Differences in Adaptation Rates after Virtual Surgeries Provide Direct Evidence for Modularity

Whether the nervous system relies on modularity to simplify acquisition and control of complex motor skills remains controversial. To date, evidence for modularity has been indirect, based on statistical regularities in the motor commands captured by muscle synergies. Here we provide direct evidence by testing the prediction that in a truly modular controller it must be harder to adapt to perturbations that are incompatible with the modules. We investigated a reaching task in which human subjects used myoelectric control to move a mass in a virtual environment. In this environment we could perturb the normal muscle-to-force mapping, as in a complex surgical rearrangement of the tendons, by altering the mapping between recorded muscle activity and simulated force applied on the mass. After identifying muscle synergies, we performed two types of virtual surgeries. After compatible virtual surgeries, a full range of movements could still be achieved recombining the synergies, whereas after incompatible virtual surgeries, new or modified synergies would be required. Adaptation rates after the two types of surgery were compared. If synergies were only a parsimonious description of the regularities in the muscle patterns generated by a nonmodular controller, we would expect adaptation rates to be similar, as both types of surgeries could be compensated with similar changes in the muscle patterns. In contrast, as predicted by modularity, we found strikingly faster adaptation after compatible surgeries than after incompatible ones. These results indicate that muscle synergies are key elements of a modular architecture underlying motor control and adaptation.

[1]  Emilio Bizzi,et al.  Combinations of muscle synergies in the construction of a natural motor behavior , 2003, Nature Neuroscience.

[2]  E. Bizzi,et al.  Article history: , 2005 .

[3]  Gary C. Sing,et al.  Primitives for Motor Adaptation Reflect Correlated Neural Tuning to Position and Velocity , 2009, Neuron.

[4]  Andrea d'Avella,et al.  Modularity for Sensorimotor Control: Evidence and a New Prediction , 2010, Journal of motor behavior.

[5]  Reza Shadmehr,et al.  Quantifying Generalization from Trial-by-Trial Behavior of Adaptive Systems that Learn with Basis Functions: Theory and Experiments in Human Motor Control , 2003, The Journal of Neuroscience.

[6]  Francesco Lacquaniti,et al.  Patterned control of human locomotion , 2012, The Journal of physiology.

[7]  M. Tresch,et al.  The case for and against muscle synergies , 2022 .

[8]  A. Jackson,et al.  Flexible Cortical Control of Task-Specific Muscle Synergies , 2012, The Journal of Neuroscience.

[9]  R. Gentner,et al.  Encoding of Motor Skill in the Corticomuscular System of Musicians , 2010, Current Biology.

[10]  J. Krakauer,et al.  Error correction, sensory prediction, and adaptation in motor control. , 2010, Annual review of neuroscience.

[11]  Seyed A Safavynia,et al.  Muscle Synergies: Implications for Clinical Evaluation and Rehabilitation of Movement. , 2011, Topics in spinal cord injury rehabilitation.

[12]  Ferdinando A Mussa-Ivaldi,et al.  Remapping hand movements in a novel geometrical environment. , 2005, Journal of neurophysiology.

[13]  Joseph Classen,et al.  Modular Organization of Finger Movements by the Human Central Nervous System , 2006, Neuron.

[14]  E. Bizzi,et al.  Stability of muscle synergies for voluntary actions after cortical stroke in humans , 2009, Proceedings of the National Academy of Sciences.

[15]  J. Krakauer,et al.  Human sensorimotor learning: adaptation, skill, and beyond , 2011, Current Opinion in Neurobiology.

[16]  Lena H Ting,et al.  Neuromechanics of muscle synergies for posture and movement , 2007, Current Opinion in Neurobiology.

[17]  E. Bizzi,et al.  The construction of movement by the spinal cord , 1999, Nature Neuroscience.

[18]  Gerald E Loeb,et al.  Virtual biomechanics: a new method for online reconstruction of force from EMG recordings. , 2012, Journal of neurophysiology.

[19]  D. Wolpert,et al.  Principles of sensorimotor learning , 2011, Nature Reviews Neuroscience.

[20]  Euljoon Park,et al.  Adaptive filtering of the electromyographic signal for prosthetic control and force estimation , 1995, IEEE Transactions on Biomedical Engineering.

[21]  Ethan R. Buch,et al.  Noninvasive cortical stimulation enhances motor skill acquisition over multiple days through an effect on consolidation , 2009, Proceedings of the National Academy of Sciences.

