Generating variability from motor primitives during infant locomotor development

  1. Elodie Hinnekens
  2. Marianne Barbu-Roth
  3. Manh-Cuong Do
  4. Bastien Berret
  5. Caroline Teulier

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    In learning to walk, infants must balance the need to explore their movement repertoire with the need to establish regular movement patterns. Using a longitudinal approach, this paper suggests that while young infants generate high variability from a small number of regular patterns ('primitives'), older infants use a greater number of primitives with less variability. These interesting conclusions are not currently fully supported by the small and somewhat selective sample of data, and some alternative explanations need to be considered more thoroughly.

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Abstract

Motor variability is a fundamental feature of developing systems allowing motor exploration and learning. In human infants, leg movements involve a small number of basic coordination patterns called locomotor primitives, but whether and when motor variability could emerge from these primitives remains unknown. Here we longitudinally followed 18 infants on 2–3 time points between birth (~4 days old) and walking onset (~14 months old) and recorded the activity of their leg muscles during locomotor or rhythmic movements. Using unsupervised machine learning, we show that the structure of trial-to-trial variability changes during early development. In the neonatal period, infants own a minimal number of motor primitives but generate a maximal motor variability across trials thanks to variable activations of these primitives. A few months later, toddlers generate significantly less variability despite the existence of more primitives due to more regularity within their activation. These results suggest that human neonates initiate motor exploration as soon as birth by variably activating a few basic locomotor primitives that later fraction and become more consistently activated by the motor system.

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  1. Version published to 10.7554/elife.87463 on eLife
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    Author Response

    Reviewer #1 (Public Review):

    This paper has significant strengths in taking a rich, quantitative, neurally-grounded approach to the development of human walking. It provides a rich empirical dataset of EMG and kinematic data at this challenging age, as well as sophisticated analyses of these data in terms of motor primitives, which are a concept that has recently been usefully applied to understanding human walking and its development.

    STRENGTHS

    It builds on emerging literature in this field and adds data at the key age of infancy-toddlerhood.

    It takes a longitudinal approach, sampling children at the ages of newborn, 3 months, and newly walking. This is still reasonably rare in developmental research and allows for a powerful, robust interpretation of data: the authors should be commended for taking this approach.

    WEAKNESSES

    Some aspects of the work could have been more clearly introduced. This includes neural aspects: the location of the CNS control centres at the spinal level, and which higher centres control them (e.g. brainstem); the justification for understanding primitives as modular (no cross-talk or feedback). It also includes developmental aspects: introducing the stepping reflex, and behavioural aspects of infant motor variability (e.g. Adolph, Hoch & Cole, TICS, 2018).

    The patterns relate to walking in a stereotypical manner, yet children's walking is full of skips, jumps, and climbs - both in relation to external obstacles and on even ground. Indeed, it is a challenge to get children to 'walk normally' in a lab. Thus, variability is in fact greater than is discussed here and this should be acknowledged.

    Thanks for the remarks. We reviewed the introduction and clarified these points. Mainly, we realized that we were not clear enough about the type of variability that we focused on, and added a paragraph at the top of the introduction to clearly define the different types of variability that exist during development and to specify that we only focus on the ability to produce a given coordination mode (like for example alternated leg movements) with various muscle activities (line 34-44). We also added some specification about the neural structures that are known to be involved in modularity in animals (line 53-58).

    The analyses are based on a limited sample of the data. (1) I am not clear on what basis the coders selected cycles, and why 5 cycles were selected. (2) It is not clear why certain movement parameters (cycle duration and flexion/extension proportions) and not others (e.g. step length, double support time) were selected. In particular, it is not clear why the authors focus on temporal, rather than spatial, variability. (3) Some data are based on stepping, and some on kicking. Because it's not clear that these are really equivalent, and because there are small samples of each (n<10), it's not clear that there is enough data to allow us to come to strong conclusions. The sample size should be justified - on the basis of power analyses and/or previous work in this area (e.g. Dominici, Science, n=40). From the results, where p values often hover around p=0.06, the paper seems underpowered to detect a decrease in variability with age for stepping kinematics and primitives.

