Neural population dynamics during reaching

  • Nature volume 487, pages 5156 (05 July 2012)
  • doi:10.1038/nature11129
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Most theories of motor cortex have assumed that neural activity represents movement parameters. This view derives from what is known about primary visual cortex, where neural activity represents patterns of light. Yet it is unclear how well the analogy between motor and visual cortex holds. Single-neuron responses in motor cortex are complex, and there is marked disagreement regarding which movement parameters are represented. A better analogy might be with other motor systems, where a common principle is rhythmic neural activity. Here we find that motor cortex responses during reaching contain a brief but strong oscillatory component, something quite unexpected for a non-periodic behaviour. Oscillation amplitude and phase followed naturally from the preparatory state, suggesting a mechanistic role for preparatory neural activity. These results demonstrate an unexpected yet surprisingly simple structure in the population response. This underlying structure explains many of the confusing features of individual neural responses.

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  1. 1.

    An enduring map of the motor cortex. Exp. Physiol. 93, 798–802 (2008)

  2. 2.

    Relation of pyramidal tract activity to force exerted during voluntary movement. J. Neurophysiol. 31, 14–27 (1968)

  3. 3.

    Do neurons in the motor cortex encode movement direction? An alternative hypothesis. Neurosci. Lett. 91, 106–111 (1988)

  4. 4.

    Are movement parameters recognizably coded in the activity of single neurons? Behav. Brain Sci. 15, 679–690 (1992)

  5. 5.

    Theoretical considerations for the analysis of population coding in motor cortex. Neural Comput. 6, 29–37 (1994)

  6. 6.

    Direct cortical control of muscle activation in voluntary arm movements: a model. Nature Neurosci. 3, 391–398 (2000)

  7. 7.

    Encoding in the motor cortex: was Evarts right after all? Focus on “motor cortex neural correlates of output kinematics and kinetics during isometric-force and arm-reaching tasks”. J. Neurophysiol. 94, 2261–2262 (2005)

  8. 8.

    Inconvenient truths about neural processing in primary motor cortex. J. Physiol. (Lond.) 586, 1217–1224 (2008)

  9. 9.

    , & Control of muscle synergies by cortical ensembles. Adv. Exp. Med. Biol. 629, 179–199 (2009)

  10. 10.

    & Relationship between unconstrained arm movements and single-neuron firing in the macaque motor cortex. J. Neurosci. 27, 2760–2780 (2007)

  11. 11.

    From intention to action: motor cortex and the control of reaching movements. Adv. Exp. Med. Biol. 629, 139–178 (2009)

  12. 12.

    , & Neuronal population coding of movement direction. Science 233, 1416–1419 (1986)

  13. 13.

    , & Muscle and movement representations in the primary motor cortex. Science 285, 2136–2139 (1999)

  14. 14.

    & Temporal complexity and heterogeneity of single-neuron activity in premotor and motor cortex. J. Neurophysiol. 97, 4235–4257 (2007)

  15. 15.

    , , , & Cortical preparatory activity: representation of movement or first cog in a dynamical machine? Neuron 68, 387–400 (2010)

  16. 16.

    & Optimal feedback control as a theory of motor coordination. Nature Neurosci. 5, 1226–1235 (2002)

  17. 17.

    New insights into motor cortex. Neuron 71, 387–388 (2011)

  18. 18.

    , & Preparatory activity in premotor and motor cortex reflects the speed of the upcoming reach. J. Neurophysiol. 96, 3130–3146 (2006)

  19. 19.

    Preparing for speed. Focus on: “preparatory activity in premotor and motor cortex reflects the speed of the upcoming reach”. J. Neurophysiol. 96, 2842–2843 (2006)

  20. 20.

    & Visuomotor coordination in reaching and locomotion. Science 245, 1209–1210 (1989)

  21. 21.

    Biological pattern generation: the cellular and computational logic of networks in motion. Neuron 52, 751–766 (2006)

  22. 22.

    & How the brain generates movement. Neural Comput. 24, 289–331 (2011)

  23. 23.

    & Rhythmic swimming activity in neurones of the isolated nerve cord of the leech. J. Exp. Biol. 65, 643–668 (1976)

  24. 24.

    & Imaging dedicated and multifunctional neural circuits generating distinct behaviors. J. Neurosci. 26, 10925–10933 (2006)

  25. 25.

    , & Optical imaging of neuronal populations during decision-making. Science 307, 896–901 (2005)

  26. 26.

    , , & in Progress in Brain Research: Enhancing Performance for Action and Perception (eds , , & ) (Elsevier, 2011)

  27. 27.

    & Motor cortical representation of speed and direction during reaching. J. Neurophysiol. 82, 2676–2692 (1999)

  28. 28.

    & Covariation of primate dorsal premotor cell activity with direction and amplitude during a memorized-delay reaching task. J. Neurophysiol. 84, 152–165 (2000)

  29. 29.

    et al. Roles of monkey premotor neuron classes in movement preparation and execution. J. Neurophysiol. 104, 799–810 (2010)

  30. 30.

    , & Motor cortex neural correlates of output kinematics and kinetics during isometric-force and arm-reaching tasks. J. Neurophysiol. 94, 2353–2378 (2005)

  31. 31.

    I of the Vortex (MIT Press, 2002)

  32. 32.

    , , & The cortex as a central pattern generator. Nature Rev. Neurosci. 6, 477–483 (2005)

  33. 33.

    , & Sequential activation of motor cortical neurons contributes to intralimb coordination during reaching in the cat by modulating muscle synergies. J. Neurophysiol. 105, 388–409 (2011)

  34. 34.

