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    Nicolas Schweighofer, MS, PhD

    TitleAssociate Professor
    SchoolHerman Ostrow School of Dentistry of USC
    DepartmentBiokinesiology and Physical Therapy
    AddressCHP 155
    Health Sciences Campus
    Los Angeles California 90089-9006
    Phone+1 323 442 1838
    vCardDownload vCard

      Collapse Overview 
      Collapse Overview
      The goal of the work on neuro-computational models is to understand the neural bases of motor learning. We are notably investigating motor plasticity in the cerebellum, cortical map plasticity and reorganization in the sensorimotor cortex, multiple task learning, and adaptive decision-making during motor learning in healthy and lesioned brains. When appropriate, we test our predictions by conducting behavioral and/or brain imaging (fMRI and TMS) experiments either at USC or with our collaborators at ATR in Japan or at INSERM in France.

      The goal of the work on learning optimization is to enhance re-learning of motor skills in patients with stroke. Despite great progress in psychology and neuroscience, physical therapists treating patients with stroke rely on non-specific guidelines to determine task practice schedules for functional motor skill re-acquisition. Using algorithms that combine neuroscience-based models and artificial intelligence, we aim at defining and testing adaptive practice schedules, with particular emphasis on the micro-schedules of the practice.


      Collapse Bibliographic 
      Collapse Publications
      Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Researchers can login to make corrections and additions, or contact us for help.
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      1. Park H, Schweighofer N. Nonlinear mixed-effects model reveals a distinction between learning and performance in intensive reach training post-stroke. J Neuroeng Rehabil. 2017 Mar 17; 14(1):21. PMID: 28302158.
        View in: PubMed
      2. Wang C, Xiao Y, Burdet E, Gordon J, Schweighofer N. The duration of reaching movement is longer than predicted by minimum variance. J Neurophysiol. 2016 Nov 1; 116(5):2342-2345. PMID: 27559137.
        View in: PubMed
      3. Lang EJ, Apps R, Bengtsson F, Cerminara NL, De Zeeuw CI, Ebner TJ, Heck DH, Jaeger D, J├Ârntell H, Kawato M, Otis TS, Ozyildirim O, Popa LS, Reeves AM, Schweighofer N, Sugihara I, Xiao J. The Roles of the Olivocerebellar Pathway in Motor Learning and Motor Control. A Consensus Paper. Cerebellum. 2016 May 19. PMID: 27193702.
        View in: PubMed
      4. Reinkensmeyer DJ, Burdet E, Casadio M, Krakauer JW, Kwakkel G, Lang CE, Swinnen SP, Ward NS, Schweighofer N. Computational neurorehabilitation: modeling plasticity and learning to predict recovery. J Neuroeng Rehabil. 2016; 13(1):42. PMID: 27130577.
        View in: PubMed
      5. Lee JY, Oh Y, Kim SS, Scheidt RA, Schweighofer N. Optimal Schedules in Multitask Motor Learning. Neural Comput. 2016 Apr; 28(4):667-85. PMID: 26890347.
        View in: PubMed
      6. Kim S, Ogawa K, Lv J, Schweighofer N, Imamizu H. Neural Substrates Related to Motor Memory with Multiple Timescales in Sensorimotor Adaptation. PLoS Biol. 2015 Dec; 13(12):e1002312. PMID: 26645916.
        View in: PubMed
      7. Gueugneau N, Schweighofer N, Papaxanthis C. Daily update of motor predictions by physical activity. Sci Rep. 2015; 5:17933. PMID: 26632341.
        View in: PubMed
      8. Kim S, Oh Y, Schweighofer N. Between-Trial Forgetting Due to Interference and Time in Motor Adaptation. PLoS One. 2015; 10(11):e0142963. PMID: 26599075.
        View in: PubMed
      9. Park H, Kim S, Winstein CJ, Gordon J, Schweighofer N. Short-Duration and Intensive Training Improves Long-Term Reaching Performance in Individuals With Chronic Stroke. Neurorehabil Neural Repair. 2016 Jul; 30(6):551-61. PMID: 26405046.
        View in: PubMed
      10. Schweighofer N, Xiao Y, Kim S, Yoshioka T, Gordon J, Osu R. Effort, success, and nonuse determine arm choice. J Neurophysiol. 2015 Jul; 114(1):551-9. PMID: 25948869.