    We initially limited to 5 the number of cycles to analyze in each individual and age in order to make the indexes of variability comparable across individuals and ages. However, as detailed in the general response above, in the new version of the manuscript we preprocessed (i.e. filtered and normalized) a different amount of data in each individual and age (i.e. between 5 and 22 cycles depending on what was available) and we reproduced every analysis of the paper for 5 randomly chosen combinations of 5 cycles when strictly more than 5 cycles were available (i.e. we used a bootstrapping approach, limiting the number of combinations to 5 because of the processing time of the algorithm). Therefore, every result presented in the paper correspond to an average value computed across these 5 random combinations (except when the number of available cycles was strictly equal to 5), which allowed to include a different number of steps in the analysis while keeping the indexes comparable across individuals and ages. This raised the number of cycles included in the analysis from 200 to 586.

    We do not present data on step length and double support time because we wanted to apply our analyses on the two behaviors (i.e. stepping and kicking) and there are no step length or support phase in kicking. Moreover, we do not have access to these data. In fact, the available space on the skin on newborns was limited after having disposed EMG sensors, and we could not dispose enough 3D markers to analyze step length. Furthermore, we had to record toddler’s walking in a room that was not equipped with motion capture, therefore we did not have access to any marker’s position at walking onset. As such, we report kinematic parameters that were available for each behavior, which are stride duration, variability of stride duration and percentage of extension phase. This was clarified in the manuscript line 581-583.

    As detailed in our general response, we had chosen a very conservative approach which reduced the amount of data that were presented in the original manuscript, however we systematically reviewed our data and we now present our analyses on 18 infants, of which 11 stepped at birth, 15 stepped at 3 months old, 15 kicked at birth, 15 kicked at 3 months old, and 15 were recorded at walking onset. Each infant was followed longitudinally and we only present data if they are available on at least two time points. The results were reinforced with this new number of included individuals, and the p values are stronger (see table S1 were all the p-values are reported, line 979).

    There are some points of interpretation that could have been clearer, for example highlighting how one might distinguish between variability as incidental (motor noise) or purposeful (for exploration); and how studying the time around walking onset can contribute to the broader literature on this topic.

    The main result of this study is that the structure of EMG variability evolves during the first year of life, but the origin of this variability (incidental or purposeful) remains unknown. Be it purposeful or incidental, variability might arise at any level of the nervous system (Dhawale et al., 2017), and here we propose that it arises at the level of primitives’ activation during early development. As this is coherent with the fact that different pharmacological or electrical stimuli applied to the spinal cord of neonatal rodents can generate variability (Kiehn and Kjærulff, 1996; Klein et al., 2010), we can hypothesize that such variability could be purposely generated at a supra-spinal level during early development. However, even if it is generated at this level, variability could result from an instability of the command rather than from purposeful explorations. Interestingly, the distinction itself might be challenging, because both types of variability (incidental or purposeful) might contribute to exploration: theoretically, variability might be useful for exploration and learning even if it has not been purposely generated by the individual (Dhawale et al., 2017). As such we used animal literature to make hypothesis about the origin of this variability but we are not aware or any protocol that could have helped to discriminate among the two. This was specified line 388-389: “As similar neurophysiological investigations cannot be conducted in human infants, discriminating among purposeful and incidental variability remains challenging,”.

    The time around walking onset was chosen to match previous literature on the topic (mainly, Dominici et al., (2011), but it also matches the period that is more and more recommended as a period when to intervene in early therapy. This was discussed line 469-471: “Overall, when compared with adult values (Figure 3, Figure 5, Table S3), our results suggest an immaturity of the modular system before and around walking onset, which confirms that infancy should be an ideal period of plasticity to benefit from in therapy (Ulrich et al., 2010; Morgan et al., 2021).”.
    As the age of walking onset is highly variable across infants (Martorell et al., 2006), we also chose to focus on walking onset rather than age to standardize recruitment along experience rather than age, as EMG variability is known to rapidly evolve with experience after a few months of walking experience (Chang et al., 2006). In the new version of the manuscript, we highlighted this variability by allocating legends according to the age of walking onset (Figure 2, Figure 3 and Figure 5, see Figure 3E detailing this legend).

