., & Thompson P.M. (2020) The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain-behavior relationships after stroke. Human Brain Mapping, 2020, 1–20
2019
Oh Y*, and Schweighofer N. (2019) Minimizing Precision-Weighted Sensory Prediction Errors via Memory Formation and Switching in Motor Adaptation, Journal of Neuroscience, 39 (46), 9237-9250
Kim A., Schweighofer N., Finley J.M. (2019) Locomotor skill acquisition in virtual reality shows sustained transfer to the real world. Journal of Neuroengineering and Rehabilitation, 16(1), 1-10.
Winstein C., Kim B., Kim, S., Martinez C., and Schweighofer N. (2019) Dosage Matters: A Phase IIb Randomized Controlled Trial of Motor Therapy in the Chronic Phase after Stroke, Stroke, 50(7):1831-1837. doi: 10.1161/STROKEAHA
Lefebvre S., Jann K, Schmiesing A., Ito K., Jog M., Qiao Y., Cabeen R., Shi Y., Schweighofer N., Wang D.J., Liew S.L. (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,
2018
Lee K.*, Oh Y.*, Izawa J. #, Schweighofer N.# (2018) Sensory prediction errors, not performance errors, update memories in visuomotor adaptation. Scientific reports, 8: 16483
Kim S.*, Park H.*, Winstein C., and Schweighofer N. (2018) Measuring habitual arm use post-stroke. Frontiers in Neurology, 9, 883
Schweighofer, N., Wang, C., Mottet, D.; Laffont I., Bakhti K., Reinkensmeyer, D; and Remy-Neris O. (2018) Dissociating motor learning from recovery in exoskeleton training post-stroke Journal of NeuroEngineering and Rehabilitation, 15(1):89. doi: 10.1186/s12984-018-0428-1.
Kim, B., Fisher, B.E., Schweighofer, N., Leahy, R.M., Haldar, J.P., Choi, S., Kay, D.B., Gordon, J. and Winstein, C.J., (2018) A comparison of seven different DTI-derived estimates of corticospinal tract structural characteristics in chronic stroke survivors. Journal of neuroscience methods, 304, 66-75.
2017
Bakhti KKA, Mottet D, Schweighofer N, Froger J, Laffont I. (2017) Proximal arm non-use when reaching after a stroke Neuroscience Letters. 657, 91-96
2016
Wang C., Xiao Y., Burdet E., Gordon J., and Schweighofer N. (2016)
The duration of reaching movement is longer than predicted by minimum variance Journal of Neurophysiology. DOI: 10.1152/jn.00148.2016
Park H., Kim S., Winstein C.J., Gordon J., and Schweighofer N. (2016)
Short-duration and intensive training improves long-term reaching performance in individuals with chronic stroke Neurorehabilitation and Neural Repair. 30(6), 551-561
Reinkensmeyer D.J., Burdet E., Casadio M., Krakauer J.W., Kwakkel G., Lang C.E., Swinnen S.P., Ward N.S. and Schweighofer N. (2016) Computational neurorehabilitation: modeling plasticity and learning to predict recovery Journal of Neuroengineering and Neural Repair. 13(1):42
Lee J.Y., Oh Y., Kim S.S., Scheidt R.A., and Schweighofer N. (2016) Optimal schedules in multitask motor learning Neural Computation. 28(4):667-685
Lang E.J., Apps R., Bengtsson F., Cerminara N.L., De Zeeuw C.I., Ebner T.J., Heck D.H., Jaeger D., Jörntell H., Kawato M., Otis T.S., Ozyildirim O., Popa L.S., Reeves A.M., Schweighofer N., Sugihara I., and Xiao J. (2016) The roles of the olivocerebellar pathway in motor learning and motor control. A consensus paper The Cerebellum.
2015
Kim S.S., Ogawa K., Lv. J., Schweighofer N.* and Imamizu H.* (2015) Neural substrates related to motor memory with multiple timescales in sensorimotor adaptation PLoS Biology. 13(12):e1002312
Gueugneau N., Schweighofer N. and Papaxanthis C. (2015) Daily update of motor predictions by physical activity Scientific Reports. 5:1-9
Kim S.S., Oh Y., and Schweighofer N. (2015) Between trial forgetting due to interference and time in motor adaptation PLoS One. 10(11):e0142963
Bains A.S. and Schweighofer N. (2015) Robust use-dependent learning in arm movements Translational and Computational Motor Control.
Schweighofer N., Xiao Y., Kim S., Yoshioka T., Gordon J., and Osu R. (2015)
Effort, success, and non-use determine arm choice Journal of Neurophysiology. 114(1):551-559
2014
Bains A.S. and Schweighofer N. (2014) Time-sensitive reorganization of the somatosensory cortex poststroke depends on interaction between Hebbian and homeoplasticity: a simulation study Journal of Neurophysiology. 112(12):3240-3250
Sargent B., Schweighofer N., Kubo M., and Fetters L. (2014) Infant exploratory learning: influence on leg joint coordination PLoS One. 9(3):e91500
Winstein C.J., Wolf S.L., and Schweighofer N. (2014) Task oriented training to promote upper extremity recovery In Stein et al. (Eds.), Stroke Recovery and Rehabilitation, 2nd Ed. New York, NY: Demos Medical.