        View in: PubMed
      11. Bains AS, Schweighofer N. Time-sensitive reorganization of the somatosensory cortex poststroke depends on interaction between Hebbian and homeoplasticity: a simulation study. J Neurophysiol. 2014 Dec 15; 112(12):3240-50. PMID: 25274347.
        View in: PubMed
      12. Laffont I, Bakhti K, Coroian F, van Dokkum L, Mottet D, Schweighofer N, Froger J. Innovative technologies applied to sensorimotor rehabilitation after stroke. Ann Phys Rehabil Med. 2014 Nov; 57(8):543-51. PMID: 25261273.
        View in: PubMed
      13. Sargent B, Schweighofer N, Kubo M, Fetters L. Infant exploratory learning: influence on leg joint coordination. PLoS One. 2014; 9(3):e91500. PMID: 24626202.
        View in: PubMed
      14. Schweighofer N, Lang EJ, Kawato M. Role of the olivo-cerebellar complex in motor learning and control. Front Neural Circuits. 2013; 7:94. PMID: 23754983.
        View in: PubMed
      15. Onizuka M, Hoang H, Kawato M, Tokuda IT, Schweighofer N, Katori Y, Aihara K, Lang EJ, Toyama K. Solution to the inverse problem of estimating gap-junctional and inhibitory conductance in inferior olive neurons from spike trains by network model simulation. Neural Netw. 2013 Nov; 47:51-63. PMID: 23428796.
        View in: PubMed
      16. Han CE, Kim S, Chen S, Lai YH, Lee JY, Osu R, Winstein CJ, Schweighofer N. Quantifying arm nonuse in individuals poststroke. Neurorehabil Neural Repair. 2013 Jun; 27(5):439-47. PMID: 23353185.
        View in: PubMed
      17. Tokuda IT, Hoang H, Schweighofer N, Kawato M. Adaptive coupling of inferior olive neurons in cerebellar learning. Neural Netw. 2013 Nov; 47:42-50. PMID: 23337637.
        View in: PubMed
      18. Chen S, Lewthwaite R, Schweighofer N, Winstein CJ. Discriminant validity of a new measure of self-efficacy for reaching movements after stroke-induced hemiparesis. J Hand Ther. 2013 Apr-Jun; 26(2):116-22; quiz 123. PMID: 23123014.
        View in: PubMed
      19. Schweighofer N, Choi Y, Winstein C, Gordon J. Task-oriented rehabilitation robotics. Am J Phys Med Rehabil. 2012 Nov; 91(11 Suppl 3):S270-9. PMID: 23080042.
        View in: PubMed
      20. Hidaka Y, Han CE, Wolf SL, Winstein CJ, Schweighofer N. Use It and Improve It or Lose It: Interactions between Arm Function and Use in Humans Post-stroke. PLoS Comput Biol. 2012 Feb; 8(2):e1002343. PMID: 22761551.
        View in: PubMed
      21. Demoto Y, Okada G, Okamoto Y, Kunisato Y, Aoyama S, Onoda K, Munakata A, Nomura M, Tanaka SC, Schweighofer N, Doya K, Yamawaki S. Neural and personality correlates of individual differences related to the effects of acute tryptophan depletion on future reward evaluation. Neuropsychobiology. 2012; 65(2):55-64. PMID: 22222380.
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      22. Schweighofer N, Lee JY, Goh HT, Choi Y, Kim SS, Stewart JC, Lewthwaite R, Winstein CJ. Mechanisms of the contextual interference effect in individuals poststroke. J Neurophysiol. 2011 Nov; 106(5):2632-41. PMID: 21832031.
        View in: PubMed
      23. Choi Y, Gordon J, Park H, Schweighofer N. Feasibility of the adaptive and automatic presentation of tasks (ADAPT) system for rehabilitation of upper extremity function post-stroke. J Neuroeng Rehabil. 2011; 8:42. PMID: 21813010.
