Two of the most common neurological and neuromuscular diseases in childhood are cerebral palsy (CP) and Duchenne muscular dystrophy (DMD) (Sussman, 2002; Rosenbaum et al., 2007; Graham et al., 2016). CP is defined as “a group of permanent disorders of the development of movement and posture, causing activity limitations attributed to non-progressive disturbances that occurred in the developing fetal or infant brain” (Rosenbaum et al., 2007). DMD is characterized by an altered gene on the X-chromosome, which codes for the protein dystrophin. Lack of dystrophin in muscles leads to a disbalance between damage and repair of the muscle fibers (Kobayashi and Campbell, 2012). This damage results in muscles that predominantly consist of fat and fibrous tissue (Sussman, 2002; Jones et al., 2010). Although CP and DMD have different origins and expressions, they have at least one symptom in common: muscle weakness. In both groups, muscle weakness is considered an important contributor to their pathological gait patterns (Sutherland et al., 1981; D'Angelo et al., 2009; Gage et al., 2009; Gaudreault et al., 2010; Doglio et al., 2011; Ganea et al., 2012; Steele et al., 2012).

There are only a small number of studies describing DMD gait (Sutherland et al., 1981; D'Angelo et al., 2009; Gaudreault et al., 2010; Doglio et al., 2011; Ganea et al., 2012; Ropars et al., 2016). Furthermore, none of these studies have verified to what extent these gait deviations were associated with muscle weakness (Sutherland et al., 1981; D'Angelo et al., 2009; Gaudreault et al., 2010; Doglio et al., 2011; Ganea et al., 2012; Ropars et al., 2016). In CP, several researchers have analyzed the relationship between muscle weakness and gait impairments, but their results are inconsistent (Damiano et al., 1995, 2010; Wiley and Damiano, 1998; Desloovere et al., 2006; Lee et al., 2008; Dallmeijer et al., 2011; Eek et al., 2011; Sagawa et al., 2013; Meyns et al., 2016; Shin et al., 2016). In DMD, muscle weakness is caused by non-neural changes in muscle morphology, whereas in CP, muscle weakness has neural as well as non-neural components. Neural components are considered the primary cause of weakness and are the result of the original brain injury (Gage et al., 2009). Examples include altered motor unit recruitment patterns and decreased selective motor control (Gage et al., 2009; Mockford and Caulton, 2010). Non-neural components are considered secondary causes of muscle weakness in CP (Gage et al., 2009), including changes in muscle morphology or lever-arm dysfunction due to bony deformities (Gage et al., 2009; Barrett and Lichtwark, 2010). The effect of these neural and non-neural changes on gait can be very different than their effect on strength assessments, such as maximal voluntary isometric contractions (MVICs). This could be an important reason for the discrepancies in previous studies analyzing the relationship between muscle weakness and altered gait in CP.

Despite the lack of consensus on how muscle weakness contributes to impaired gait, there is no doubt that it is a constraint the central nervous system (CNS) needs to deal with when initiating and controlling gait. Since children with CP and boys with DMD have different etiologies of weakness, the evaluation of how the CNS copes with muscle weakness in both populations has the potential to increase our understanding of the relationship between muscle weakness and gait deviations. In particular, it will help to differentiate between the relative effects of both neural and non-neural components of weakness on gait.