    Reviewer #3 (Public Review):

    Hinnekens et al. examined the development of humans' leg movements as they learn to step, kick, and independently walk during infancy. An established theory argues that motor movements can be composed of a finite set of building blocks ("motor primitives"), just like any word can be composed of a finite set of letters. In their paper, Hinnekens et al. follow up this theory by longitudinally recording muscle activations of infants using EMG (at three time points: a few days after birth, at 3 months, and shortly after they learned to walk independently). The authors examined two modules that underlie the infants' stepping and two modules that underlie toddler walking, all based on previous literature. The authors also examined different modules that underlie infants' upright stepping and supine kicking. The authors used supervised machine learning (an advanced version of factor analysis) to identify the modules and to track their change at the different developmental time points. The authors found that trial-to-trial variability in the structure of primitives reduces from newborns to toddlers, even though the number of primitives increased. The authors relate these findings to motor exploration by arguing that newborns generate high variability with a low number of primitives.

    The paper has one clear strength - its longitudinal recordings. Unlike most papers in this area of research, the authors follow the same individuals from birth until they learn to walk and the comparison between the use of primitives is done on the same infants. This is certainly novel.

    That said, the contribution of the paper to the literature is unclear and it suffers from some critical weaknesses that challenge the current conclusions in the paper, based on the existing data.

    1. Although the data is based on longitudinal recordings, and this is certainly desirable, the paper is based only on 10 infants. Moreover, only seven infants contributed supine data at the first time points and only six infants contributed upright data at the different time points. The paper would benefit from a more reliable dataset that includes more infants and time points to compare. To conclude the authors' conclusions, much richer data is required.

    As detailed in our general response, we had chosen a very conservative approach which reduced the amount of data that were presented in the original manuscript, however we systematically reviewed our data and we now present our analyses on 18 infants, of which 11 stepped at birth, 15 stepped at 3 months old, 15 kicked at birth, 15 kicked at 3 months old, and 15 were recorded at walking onset. Each infant was followed longitudinally and we only present data if they are available on at least two time points. The results were confirmed by those analyses that yielded stronger p-values (see table S1, line 979).

    1. Relatedly, although the strength of longitudinal data is compared between individuals and has significant insights into individual differences in development, this was not clearly (sometimes not at all) discussed in the paper. The work would benefit from more focus on individual differences and a clear explanation of its contribution to the field from that aspect. The key arguments in the paper focus on the ratio between the number of primitives and the variability in each time point, but none of this from the lens of individual differences. This is challenging to do because there are not many individuals who contribute to the dataset but otherwise, it is not clear what the paper contributes to previous work and more critically.

    Thanks for the suggestion. To follow this remark, we modified each figure of the paper so the 18 individuals would each have their own color and could be followed across figures. Also, as the age of walking onset was different across infants, we allocated colors to each infant based on when they started to walk (Figure 2, Figure 3, Figure 5). Moreover, increasing our cohort highlighted some interindividual differences in the development of kicking only between birth and three months old (Figure 3, Figure 5, Table S1). This was discussed in a new paragraph of the discussion (line 469-487).

    1. The motivation for the paper is unclear. Why did the authors do what they did? Why is this important to do it the way they did? In the current manuscript, it is not clear why they used this design to get those conclusions.

    The main rational of the paper was to explore a paradox of the literature on early locomotor development: on one hand, newborn infants produce a highly variable muscular activity (Teulier et al., 2012), but on the other hand authors report that they produce rhythmic movement with a small number of invariant modules (Dominici et al., 2011; Sylos-labini et al., 2020). As the latest studies were based on averaged or single-step data, our main goal was to assess both EMG variability and features of modularity in the same cohort, in an attempt to refute or explain this paradox. We reviewed and clarified the introduction on this matter by clarifying the place of our study among the broader literature on variability in development (line 34-44) and by deepening explanations about the abovementioned paradox in relation to previous studies on infants’ modularity (line 72-96).

    1. The data selection process is also not clear. At each time point and from each infant, the authors examined 5 cycles from the same leg. The definition of a cycle was hip-flexion onset to another hipflexion onset on one side of hip extension. It is not clear what variability (measured by % of the cycle in flexion and extension) means in this case because infants hold their legs in one position for a long time. What are those 5 cycles? Why five? A lot of information is missing there about the arbitrary selection of analytic parameters. In addition, the authors argue they performed the same analyses with different parameters and that they got similar results. However, those results are not given in detail and it is hard to compare them with the authors' report.

