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. 2012 Jan;107(1):159-77.
doi: 10.1152/jn.00653.2011. Epub 2011 Sep 28.

Task-level feedback can explain temporal recruitment of spatially fixed muscle synergies throughout postural perturbations

Seyed A Safavynia  1 , Lena H Ting
Affiliations

Task-level feedback can explain temporal recruitment of spatially fixed muscle synergies throughout postural perturbations

Seyed A Safavynia et al. J Neurophysiol. 2012 Jan.

Abstract

Recent evidence suggests that complex spatiotemporal patterns of muscle activity can be explained with a low-dimensional set of muscle synergies or M-modes. While it is clear that both spatial and temporal aspects of muscle coordination may be low dimensional, constraints on spatial versus temporal features of muscle coordination likely involve different neural control mechanisms. We hypothesized that the low-dimensional spatial and temporal features of muscle coordination are independent of each other. We further hypothesized that in reactive feedback tasks, spatially fixed muscle coordination patterns-or muscle synergies-are hierarchically recruited via time-varying neural commands based on delayed task-level feedback. We explicitly compared the ability of spatially fixed (SF) versus temporally fixed (TF) muscle synergies to reconstruct the entire time course of muscle activity during postural responses to anterior-posterior support-surface translations. While both SF and TF muscle synergies could account for EMG variability in a postural task, SF muscle synergies produced more consistent and physiologically interpretable results than TF muscle synergies during postural responses to perturbations. Moreover, a majority of SF muscle synergies were consistent in structure when extracted from epochs throughout postural responses. Temporal patterns of SF muscle synergy recruitment were well-reconstructed by delayed feedback of center of mass (CoM) kinematics and reproduced EMG activity of multiple muscles. Consistent with the idea that independent and hierarchical low-dimensional neural control structures define spatial and temporal patterns of muscle activity, our results suggest that CoM kinematics are a task variable used to recruit SF muscle synergies for feedback control of balance.