    & Basal ganglia and cerebellar loops: motor and cognitive circuits. Brain Res. Brain Res. Rev. 31, 236–250 (2000)

  35. 35.

    , , & Differential dynamics of activity changes in dorsolateral and dorsomedial striatal loops during learning. Neuron 66, 781–795 (2010)

  36. 36.

    , & Comparison of neural responses in primary motor cortex to transient and continuous loads during posture. J. Neurophysiol. 101, 150–163 (2008)

  37. 37.

    & Generating coherent patterns of activity from chaotic neural networks. Neuron 63, 544–557 (2009)

  38. 38.

    Optimal feedback control and the neural basis of volitional motor control. Nature Rev. Neurosci. 5, 532–546 (2004)

  39. 39.

    , , , & Autonomous head-mounted electrophysiology systems for freely behaving primates. Curr. Opin. Neurobiol. 20, 676–686 (2010)

  40. 40.

    et al. in Proc. of the 5th International IEEE EMBS Conference on Neural Engineering 613–615 (IEEE, 2011)

  41. 41.

    et al. A high-rate long-range wireless transmission system for simultaneous multichannel neural recording applications. IEEE Trans. Biomed. Circ. Syst. 4, 181–191 (2010)

  42. 42.

    , , , & Neural variability in premotor cortex provides a signature of motor preparation. J. Neurosci. 26, 3697–3712 (2006)

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We are deeply grateful to K. Briggman and W. Kristan for providing data recorded from the leech. We thank M. Risch for animal care, S. Eisensee for administrative support, and D. Haven and B. Oskotsky for information technology support. We thank Z. Ghahramani and C. Rasmussen for discussion of jPCA and related methods. We thank D. Sussillo, S. Grossman and M. Sahani for analysis suggestions and commentary on the manuscript. This work was supported by a Helen Hay Whitney postdoctoral fellowship and National Institutes of Health (NIH) postdoctoral training fellowship (M.M.C.), the Burroughs Wellcome Fund Career Awards in the Biomedical Sciences (M.M.C., K.V.S.), Engineering and Physical Sciences Research Council grant EP/H019472/1 and the McDonnell Center (J.P.C.), a National Science Foundation graduate research fellowship (M.T.K.), a Texas Instruments Stanford Graduate Fellowship (J.D.F.), a Paul and Daisy Soros Fellowship (P.N.), the Stanford Medical Scientist Training Program (P.N.), and these awards to K.V.S.: NIH Director’s Pioneer Award (1DP1OD006409), NIH NINDS EUREKA Award (R01-NS066311), NIH NINDS BRP (R01-NS064318), NIH NINDS CRCNS (R01-NS054283), DARPA-DSO REPAIR (N66001-10-C-2010), Stanford Center for Integrated Systems, NSF Center for Neuromorphic Systems Engineering at Caltech, Office of Naval Research, and the Whitaker Foundation, the McKnight Foundation, the Sloan Foundation and the Weston Havens Foundation.

Author information

Author notes

    • Mark M. Churchland
    •  & John P. Cunningham

    These authors contributed equally to this work.


  1. Department of Neuroscience, Kavli Institute for Brain Science, David Mahoney Center, Columbia University Medical Center, New York, New York 10032, USA

    • Mark M. Churchland
  2. Department of Electrical Engineering, Stanford University, Stanford, California 94305, USA

    • Mark M. Churchland
    • , Matthew T. Kaufman
    • , Justin D. Foster
    • , Stephen I. Ryu
    •  & Krishna V. Shenoy
  3. Neurosciences Program, Stanford University, Stanford, California 94305, USA

    • Mark M. Churchland
    • , Matthew T. Kaufman
    •  & Krishna V. Shenoy
  4. Department of Biomedical Engineering, Washington University in St Louis, St Louis, Missouri 63130, USA

    • John P. Cunningham
  5. Department of Engineering, University of Cambridge, Cambridge CB2 1PZ, UK

    • John P. Cunningham
  6. Department of Bioengineering, Stanford University, Stanford, California 94705, USA

    • Paul Nuyujukian
    •  & Krishna V. Shenoy
  7. Stanford University School of Medicine, Stanford, California 94305, USA

    • Paul Nuyujukian
  8. Department of Neurosurgery, Palo Alto Medical Foundation, Palo Alto, California 94301, USA

    • Stephen I. Ryu
  9. Department of Neurobiology, Stanford University School of Medicine, Stanford, California 94305, USA

    • Krishna V. Shenoy


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The jPCA method was designed by J.P.C. and M.M.C. M.M.C. and M.T.K. collected data from the reaching monkeys. J.D.F. and P.N. collected data from the walking monkey. S.I.R. led the array implantation surgeries. K.V.S. contributed to all aspects of the work. All authors discussed the results and commented on the analyses and manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Mark M. Churchland.

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    This file contains Supplementary Figures 1-11, Supplementary Text and Data, legends for Supplementary Movies 1-5 and additional references.


  1. 1.

    Supplementary Movie 1

    This move shows the neural trajectory in the walking monkey (2× real time) - see Supplementary Information file for full legend.

  2. 2.

    Supplementary Movie 2

    This movie Illustrates how the PCA axes were rotated to find the jPCA projection - see Supplementary Information file for full legend.

  3. 3.

    Supplementary Movie 3

    This movie shows the jPCA projections as a function of time - see Supplementary Information file for full legend.

  4. 4.

    Supplementary Movie 4

    This movie shows the jPCA projections as a function of time after applying the shuffle control - see Supplementary Information file for full legend.

  5. 5.

    Supplementary Movie 5

    This movie shows the jPCA projections as a function of time for populations of muscle recordings - see Supplementary Information file for full legend.


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