    We entirely reviewed our data and less selection were applied in the current manuscript. Here is the complete data selection process:

    Among the 18 infants that we followed from birth on, 15 were followed until walking onset (among the other three, one had moved and the other two could not be seen around walking onset because of the covid pandemic). Around birth and three months old, in each infant we tried to elicit stepping (by holding the infant in an upright position with his feet above a surface) and kicking (by placing the infant in a supine position). Therefore, we systematically analyzed each video from every infant and every age to spot and count every alternated leg movement within the two behaviors. After this step, we checked the quality of EMG data for the 10 muscles that were recorded. As our analysis has to be based on the same number of muscles for each individual, if the quality of the signal was too low for even one muscle during a leg cycle, the cycle had to be removed from the analysis. After this check, if less than 5 alternated leg cycles were available, the whole trial was removed from the analysis. The rational is that the hypotheses that we tested were mainly about intra-individual variability and therefore analyses had to be based on a minimal number of cycles. In newborns this was particularly challenging because we were limited in recording time (1 to 2 minutes), moreover we did not always have qualitative EMG data because we always reduced the amount of adhesive surface on the skin for ethical reasons. Therefore for several babies we could not observe enough cycles to include them in the analysis, however in the current version of the manuscript we present data on 11 babies for newborn stepping, 15 babies for 3 mo stepping, 15 babies for newborn kicking, 15 babies for 3 mo kicking, and 15 babies for toddlers walking. The trials that were not included are grey in Table 1 of this document. For every other trial, the exact number of remaining cycles are reported in the same table.

    In the previous version of the manuscript, as we wanted the indexes to be comparable across individuals and ages, we had systematically analyzed 5 cycles that were randomly chosen among the available one. However this created data loss. As detailed in the general response above, to be less selective and to include every available cycle, we now rely on a new approach: if more than 5 cycles were available, we computed every variable of the study 5 times (for 5 random combinations of 5 cycles that were randomly chosen among every available cycle). The variables were averaged afterwards. Thanks to this new approach, 586 cycles are now included in the analysis, which confirmed the robustness of our findings.

    Infants can indeed hold their legs in one position for a long time but all of our results were obtained after having normalized each phase of flexion or extension by a given number of time points (see Figure 6, Temporal normalization). Our results were also verified with a different temporal normalization, directly normalizing the cycle instead of the phases. We choose not to report more results in the main text for the overall readability of the paper but here are the same table of p-value as in the appendix of the paper with a normalization based on cycles instead of phases.

    1. The recording times are not common across individuals. One newborn was recorded after 1 day and the other after 21 days. Not sure this is comparable, especially if the main contribution of the paper is the longitudinal data. Moreover, the second recording was conducted between 74 days to 122 days. This range is too broad. Same for the third time point - one walk onset is not reported, some infants were recorded at <380 days and some >500 days. This difference challenges the reliability of the data.

    Given the high inter-individual variability that relates to the age of walking onset (Martorell et al., 2006) it is often a challenge in developmental sciences to choose between standardizing recruitment according to the age or according to the experience. In the present study, we choose to recruit toddlers of similar experience (i.e. around walking onset) rather than on similar age because motor variability is known to depend a lot on experience, in particular regarding EMG data during the first months of walking (Chang et al., 2006). However, we agree with the reviewer that the age of walking onset is an important source of inter-individual variability and therefore we modified each figure of the paper so the 18 individuals would each have their own color which was ordered and allocated according to the age of walking onset (see Figure 3E detailing this legend).

    Regarding the other recording points, and the experience after walking onset, the recording time can indeed vary across individual despite our efforts during data collection to prevent this phenomenon. Main reasons were benign diseases of infants or work constraints for parents that induced postponements of the appointments. However, we report the precise age of each infant for each recording as well as individual data underlying each global figure (see source data of Figure 2, Figure 3 and Figure 5). Based on these data we checked that the individual that were recorded later than the others (for example, subject 1 and subject 14 who were recorded at 21 days for the 1st time point) did not demonstrate aberrant values.

    1. Conceptually, I'm not sure I understand why the authors selected leg alternation (and not other types of movements) as their modules. I was not convinced that leg alternations reflect their real-life locomotor experience (e.g., short bouts in all directions), and therefore the variability measured in this work does not reflect the variability of infants' natural locomotor behaviour.

