Multi-timescale neural adaptation underlying long-term musculoskeletal reorganization

Reviewer #1 (Public review):

Summary:

Many studies have investigated adaptation to altered sensorimotor mappings or to an altered mechanical environment. This paper asks a different but also important question in motor control and neurorehabilitation: how does the brain adapt to changes in the controlled plant? The authors addressed this question by performing a tendon transfer surgery in two monkeys during which the swapped tendons flexing and extending the digits. They then monitored changes in task performance, muscle activation and kinematics post-recovery over several months, to assess changes in putative neural strategies.

Strengths:

(1) The authors performed complicated tendon transfer experiments to address their question of how the nervous system adapts to changes in the organisation of the neuromusculoskeletal system, and present very interesting data characterising neural (and in one monkey, also behavioural) changes post tendon transfer over several months.

(2) The fact that the authors had to employ to two slightly different tasks -one more artificial, the other more naturalistic- in the two monkeys and yet found qualitatively similar changes across them makes the findings more compelling.

(3) The paper is quite well written, and the analyses are sound, although some analyses could be improved (suggestions below).

Weaknesses:

(1) I think this is an important paper, paper but I'm puzzled about a tension in the results. On the one hand, it looks like the behavioural gains post-TT happen rather smoothly over time (Figure 5). On the other, muscle synergy activations changes abruptly at specific days (around day ~65 for Monkey A and around day ~45 for monkey B; e.g., Figure 6). How do the authors reconcile this tension? In other words, how do they think that this drastic behavioural transition can arise from what appears to be step-by-step, continuous changes in muscle coordination? Is it "just" subtle changes in movements/posture exploiting the mechanical coupling between wrist and finger movements combined with subtle changes in synergies and they just happen to all kick in at the same time? This feels to me the core of the paper and should be addressed more directly.

(2) The muscles synergy analyses, which are an important part of the paper, could be improved. In particular:

(2a) When measuring the cross-correlation between the activation of synergies, the authors should include error bars, and should also look at the lag between the signals.

(2b) Figure 7C and related figures, the authors state that the activation of muscle synergies revert to pre-TT patterns toward the end of the experiments. However, there are noticeable differences for both monkeys (at the end of the "task range" for synergy B for monkey A, and around 50 % task range for synergy B for monkey B). The authors should measure this, e.g., by quantifying the per-sample correlation between pre-TT and post-TT activation amplitudes. Same for Figures 8I,J, etc.

(2c) In Figures 9 and 10, the authors show the cross-correlation of the activation coefficients of different synergies; the authors should also look at the correlation between activation profiles because it provides additional information.

(2d) Figure 11: the authors talk about a key difference in how Synergy B (the extensor finger) evolved between monkeys post-TT. However, to me this figure feels more like a difference in quantity -the time course- than quality, since for both monkeys the aaEMG levels pretty much go back to close to baseline levels -even if there's a statistically significant difference only for Monkey B. What am I missing?

(2e) Lines 408-09 and above: The authors claim that "The development of a compensatory strategy, primarily involving the wrist flexor synergy (Synergy C), appears crucial for enabling the final phase of adaptation", which feels true intuitively and also based on the analysis in Figure 8, but Figure 11 suggests this is only true for Monkey A . How can these statements be reconciled?

(3) Experimental design: at least for the monkey who was trained on the "artificial task" (Monkey A), it would have been good if the authors had also tested him on naturalistic grasping, like the second monkey, to see to what extent the neural changes generalise across behaviours or are task-specific. Do the authors have some data that could be used to assessed this even if less systematically?

(4) Monkey's B behaviour pre-tendon transfer seems more variable than that of Monkey A (e.g., the larger error bars in Figure 5 compared to monkey A, the fluctuating cross-correlation between FDS pre and EDC post in Figure 6Q), this should be quantified to better ground the results since it also shows more variability post-TT.

