Review Article | Published:

Optimal feedback control and the neural basis of volitional motor control

Nature Reviews Neuroscience volume 5, pages 532546 (2004) | Download Citation

Subjects

Abstract

Skilled motor behaviour, from the graceful leap of a ballerina to a precise pitch by a baseball player, appears effortless but reflects an intimate interaction between the complex mechanical properties of the body and control by a highly distributed circuit in the CNS. An important challenge for understanding motor function is to connect these three levels of the motor system — motor behaviour, limb mechanics and neural control. Optimal feedback control theory might provide the important link across these levels of the motor system and help to unravel how the primary motor cortex and other regions of the brain plan and control movement.

Key points

  • The motor system can be considered at three levels: motor behaviour, limb mechanics and neural control. Although our understanding at each level continues to grow, linking these levels into a cohesive framework is an important challenge for neuroscientists.

  • The peripheral motor system is a complex filter that converts patterns of muscle activity into movements. This conversion depends on the properties of muscle, multi-joint mechanics with uncoupled joint motion and muscular torque, as well as environmental forces acting on the limbs.

  • Despite these complexities, body movements are smooth and graceful. For example, hand trajectories during reaching movements are fairly straight, and hand velocity follows a smooth, bell-shaped profile. The motor system compensates for the complexities of limb mechanics, and also can adapt to perceptual or mechanical perturbations. There is considerable noise in the motor system, which is reflected in trial-to-trial variability, but task-relevant features are less variable.

  • Motor control involves the spinal cord, brainstem and cerebral cortex. Neurophysiological studies of motor control often involve recording the activity of neurons in different brain regions and relating such activity to aspects of sensorimotor function.

  • Such recordings indicate that neural activity in primary motor cortex (M1) correlates with hand direction, speed and distance of movement. However, theoretical studies have shown that such correlations can arise even if neurons code other details such as muscle activity or joint motion. There is also evidence that M1 behaves like or forms part of an inverse internal model that converts spatial goals or trajectories into detailed motor patterns.

  • Optimal feedback control might provide a link between the different levels of motor control. An optimal feedback controller uses an optimal estimate of the state of the system, generated through sensory feedback and efferent copy, and uses this feedback to adjust its output towards a specific goal. 'Errors' are corrected only if they adversely affect motor performance.

  • This control theory is consistent with a number of features of motor behaviour and of neural processing in M1. For example, the activity of M1 neurons varies depending on the behavioural context, and M1 receives a rich mix of sensory inputs.

  • Although the mathematics to compute an optimal feedback controller are quite complex, such controllers provide an important bridge to link limb mechanics, motor behaviour and the neural basis of motor control.As a theory, optimal feedback control generates a number of neurophysiological questions on how such a controller is created by the highly distributed circuitry involved in sensorimotor function.

  • Subscribe to Nature Reviews Neuroscience for full access:

    $265

    Subscribe

Additional access options:

Already a subscriber?  Log in  now or  Register  for online access.

References

  1. 1.

    Role of motor cortex in coordinating multi-joint movements: is it time for a new paradigm? Can. J. Physiol. Pharmacol. 78, 923–933 (2000).

  2. 2.

    The heat of shortening and the dynamic constants of muscle. Proc. R. Soc. Lond. B 126, 136–195 (1938).

  3. 3.

    , & The variation in isometric tension with sarcomere length in vertebrate muscle fibres. J. Physiol. (Lond.) 184, 170–192 (1966).

  4. 4.

    , , & Physiological types and histochemical profiles in motor units of the cat gastrocnemius. J. Physiol. (Lond.) 234, 723–748 (1973).

  5. 5.

    , & Mechanics of feline soleus: I. effect of fascicle length and velocity on force output. J. Muscle Res. Cell Motil. 17, 207–219 (1996).

  6. 6.

    , & Virtual muscle: a computational approach to understanding the effects of muscle properties on motor control. J. Neurosci. Methods 101, 117–130 (2000).

  7. 7.

    Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control. Crit. Rev. Biomed. Eng. 17, 359–411 (1989).

  8. 8.

    in Exercise and Sport Sciences Reviews (ed. Pandolf, K. B.) 89–137 (Williams & Wilkins, Baltimore, 1989).