    We fully agree that leg alternation do not reflect the whole variability that underlies real-life locomotor experience of these infants, however we did not intend to focus here on all the variability that exists during development but more specifically on the variability that allows to produce a given type of behavior with different inputs. This variability is interesting to study because infants tend to use steadier and steadier patterns of coordination to produce a given movement (Teulier et al., 2012), suggesting that they explore among different possible muscular associations before choosing some. As we wanted to study this phenomenon, it appeared methodologically pertinent to fix other sources of variability (i.e. to study different behaviors separately and to study only one coordination mode), as is commonly done in other EMG-based studies of the field (Dominici et al., 2011; Sylos-labini et al., 2020; Teulier et al., 2012). This choice allowed to remain comparable between infants and toddlers. Indeed, while infants produce numerous coordinative patterns while stepping or kicking, such as parallel cycles or singles cycles for example, toddlers only produce alternated flexion and extension cycle of the lower-limb when walking. Therefore, by selecting alternating cycles of flexion and extension only in infants, we ensure that the differences of variability that we observe between ages is not due to the ability of producing various movement, but really due to the ability of producing a given movement with various muscle outputs. Accordingly, and following our results, it allows to conclude that the structure of variability evolve between birth and independent walking to command a given movement. To explain this notion that relates to the redundancy of motor control, we added a new paragraph at the top of the introduction to better explain the place of our studies among broader literature on infant variability (line 34-44). We also clearly wrote in the discussion that our conclusions did not apply to every developmental source of variability (line 393-395): “As we observed such structure within alternated leg movements, other studies are needed to explore the extent of these results to other early behaviors or coordination modes”.

    1. There is not enough rationale for why the specific measurements (IEV, VAF, IRV, etc.) were used and why those are the appropriate ones for the address the questions in the paper. What is the justification for using those measurements?

    As our main goal is to characterize how EMG variability can be generated in a modular system, we defined those metrics as directly representative of the different features that we wanted to study: variability of the EMG output, dimensionality of the underlying modular organization, variability of module activations and selectivity of the command (be it through module activations or within module themselves). While VAF is commonly used in muscle synergies studies, this study is the first to explore how cycle-to-cycle variability could be generated in a modular system, and therefore these indexes were defined for its proper needs. As such to clarify their role to a broad audience we included a new table at the beginning of the Results section (see Table 1 of the ms, line 176).

    1. Some of the conclusions, especially those that relate to motor exploration, are not based on sufficient data. Motor exploration was not explicitly measured in this study, and how motor exploration is reflected by the current data and analyses is not clear.

    We fully agree with the reviewer: while we observed that the structure of EMG variability evolves during the first year of life, the origin of this variability (incidental or purposeful) remains unknown. This was specified line 388-389 “As similar neurophysiological investigations cannot be conducted in human infants, discriminating among purposeful and incidental variability remains challenging,”.

  5. eLife

    eLife assessment

    In learning to walk, infants must balance the need to explore their movement repertoire with the need to establish regular movement patterns. Using a longitudinal approach, this paper suggests that while young infants generate high variability from a small number of regular patterns ('primitives'), older infants use a greater number of primitives with less variability. These interesting conclusions are not currently fully supported by the small and somewhat selective sample of data, and some alternative explanations need to be considered more thoroughly.

  6. eLife

    Reviewer #1 (Public Review):

    This paper has significant strengths in taking a rich, quantitative, neurally-grounded approach to the development of human walking. It provides a rich empirical dataset of EMG and kinematic data at this challenging age, as well as sophisticated analyses of these data in terms of motor primitives, which are a concept that has recently been usefully applied to understanding human walking and its development.

    STRENGTHS

    It builds on emerging literature in this field and adds data at the key age of infancy-toddlerhood.

    It takes a longitudinal approach, sampling children at the ages of newborn, 3 months, and newly walking. This is still reasonably rare in developmental research and allows for a powerful, robust interpretation of data: the authors should be commended for taking this approach.

    WEAKNESSES

    Some aspects of the work could have been more clearly introduced. This includes neural aspects: the location of the CNS control centres at the spinal level, and which higher centres control them (e.g. brainstem); the justification for understanding primitives as modular (no cross-talk or feedback). It also includes developmental aspects: introducing the stepping reflex, and behavioural aspects of infant motor variability (e.g. Adolph, Hoch & Cole, TICS, 2018).