(5) Minor: Figure 12 is interesting and supports the idea that monkeys may exploit the biomechanical coupling between wrist and fingers as part of their function recovery. It would be interesting to measure whether there is a change in such coupling (tenodesis) over time, e.g., by plotting change in wrist angle vs change in MCP angle as a scatter plot (one dot per trial), and in the same plot show all the days, colour coded by day. Would the relationship remain largely constant or fluctuate slightly early on? I feel this analysis could also help address my point (1) above.

Reviewer #2 (Public review):

Summary:

This study tackles an important question for both basic science understanding and translational relevance - how does the nervous system learn to control a changing body? Of course, all bodies change slowly over time, including basic parameters like size and weight distribution, but many types of diseases and injuries also alter the body and require neural adaptation to sustain normal control. A dramatic example from the clinic is the use of tendon transfer surgery in patients with near tetraplegia that allows them to use more proximal arm muscles to control the hand. Here, the authors sought to ask what strategies may be used when an animal adapts its motor control in response to tendon transfer. They focus on whether recovered functions leverage fractionated control over each muscle separately or, alternatively, whether there is evidence for modular control in which pre-existing synergies are recruited differently after the surgery. Overall, this work is very promising and advances the use of tendon transfer in animal models as a powerful way to study motor control flexibility, but the incomplete data and difficulty comparing between the two subjects mean that evidence is lacking for some of the conclusions.

Strengths:

A major strength of this paper is its motivating idea of using tendon transfer between flexor and extensor muscles in non-human primate wrist control to ask what adaptations are possible, how they evolve over time, and what might be the underlying neural control strategies. This is a creative and ambitious approach. Moreover, these surgeries are likely very challenging to do properly, and the authors rigorously documented the effectiveness of the transfer, particularly for Monkey A.

The results are promising, and there are two very interesting findings suggested by the data. First, when a single muscle out of a related group is manipulated, there is aberrant muscle activity detected across related muscles that are coordinated with each other and impacted as a group. For example, when the main finger extensor muscle now becomes a flexor, the timing of its activation is changed, and this is accompanied by similar changes in a more minor finger extensor as well as in wrist extensor muscles. This finding was observed in both monkeys and likely reflects a modular adaptive response. Second, there is a biphasic response in the weeks following injury, with an early phase in which the magnitude of an extensor synergy was increased and the timing of flexor and extensor recruitment was altered, followed by a later phase in which the timing and overall magnitude are restored.

Weaknesses:

The most notable weakness of the study is the incompleteness of the data. Monkey A has excellent quality EMG in all relevant muscles, but no analysis of video data, while Monkey B has some video data kinematics and moderate quality EMG, but the signal in the transferred FDS muscle was lost. These issues could be overcome by aligning data between the two monkeys, but the behavior tasks performed by each monkey are different, and so are the resulting muscle synergies detected (e.g., for synergies C and D), and different timepoints were analyzed in each monkey. As a result, it is difficult to make general conclusions from the study, and it awaits further analysis or the addition of another subject.

A second weakness is the insufficient analysis of the movements themselves, particularly for Monkey A. The main metrics analyzed were the time from task engagement (touch) to action onset and the time spent in an off-target location - neither of these measures can be related directly to muscle activity or the movement. Since the authors have video data for both monkeys, it is surprising that it was not used to extract landmarks for kinematic analysis, or at least hand/endpoint trajectory, and how it is adjusted over time. Adding more behavior data and aligning it with the EMG data would be very helpful for characterizing motor recovery and is needed to support conclusions about underlying neural control strategies for functional improvement.

Considering specific conclusions, the statement that the monkeys learned to use "tenodesis" over time by increasing activation of a wrist flexor muscle synergy does not seem to be fully supported by the data. Monkey A data includes EMG for two wrist flexors and a clear wrist flexor synergy, but it seems that, when comparing baseline and the final post-surgery timepoints, the main change is decreased activity around grasp after tendon transfer (at 0% of the task range if I understand this correctly) (Figure 8E and Figure S2-H vs R and -I vs S). It is clear that Monkey B increases the flexion of the wrist joint over time from the kinematic data, but the activity pattern in the only recorded wrist flexor (PL) doesn't change much with time (Figure S2-AN) and this monkey does not have a clear wrist flexor synergy (PL is active in the flexor synergy A while synergy C mainly reflects deltoid activity). Given these issues, it is not clear how to align the EMG and kinematic data and interpret these findings.