  9. 9.

    & Morphometry of Macaca mulatta forelimb. I. Shoulder and elbow muscles and segment inertial parameters. J. Morphol. 245, 206–224 (2000).

  10. 10.

    , , & Morphometry of Macaca mulatta forelimb. II. Fiber-type composition in shoulder and elbow muscles. J. Morphol. 251, 323–332 (2002).

  11. 11.

    & Morphometry of Macaca mulatta forelimb. III. Moment arm of shoulder and elbow muscles. J. Morphol. 255, 301–314 (2003).

  12. 12.

    & Dynamic interactions between limb segments during planar arm movement. Biol. Cybern. 44, 67–77 (1982).

  13. 13.

    & in Exercise and Sport Sciences Reviews (ed. Pandolf, K. B.) 187–230 (Williams & Wilkins, Baltimore, 1989).

  14. 14.

    , & Neural, mechanical, and geometric factors subserving arm posture in humans. J. Neurosci. 5, 2732–2743 (1985).

  15. 15.

    et al. Kinematics and kinetics of multi-joint reaching in non-human primates. J. Neurophysiol. 89, 2667–2677 (2003).

  16. 16.

    , & Tension distribution to the five digits of the hand by neuromuscular compartments in the macaque flexor digitorum profundus. J. Neurosci. 21, 2150–2158 (2001).

  17. 17.

    , & Towards a realistic biomechanical model of the thumb: the choice of kinematic description may be more critical than the solution method or the variability/uncertainty of musculoskeletal parameters. J. Biomech. 36, 1019–1030 (2003).

  18. 18.

    in Dynamic Models of Motor Planning (ed. Culicover, P.) 192–198 (Nature Publishing Group, London, 2002).

  19. 19.

    Spatial control of arm movements. Exp. Brain Res. 42, 223–227 (1981).

  20. 20.

    & The coordination of arm movements: an experimentally confirmed mathematical model. J. Neurosci. 5, 1688–1703 (1985).

  21. 21.

    & Role of intrinsic muscle properties in producing smooth movements. IEEE Trans. Biomed. Eng. 44, 165–176 (1997).

  22. 22.

    & Stability properties of human reaching movements. Exp. Brain Res. 107, 125–136 (1995).

  23. 23.

    & Rapid adaptation to coriolis force perturbations of arm trajectory. J. Neurophysiol. 72, 299–313 (1994).

  24. 24.

    & Rapid adaptation to coriolis force perturbations of arm trajectory. J. Neurosci. 14, 3208–3224 (1994). References 23 and 24 are classic studies that illustrate how subjects modify motor commands to compensate for mechanical loads applied to the limb during reaching.

  25. 25.

    & Trajectory adaptation to a nonlinear visuomotor transformation: evidence of motion planning in visually perceived space. J. Neurophysiol. 74, 2174–2178 (1995).

  26. 26.

    , & Intersegmental dynamics are controlled by sequential anticipatory, error correction, and postural mechanisms. J. Neurophysiol. 81, 1045–1056 (1999).

  27. 27.

    , , & Prediction precedes control in motor learning. Curr. Biol. 13, 146–150 (2003).

  28. 28.

    & A motor learning strategy reflects neural circuitry for limb control. Nature Neurosci. 6, 399–403 (2003).

  29. 29.

    & The computation of position sense from spindles in mono- and multiarticular muscles. J. Neurosci. 14, 7529–7540 (1994).

  30. 30.

    & Signal-dependent noise determines motor planning. Nature 394, 780–784 (1998). This study illustrates how optimal strategies for minimizing signal-dependent noise lead to bell-shaped velocity profiles and relatively straight hand trajectories.

  31. 31.

    Human muscle spindle discharge during isometric voluntary contractions. Amplitude relations between spindle frequency and torque. Acta Physiol. Scand. 90, 319–336 (1974).

  32. 32.

    Kinematic and kinetic patterns in human gait: variability and compensating effects. Hum. Mov. Sci. 3, 51–76 (1984).

  33. 33.

    & Coordinate transformations in the control of cat posture. J. Neurophysiol. 72, 1496–1515 (1994).

