A simulation study of the degrees of freedom of movement in reaching and grasping.

The question of independently controlled components in the act of reaching and grasping has attracted interest experimentally and theoretically. Data from 35 studies were recently found consistent with simulated kinematic finger and thumb trajectories optimised for minimum jerk. The present study closely reproduces those trajectories using a discrete-time model based on minimum acceleration. That model was further used to generate two-dimensional trajectories for finger and thumb to reach and grasp an elliptical object with varying position and/or orientation. Orthogonalisation of these four trajectories revealed one degree of freedom when direction of reach was constant and two degrees of freedom when direction of reach varied, irrespective of object distance and orientation. These simulations indicate that reach and grasp movements contain redundancy that is removable by formation of task-dependent synergies. As skilled movement can be planned and executed in a low dimension workspace, control of these independent components lessens central workload.

[1]  David W. Clarke,et al.  Generalized predictive control - Part I. The basic algorithm , 1987, Autom..

[2]  D. Glencross,et al.  Motor control and sensory motor integration : issues and directions , 1995 .

[3]  C. MacKenzie,et al.  The speed-accuracy trade-off in manual prehension: effects of movement amplitude, object size and object width on kinematic characteristics , 2004, Experimental Brain Research.

[4]  M. A. Goodale,et al.  Factors affecting higher-order movement planning: a kinematic analysis of human prehension , 2004, Experimental Brain Research.

[5]  Peter D. Neilson,et al.  A neuroengineering solution to the optimal tracking problem , 1999 .

[6]  K. J. W. Craik.  Theory of the human operator in control systems; the operator as an engineering system. , 1947 .

[7]  Howard N. Zelaznik,et al.  Advances in Motor Learning and Control , 1996 .

[8]  P D Neilson,et al.  The problem of redundancy in movement control: The adaptive model theory approach , 1993, Psychological research.

[9]  M. Jeannerod.  Visuomotor channels: Their integration in goal-directed prehension , 1999 .

[10]  M. Jeannerod,et al.  Selective perturbation of visual input during prehension movements , 1991, Experimental Brain Research.

[11]  V. Mountcastle,et al.  An organizing principle for cerebral function : the unit module and the distributed system , 1978 .

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

[13]  M. Jeannerod.  The timing of natural prehension movements. , 1984, Journal of motor behavior.

[14]  J. S. Barlow.  The mindful brain: B.M. Edelman and V.B. Mountcastle (MIT Press, Cambridge, Mass., 1978, 100 p., U.S. $ 10.00) , 1979 .

[15]  S. Chieffi,et al.  Coordination between the transport and the grasp components during prehension movements , 2004, Experimental Brain Research.

[16]  C. Darian‐Smith,et al.  Thalamic projections to sensorimotor cortex in the newborn macaque , 1990, The Journal of comparative neurology.

[17]  V. Mountcastle.  The columnar organization of the neocortex. , 1997, Brain : a journal of neurology.

[18]  Annette Ostling,et al.  Reliable short-term memory in the trion model: toward a cortical language and grammar , 2001, Biological Cybernetics.

[19]  B. Bergum,et al.  Attention and performance IX , 1982 .

[20]  Weiping Li,et al.  Applied Nonlinear Control , 1991 .

[21]  William Anthony Sparrow,et al.  Energetics of human activity , 2000 .

[22]  David N. Lee,et al.  A Theory of Visual Control of Braking Based on Information about Time-to-Collision , 1976, Perception.

[23]  Michael A. Arbib,et al.  Perceptual Structures and Distributed Motor Control , 1981 .

[24]  Hanspeter A. Mallot,et al.  On Information Processing in the Cat’s Visual Cortex , 1986 .

[25]  Rodney M. J. Cotterill.  Computer simulation in brain science: Contents , 1988 .

[26]  V. Mountcastle.  Perceptual Neuroscience: The Cerebral Cortex , 1998 .

[27]  H. Zelaznik,et al.  Motor-output variability: a theory for the accuracy of rapid motor acts. , 1979, Psychological review.

[28]  Katsuhiko Ogata,et al.  Discrete-time control systems , 1987 .

[29]  M. Jeannerod,et al.  Influence of object position and size on human prehension movements , 1997, Experimental Brain Research.

[30]  T. Flash,et al.  The coordination of arm movements: an experimentally confirmed mathematical model , 1985, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[31]  K. J. Craik.  THEORY OF THE HUMAN OPERATOR IN CONTROL SYSTEMS , 1948 .

[32]  E. Brenner,et al.  A new view on grasping. , 1999, Motor control.

[33]  A. Isidori.  Nonlinear Control Systems , 1985 .

[34]  V. Braitenberg.  Two Views of the Cerebral Cortex , 1986 .

[35]  E. C. Poulton,et al.  Tracking skill and manual control , 1974 .

[36]  Peter D. Neilson,et al.  Neural mechanisms for control of multivariable, redundant, nonlinear musculoskeletal systems , 2001, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).

[37]  J. R. Hughes,et al.  Cerebral cortex. Vol. 2. Functional properties of cortical cells , 1985 .

[38]  B. Noble.  Applied Linear Algebra , 1969 .

[39]  J. Summers.  Approaches to the study of motor control and learning , 1992 .

[40]  Susan Eitelman,et al.  Matlab Version 6.5 Release 13. The MathWorks, Inc., 3 Apple Hill Dr., Natick, MA 01760-2098; 508/647-7000, Fax 508/647-7001, www.mathworks.com , 2003 .

[41]  M. Jeannerod.  Intersegmental coordination during reaching at natural visual objects , 1981 .

[42]  Gordon L. Shaw,et al.  Computer simulation in brain science: Simulations of the trion model and the search for the code of higher cortical processing , 1988 .

[43]  P D Neilson,et al.  Influence of intermittency and synergy on grasping. , 1999, Motor control.