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A sensory source for motor variation

Author

Listed:
  • Leslie C. Osborne

    (Sloan-Swartz Center for Theoretical Neurobiology, W. M. Keck Foundation Center for Integrative Neuroscience, Department of Physiology)

  • Stephen G. Lisberger

    (Sloan-Swartz Center for Theoretical Neurobiology, W. M. Keck Foundation Center for Integrative Neuroscience, Department of Physiology
    University of California at San Francisco)

  • William Bialek

    (Princeton University)

Abstract

Suppose that the variability in our movements1,2,3,4,5,6,7,8,9 is caused not by noise in the motor system itself, nor by fluctuations in our intentions or plans, but rather by errors in our sensory estimates of the external parameters that define the appropriate action. For tasks in which precision is at a premium, performance would be optimal if no noise were added in movement planning and execution: motor output would be as accurate as possible given the quality of sensory inputs. Here we use visually guided smooth-pursuit eye movements in primates10 as a testing ground for this notion of optimality. In response to repeated presentations of identical target motions, nearly 92% of the variance in eye trajectory can be accounted for as a consequence of errors in sensory estimates of the speed, direction and timing of target motion, plus a small background noise that is observed both during eye movements and during fixations. The magnitudes of the inferred sensory errors agree with the observed thresholds for sensory discrimination by perceptual systems, suggesting that the very different neural processes of perception and action are limited by the same sources of noise.

Suggested Citation

  • Leslie C. Osborne & Stephen G. Lisberger & William Bialek, 2005. "A sensory source for motor variation," Nature, Nature, vol. 437(7057), pages 412-416, September.
    • Handle: RePEc:nat:nature:v:437:y:2005:i:7057:d:10.1038_nature03961
    DOI: 10.1038/nature03961
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    Citations

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    Cited by:

    1. Seth W. Egger & Stephen G. Lisberger, 2022. "Neural structure of a sensory decoder for motor control," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    2. Joseph A Lombardo & Matthew V Macellaio & Bing Liu & Stephanie E Palmer & Leslie C Osborne, 2018. "State dependence of stimulus-induced variability tuning in macaque MT," PLOS Computational Biology, Public Library of Science, vol. 14(10), pages 1-28, October.
    3. Dagmar Sternad & Masaki O Abe & Xiaogang Hu & Hermann Müller, 2011. "Neuromotor Noise, Error Tolerance and Velocity-Dependent Costs in Skilled Performance," PLOS Computational Biology, Public Library of Science, vol. 7(9), pages 1-15, September.
    4. Joby John & Jonathan B Dingwell & Joseph P Cusumano, 2016. "Error Correction and the Structure of Inter-Trial Fluctuations in a Redundant Movement Task," PLOS Computational Biology, Public Library of Science, vol. 12(9), pages 1-30, September.
    5. Kang He & You Liang & Farnaz Abdollahi & Moria Fisher Bittmann & Konrad Kording & Kunlin Wei, 2016. "The Statistical Determinants of the Speed of Motor Learning," PLOS Computational Biology, Public Library of Science, vol. 12(9), pages 1-20, September.
    6. Paolo Tommasino & Antonella Maselli & Domenico Campolo & Francesco Lacquaniti & Andrea d’Avella, 2021. "A Hessian-based decomposition characterizes how performance in complex motor skills depends on individual strategy and variability," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-32, June.
    7. Greg J Stephens & Bethany Johnson-Kerner & William Bialek & William S Ryu, 2008. "Dimensionality and Dynamics in the Behavior of C. elegans," PLOS Computational Biology, Public Library of Science, vol. 4(4), pages 1-10, April.
    8. Kenta Tominaga & André Lee & Eckart Altenmüller & Fumio Miyazaki & Shinichi Furuya, 2016. "Kinematic Origins of Motor Inconsistency in Expert Pianists," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-15, August.
    9. Jonathan B Dingwell & Joby John & Joseph P Cusumano, 2010. "Do Humans Optimally Exploit Redundancy to Control Step Variability in Walking?," PLOS Computational Biology, Public Library of Science, vol. 6(7), pages 1-15, July.
    10. Caroline Haimerl & Douglas A. Ruff & Marlene R. Cohen & Cristina Savin & Eero P. Simoncelli, 2023. "Targeted V1 comodulation supports task-adaptive sensory decisions," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    11. John Porrill & Paul Dean, 2008. "Silent Synapses, LTP, and the Indirect Parallel-Fibre Pathway: Computational Consequences of Optimal Cerebellar Noise-Processing," PLOS Computational Biology, Public Library of Science, vol. 4(5), pages 1-9, May.
    12. Alexander Maye & Chih-hao Hsieh & George Sugihara & Björn Brembs, 2007. "Order in Spontaneous Behavior," PLOS ONE, Public Library of Science, vol. 2(5), pages 1-14, May.
    13. Biyu J He & John M Zempel, 2013. "Average Is Optimal: An Inverted-U Relationship between Trial-to-Trial Brain Activity and Behavioral Performance," PLOS Computational Biology, Public Library of Science, vol. 9(11), pages 1-14, November.

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