Letter | Published:

Corticostriatal plasticity is necessary for learning intentional neuroprosthetic skills

Nature volume 483, pages 331335 (15 March 2012) | Download Citation

Abstract

The ability to learn new skills and perfect them with practice applies not only to physical skills but also to abstract skills1, like motor planning or neuroprosthetic actions. Although plasticity in corticostriatal circuits has been implicated in learning physical skills2,3,4, it remains unclear if similar circuits or processes are required for abstract skill learning. Here we use a novel behavioural task in rodents to investigate the role of corticostriatal plasticity in abstract skill learning. Rodents learned to control the pitch of an auditory cursor to reach one of two targets by modulating activity in primary motor cortex irrespective of physical movement. Degradation of the relation between action and outcome, as well as sensory-specific devaluation and omission tests, demonstrate that these learned neuroprosthetic actions are intentional and goal-directed, rather than habitual. Striatal neurons change their activity with learning, with more neurons modulating their activity in relation to target-reaching as learning progresses. Concomitantly, strong relations between the activity of neurons in motor cortex and the striatum emerge. Specific deletion of striatal NMDA receptors impairs the development of this corticostriatal plasticity, and disrupts the ability to learn neuroprosthetic skills. These results suggest that corticostriatal plasticity is necessary for abstract skill learning, and that neuroprosthetic movements capitalize on the neural circuitry involved in natural motor learning.

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References

  1. 1.

    Cognitive skill acquisition. Annu. Rev. Neurosci. 47, 513–539 (1996)

  2. 2.

    et al. Dynamic reorganization of striatal circuits during the acquisition and consolidation of a skill. Nature Neurosci. 12, 333–341 (2009)

  3. 3.

    , , , & Activity of striatal neurons reflects dynamic encoding and recoding of procedural memories. Nature 437, 1158–1161 (2005)

  4. 4.

    & Dynamic encoding of action selection by the medial striatum. J. Neurosci. 29, 3148–3159 (2009)

  5. 5.

    , & Consolidation in human motor memory. Nature 382, 252–255 (1996)

  6. 6.

    Volitional control of neural activity: implications for brain–computer interfaces. J. Physiol. (Lond.) 579, 571–579 (2007)

  7. 7.

    et al. Parallel neural networks for learning sequential procedures. Trends Neurosci. 22, 464–471 (1999)

  8. 8.

    & Comparison of learning-related neuronal activity in the dorsal premotor cortex and striatum. Eur. J. Neurosci. 19, 721–740 (2004)

  9. 9.

    , & Learning-induced LTP in neocortex. Science 290, 533–536 (2000)

  10. 10.

    , & Cognitive neurophysiology of the motor cortex. Science 260, 47–52 (1993)

  11. 11.

    , , , & Cortical correlates of learning in monkeys adapting to a new dynamical environment. Proc. Natl Acad. Sci. USA 97, 2259–2263 (2000)

  12. 12.

    & Distinct roles of the anterior cingulate and prefrontal cortex in the acquisition and performance of a cognitive skill. Proc. Natl Acad. Sci. USA 103, 12941–12946 (2006)

  13. 13.

    , & Frontal cortex and the discovery of abstract action rules. Neuron 66, 315–326 (2010)

  14. 14.

    , & Direct cortical control of 3D neuroprosthetic devices. Science 296, 1829–1832 (2002)

  15. 15.

    et al. Learning to control a brain-machine interface for reaching and grasping by primates. PLoS Biol. 1, 193–208 (2003)

  16. 16.

    & Emergence of a stable cortical map for neuroprosthetic control. PLoS Biol. 7, e1000153 (2009)

  17. 17.

    , , & Reversible large-scale modification of cortical networks during neuroprosthetic control. Nature Neurosci. 14, 662–667 (2011)

  18. 18.

    , , & Dynamic functional changes associated with cognitive skill learning of an adapted version of the Tower of London task. Neuroimage 20, 1649–1660 (2003)

  19. 19.

    , , & Striatal activation during acquisition of a cognitive skill. Neuropsychology 13, 564–574 (1999)

  20. 20.