2013
Kim S.S., Ogawa K., Lv J., Schweighofer N., and Imamizu, H. (2013)
Neural correlates of motor memory with multiple time scales in sensorimotor adaptation Translational and Computational Motor Control.
Onizuka M., Hoang H., Kawato M., Tokuda I.T., Schweighofer N., Katori Y., Aihara K., Lang E.J., and Toyama K. (2013) Solution to the inverse problem of estimating gap-junctional and inhibitory conductance in inferior olive neurons from the spike trains by network model simulation Neural Networks. 47:51-63
Han C.E., Kim S., Chen S., Lai Y.H., Lee J.-Y., Osu R., Winstein C.J., and Schweighofer N. (2013) Quantifying arm nonuse in individuals poststroke
Neurorehabilitation and Neural Repair. 27(5):439-447
Tokuda I.T., Hoang H., Schweighofer N., and Kawato M. (2013) Adaptive coupling of inferior olive neurons in cerebellar learning Neural Networks. 47:42-50
2012
Schweighofer N., Choi Y., Winstein C.J., and Gordon, J. (2012)
Task-oriented rehabilitation robotics American Journal of Physical Medicine & Rehabilitation. 91(11)
Hidaka Y., Han C.E., Wolf S.L., Winstein C.J.,and Schweighofer N. (2012) Use it and improve it or lose it: Interactions between arm function and use in humans post-stroke PLoS Computational Biology. 8(2):e1002343
2011
Qi F. and Schweighofer N. (2011) Including prior knowledge for accurate and fast motor threshold estimation Brain Stimulation. 4(1):60-61
Schweighofer N., Lee J.-Y., Goh H.T., Choi Y., Kim S., Stewart J.C., Lewthwaite R.,and Winstein C.J. (2011) Mechanisms of the contextual interference effect in individuals post-stroke Journal of Neurophysiology. 106(5):2632-2641
Choi Y., Gordon J., Park H.,and Schweighofer N. (2011) Feasibility of the Adaptive and Automatic Presentation of Tasks (ADAPT) system for rehabilitation of upper extremity function post-stroke Journal of Neuroengineering and Rehabilitation. 8(1):42 **This will need to be reuploaded.
Kawato M., Kuroda S., and Schweighofer N. (2011) Cerebellar supervised learning revisited:biophysical modeling and degrees-of-freedom control Current Opinion in Neurobiology. 21:791-800
Frey S.H., Fogassi L., Grafton S., Picard N., Rothwell J.C., Schweighofer N., Corbetta M.,and Fitzpatrick S.M. (2011) Neurological principles and rehabilitation of action disorders: Computation, Anatomy, and Physiology (CAP)model Neurorehabilitation and Neural Repair. 25(5Suppl):6S-20S
Abe M., Schambra H., Wassermann E.M., Luckenbaugh D., Schweighofer N.,and Cohen L.G. (2011) Reward improves long-term retention of a motor memory through induction of offline memory gains Current Biology. 21:557-562
Qi F., Wu A., and Schweighofer N. (2011) Fast estimation of TMS motor threshold
Brain Stimulation. 4:50-57
2010
Tokuda I., Han C.E., Aihara K., Kawato M.,and Schweighofer N. (2010) Role of chaotic resonance in cerebellar learning Neural Networks. 23(7):836-842
Gentili R., Han C.E., Schweighofer N.,and Papaxanthis C. (2010) Motor learning without doing: Trial-by-trial improvement in motor performance during mental training Journal of Neurophysiology. 104(2):774-783
Callan D. and Schweighofer N. (2010) Neural correlates of the spacing effect in explicit verbal semantic encoding support the deficient-processing theory Human Brain Mapping. 31(4):645-659
2009
Tanaka S., Shishida K., Schweighofer N.,Okamoto Y., Yamawaki S., and Doya K.(2009) Serotonin affects association of aversive outcomes to past actions Journal of Neuroscience. 29(50):15669-15674
Schweighofer N., Han C.E., Wolf S.L., Arbib, M.A.and Winstein C. (2009) A functional threshold for long-term use of hand and arm function can be determined: Predictions from a computational model and supporting data from the Extremity Constraint-Induced Therapy Evaluation (EXCITE) Trial Physical Therapy. 89(12):1327-1336
Lee J.-Y. and Schweighofer N. (2009) Dual-adaptation supports a parallel architecture of motor memory Journal of Neuroscience. 29:10396-10404
Choi Y.G., Gordon J., Kim D., and Schweighofer N.(2009) An adaptive automated robotic task-practice system for rehabilitation of arm functions after stroke IEEE Transactions On Robotics. 24:556-568
2008