        View in: PubMed
      24. Onoda K, Okamoto Y, Kunisato Y, Aoyama S, Shishida K, Okada G, Tanaka SC, Schweighofer N, Yamaguchi S, Doya K, Yamawaki S. Inter-individual discount factor differences in reward prediction are topographically associated with caudate activation. Exp Brain Res. 2011 Aug; 212(4):593-601. PMID: 21695536.
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      25. Kawato M, Kuroda S, Schweighofer N. Cerebellar supervised learning revisited: biophysical modeling and degrees-of-freedom control. Curr Opin Neurobiol. 2011 Oct; 21(5):791-800. PMID: 21665461.
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      26. Frey SH, Fogassi L, Grafton S, Picard N, Rothwell JC, Schweighofer N, Corbetta M, Fitzpatrick SM. Neurological principles and rehabilitation of action disorders: computation, anatomy, and physiology (CAP) model. Neurorehabil Neural Repair. 2011 Jun; 25(5 Suppl):6S-20S. PMID: 21613534.
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      27. Abe M, Schambra H, Wassermann EM, Luckenbaugh D, Schweighofer N, Cohen LG. Reward improves long-term retention of a motor memory through induction of offline memory gains. Curr Biol. 2011 Apr 12; 21(7):557-62. PMID: 21419628.
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      28. Qi F, Schweighofer N. Including prior knowledge for accurate and fast motor threshold estimation. Brain Stimul. 2011 Jan; 4(1):60-1. PMID: 21255758.
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      29. Qi F, Wu AD, Schweighofer N. Fast estimation of transcranial magnetic stimulation motor threshold. Brain Stimul. 2011 Jan; 4(1):50-7. PMID: 21255756.
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      30. Gentili R, Han CE, Schweighofer N, Papaxanthis C. Motor learning without doing: trial-by-trial improvement in motor performance during mental training. J Neurophysiol. 2010 Aug; 104(2):774-83. PMID: 20538766.
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      31. Tokuda IT, Han CE, Aihara K, Kawato M, Schweighofer N. The role of chaotic resonance in cerebellar learning. Neural Netw. 2010 Sep; 23(7):836-42. PMID: 20494551.
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      32. Callan DE, Schweighofer N. Neural correlates of the spacing effect in explicit verbal semantic encoding support the deficient-processing theory. Hum Brain Mapp. 2010 Apr; 31(4):645-59. PMID: 19882649.
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      33. Tanaka SC, Shishida K, Schweighofer N, Okamoto Y, Yamawaki S, Doya K. Serotonin affects association of aversive outcomes to past actions. J Neurosci. 2009 Dec 16; 29(50):15669-74. PMID: 20016081.
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      34. Schweighofer N, Han CE, Wolf SL, Arbib MA, Winstein CJ. 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. Phys Ther. 2009 Dec; 89(12):1327-36. PMID: 19797304.
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      35. Lee JY, Schweighofer N. Dual adaptation supports a parallel architecture of motor memory. J Neurosci. 2009 Aug 19; 29(33):10396-404. PMID: 19692614.
        View in: PubMed
      36. Han CE, Arbib MA, Schweighofer N. Stroke rehabilitation reaches a threshold. PLoS Comput Biol. 2008; 4(8):e1000133. PMID: 18769588.
        View in: PubMed
      37. Choi Y, Qi F, Gordon J, Schweighofer N. Performance-based adaptive schedules enhance motor learning. J Mot Behav. 2008 Jul; 40(4):273-80. PMID: 18628104.
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      38. Schweighofer N, Bertin M, Shishida K, Okamoto Y, Tanaka SC, Yamawaki S, Doya K. Low-serotonin levels increase delayed reward discounting in humans. J Neurosci. 2008 Apr 23; 28(17):4528-32. PMID: 18434531.
        View in: PubMed
      39. Callan DE, Schweighofer N. Positive and negative modulation of word learning by reward anticipation. Hum Brain Mapp. 2008 Feb; 29(2):237-49. PMID: 17390317.
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      40. Tanaka SC, Schweighofer N, Asahi S, Shishida K, Okamoto Y, Yamawaki S, Doya K. Serotonin differentially regulates short- and long-term prediction of rewards in the ventral and dorsal striatum. PLoS One. 2007; 2(12):e1333. PMID: 18091999.
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      41. Bertin M, Schweighofer N, Doya K. Multiple model-based reinforcement learning explains dopamine neuronal activity. Neural Netw. 2007 Aug; 20(6):668-75. PMID: 17611074.
