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task-relevant variability. Task-relevant variability does not affect selected performance variables. M-mode is a set of muscles within which the CNS scales the activation level in parallel either in time10 or space11 . Mathematically, a M-mode represents a unitary n-dimensional vector, where n is the number of the muscles formed it and each n-dimension (vectorâs components) represents the fixed weighted contribution of the n-muscle to the M-mode. A muscle can participate in multiple M-mode. The CNS controls the n-dimensional vectorâs magnitude by scaling linearly its elements, the weighting coefficients of the muscles (Latash, 2008b; Latash, 2012; Ting, 2007; Ting and Chvatal, 2011). Following Ting (2007) and according the nomenclature of Figure (1.15), the net activation pattern for any given muscle (m[N Ã1] ) on the course of performing an action is a linear combination of the sum of the fixed elements of the M-modes vectors W1âk that are structured temporally by the scaling coefficients of the neural commands vectors C1âk m[N Ã1] = k X Ci (t 1âN ) Â· w i (1.3) i=1 and the activation patterns of all muscles formed the M-modes at any given instant t is m[1Ãn] = k X ci (t) Â· Wi . (1.4) i=1 Therefore, the activation patterns of all muscles on the course of an action is m[N Ãn] = k X Ci (t 1âN ) Â· Wi . (1.5) i=1 Several M-modes may form a muscle synergy, i.e., a neural organization that provides stability of a performance variable by co-varied adjustments of its elements, the M-modes (Latash, 2008b; Latash, 2012). Assuming that synergies are organized in a hierarchical control scheme, a M-mode may be viewed as a performance variable itself, stabilized by a lower level synergy that uses firing patterns of individual motor units as elements (Latash, 2008b; Latash, 2012). Assuming that the M-modes are fixed throughout certain task repetitions, whereas their scaling factors are varied (Ting and Chvatal, 2011), the low level synergy ensures that the proportion of the weighted contribution of each muscle on the M-mode does not change. This is equivalent to the notion that the low level synergy stabilizes the direction of the n-dimensional vector within the muscle activation space, and mathematically represents the angles formed between the n-dimensional vectors of the M-mode across tasks and repetitions (Fig. 1.15). Recently, experiments showed that the organization of muscles into groups in complex whole-body tasks can differ significantly across both task variations and subjects (Danna-Dos-Santos et al., 2009; FrÃ¨re et al., 2012), but either with similar temporal profiles of the gains at which the M-modes are rectruited (FrÃ¨re et al., 2012), or with gains that help stabilizing important mechanical variables like COP shifts (Danna-Dos-Santos et al., 2009)âi.e., the ability to organize muscles co-variation 10 11 On the course of performing an action. Across actions with different parameters. 39