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Neural population dynamics during reaching

Abstract

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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Figure 1: Oscillation of neural firing rates during three movement types.
Figure 2: Firing rate versus time for ten example neurons, highlighting the multiphasic response patterns.
Figure 3: Projections of the neural population response.
Figure 4: Projections of simulated neural and muscle populations.
Figure 5: Illustration of how a simple model generates fits to EMG using a pair of brief rotations.
Figure 6: Consistency of rotational dynamics for real and simulated data.

References

  1. 1

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

    ADS  CAS  Article  Google Scholar 

  2. 2

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

    CAS  Article  Google Scholar 

  3. 3

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

    CAS  Article  Google Scholar 

  4. 4

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

    Google Scholar 

  5. 5

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

    Article  Google Scholar 

  6. 6

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

    CAS  Article  Google Scholar 

  7. 7

    Hatsopoulos, N. G. 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)

    Article  Google Scholar 

  8. 8

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

    CAS  Article  Google Scholar 

  9. 9

    Morrow, M. M., Pohlmeyer, E. A. & Miller, L. E. Control of muscle synergies by cortical ensembles . Adv. Exp. Med. Biol. 629, 179–199 (2009)

    Article  Google Scholar 

  10. 10

    Aflalo, T. N. & Graziano, M. S. A. Relationship between unconstrained arm movements and single-neuron firing in the macaque motor cortex. J. Neurosci. 27, 2760–2780 (2007)

    CAS  Article  Google Scholar 

  11. 11

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

    Article  Google Scholar 

  12. 12

    Georgopoulos, A. P., Schwartz, A. B. & Kettner, R. E. Neuronal population coding of movement direction. Science 233, 1416–1419 (1986)

    ADS  CAS  Article  Google Scholar 

  13. 13

    Kakei, S., Hoffman, D. S. & Strick, P. L. Muscle and movement representations in the primary motor cortex. Science 285, 2136–2139 (1999)

    CAS  Article  Google Scholar 

  14. 14

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

    Article  Google Scholar 

  15. 15

    Churchland, M. M., Cunningham, J. P., Kaufman, M. T., Ryu, S. I. & Shenoy, K. V. Cortical preparatory activity: representation of movement or first cog in a dynamical machine? Neuron 68, 387–400 (2010)

    CAS  Article  Google Scholar 

  16. 16

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

    CAS  Article  Google Scholar 

  17. 17

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

    CAS  Article  Google Scholar 

  18. 18

    Churchland, M. M., Santhanam, G. & Shenoy, K. V. Preparatory activity in premotor and motor cortex reflects the speed of the upcoming reach. J. Neurophysiol. 96, 3130–3146 (2006)

    Article  Google Scholar 

  19. 19

    Cisek, P. 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)

    Article  Google Scholar 

  20. 20

    Georgopoulos, A. P. & Grillner, S. Visuomotor coordination in reaching and locomotion. Science 245, 1209–1210 (1989)

    ADS  CAS  Article  Google Scholar 

  21. 21

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

    CAS  Article  Google Scholar 

  22. 22

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

    MathSciNet  Article  Google Scholar 

  23. 23

    Kristan, W. B., Jr & Calabrese, R. L. Rhythmic swimming activity in neurones of the isolated nerve cord of the leech. J. Exp. Biol. 65, 643–668 (1976)

    PubMed  Google Scholar 

  24. 24

    Briggman, K. L. & Kristan, W. B., Jr Imaging dedicated and multifunctional neural circuits generating distinct behaviors. J. Neurosci. 26, 10925–10933 (2006)

    CAS  Article  Google Scholar 

  25. 25

    Briggman, K. L., Abarbanel, H. D. & Kristan, W. B., Jr Optical imaging of neuronal populations during decision-making. Science 307, 896–901 (2005)