Han C.E., Arbib M.A., and Schweighofer N.(2008) Stroke rehabilitation reaches a threshold PLoS Computational Biology. 4(8):e1000133
Choi Y.G., Qi F., Gordon J.,and Schweighofer N. (2008) Performance-based adaptive schedules enhance motor learning Journal of Motor Behavior. 40:273-280
Schweighofer N., Bertin M., Shishida K.,Okamoto Y., Tanaka S.C., Yamawaki S.,and Doya K. (2008) Low-serotonin levels increase delayed reward discounting in humans Journal of Neuroscience. 28:4528-4532
Callan D. and Schweighofer N. (2008) Positive and negative modulation of word learning by reward anticipation Human Brain Mapping. 29:237-249
2007
Tanaka S.C., Schweighofer N., Asahi S., Shishida K., Okamoto Y., Yamawaki S.,and Doya K. (2007) Serotonin differentially regulates short- and long-term prediction of rewards in the ventral and dorsal striatum PLoS One. 2(12):e1333
Bertin M., Schweighofer N., and Doya K.(2007) Multiple model-based reinforcement learning explains dopamine neuronal activity Neural Networks. 20:668-675
Schweighofer N., Tanaka S., and Doya K.(2007) Serotonin and the evaluation of future rewards: Theory, experiments, and possible neural mechanisms Annals of the New York Academy of Science. 1104:289-300
2006 and before
Schweighofer N., Shishida K., Han C.E., Okamoto Y., Tanaka S.C., Yamawaki S.,and Doya K. (2006) Humans can adopt optimal discounting strategy under real-time constraints PLoS Computational Biology. 11:1349-1356
Pozzo T., Papaxanthis C., Petit J.L., Schweighofer N., and Stucchi N.(2006). Kinematic features of movement tunes perception and action coupling Behav Brain Research. 169:75-82
Schaal S. and Schweighofer N. (2005) Computational motor control in humans and robots Current Opinion in Neurobiology. 25:1-8
Schweighofer N., Doya K., ChironJ.V., Fukai H., Furukawa T., and Kawato M.(2004)
Chaos may enhance information transmission in the inferior olive Proceedings of the National Academy of Sciences. 101:4655-4660
Schweighofer N., Doya K., and Kuroda S.(2004) Cerebellar aminergic neuromodulation: Towards a functional understanding Brain Research Reviews. 44:103-106
Schweighofer N. and Doya K. (2003) Meta-learning in reinforcement learning
Neural Networks. 16:5-9
Kuroda S., Schweighofer N., and Kawato M.(2001) Exploration of signal transduction pathways in cerebellar long-term depression by kinetic simulation Journal of Neuroscience. 21:5693-5702
Schweighofer N., Doya K., and Lay F.(2001) Unsupervised learning of granule cell sparse codes enhances cerebellar adaptive control Neuroscience. 103:35-50
Schweighofer N. and Ferriol G.(2000) Diffusion of nitric oxide canfacilitate cerebellar learning: A simulation study Proceedings of the National Academy of Sciences. 97:10661-5
Spoelstra J., Schweighofer N.,and Arbib M.A. (2000) Cerebellar learning of accurate predictive control for fast reaching movements Biological Cybernetics. 82:321-333
Schweighofer N., Doya K., and Kawato M.(1999) Electrophysiological properties of the inferior olive neurons: A compartmental model Journal of Neurophysiology. 82:804-817
Spoelstra J., Arbib M.A.,and Schweighofer N. (1999) Cerebellar adaptive control of a biomimetic manipulator Neurocomputing. 82:804-817
Schweighofer N. (1998) A model of activity-dependent formation of cerebellar microzones Biological Cybernetics. 79:97-107
Schweighofer N., Arbib, M.A. and Kawato, M.(1998) Role of the cerebellum in reaching movements in humans. I. Distributed inverse dynamics control European Journal of Neuroscience. 10:86-94
Schweighofer N., Spoelstra J., Arbib M.A,and Kawato M. (1998) Role of the cerebellum in reaching movements in humans. II. A neural model of the intermediate cerebellum European Journal of Neuroscience. 10:95-105
Schweighofer N. and Arbib M.A.(1998) A model of cerebellar meta plasticity
Learning & Memory. 4:421-428
Schweighofer N., Arbib M.A.,and Dominey P.F. (1996) A model of the cerebellum in adaptive control of saccadic gain. I. The model and its biological substrate
Biological Cybernetics. 75:19-28
Schweighofer N., Arbib M.A.,and Dominey P.F. (1996) A model of the cerebellum in adaptive control of saccadic gain. II. Simulation results Biological Cybernetics. 75:29-36