    The patterns relate to walking in a stereotypical manner, yet children's walking is full of skips, jumps, and climbs - both in relation to external obstacles and on even ground. Indeed, it is a challenge to get children to 'walk normally' in a lab. Thus, variability is in fact greater than is discussed here and this should be acknowledged.

    The analyses are based on a limited sample of the data. (1) I am not clear on what basis the coders selected cycles, and why 5 cycles were selected. (2) It is not clear why certain movement parameters (cycle duration and flexion/extension proportions) and not others (e.g. step length, double support time) were selected. In particular, it is not clear why the authors focus on temporal, rather than spatial, variability. (3) Some data are based on stepping, and some on kicking. Because it's not clear that these are really equivalent, and because there are small samples of each (n<10), it's not clear that there is enough data to allow us to come to strong conclusions. The sample size should be justified - on the basis of power analyses and/or previous work in this area (e.g. Dominici, Science, n=40). From the results, where p values often hover around p=0.06, the paper seems underpowered to detect a decrease in variability with age for stepping kinematics and primitives.

    There are some points of interpretation that could have been clearer, for example highlighting how one might distinguish between variability as incidental (motor noise) or purposeful (for exploration); and how studying the time around walking onset can contribute to the broader literature on this topic.

  7. eLife

    Reviewer #2 (Public Review):

    In this work, the authors attempt to resolve an apparent paradox in human locomotor development. Previous works have reported that neonates exhibit highly variable movement, which is believed to be important for driving exploration-based motor skill learning. Yet, other recent studies have also demonstrated that locomotor behaviors of newborn babies are generated by a very small number of invariant motor primitives that may underpin stereotypical innate motor behaviors. Indeed, as infants acquire the ability to walk independently, the number of motor primitives tends to increase while the overall motor variability decreases. Hinnekens et al. propose that this apparent paradox can be explained by following the variability of the activations of the motor primitives (or motor modules) as the locomotor behaviors of infants mature. The authors collected bilateral EMGs from infants longitudinally at 3 time points (from ~4 days old to walking onset) and used a well-known machine learning algorithm (non-negative matrix factorization) to extract both spatial and temporal motor modules, along with their activations, from the EMGs. They found that at birth, the cycle-to-cycle activations of the small number of modules were highly variable. But as the infants developed into toddlers, while the number of motor modules increased, their activations across cycles also became less variable. The authors conclude that early motor exploration is driven by the variable activation of a small number of motor modules, which would later fractionate into more modules that are more stably recruited across step cycles.

    STRENGTHS:

    Overall, this work is a valuable addition to the growing literature on the development of motor modules. It not only emphasizes how motor variability is a hallmark of typical motor development, but also suggests the relatively new concept that development-related motor variability originates from the variable activations of early motor modules. Indeed, recent works have proposed that in human adults, the motor variability that drives early motor skill learning may likewise originate from the variable recruitment of motor modules. With this work, it may become possible to conceptually unite the provenance of motor variability that drives both early development and adult learning under the modularity framework. The authors are also commended for their huge effort in collecting this very valuable data from newborn infants and following them with multiple recording sessions till their walking onset. The demonstration of the same longitudinal trend in variability and modules in two different motor behaviors (stepping and kicking) is also highly appreciated.

    WEAKNESSES:

    The analysis of EMGs relies on a model of motor modules that assumes that multi-muscle activities across step cycles are generated by the variable activations of fixed spatial modules and fixed temporal modules (line 511); thus, by design, after the identification of the spatial (w_j in equation 511) and temporal (w_i(t) in equation 511) modules, the only variable that is adjustable for explaining motor variability is the modules' activation coefficient (a_ijs in equation 511). But it is possible that the observed EMG or kinematic variability may be equally, if not better, accounted for by the cycle-to-cycle variation of the spatial and/or the temporal modules themselves. In fact, the variances of any combination of w_j, w_i(t), and a_ijs may all contribute to EMG variability, even though with the present model, the variance of w_j and w_i(t) are not considered. Therefore, the conclusion that motor variability is generated by variable activations of fixed modules can only be argued based on how well a single model (i.e., line 511) describes the data, rather than by excluding other alternatives (but equally legitimate a priori) models with perhaps less explanatory power. Notably, recent works (e.g., Cheung et al., 2020, IEEE-OJEMB; Berger, d'Avella et al., 2022, JNP) have shown or implied that the variability of the spatial/temporal modules themselves, in addition to their activation coefficients, may be a source of learning-related motor variability.