  34. 34.

    & The uncontrolled manifold concept: identifying control variables for a functional task. Exp. Brain Res. 126, 289–306 (1999).

  35. 35.

    , & Identifying the control structure of multijoint coordination during pistol shooting. Exp. Brain Res. 135, 382–404 (2000).

  36. 36.

    , & The role of inertial sensitivity in motor planning. J. Neurosci. 18, 5948–5957 (1998).

  37. 37.

    & Bayesian integration in sensorimotor learning. Nature 427, 244–247 (2004).

  38. 38.

    & Optimal feedback control as a theory of motor coordination. Nature Neurosci. 5, 1226–1235 (2002). This study illustrates how optimal feedback control can predict many features of volitional motor control, including muscle synergies, motor coordination and variable but accurate movements.

  39. 39.

    Cosine tuning minimizes motor errors. Neural Comput. 14, 1233–1260 (2002).

  40. 40.

    , & The role of execution noise in movement variability. J. Neurophysiol. 91, 1050–1063 (2004).

  41. 41.

    & Comparison between macaques' and humans' kinematics of prehension: the role of morphological differences and control mechanisms. Behav. Brain Res. 131, 169–184 (2002).

  42. 42.

    & Cortical Function and Voluntary Movement (Clarendon, Oxford, 1993).

  43. 43.

    Functional organization of motor cortex and its participation in voluntary movements. Comp. Primate Biol. 4, 501–624 (1988).

  44. 44.

    , & The premotor cortex and nonstandard sensorimotor mapping. Can. J. Physiol. Pharmacol. 74, 469–482 (1996).

  45. 45.

    & Overlap of internal models in motor cortex for mechanical loads during reaching. Nature 417, 938–941 (2002).

  46. 46.

    , , Coding of modified body schema during tool use by macaque postcentral neurones. Neuroreport 7, 2325–2330 (1996). The first in a series of studies to show how neural activity related to the hand is modified when monkeys are trained to use a rake to retrieve food rewards.

  47. 47.

    , , & Premotor and parietal cortex: corticocortical connectivity and combinatorial computations. Annu. Rev. Neurosci. 20, 25–42 (1997).

  48. 48.

    , , & Multiple levels of representation of reaching in the parieto-frontal network. Cereb. Cortex 13, 1009–1022 (2003).

  49. 49.

    & The cortical motor system. Neuron 31, 889–901 (2001).

  50. 50.

    , , & Cortical control of reaching movements. Curr. Opin. Neurobiol. 7, 849–859 (1997).

  51. 51.

    Sequential organization of multiple movements: involvement of cortical motor areas. Annu. Rev. Neurosci. 24, 631–651 (2001).

  52. 52.

    & Effects of a primary motor cortex lesion on step-tracking movements of the wrist. J. Neurophysiol. 73, 891–895 (1995).

  53. 53.

    & Spinal cord terminations of the medial wall motor areas in macaque monkeys. J. Neurosci. 16, 6513–6525 (1996).

  54. 54.

    & Postspike facilitation of forelimb muscle activity by primate corticomotoneuronal cells. J. Neurophysiol. 44, 751–772 (1980).

  55. 55.

    , & Divergent projection of individual corticospinal axons to motoneurons of multiple muscles in the monkey. Neurosci. Lett. 23, 7–12 (1981).

  56. 56.

    , & Corticomotoneuronal synapses in the monkey: light microscopic localization upon motoneurons of intrinsic muscles of the hand. J. Comp. Neurol. 232, 499–510 (1985).

  57. 57.

    , , & Correlations between corticomotoneuronal (CM) cell postspike effects and cell-target muscle covariation. J. Neurophysiol. 83, 99–115 (2000).

  58. 58.

    & Variation in form of the pyramidal tract and its relationship to digital dexterity. Brain Behav. Evol. 12, 161–200 (1975).

  59. 59.

    , , & Striking differences in transmission of corticospinal excitation to upper limb motoneurons in two primate species. J. Neurophysiol. 84, 698–709 (2000).

  60. 60.

    , & Accuracy of planar reaching movements. I. Independence of direction and extent variability. Exp. Brain Res. 99, 97–111 (1994).