[22]  Francesco Lacquaniti,et al.  Control of reaching movements by muscle synergy combinations , 2013, Front. Comput. Neurosci..

[23]  H. Sebastian Seung,et al.  Learning the parts of objects by non-negative matrix factorization , 1999, Nature.

[24]  Francesco Lacquaniti,et al.  Modulation of phasic and tonic muscle synergies with reaching direction and speed. , 2008, Journal of neurophysiology.

[25]  R. Ivry,et al.  An Explicit Strategy Prevails When the Cerebellum Fails to Compute Movement Errors , 2010, The Cerebellum.

[26]  Daniel A. Braun,et al.  Motor Task Variation Induces Structural Learning , 2009, Current Biology.

[27]  A. d’Avella,et al.  Locomotor Primitives in Newborn Babies and Their Development , 2011, Science.

[28]  C Ghez,et al.  Learning of Visuomotor Transformations for Vectorial Planning of Reaching Trajectories , 2000, The Journal of Neuroscience.

[29]  S. Giszter,et al.  Modular Premotor Drives and Unit Bursts as Primitives for Frog Motor Behaviors , 2004, The Journal of Neuroscience.

[30]  Lena H. Ting,et al.  Optimization of Muscle Activity for Task-Level Goals Predicts Complex Changes in Limb Forces across Biomechanical Contexts , 2012, PLoS Comput. Biol..

[31]  P. Strick,et al.  Muscle representation in the macaque motor cortex: an anatomical perspective. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[32]  Lena H Ting,et al.  A limited set of muscle synergies for force control during a postural task. , 2005, Journal of neurophysiology.

[33]  Simon A. Overduin,et al.  Microstimulation Activates a Handful of Muscle Synergies , 2012, Neuron.

[34]  Nicholas G Hatsopoulos,et al.  The science of neural interface systems. , 2009, Annual review of neuroscience.

[35]  J. Krakauer,et al.  A computational neuroanatomy for motor control , 2008, Experimental Brain Research.

[36]  W. Kargo,et al.  Early Skill Learning Is Expressed through Selection and Tuning of Cortically Represented Muscle Synergies , 2003, The Journal of Neuroscience.

[37]  F. Lacquaniti,et al.  Five basic muscle activation patterns account for muscle activity during human locomotion , 2004, The Journal of physiology.

[38]  Anthony Jarc,et al.  Simplified and effective motor control based on muscle synergies to exploit musculoskeletal dynamics , 2009, Proceedings of the National Academy of Sciences.

[39]  N. A. Bernshteĭn The co-ordination and regulation of movements , 1967 .

[40]  R. Shadmehr,et al.  Interacting Adaptive Processes with Different Timescales Underlie Short-Term Motor Learning , 2006, PLoS biology.

[41]  Francisco J. Valero Cuevas,et al.  Challenges and New Approaches to Proving the Existence of Muscle Synergies of Neural Origin , 2012, PLoS Comput. Biol..

[42]  P. Celnik,et al.  Dissociating the roles of the cerebellum and motor cortex during adaptive learning: the motor cortex retains what the cerebellum learns. , 2011, Cerebral cortex.

[43]  F A Mussa-Ivaldi,et al.  Adaptive representation of dynamics during learning of a motor task , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[44]  E. Todorov Optimality principles in sensorimotor control , 2004, Nature Neuroscience.

[45]  Simon A. Overduin,et al.  Modulation of Muscle Synergy Recruitment in Primate Grasping , 2008, The Journal of Neuroscience.

[46]  E. Bizzi,et al.  Muscle synergy patterns as physiological markers of motor cortical damage , 2012, Proceedings of the National Academy of Sciences.

[47]  W. T. Thach,et al.  Throwing while looking through prisms. II. Specificity and storage of multiple gaze-throw calibrations. , 1996, Brain : a journal of neurology.

[48]  Reza Shadmehr,et al.  Learning of action through adaptive combination of motor primitives , 2000, Nature.

[49]  Francesco Lacquaniti,et al.  Control of Fast-Reaching Movements by Muscle Synergy Combinations , 2006, The Journal of Neuroscience.

[50]  L. Ting,et al.  Muscle synergies characterizing human postural responses. , 2007, Journal of neurophysiology.

[51]  Aymar de Rugy,et al.  Muscle Coordination Is Habitual Rather than Optimal , 2012, The Journal of Neuroscience.