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      42. Schweighofer N, Tanaka SC, Doya K. Serotonin and the evaluation of future rewards: theory, experiments, and possible neural mechanisms. Ann N Y Acad Sci. 2007 May; 1104:289-300. PMID: 17360806.
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      43. Schweighofer N, Shishida K, Han CE, Okamoto Y, Tanaka SC, Yamawaki S, Doya K. Humans can adopt optimal discounting strategy under real-time constraints. PLoS Comput Biol. 2006 Nov 10; 2(11):e152. PMID: 17096592.
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      44. Pozzo T, Papaxanthis C, Petit JL, Schweighofer N, Stucchi N. Kinematic features of movement tunes perception and action coupling. Behav Brain Res. 2006 Apr 25; 169(1):75-82. PMID: 16430976.
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      45. Schaal S, Schweighofer N. Computational motor control in humans and robots. Curr Opin Neurobiol. 2005 Dec; 15(6):675-82. PMID: 16271466.
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      46. Schweighofer N, Doya K, Fukai H, Chiron JV, Furukawa T, Kawato M. Chaos may enhance information transmission in the inferior olive. Proc Natl Acad Sci U S A. 2004 Mar 30; 101(13):4655-60. PMID: 15070773.
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      47. Schweighofer N, Doya K, Kuroda S. Cerebellar aminergic neuromodulation: towards a functional understanding. Brain Res Brain Res Rev. 2004 Mar; 44(2-3):103-16. PMID: 15003388.
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      48. Schweighofer N, Doya K. Meta-learning in reinforcement learning. Neural Netw. 2003 Jan; 16(1):5-9. PMID: 12576101.
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      49. Kuroda S, Schweighofer N, Kawato M. Exploration of signal transduction pathways in cerebellar long-term depression by kinetic simulation. J Neurosci. 2001 Aug 1; 21(15):5693-702. PMID: 11466441.
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      50. Schweighofer N, Doya K, Lay F. Unsupervised learning of granule cell sparse codes enhances cerebellar adaptive control. Neuroscience. 2001; 103(1):35-50. PMID: 11311786.
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      51. Schweighofer N, Ferriol G. Diffusion of nitric oxide can facilitate cerebellar learning: A simulation study. Proc Natl Acad Sci U S A. 2000 Sep 12; 97(19):10661-5. PMID: 10984547.
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      52. Spoelstra J, Schweighofer N, Arbib MA. Cerebellar learning of accurate predictive control for fast-reaching movements. Biol Cybern. 2000 Apr; 82(4):321-33. PMID: 10804064.
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      53. Schweighofer N, Doya K, Kawato M. Electrophysiological properties of inferior olive neurons: A compartmental model. J Neurophysiol. 1999 Aug; 82(2):804-17. PMID: 10444678.
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      54. Schweighofer N. A model of activity-dependent formation of cerebellar microzones. Biol Cybern. 1998 Aug; 79(2):97-107. PMID: 9791930.
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      55. Schweighofer N, Spoelstra J, Arbib MA, Kawato M. Role of the cerebellum in reaching movements in humans. II. A neural model of the intermediate cerebellum. Eur J Neurosci. 1998 Jan; 10(1):95-105. PMID: 9753117.
        View in: PubMed
      56. Schweighofer N, Arbib MA. A model of cerebellar metaplasticity. Learn Mem. 1998 Jan-Feb; 4(5):421-8. PMID: 10701881.
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      57. Schweighofer N, Arbib MA, Kawato M. Role of the cerebellum in reaching movements in humans. I. Distributed inverse dynamics control. Eur J Neurosci. 1998 Jan; 10(1):86-94. PMID: 9753116.
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      58. Schweighofer N, Arbib MA, Dominey PF. A model of the cerebellum in adaptive control of saccadic gain. I. The model and its biological substrate. Biol Cybern. 1996 Jul; 75(1):19-28. PMID: 8765653.
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      59. Schweighofer N, Arbib MA, Dominey PF. A model of the cerebellum in adaptive control of saccadic gain. II. Simulation results. Biol Cybern. 1996 Jul; 75(1):29-36. PMID: 8765654.
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