    & Different time courses of learning-related activity in the prefrontal cortex and striatum. Nature 433, 873–876 (2005)

  21. 21.

    et al. The acquisition of skilled motor performance: fast and slow experience-driven changes in primary motor cortex. Proc. Natl Acad. Sci. USA 95, 861–868 (1998)

  22. 22.

    , , & Investigating neural correlates of behavior in freely behaving rodents using inertial sensors. J. Neurophysiol. 104, 569–575 (2010)

  23. 23.

    & Goal-directed instrumental action: contingency and incentive learning and their cortical substrates. Neuropharmacology 37, 407–419 (1998)

  24. 24.

    , & Inactivation of dorsolateral striatum enhances sensitivity to changes in the action-outcome contingency in instrumental conditioning. Behav. Brain Res. 166, 189–196 (2006)

  25. 25.

    , , & Endocannabinoid signaling is critical for habit formation. Front. Integr. Neurosci. 1, 1–12 (2007)

  26. 26.

    , & Differential corticostriatal plasticity during fast and slow motor skill learning in mice. Curr. Biol. 14, 1124–1134 (2004)

  27. 27.

    & Start/stop signals emerge in nigrostriatal circuits during sequence learning. Nature 466, 457–462 (2010)

  28. 28.

    , & Differential activation of monkey striatal neurons in the early and late stages of procedural learning. Exp. Brain Res. 146, 122–126 (2002)

  29. 29.

    , , & Long-term potentiation in the striatum is unmasked by removing the voltage-dependent magnesium block of NMDA receptor channels. Eur. J. Neurosci. 4, 929–935 (1992)

  30. 30.

    et al. Disrupted motor learning and long-term synaptic plasticity in mice lacking NMDAR1 in the striatum. Proc. Natl Acad. Sci. USA 103, 15254–15259 (2006)

Download references

Acknowledgements

We thank S. Venkatraman for the three-axis accelerometer, Y. Li for the RGS9L-Cre mice, K. Nakazawa for the NMDAR1-loxP mice, G. Luo for genotyping, M. Davis for advice on staining and G. Martins for performing immunohistochemistry. This work was supported by National Science Foundation CAREER Award 0954243, the Multiscale Systems Research Center and the Defense Advanced Research Projects Agency contract N66001-10-C-2008 to J.M.C., and the Division of Intramural Clinical and Basic Research of the National Institute on Alcohol Abuse and Alcoholism, Marie Curie International Reintegration Grant 239527 and European Research Council STG 243393 to R.M.C.

Author information

Author notes

    • Aaron C. Koralek
    •  & Xin Jin

    These authors contributed equally to this work.

Affiliations

  1. Helen Wills Neuroscience Institute, University of California, Berkeley, California 94720, USA

    • Aaron C. Koralek
    • , John D. Long II
    •  & Jose M. Carmena
  2. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California 94720, USA

    • Jose M. Carmena
  3. Program in Cognitive Science, University of California, Berkeley, California 94720, USA

    • Jose M. Carmena
  4. UC Berkeley and UC San Francisco Joint Graduate Group in Bioengineering, University of California, Berkeley, California 94720, USA

    • Jose M. Carmena
  5. Laboratory for Integrative Neuroscience, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, 5625 Fishers Lane, Bethesda, Maryland 20892-9412, USA

    • Xin Jin
    •  & Rui M. Costa
  6. Champalimaud Neuroscience Programme, Champalimaud Center for the Unknown, Avenida de Brasília, 1400-038 Lisbon, Portugal

    • Rui M. Costa

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Contributions

A.C.K., X.J., J.D.L., R.M.C. and J.M.C. designed experiments. A.C.K., X.J. and J.D.L. conducted experiments. A.C.K., X.J., R.M.C. and J.M.C. analysed data and wrote the paper.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Rui M. Costa or Jose M. Carmena.

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    This file contains Supplementary Methods, Supplementary References and Supplementary Figures 1-13.

Videos

  1. 1.

    Supplementary Movie 1

    This file shows an example of locomotor activity for a control mouse with electrode implantation and used in the BMI experiments.

  2. 2.

    Supplementary Movie 2

    This file shows an example of locomotor activity for a RGS9L-Cre/Nr1f/fmouse with electrode implantation and used in the BMI experiments.

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DOI

https://doi.org/10.1038/nature10845

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