  61. 61.

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

  62. 62.

    & Moving in three-dimensional space: frames of reference, vectors, and coordinate systems. Annu. Rev. Neurosci. 15, 167–191 (1992).

  63. 63.

    & Cerebral cortical mechanisms of reaching movements. Science 255, 1517–1523 (1992).

  64. 64.

    , , & On the relations between the direction of two-dimensional arm movements and cell discharge in primate motor cortex. J. Neurosci. 2, 1527–1537 (1982).

  65. 65.

    , , & Spatial coding of movement: a hypothesis concerning the coding of movement directions by motor cortical populations. Exp. Brain Res. (Suppl.) 7, 327–336 (1983).

  66. 66.

    , , & Temporal encoding of movement kinematics in the discharge of primate primary motor and premotor neurons. J. Neurophysiol. 73, 836–854 (1995).

  67. 67.

    Motor cortical activity during drawing movements: population representation during sinusoid tracing. J. Neurophysiol. 70, 28–36 (1993).

  68. 68.

    , & Cortical mechanisms related to the direction of two-dimensional arm movements: relations in parietal area 5 and comparison with motor cortex. Exp. Brain Res. 51, 247–260 (1983).

  69. 69.

    , & Tactile activity in primate primary somatosensory cortex during active arm movements: correlation with receptive field properties. J. Neurophysiol. 71, 161–172 (1994).

  70. 70.

    , , , & Making arm movements within different parts of space: the premotor and motor cortical representation of a coordinate system for reaching to visual targets. J. Neurosci. 11, 1182–1197 (1991).

  71. 71.

    , & Comparison of cerebellar and motor cortex activity during reaching: directional tuning and response variability. J. Neurophysiol. 69, 1136–1149 (1993).

  72. 72.

    & Modulation of dorsal spinocerebellar responses to limb movement. II. Effect of sensory input. J. Neurophysiol. 90, 3372–3383 (2003).

  73. 73.

    , & Directional tuning of human forearm muscle afferents during voluntary wrist movements. J. Physiol. (Lond.) 536, 635–647 (2001).

  74. 74.

    , , & Proprioceptive population coding of limb position in humans. Exp. Brain Res. 149, 512–519 (2003).

  75. 75.

    , , & A comparison of movement direction-related versus load direction-related activity in primate motor cortex, using a two-dimensional reaching task. J. Neurosci. 9, 2080–2102 (1989).

  76. 76.

    & Reaching movements with similar hand paths but different arm orientations: I. Activity of individual cells in motor cortex. J. Neurophysiol. 77, 826–852 (1997).

  77. 77.

    Current issues in directional motor control. Trends Neurosci. 18, 506–510 (1995).

  78. 78.

    On the translation of directional motor cortical commands to activation of muscles via spinal interneuronal systems. Cogn. Brain Res. 3, 151–155 (1996).

  79. 79.

    , & The spinal frog takes into account the scheme of its body during the wiping reflex. Science 209, 1261–1263 (1980).

  80. 80.

    & Afferent roles in hind limb wipe-reflex trajectories: free-limb kinematics and motor patterns. J. Neurophysiol. 83, 1480–1501 (2000).

  81. 81.

    , & Combinations of muscle synergies in the construction of a natural motor behavior. Nature Neurosci. 6, 300–308 (2003).

  82. 82.

    & One motor cortex, two different views. Nature Neurosci. 3, 963–965 (2000).

  83. 83.

    & One motor cortex, two different views. Nature Neurosci. 3, 963–965 (2000).

  84. 84.

    Reply to 'One motor cortex, two different views'. Nature Neurosci. 3, 963–964 (2000).

  85. 85.

    Reply to 'One motor cortex, two different views'. Nature Neuroscience 3, 964–965 (2000).

  86. 86.

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

  87. 87.

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

  88. 88.

    Neural population codes. Curr. Opin. Neurobiol. 13, 238–249 (2003).

  89. 89.

    , , & Dissociation between hand motion and population vectors from neural activity in motor cortex. Nature 413, 161–165 (2001).

  90. 90.

    The role of primary motor cortex in goal-directed movements: insights from neurophysiological studies on non-human primates. Curr. Opin. Neurobiol. 13, 671–677 (2003).