The regulation of human gait is not entirely understood, largely due to the abundant degrees of freedom (DOFs) and complexity of the human body (Latash, 2012). One of the theories for how humans control this abundance, is the use of muscle synergies instead of individual control of each muscle. Muscle synergies have been defined as the “consistent patterns of multi-muscle coordination that generate specific action” (Ting et al., 2015). Synergistic patterns of muscle recruitment have been well documented during various rhythmic tasks, including walking (d'Avella et al., 2003; Dietz, 2003; Nielsen, 2003; Barroso et al., 2013). Central pattern generators in the spinal cord and supra-spinal structures are thought to contribute to the regulation of these synergistic muscle activations (Lacquaniti et al., 1999; Dietz, 2002, 2003; Nielsen, 2003; Petersen et al., 2012). Synergies are flexible, thereby allowing to compensate for internal and external disturbances without affecting the outcome of the intended movement (Latash et al., 2002; Ting et al., 2015). This suggests that neural as well as non-neural components can affect synergies (Kutch and Valero-Cuevas, 2012; Bizzi and Cheung, 2013; Clark, 2015). In synergy analysis, evaluating the “total variance accounted for” (tVAF) by a given number of synergies can quantify the complexity of an individual's muscle activation patterns during dynamic tasks. The tVAF by one synergy (tVAF₁) can provide a summary measure of synergy complexity. When tVAF₁ is high, one synergy can explain a large part of the variance in muscle activity, representing a decrease in complexity of motor control during the analyzed task (Steele et al., 2015; Ting et al., 2015). Individuals with a CNS motor lesion, such as in CP or stroke, have higher tVAF₁ during gait than age-related healthy controls (Clark et al., 2010; Clark, 2015; Steele et al., 2015; Tang et al., 2015; Ting et al., 2015). Further, this decrease in complexity of motor control in children with CP was found to be related to muscle weakness (Steele et al., 2015). However, in these prior studies, muscle weakness was measured via a global summary score from manual muscle testing (MMT) (Steele et al., 2015). Not only does MMT have low reliability in young children with developmental disabilities (Mahony et al., 2009), but these analyses also limit our understanding of whether weakness of specific muscles affects control of gait.

If muscle weakness is a constraint for the CNS, it could limit the available degrees of freedom (DOFs) and negatively influence complexity of motor control, not only in CP, but also in boys with DMD. In children with CP, there is one confounding factor: the influence of the brain lesion on synergies and muscle weakness. Alterations in the CNS, such as the brain lesion in CP, affect a substantial part of synergy regulation (Lacquaniti et al., 1999; Dietz, 2002, 2003; Nielsen, 2003; Petersen et al., 2012). This brain lesion also underlies muscle weakness (its neural component) (Gage et al., 2009; Mockford and Caulton, 2010). The relationship between muscle weakness and tVAF₁ found in the previous study (Steele et al., 2015) could be caused by their mutual underlying source: the alterations in the CNS. This poses the research question: is muscle weakness contributing to higher tVAF₁ during gait in children with CP or is the higher tVAF₁ a quantification of the underlying brain lesion?

The primary goal of this research was to compare and contrast the impact of muscle weakness on tVAF₁ extracted from synergy analysis during gait for children with CP and DMD. We evaluated tVAF₁ during gait at self-selected walking speed for three groups of children: children with CP, children with DMD, and TD children. We expected decreases in complexity of motor control (increase in tVAF₁) in both CP and DMD children when compared to a control group of TD children. However, in children with CP, due to the addition of a neural component of muscle weakness, a higher tVAF₁ was expected than in DMD. As a secondary goal, we also sought to analyze the effect of muscle weakness of four muscle groups (knee extensors, knee flexors, plantar flexors, and dorsiflexors) on complexity of motor control. Muscle weakness was assessed via MVICs with a standardized protocol, using a hand-held dynamometer (HHD) in a fixed position (Goudriaan et al., 2018). We hypothesized that of the four measured muscle groups, the plantar flexors would be largely responsible for higher tVAF₁ in both CP and DMD, because of their importance during gait (van der Krogt et al., 2012). For an overview of the complete study design we refer to Table 1.

In preparation of this study, we performed a power analysis based on a pilot study (Goudriaan et al., 2016) to determine the sample size of the three groups (CP, DMD, and TD; Table 1). The pilot study indicated that for an effect size of d = 1.23, α = 0.05, and power (1-β) = 0.80 a minimal sample size of 12 participants per group would be required to test our main hypothesis (GPower 3.1.9, Faul et al., 2007).

In the three study groups (CP, DMD, and TD), all five muscles showed good quality sEMG data for all 10 concatenated steps and could be included in the NNMF analysis, with the exception of the GLU for one of the TD children. The outcomes of the Kruskal-Wallis H-Test showed significant group differences for all assessed parameters (all p < 0.005). The results of the post-hoc Mann Whitney U-test on all parameters are plotted in Figure 2.

The tVAF₁ was significantly higher in the children with CP compared to DMD and TD children (both p < 0.005). No significant differences in tVAF₁ were found between the boys with DMD and the TD children. Median values for tVAF₁ were 0.74 in CP, 0.60 in DMD, and 0.65 in the TD children. The interquartile ranges (IQRs) were similar for the three groups, 0.09 for the children with CP, and 0.07 for both the boys with DMD and the TD children.

