Timing of continuous motor imagery: the two-thirds power law originates in trajectory planning.

The two-thirds power law, v = γκ(-1/3), expresses a robust local relationship between the geometrical and temporal aspects of human movement, represented by curvature κ and speed v, with a piecewise constant γ. This law is equivalent to moving at a constant equi-affine speed and thus constitutes an important example of motor invariance. Whether this kinematic regularity reflects central planning or peripheral biomechanical effects has been strongly debated. Motor imagery, i.e., forming mental images of a motor action, allows unique access to the temporal structure of motor planning. Earlier studies have shown that imagined discrete movements obey Fitts's law and their durations are well correlated with those of actual movements. Hence, it is natural to examine whether the temporal properties of continuous imagined movements comply with the two-thirds power law. A novel experimental paradigm for recording sparse imagery data from a continuous cyclic tracing task was developed. Using the likelihood ratio test, we concluded that for most subjects the distributions of the marked positions describing the imagined trajectory were significantly better explained by the two-thirds power law than by a constant Euclidean speed or by two other power law models. With nonlinear regression, the β parameter values in a generalized power law, v = γκ(-β), were inferred from the marked position records. This resulted in highly variable yet mostly positive β values. Our results imply that imagined trajectories do follow the two-thirds power law. Our findings therefore support the conclusion that the coupling between velocity and curvature originates in centrally represented motion planning.

[1]  R. C. Oldfield The assessment and analysis of handedness: the Edinburgh inventory. , 1971, Neuropsychologia.

[2]  S. Blakemore,et al.  Action prediction in the cerebellum and in the parietal lobe , 2003, Experimental Brain Research.

[3]  M. A. Arbib,et al.  Models of Trajectory Formation and Temporal Interaction of Reach and Grasp. , 1993, Journal of motor behavior.

[4]  S. Schaal,et al.  Origins and violations of the 2/3 power law in rhythmic three-dimensional arm movements , 2000, Experimental Brain Research.

[5]  P. Viviani,et al.  The law relating the kinematic and figural aspects of drawing movements. , 1983, Acta psychologica.

[6]  Charalambos Papaxanthis,et al.  The influence of eye movements on the temporal features of executed and imagined arm movements , 2008, Brain Research.

[7]  J. Baron,et al.  Does motor imagery share neural networks with executed movement: a multivariate fMRI analysis , 2013, Front. Hum. Neurosci..

[8]  D. Ostry,et al.  Origins of the power law relation between movement velocity and curvature: modeling the effects of muscle mechanics and limb dynamics. , 1996, Journal of neurophysiology.

[9]  Eran Dayan,et al.  Alpha and Beta Band Event-Related Desynchronization Reflects Kinematic Regularities , 2015, The Journal of Neuroscience.

[10]  Alain Berthoz,et al.  Movement Timing and Invariance Arise from Several Geometries , 2009, PLoS Comput. Biol..

[11]  Craig Hall,et al.  The MIQ-RS: A Suitable Option for Examining Movement Imagery Ability , 2007, Evidence-based complementary and alternative medicine : eCAM.

[12]  M. Jeannerod Mental imagery in the motor context , 1995, Neuropsychologia.

[13]  D. Wolpert,et al.  Motor prediction , 2001, Current Biology.

[14]  P. Morasso,et al.  Trajectory formation and handwriting: A computational model , 1982, Biological Cybernetics.

[15]  Talma Hendler,et al.  Neural representations of kinematic laws of motion: Evidence for action-perception coupling , 2007, Proceedings of the National Academy of Sciences.

[16]  Paolo Viviani,et al.  Do Units of Motor Action Really Exist , 1986 .

[17]  Marco Schieppati,et al.  Imagined and actual arm movements have similar durations when performed under different conditions of direction and mass , 2002, Experimental Brain Research.

[18]  Olivier White,et al.  The Relation between Geometry and Time in Mental Actions , 2012, PloS one.

[19]  Tamar Flash,et al.  Motor primitives in vertebrates and invertebrates , 2005, Current Opinion in Neurobiology.

[20]  T. Flash,et al.  Velocity and curvature in human locomotion along complex curved paths: a comparison with hand movements , 2005, Experimental Brain Research.

[21]  Aymeric Guillot,et al.  Understanding the timing of motor imagery: recent findings and future directions , 2012 .

[22]  G. Sapiro,et al.  Constant Affine Velocity Predicts the 1 3 Power Law of Planar Motion Perception and Generation , 1997, Vision Research.

[23]  P Viviani,et al.  The Relationship between Curvature and Velocity in Two-Dimensional Smooth Pursuit Eye Movements , 1997, The Journal of Neuroscience.

[24]  A. Schwartz,et al.  Motor cortical activity during drawing movements: population representation during lemniscate tracing. , 1999, Journal of neurophysiology.

[25]  M. Erb,et al.  Activation of Cortical and Cerebellar Motor Areas during Executed and Imagined Hand Movements: An fMRI Study , 1999, Journal of Cognitive Neuroscience.

[26]  M. Jeannerod,et al.  Mentally simulated movements in virtual reality: does Fitt's law hold in motor imagery? , 1995, Behavioural Brain Research.

[27]  T. Flash,et al.  Minimum-jerk, two-thirds power law, and isochrony: converging approaches to movement planning. , 1995, Journal of experimental psychology. Human perception and performance.

[28]  Catalina Llanos,et al.  How similar are motor imagery and movement? , 2008, Behavioral neuroscience.

[29]  K. Reilly,et al.  Disentangling motor execution from motor imagery with the phantom limb. , 2012, Brain : a journal of neurology.

[30]  W. Helsen,et al.  The eyes as a mirror of our thoughts: Quantification of motor imagery of goal-directed movements through eye movement registration , 2008, Behavioural Brain Research.

[31]  Mark Chiew,et al.  Investigation of fMRI neurofeedback of differential primary motor cortex activity using kinesthetic motor imagery , 2012, NeuroImage.

[32]  Yoram Ben-Shaul,et al.  A Compact Representation of Drawing Movements with Sequences of Parabolic Primitives , 2009, PLoS Comput. Biol..

[33]  Catalina Llanos,et al.  The kinematics of motor imagery: Comparing the dynamics of real and virtual movements , 2009, Neuropsychologia.

[34]  R. J. van Beers,et al.  The role of execution noise in movement variability. , 2004, Journal of neurophysiology.

[35]  A. Vinter,et al.  Mental Representation of Arm Motion Dynamics in Children and Adolescents , 2013, PloS one.

[36]  Michael I. Jordan,et al.  Optimal feedback control as a theory of motor coordination , 2002, Nature Neuroscience.

[37]  P. Jackson,et al.  The neural network of motor imagery: An ALE meta-analysis , 2013, Neuroscience & Biobehavioral Reviews.

[38]  Stephen M. Tasko,et al.  Speed-curvature relations for speech-related articulatory movement , 2004, J. Phonetics.

[39]  P. Viviani,et al.  Biological movements look uniform: evidence of motor-perceptual interactions. , 1992, Journal of experimental psychology. Human perception and performance.

[40]  F. Lacquaniti,et al.  Two-thirds power law in human locomotion: role of ground contact forces , 2002, Neuroreport.

[41]  P. Viviani,et al.  A developmental study of the relationship between geometry and kinematics in drawing movements. , 1991, Journal of experimental psychology. Human perception and performance.