  8. eLife

    Reviewer #3 (Public Review):

    Hinnekens et al. examined the development of humans' leg movements as they learn to step, kick, and independently walk during infancy. An established theory argues that motor movements can be composed of a finite set of building blocks ("motor primitives"), just like any word can be composed of a finite set of letters. In their paper, Hinnekens et al. follow up this theory by longitudinally recording muscle activations of infants using EMG (at three time points: a few days after birth, at 3 months, and shortly after they learned to walk independently). The authors examined two modules that underlie the infants' stepping and two modules that underlie toddler walking, all based on previous literature. The authors also examined different modules that underlie infants' upright stepping and supine kicking. The authors used supervised machine learning (an advanced version of factor analysis) to identify the modules and to track their change at the different developmental time points. The authors found that trial-to-trial variability in the structure of primitives reduces from newborns to toddlers, even though the number of primitives increased. The authors relate these findings to motor exploration by arguing that newborns generate high variability with a low number of primitives.

    The paper has one clear strength - its longitudinal recordings. Unlike most papers in this area of research, the authors follow the same individuals from birth until they learn to walk and the comparison between the use of primitives is done on the same infants. This is certainly novel.

    That said, the contribution of the paper to the literature is unclear and it suffers from some critical weaknesses that challenge the current conclusions in the paper, based on the existing data.

    1. Although the data is based on longitudinal recordings, and this is certainly desirable, the paper is based only on 10 infants. Moreover, only seven infants contributed supine data at the first time points and only six infants contributed upright data at the different time points. The paper would benefit from a more reliable dataset that includes more infants and time points to compare. To conclude the authors' conclusions, much richer data is required.

    2. Relatedly, although the strength of longitudinal data is compared between individuals and has significant insights into individual differences in development, this was not clearly (sometimes not at all) discussed in the paper. The work would benefit from more focus on individual differences and a clear explanation of its contribution to the field from that aspect. The key arguments in the paper focus on the ratio between the number of primitives and the variability in each time point, but none of this from the lens of individual differences. This is challenging to do because there are not many individuals who contribute to the dataset but otherwise, it is not clear what the paper contributes to previous work and more critically.

    3. The motivation for the paper is unclear. Why did the authors do what they did? Why is this important to do it the way they did? In the current manuscript, it is not clear why they used this design to get those conclusions.

    4. The data selection process is also not clear. At each time point and from each infant, the authors examined 5 cycles from the same leg. The definition of a cycle was hip-flexion onset to another hip-flexion onset on one side of hip extension. It is not clear what variability (measured by % of the cycle in flexion and extension) means in this case because infants hold their legs in one position for a long time. What are those 5 cycles? Why five? A lot of information is missing there about the arbitrary selection of analytic parameters. In addition, the authors argue they performed the same analyses with different parameters and that they got similar results. However, those results are not given in detail and it is hard to compare them with the authors' report.

    5. The recording times are not common across individuals. One newborn was recorded after 1 day and the other after 21 days. Not sure this is comparable, especially if the main contribution of the paper is the longitudinal data. Moreover, the second recording was conducted between 74 days to 122 days. This range is too broad. Same for the third time point - one walk onset is not reported, some infants were recorded at <380 days and some >500 days. This difference challenges the reliability of the data.

    6. Conceptually, I'm not sure I understand why the authors selected leg alternation (and not other types of movements) as their modules. I was not convinced that leg alternations reflect their real-life locomotor experience (e.g., short bouts in all directions), and therefore the variability measured in this work does not reflect the variability of infants' natural locomotor behaviour.

    7. There is not enough rationale for why the specific measurements (IEV, VAF, IRV, etc.) were used and why those are the appropriate ones for the address the questions in the paper. What is the justification for using those measurements?

    8. Some of the conclusions, especially those that relate to motor exploration, are not based on sufficient data. Motor exploration was not explicitly measured in this study, and how motor exploration is reflected by the current data and analyses is not clear.

  9. Version published to 10.1101/2022.05.05.490063v1 on bioRxiv