  91. 91.

    , , & Is the cerebellum a smith predictor? J. Motor Behav. 25, 203–216 (1993).

  92. 92.

    & Computational approaches to motor control and their potential role for interpreting motor dysfunction. Curr. Opin. Neurol. 16, 693–698 (2003).

  93. 93.

    & Primary motor cortical neurons encode functional muscle synergies. Exp. Brain Res. 146, 233–243 (2002).

  94. 94.

    & Corticomotoneuronal contribution to the fractionation of muscle activity during precision grip in the monkey. J. Neurophysiol. 75, 1826–1842 (1996).

  95. 95.

    & Systematic changes in motor cortex cell activity with arm posture during directional isometric force generation. J. Neurophysiol. 89, 212–228 (2003).

  96. 96.

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

  97. 97.

    Premotor cortex: sensory cues and movement. Behav. Brain Res. 18, 175–185 (1985).

  98. 98.

    , & in Neural Programming (ed. Ito, M.) 13–24 (Karger, Basel, 1989).

  99. 99.

    & Differential effects of muscimol microinjection into dorsal and ventral aspects of the premotor cortex of monkeys. J. Neurophysiol. 71, 1151–1164 (1994).

  100. 100.

    & Reacquisition deficits in prism adaptation after muscimol microinjection into the ventral premotor cortex of monkeys. J. Neurophysiol. 81, 1927–1938 (1999).

  101. 101.

    , & The effects of cooling supplementary motor area and midline cerebral cortex on neuronal responses in area 4 of monkeys. Electroencephalogr. Clin. Neurophysiol. 85, 61–71 (1992).

  102. 102.

    The brainstem control of saccadic eye movements. Nature Rev. Neurosci. 3, 952–964 (2002).

  103. 103.

    , & The brainstem burst generator for saccadic eye movements: a modern synthesis. Exp. Brain Res. 142, 439–462 (2002).

  104. 104.

    in Basic Mechanisms of Ocular Motility and Their Clinical Implications (eds Lennerstand, G. & Bach-y-Rita, P.) 337–374 (Pergamon, Oxford, 1975).

  105. 105.

    & Central organization and modeling of eye-head coordination during orienting gaze shifts. Ann. NY Acad. Sci. 656, 452–471 (1992).

  106. 106.

    in Cerebral Motor Control in Man: Long Loop Mechanisms. (ed. Desmedt, J. E.) 193–215 (Karger, Basel, 1978).

  107. 107.

    Hard lessons in motor control from the mammalian spinal cord. Trends Neurosci. 10, 108–113 (1987).

  108. 108.

    & The origin and use of positional frames of reference in motor control. Behav. Brain Sci. 18, 724–807 (1995).

  109. 109.

    & The case for an internal dynamics model versus equilibrium point control in human movement. J. Physiol. (Lond.) 549, 953–963 (2003).

  110. 110.

    , & A self-organizing neural model of motor equivalent reaching and tool use by a multi-joint arm. J. Cogn. Neurosci. 5, 408–435 (1993).

  111. 111.

    , & A cortico-spinal model of reaching and proprioception under multiple task constraints. J. Cogn. Neurosci. 10, 425–444 (1998).

  112. 112.

    & Optimal muscular coordination strategies for jumping. J. Biomech. 24, 1–10 (1991).

  113. 113.

    , & Formation and control of optimal trajectory in human multijoint arm movement. Minimum torque-change model. Biol. Cybern. 61, 89–101 (1989).

  114. 114.

    & Models of trajectory formation and temporal interaction of reach and grasp. J. Motor Behav. 25, 175–192 (1993).

  115. 115.

    An organizing principle for a class of voluntary movements. J. Neurosci. 4, 2745–2754 (1984).

  116. 116.

    , & Experimentally confirmed mathematical model for human control of a non-rigid object. J. Neurophysiol. 91, 1158–1170 (2004). This study illustrates how the motor system calculates state variables not only related to body motion, but also related to motion of grasped non-rigid objects.

  117. 117.