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Figures

Fig. 1.
Fig. 1.
Hypotheses and concepts explored in the present study. A: muscle synergies with fixed spatial weightings [spatially fixed (SF) muscle synergies]. Here the nervous system organizes muscle activity spatially. The nervous system can variably recruit SF muscle synergies when a specific muscle combination is desired throughout a task in a feedback or feedforward manner. B: muscle synergies with fixed temporal recruitment [temporally fixed (TF) muscle synergies]. In this hypothesis, the nervous system uses fixed temporal sequences to recruit muscles during a task, consistent with feedforward control. When a specific temporal sequence is executed, a set of muscles that can vary across directions and trials is chosen to reproduce EMG activity necessary to achieve the task.
Fig. 2.
Fig. 2.
Representative postural response to a forward ramp-and-hold perturbation. Subjects exhibit motion of individual joints as well as center of mass (CoM) and activate muscles over body segments in response to a forward (90°) perturbation. Initially (start epoch), CoM kinematics [displacement (d), velocity (v), acceleration (a)] were all opposite the direction of platform motion. However, when the platform decelerated (stop epoch), CoM acceleration was in the opposite direction of CoM displacement and velocity. Intermuscular coordination patterns also changed throughout the perturbations; the major muscles activated in the start epoch [tibialis anterior (TA), erector spinae (ERSP), semitendinosus (SEMT)] were different from those activated in the stop epoch [TA, vastus medialis (VMED)]. Overlaid muscle traces shown are for individual trials (5 total).
Fig. 3.
Fig. 3.
Delayed feedback model. Recorded CoM kinematics from anterior-posterior (A-P) perturbations are used to reconstruct SF muscle synergy recruitment patterns throughout a perturbation. Each component of CoM motion is multiplied by a feedback gain at a common time delay and linearly added to produce a reconstructed SF muscle synergy recruitment pattern.
Fig. 4.
Fig. 4.
Variability accounted for (VAF) comparisons using TF vs. SF muscle synergies. A: total and muscle VAF for all subjects. Nsyn-S SF muscle synergies explain a significantly larger portion of the data set than Nsyn-T or Nsyn-S TF muscle synergies but significantly less variability than Nsyn-P TF muscle synergies. Error bars represent SD. *P < 0.05, ‡P < 0.01, ANOVA, Tukey-Kramer post hoc tests. B: total VAF for subject 1. Left: total VAF vs. number of components. Total VAF with Nsyn-S SF muscle synergies is higher than VAF with Nsyn-T or Nsyn-S TF muscle synergies. Both methods of synergy extraction account for significantly more variability than with shuffled muscle synergies. Right: total VAF vs. number of parameters incorporated into the muscle synergy extraction. VAF of TF muscle synergies was always higher than SF muscle synergies. However, many more TF muscle synergies (25) were needed to incorporate the same number of parameters as SF muscle synergies (6). Error bars represent the estimated 95% confidence interval of VAF.
Fig. 5.
Fig. 5.
Comparison of SF vs. TF muscle synergy structure and muscle reconstructions. A: muscle synergy structure. SF muscle synergies organize muscle activity into groups of muscles that have common spatial activation patterns (left). TF muscle synergies organize muscle activity into consistent temporal patterns (right). As the number of TF muscle synergies increases, temporal patterns of activation become more localized in time. Data are shown for subject 1. B: muscle reconstructions during a forward-leftward (150°) perturbation. A small subset of SF muscle synergies was recruited to reconstruct each muscle (left). Note that multiple SF muscle synergies contributed to the reconstruction of muscles with multiple actions [i.e., W4 and W6 for rectus femoris (RFEM)], and separate SF muscle synergies were recruited in antagonistic muscle pairs [W4 for TA, W2 for medial gastrocnemius (MGAS)]. In contrast, a majority of TF muscle synergies was recruited to reconstruct each muscle (right). The same TF muscle synergies were used to recruit antagonistic muscle pairs. Gray lines, smoothed EMG; black lines, reconstructed EMG; colored lines, individual muscle synergy contributions. REAB, rectus abdominus; TFL, tensor fascia lata; BFLH, biceps femoris, long head; PERO, peroneus; LGAS, lateral gastrocnemius; EXOB, external oblique; GMED, gluteus medius; VLAT, vastus lateralis; SOL, soleus; ADMG, adductor magnus.
Fig. 6.
Fig. 6.
Variable SF muscle synergy recruitment vs. variable TF muscle synergy weighting across multidirectional perturbations. A: SF muscle synergies. SF muscle synergy recruitment was variable over directions but consistently recruited in backward and leftward (210–300°) perturbations. B: TF muscle synergies. TF muscle synergy weightings changed considerably over directions and trials and included antagonistic pairs of muscles. Data are shown for the same subject as in Fig. 5 (subject 1).
Fig. 7.
Fig. 7.
Comparison of SF muscle synergy structure across various epochs throughout a perturbation. A: comparisons for a subject with high structural consistency (subject 7). SF muscle synergies extracted independently from start, plateau, stop, and stable epochs were similar to those extracted from all epochs pooled together (all). W1, W2, W3, and W6 were identified in every epoch, while W4 and W5 were only identified in some epochs. B: comparisons for a subject with low structural consistency (subject 5). W3 and W6 were identified in every epoch, while W1, W2, W4, and W5 were only identified in some epochs. Three SF muscle synergies were uncorrelated at P < 0.01 (r < 0.623) and were considered “additional.” W7 was mainly composed of ankle muscles TA and PERO, W8 was mainly composed of RFEM, a biarticular muscle that aids in hip flexion, and W9 had large involvement of hamstrings (BFLH, SEMT) and muscles with actions at the trunk and hip (EXOB, ERSP, GMED).
Fig. 8.
Fig. 8.
SF muscle synergies extracted from the entire time course of perturbations for all subjects. Five of 10 SF muscle synergies (W1, W2, W3, W5, W6) were similar in at least 7 of 8 subjects. Of the remaining SF muscle synergies, W8 and W9 had large contributions from the hamstrings (BFLH, SEMT), biarticular muscles that aid in hip extension. W10 had large contributions from trunk muscles. Gray shaded and outlined SF muscle synergies were active during A-P perturbations (n = 44). For active SF muscle synergies, shaded muscle synergies were well-reconstructed with a delayed feedback model based on CoM motion across A-P trials (34/44). Outlined muscle synergies (10/44) were poorly reconstructed by the feedback model. Of these 10 SF muscle synergies, 6 had major contribution of mono- and biarticular muscles acting at the hip. Numbers indicate r values for comparisons.
Fig. 9.
Fig. 9.
Feedback model reconstruction of SF muscle synergy recruitment patterns. Data are shown for subject 2. A: reconstruction of recruitment patterns in a forward and backward perturbation. SF muscle synergies (W1–W6) are differentially recruited throughout A-P perturbations. Active SF muscle synergies (shaded) were reconstructed with a delayed feedback model based on CoM motion. W1, W2, and W6 were well-reconstructed across trials (mean r2 ≥ 0.5 or mean VAF ≥ 75% for all trials). W2 was poorly reconstructed over trials. W5 was well-reconstructed in forward perturbations but poorly reconstructed in backward perturbations. Both W1 and W6 have major contributions from mono- and biarticular muscles affecting the trunk (REAB, RFEM, GMED). Reconstructions are only shown for 1 trial for ease of interpretation. Colored lines, SF muscle synergy recruitment patterns; black lines, feedback model reconstructions. B: reconstruction of muscle synergy W1 for all forward trials. Intertrial differences in SF muscle synergy recruitment can be accounted for by differences in CoM kinematics. Using a single set of feedback gains, the feedback model can account for trial-by-trial variability in recruitment for SF muscle synergies. Numbers indicate r2 (top) and VAF (bottom) values for reconstructions. Gray lines, CoM kinematics; colored lines, muscle synergy recruitment patterns; black lines, feedback model reconstructions.
Fig. 10.
Fig. 10.
Reconstruction of individual muscle activity with SF muscle synergy recruitment patterns determined from nonnegative matrix factorization (NNMF) (unconstrained, left) and the feedback model (right) for a forward (A) and a backward (B) perturbation. Data are shown for subject 2. Although recruitment patterns determined from NNMF explain the variability better than recruitment patterns determined from the feedback model, both methods of extraction have high correlation values for active muscles in A-P perturbations. Both SF muscle synergy recruitment patterns reconstructed muscle activation patterns significantly better than when using Nsyn-T (P < 0.01 for r2 and VAF) or Nsyn-S (P < 0.01 for r2) TF muscle synergy recruitment patterns (data not shown). Gray lines, smoothed EMG; black lines, reconstructed EMG; colored lines, individual SF muscle synergy contributions.
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