The children with CP and DMD walked slower than the TD children, but this was only significant for the children with CP (p < 0.005). Median values and IQRs for non-dimensional walking speed were: 0.40 (0.07) for the CP children, 0.42 (0.05) in the boys with DMD, and 0.48 (0.10) in the TD children.

The TD children were significantly stronger in all four muscle groups than the children in the other two groups (CP and DMD, all p < 0.005). The TD children showed more inter-subject variability in MVICs compared to CP and DMD, which was indicated by the larger IQRs. Median values and IQRs in Nm/kg of the knee extensors were: 0.62 (0.26) in CP, 0.72 (0.37) in DMD, and 1.29 (0.83) in TD. For the knee flexors, these values were: 0.43 (0.37) in CP, 0.50 (0.21) in DMD, and 1.04 (0.41) in TD. The dorsiflexors had the lowest MVIC values in all groups, with median values (IQRs) of 0.07 (0.07) in CP, 0.10 (0.04) in DMD, 0.27 (0.08) in TD. For the plantar flexors, median MVIC values of 0.22 (0.19), 0.33 (0.22), and 0.86 (0.45) were found for the CP, DMD, and TD groups, respectively.

Only two moderate-to-high correlations (r ≤ 0.41) were found between muscle weakness and tVAF₁. Increased weakness in the plantar flexors was associated with higher tVAF₁ in the CP children (r = −0.72). In the boys with DMD, weaker knee extensors were associated with higher tVAF₁ (r = −0.50) (Figure 3).

When examining the PSD-plots of the three groups, they showed similar frequency bands, but in DMD the power was lower in the proximal muscle groups (Figure 4).

This study evaluated synergy complexity and strength in two common neuromuscular disorders to explore the impact of the neural and non-neural factors of muscle weakness on neuromuscular control during walking. Due to the differing etiology of these populations, this analysis helps to evaluate which factors serve as constraints to the CNS and influence impaired movement. We hypothesized that muscle weakness contributes to altered synergies and complexity of control during gait in children with CP and DMD, expressed by increased tVAF₁ during gait compared to TD children. Contrary to this hypothesis, our results suggested that the complexity of control was not influenced by the non-neural constraints of muscle weakness, since tVAF₁ was not significantly different between the children with DMD and the TD children. However, we confirmed that children with CP had reduced synergy complexity and that muscle weakness in the plantar flexors was related to higher tVAF₁ during gait. In children with DMD, increased weakness in the knee extensors influenced tVAF₁, although not enough to result in significantly different tVAF₁ between DMD and TD.

Similar to previously reported results, tVAF₁ was higher in the children with CP than in the group of TD children (Steele et al., 2015; Tang et al., 2015; Shuman et al., 2016a). The children with CP walked significantly slower than the TD children, which suggests that the differences in tVAF₁ between CP and the TD children might be more pronounced than expressed in our results, since a faster walking speed can result in higher tVAF₁ (Ivanenko, 2005; Shuman et al., 2016a). It could be that tVAF₁ gives an indirect representation of the child's neural capacity, with a higher tVAF₁ reflecting a higher level of involvement and increased muscle weakness. This agrees with the findings of Rose and McGill (2005) who determined that muscle weakness in children with CP is largely caused by neural factors. Further, the region on the motor cortex responsible for the distal muscle groups of the lower limb, is closer to the phylogenetic older parts of the brain (Volpe, 2000; Stiles and Jernigan, 2010) and it has been suggested that the older regions of the motor cortex are involved in synergy regulation (Bizzi and Cheung, 2013). Combined with the importance of the plantar flexors during gait, this might explain why we only found a strong correlation between weakness of the plantar flexors and tVAF₁ during gait and not between tVAF₁ and the other muscle groups in CP.

We checked if fibrofatty tissue in the muscles of the boys with DMD could act as an additional lowpass filter (Farina et al., 2002; Jansen et al., 2012) thereby reducing tVAF₁ (van der Krogt et al., 2016; Shuman et al., 2017). In DMD, the proximal muscle groups are more involved than the distal muscle groups, which was also represented in the PSD-plots. While the three groups showed similar frequency bands for all five muscles, the power was lower in the REF, MEH, and GLU muscles in the children with DMD. In children with DMD, fiber type IIb is the first fiber type to degenerate, which will have an influence on the frequency distribution, since these are the fast fibers connected to the motor units with the higher firing frequencies (Stackhouse et al., 2005; Jones et al., 2010).