    , & Feedback gains for correcting small perturbations to standing posture. IEEE Trans. Automatic Control 36, 322–332 (1991). One of the first examples of the use of optimal control methods to identify feedback gains, in this case, for spinal reflexes in the cat hindlimb.

  118. 118.

    An optimal control model for analyzing human postural balance. IEEE Trans. Biomed. Eng. 42, 87–101 (1995).

  119. 119.

    , , , & Optimality in human motor performance: ideal control of rapid aimed movements. Psychol. Rev. 95, 340–370 (1988).

  120. 120.

    & Fingertip contact influences human postural control. Exp. Brain Res. 100, 495–502 (1994).

  121. 121.

    Optimal Control and Estimation (Dover, New York, 1994).

  122. 122.

    , & An internal model for sensorimotor integration. Science 269, 1880–1882 (1995).

  123. 123.

    & Trajectory control in targeted force impulses. III. Compensatory adjustments for initial errors. Exp. Brain Res. 67, 253–269 (1987).

  124. 124.

    Proprioceptive regulation of locomotion. Curr. Opin. Neurobiol. 5, 786–791 (1995).

  125. 125.

    Population vectors and motor cortex: neural coding or epiphenomenon? Nature Neurosci. 3, 307–308 (2000).

  126. 126.

    & Orderly somatotopy in primary motor cortex: does it exist? Neuroimage 13, 968–974 (2001).

  127. 127.

    , , & Consistent features in the forelimb representation of primary motor cortex in rhesus macaques. J. Neurosci. 21, 2784–2792 (2001).

  128. 128.

    , & Neural activity in primary motor cortex related to mechanical loads applied to the shoulder and elbow during a postural task. J. Neurophysiol. 86, 2102–2108 (2001).

  129. 129.

    , , & Spatial organization of precentral cortex in awake primates. I. Somatosensory inputs. J. Neurophysiol. 41, 1107–1119 (1978).

  130. 130.

    Comparison of onset time and magnitude of activity for proximal arm muscles and motor cortical cells prior to reaching movements. J. Neurophysiol. 77, 1016–1022 (1997).

  131. 131.

    , & Sequential activation of neurons in primate motor cortex during unrestrained forelimb movement. J. Neurophysiol. 53, 435–445 (1985).

  132. 132.

    Functional properties of monkey motor cortex neurones receiving afferent input from the hand and fingers. J. Physiol. (Lond.) 311, 497–519 (1981).

  133. 133.

    & Sorting of somatosensory afferent information in primate motor cortex. Brain Res. 156, 364–368 (1978).

  134. 134.

    & Primary motor cortical activity related to the weight and texture of grasped objects in the monkey. J. Neurophysiol. 68, 1867–1881 (1992).

  135. 135.

    & Topographical localization in the motor cortex of the cat for somatic afferent responses and evoked movements. J. Physiol. (Lond.) 350, 33–54 (1984).

  136. 136.

    Correlations between task-related activity and responses to perturbation in primate sensorimotor cortex. J. Neurophysiol. 44, 1122–1138 (1980).

  137. 137.

    in Motor Control Mechanisms in Health and Disease (ed. Desmedt, J. E.) 329–345 (Raven, New York, 1983).

  138. 138.

    & Afferent input to movement-related precentral neurones in conscious monkeys. Proc. R. Soc. Lond. B 194, 313–339 (1976).

  139. 139.

    & in Cerebral Motor Control in Man: Long Loop Mechanisms (ed. Desmedt, J. E.) 178–192 (Karger, Basel, 1978).

  140. 140.

    The human stretch reflex and the motor cortex. Trends Neurosci. 14, 87–91 (1991).

  141. 141.

    & Quantitative evaluation of the electromyographic responses to multidirectional load perturbations of the human arm. J. Neurophysiol. 59, 1296–1313 (1988).

  142. 142.

    , , , & The central nervous system stabilizes unstable dynamics by learning optimal impedance. Nature 414, 446–449 (2001).

  143. 143.

    , & Learning the dynamics of reaching movements results in the modification of arm impedance and long-latency perturbation responses. Biol. Cybern. 85, 437–448 (2001).

  144. 144.

    , , & Effects of dentate cooling on precentral unit activity following torque pulse injections into elbow movements. Brain Res. 94, 237–251 (1975).

