STRUCTURE OF MOTOR VARIABILITY Kyung Koh

BACKGROUND Motor variability  A commonly seen features in human movements  Bernstein “repetition without repetition” In the past, motor variability is thought to be the result of error. Scholz and Schöner (2002) developed the uncontrolled manifold analysis (UCM)  Variability which creates error  Variability which does not

THE PROBLEM OF MOTOR REDUNDANCY (DEGREE OF FREEDOM PROBLEM) Degrees of freedom (DOF) = Number of independent elements in a system (e.g. joints or muscles) Degrees of freedom problem = How dose CNS select a particular solution from infinite # of solutions.

MOTOR VARIABILITY

EXAMPLE – KINETIC VARIABLE F1F1 F2F2 + error

EXAMPLE – KINETIC VARIABLE F1 F2 10N V Good V Bad F 1 + F 2 = 10N

UNCONTROLLED MANIFOLD ANALYSIS (UCM)  Task : F 1 + F 2 = 10N (= a line equation [1D])  Variability in a UCM space (task irrelevant space)  Variability in an orthogonal to UCM space (task relevant space) F1 F2 10N Basis vector for UCM space Basis vector for a subspace orthogonal to UCM

UNCONTROLLED MANIFOLD ANALYSIS (UCM)  Task : F 1 + F 2 + F 3 = 10N (= a plane equation [2D])  Variability in a UCM space (task irrelevant space)  Variability in an orthogonal to UCM space (task relevant space) F2 F3 10N Basis vectors for UCM space Basis vector for orthogonal to UCM space F1 10N

MOTOR SYNERGY  A linear transformation that transforms the data into a new coordinate system (NCS)  A method to measure variance of the data in NCS F1 F2 10N UCM coordinates PCA coordinates Uncontrolled Manifold Analysis (UCM) VS Principle Component Analysis (PCA)

EXAMPLE – KINEMATIC VARIABLE

MOTOR SYNERGIES  Motor Synergies in UCM Ratio of Vucm and Vorth are commonly used to measure synergies

STUDIES: MOTOR SYNERGIES

SUMMARY There exists motor synergy Task-specific co-variation of effectors with the purpose to stabilize a performance variable (or minimize task error ) (Latash 2002). The CNS uses all the available DOFs to generate families of equivalent solutions.  DOFs work together to achieve a goal by compensating for each errors. (Gelfand and Tsetlin 1967).

BENEFITS OF HAVING GREATER VARIABILITY IN UCM  Greater Variability in UCM space  The system is redundant.  More DoFs than necessary to perform a particular task (e.g., F1 + F2 = 10N).  During walking on an uneven surface, DOFs at the foot create variety of configuration to maintain stability.  Extra DOFs allows a system to be more flexible (e.g. when get injured) 24 DoF1 DoF

 9 subjects (5 females & 4 males)  Two experimental conditions 1) standing up onto a solid platform 2) standing up onto a narrow, padded base of support. Task :

METHODS  Task : Sit to stand movement  Task equation : Basis vectors for UCM space Basis vector for Orthogonal space

RESULTS Horizontal CM position  The horizontal CM position: V UCM > V ORT  The vertical CM position: V UCM ≈ V ORT  Stronger synergies when Narrow BOS

METHODS

RESULTS