In the children with DMD, the knee extensors are one of the most involved muscle groups (Sussman, 2002), which could explain the moderate negative correlation between the outcomes of the KE MVIC and tVAF₁. But, this non-neural weakness of the knee extensors did not sufficiently limit the complexity of control to create a difference in tVAF₁ between the children with DMD and the TD children. In other words, non-neural weakness appears to be only a small constraint for the CNS with respect to complexity of motor control.

Our results suggest that complexity of motor control, represented by tVAF₁, might be considered the neural capacity of a child, which could be difficult to alter with current treatments. Although tVAF₁ measured before treatment has been shown to be associated with changes in gait after treatment (Schwartz et al., 2016), prior research has also demonstrated that there are minimal changes in tVAF₁ after botulin toxin injections, selective dorsal rhizotomy, and single event multilevel surgeries among children with CP (Oudenhoven et al., 2016; Shuman et al., 2016b).

There are several important limitations in this research. First, we only correlated weakness with tVAF₁, whereas in children with CP and DMD, other clinical symptoms could have contributed to an increase in tVAF₁. Steele et al. (2015) determined that a higher level of spasticity and decreased selective motor control were also related to higher tVAF₁ in children with CP, although to a lesser extent than muscle weakness. Similar to muscle weakness, if a higher tVAF₁ indicates a higher level of involvement, this would not only be associated with more muscle weakness, but also with spasticity and decreased selective motor control (Ostensjø et al., 2004). In this study we focused on weakness, since DMD provides a comparison group to probe the relative impacts of non-neural factors that contribute to weakness on the results of synergy analysis. However, in children with DMD, other non-neurological symptoms besides muscle weakness are also present, such as decreased passive range motion due to contractures (Sussman, 2002). This only strengthens our conclusion that tVAF₁ represents the decreased DOFs in the CNS due to the brain lesion and that non-neural constraints have negligible influence on the complexity of motor control.

Further, due to the decreased selective motor control, an increase in level of co-contraction during strength assessments has been reported in children with CP (Mockford and Caulton, 2010). This increase in co-contraction has been suggested to be an important reason for the decrease in maximal torque output during a MVIC (Elder et al., 2003; Stackhouse et al., 2005). However, in a previous pilot study, while using the same protocol to measure MVICs, we determined that the levels of co-contraction were comparable between children with CP and TD children (Goudriaan et al., 2015). Similar results have been reported by Damiano et al. (2000), who determined that, although children with CP had higher levels of co-contraction during knee extension and knee flexion MVICs, this did not influence the outcomes of the MVICs.

Although the plantar flexors are important in maintaining a normal gait pattern, other muscle groups such as the hip abductors also play an important role (van der Krogt et al., 2012). Unfortunately, our MVIC setup did not allow for standardized strength measurements of the hip muscles, thus the influence of weakness in these muscle groups on tVAF₁ during gait should be analyzed in the future. Finally, tVAF₁ outcomes in this study were only representative of the five muscles that were included in the analysis. If other muscles were to be analyzed or more muscles included, the value of tVAF₁ could differ since synergy analyses can be dependent on the number and choice of muscles (Steele et al., 2013). However, it is expected that the relative differences in tVAF₁ between the three groups (CP, DMD and TD) would be similar.

The lack of significant differences in tVAF₁ between boys with DMD and TD children suggests that non-neural muscle weakness has little influence on complexity of motor control during gait. Although, weakness in the plantar flexors was negatively correlated with tVAF₁ in the children with CP, this is most likely the result of the common underlying cause: alterations in the CNS. Our results imply that despite the predictive value of tVAF₁ on treatment outcomes, a child's baseline tVAF₁ (i.e., the child's neural capacity) could be difficult to influence with pre-surgery therapy or may require novel intervention strategies that more directly target neural capacity.

All authors contributed to the work either to the design, data collection, analysis, interpretation, writing, or editing. KD and MG designed the experiment. Patient recruitment was performed by MVdH, NG, and GM. Data collection was done by MG. BS and KS created the original software for synergy calculation, modifications were made by MG. MG and MVdH performed quality checks on the data. Data analysis was done by MG, BS, and KS. Statistical tests were run by MG. Interpretation of the results was done by KD, KS, BS, and MG. MG and KD wrote the paper, which was edited by KS, BS, MVdH, NG, and GM. The entire process supervised by KD.