  145. 145.

    in Cerebral Motor Control in Man: Long Loop Mechanisms (ed. Desmedt, J. E) 123–140 (Karger, Basel, 1978).

  146. 146.

    , , & Dual nature of the precentral responses to limb perturbations revealed by cerebellar cooling. Brain Res. 117, 336–340 (1976).

  147. 147.

    The influence of motor preparation on the response of cerebellar neurons to limb displacements. J. Neurosci. 3, 2007–2020 (1983).

  148. 148.

    in Cerebral Motor Control in Man: Long Loop Mechanisms. (ed. Desmedt, J. E) 85–93 (Karger, Basel, 1978).

  149. 149.

    , , & Visual control of reaching movements without vision of the limb: II. Evidence of fast, unconscious processes correcting the trajectory of the hand to the final position of a double-step stimulus. Exp. Brain Res. 62, 303–311 (1986).

  150. 150.

    & Automatic control during hand reaching at undetected two-dimensional target displacements. J. Neurophysiol. 67, 455–469 (1992).

  151. 151.

    & Forward modeling allows feedback control for fast reaching movements. Trends Cogn. Sci. 4, 423–431 (2000).

  152. 152.

    & Neural correlates of a spatial sensory-to-motor transformation in primary motor cortex. J. Neurophysiol. 77, 1171–1194 (1997).

  153. 153.

    et al. Role of the posterior parietal cortex in updating reaching movements to a visual target. Nature Neurosci. 2, 563–567 (1999).

  154. 154.

    et al. A lesion of the posterior parietal cortex disrupts on-line adjustments during aiming movements. Neuropsychologia 40, 2471–2480 (2002).

  155. 155.

    Movement without proprioception. Brain Res. 71, 285–296 (1974).

  156. 156.

    , & Deafferentation in monkeys: pointing at a target without visual feedback. Exp. Neurol. 46, 178–186 (1975).

  157. 157.

    , , & Control of limb dynamics in normal subjects and patients without proprioception. J. Neurophysiol. 73, 820–835 (1995).

  158. 158.

    Cerebral Motor Control in Man: Long Loop Mechanisms (Karger, Basel, 1978).

  159. 159.

    & Anticipatory activity of motor cortex neurons in relation to direction of an intended movement. J. Neurophysiol. 39, 1062–1068 (1976).

  160. 160.

    & Primate spinal interneurons show pre-movement instructed delay activity. Nature 401, 590–594 (1999).

  161. 161.

    & Separate visual pathways for perception and action. Trends Neurosci. 15, 20–25 (1992).

  162. 162.

    & A common reference frame for movement plans in the posterior parietal cortex. Nature Rev. Neurosci. 3, 553–562 (2002).

  163. 163.

    & in The Handbook of Brain Theory and Neural Networks (ed. Arbib, M. A.) 945–948 (The MIT Press, Cambridge, 2003).

  164. 164.

    , & The cerebellum and the adaptive coordination of movement. Annu. Rev. Neurosci. 15, 403–442 (1992).

  165. 165.

    The Cerebellum and Neural Control (Raven, New York, 1984).

  166. 166.

    in The Handbook of Brain Theory and Neural Networks (ed. Arbib, M. A) 190–195 (The MIT Press, Cambridge, 2003).

  167. 167.

    , & Distributed motor commands in the limb premotor network. Trends Neurosci. 16, 27–33 (1993).

  168. 168.

    Cerebellar limb ataxia: abnormal control of self-generated and external forces. Ann. NY Acad. Sci. 978, 16–27 (2002).

  169. 169.

    & Multiple paired forward and inverse models for motor control. Neural Netw. 11, 1317–1329 (1998).

  170. 170.

    & An unfolded map of the cerebellar dentate nucleus and its projections to the cerebral cortex. J. Neurophysiol. 89, 634–639 (2003). The use of retrograde transneuronal labelling with herpes virus from injections in different areas of the cerebral cortex shows that the dentate nucleus contains anatomically separate regions for motor and non-motor domains.

  171. 171.

    & Cerebellar loops with motor cortex and prefrontal cortex of a nonhuman primate. J. Neurosci. 23, 8432–8444 (2003).