    ADS  CAS  Article  Google Scholar 

  26. 26

    Shenoy, K. V., Kaufman, M. T., Sahani, M. & Churchland, M. M. in Progress in Brain Research: Enhancing Performance for Action and Perception (eds Green, A., Chapman, E., Kalaska, J. F. & Lepore, F. ) (Elsevier, 2011)

    Google Scholar 

  27. 27

    Moran, D. W. & Schwartz, A. B. Motor cortical representation of speed and direction during reaching. J. Neurophysiol. 82, 2676–2692 (1999)

    CAS  Article  Google Scholar 

  28. 28

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

    CAS  Article  Google Scholar 

  29. 29

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

    Article  Google Scholar 

  30. 30

    Sergio, L. E., Hamel-Paquet, C. & Kalaska, J. F. Motor cortex neural correlates of output kinematics and kinetics during isometric-force and arm-reaching tasks. J. Neurophysiol. 94, 2353–2378 (2005)

    Article  Google Scholar 

  31. 31

    Llinas, R. I of the Vortex (MIT Press, 2002)

    Google Scholar 

  32. 32

    Yuste, R., MacLean, J. N., Smith, J. & Lansner, A. The cortex as a central pattern generator. Nature Rev. Neurosci. 6, 477–483 (2005)

    CAS  Article  Google Scholar 

  33. 33

    Yakovenko, S., Krouchev, N. & Drew, T. 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)

    Article  Google Scholar 

  34. 34

    Middleton, F. A. & Strick, P. L. Basal ganglia and cerebellar loops: motor and cognitive circuits. Brain Res. Brain Res. Rev. 31, 236–250 (2000)

    CAS  Article  Google Scholar 

  35. 35

    Thorn, C. A., Atallah, H., Howe, M. & Graybiel, A. M. Differential dynamics of activity changes in dorsolateral and dorsomedial striatal loops during learning. Neuron 66, 781–795 (2010)

    CAS  Article  Google Scholar 

  36. 36

    Herter, T. M., Korbel, T. & Scott, S. H. Comparison of neural responses in primary motor cortex to transient and continuous loads during posture. J. Neurophysiol. 101, 150–163 (2008)

    Article  Google Scholar 

  37. 37

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

    CAS  Article  Google Scholar 

  38. 38

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

    CAS  Article  Google Scholar 

  39. 39

    Gilja, V., Chestek, C. A., Nuyujukian, P., Foster, J. D. & Shenoy, K. V. Autonomous head-mounted electrophysiology systems for freely behaving primates. Curr. Opin. Neurobiol. 20, 676–686 (2010)

    CAS  Article  Google Scholar 

  40. 40

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

    Google Scholar 

  41. 41

    Miranda, H. 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)

    Article  Google Scholar 

  42. 42

    Churchland, M. M., Yu, B. M., Ryu, S. I., Santhanam, G. & Shenoy, K. V. Neural variability in premotor cortex provides a signature of motor preparation. J. Neurosci. 26, 3697–3712 (2006)

    CAS  Article  Google Scholar 

Download references

Acknowledgements

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.

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Authors

Contributions

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.

Corresponding author

Correspondence to Mark M. Churchland.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Information

This file contains Supplementary Figures 1-11, Supplementary Text and Data, legends for Supplementary Movies 1-5 and additional references. (PDF 2272 kb)

Supplementary Movie 1

This move shows the neural trajectory in the walking monkey (2× real time) - see Supplementary Information file for full legend. (MOV 367 kb)

Supplementary Movie 2

This movie Illustrates how the PCA axes were rotated to find the jPCA projection - see Supplementary Information file for full legend. (MOV 3066 kb)

Supplementary Movie 3

This movie shows the jPCA projections as a function of time - see Supplementary Information file for full legend. (MOV 2378 kb)

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. (MOV 1793 kb)

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. (MOV 1150 kb)

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Churchland, M., Cunningham, J., Kaufman, M. et al. Neural population dynamics during reaching. Nature 487, 51–56 (2012). https://doi.org/10.1038/nature11129

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