  172. 172.

    & Reflex and intended responses in motor cortex pyramidal tract neurons of monkey. J. Neurophysiol. 39, 1069–1080 (1976).

  173. 173.

    , & Sensory input to primate spinal cord is presynaptically inhibited during voluntary movement. Nature Neurosci. 6, 1309–1316 (2003).

  174. 174.

    , & A hierarchical foundation for models of sensorimotor control. Exp. Brain Res. 126, 1–18 (1999).

  175. 175.

    & Optimal control methods suitable for biomechanical systems. Proc. 25th Ann. Int. Conf. IEEE Eng. Biol. Med. Soc. 2, 1758–1761 (2003).

  176. 176.

    Vision (Freeman, San Francisco, 1982).

  177. 177.

    in The Handbook of Brain Theory and Neural Networks (ed. Arbib, M. A.) 968–972 (The MIT Press, Cambridge, 2003).

  178. 178.

    Internal models for motor control and trajectory planning. Curr. Opin. Neurobiol. 9, 718–727 (1999).

  179. 179.

    Complementary roles of basal ganglia and cerebellum in learning and motor control. Curr. Opin. Neurobiol. 10, 732–739 (2000).

  180. 180.

    Neocortical mechanisms in motor learning. Curr. Opin. Neurobiol. 13, 225–231 (2003).

  181. 181.

    , & Neuronal correlates of motor performance and motor learning in the primary motor cortex of monkeys adapting to an external force field. Neuron 30, 593–607 (2001).

  182. 182.

    , , , & Preparatory activity in motor cortex reflects learning of local visuomotor skills. Nature Neurosci. 6, 882–890 (2003).

  183. 183.

    , , & Changes in motor cortical activity during visuomotor adaptation. Exp. Brain Res. 121, 285–299 (1998).

  184. 184.

    in Handbook of Physiology Sec. 1 Vol. II (ed. Brooks, V. B.) 597–666 (American Physiological Society, Chicago, 1981).

  185. 185.

    & Organization of corticospinal neurons in the monkey. J. Comp. Neurol. 195, 339–365 (1981).

  186. 186.

    & Aspects of body self-calibration. Trends Cogn. Sci. 4, 279–288 (2000).

  187. 187.

    Optimal strategies for movement: success with variability. Nature Neurosci. 5, 1110–1111 (2002).

Download references

Acknowledgements

This research was supported by research grants from the Canadian Institutes of Health Research and the Natural Sciences and Engineering Research Council of Canada. I am also supported by a CIHR Investigator Award. I would also like to acknowledge expert technical support from K. Moore and J. Swaine, as well as constructive criticisms on this manuscript from P. K. Rose, D. P. Munoz, I. Kurtzer, T. Herter and other members of the CIHR Group in Sensorimotor Research.

Author information

Affiliations

  1. Department of Anatomy and Cell Biology, Centre for Neuroscience Studies, Queen's University, Kingston, Ontario K7L 3N6, Canada.  steve@biomed.queensu.ca

    • Stephen H. Scott

Authors

  1. Search for Stephen H. Scott in:

Competing interests

S.S. holds a US patent for a robotic device that is used to study limb motor function.

Glossary

MUSCULAR TORQUE

(or moment). Each muscle generates force from muscle contraction (active) and elastic forces (passive). Muscular torque for a muscle equals its total force multiplied by its moment arm (the perpendicular distance between a muscle's line of action and the joint centre of rotation).

EQUILIBRIUM POINT MODELS

A class of models that assume the CNS can control the equilibrium position established by the balance of force that is generated by the spring-like behaviour of muscle.

STATE VARIABLES

Estimates of the position of the limb or forces acting within or on the limb (or their derivative). State variables are transformed by corresponding feedback gains to generate motor output commands.

ALPHA MOTOR NEURON

Motor neurons that innervate extrafusal muscle fibres that generate force.

GAMMA MOTOR NEURON

Motor neurons that innervate intrafusal muscle fibres associated with muscle spindles.

About this article

Publication history

Published

DOI

https://doi.org/10.1038/nrn1427

Rights and permissions

To obtain permission to re-use content from this article visit RightsLink.