A more minor point regarding conclusions: statements about poor task performance and high energy expenditure being the costs that drive exploration for a new strategy are speculative and should be presented as such. Although the monkeys did take longer to complete the tasks after the surgery, they were still able to perform it successfully and in less than a second and no measurements of energy expenditure were taken.

A small concern is whether the tendon transfer effect may fail over time, either due to scar tissue formation or tendon tearing, and it would be ideal if the integrity of the intervention were re-assessed at the end of the study.

Reviewer #3 (Public review):

Summary:

In this study, Philipp et al. investigate how a monkey learns to compensate for a large, chronic biomechanical perturbation - a tendon transfer surgery, swapping the actions of two muscles that flex and extend the fingers. After performing the surgery and confirming that the muscle actions are swapped, the authors follow the monkeys' performance on grasping tasks over several months. There are several main findings:

(1) There is an initial stage of learning (around 60 days), where monkeys simply swap the activation timing of their flexors and extensors during the grasp task to compensate for the two swapped muscles.

(2) This is (seemingly paradoxically) followed by a stage where muscle activation timing returns almost to what it was pre-surgery, suggesting that monkeys suddenly swap to a new strategy that is better than the simple swap.

(3) Muscle synergies seem remarkably stable through the entire learning course, indicating that monkeys do not fractionate their muscle control to swap the activations of only the two transferred muscles.

(4) Muscle synergy activation shows a similar learning course, where the flexion synergy and extension synergy activations are temporarily swapped in the first learning stage and then revert to pre-surgery timing in the second learning stage.

(5) The second phase of learning seems to arise from making new, compensatory movements (supported by other muscle synergies) that get around the problem of swapped tendons.

Strengths:

This study is quite remarkable in scope, studying two monkeys over a period of months after a difficult tendon-transfer surgery. As the authors point out, this kind of perturbation is an excellent testbed for the kind of long-term learning that one might observe in a patient after stroke or injury, and provides unique benefits over more temporary perturbations like visuomotor transformations and studying learning through development. Moreover, while the two-stage learning course makes sense, I found the details to be genuinely surprising--specifically the fact that: (1) muscle synergies continue to be stable for months after the surgery, despite now being maladaptive; and (2) muscle activation timing reverts to pre-surgery levels by the end of the learning course. These two facts together initially make it seem like the monkey simply ignores the new biomechanics by the end of the learning course, but the authors do well to explain that this is mainly because the monkeys develop a new kind of movement to circumvent the surgical manipulation.

I found these results fascinating, especially in comparison to some recent work in motor cortex, showing that a monkey may be able to break correlations between the activities of motor cortical neurons, but only after several sessions of coaching and training (Oby et al. PNAS 2019). Even then, it seemed like the monkey was not fully breaking correlations but rather pushing existing correlations harder to succeed at the virtual task (a brain-computer interface with perturbed control).

Weaknesses:

I found the analysis to be reasonably well considered and relatively thorough. However, I do have a few suggestions that I think may elevate the work, should the authors choose to pursue them.

First, I find myself wondering about the physical healing process from the tendon transfer surgery and how it might contribute to the learning. Specifically, how long does it take for the tendons to heal and bear forces? If this itself takes a few months, it would be nice to see some discussion of this.

Second, I see that there are some changes in the muscle loadings for each synergy over the days, though they are relatively small. The authors mention that the cosine distances are very small for the conserved synergies compared to distances across synergies, but it would be good to get a sense for how variable this measure is within synergy. For example, what is the cosine similarity for a conserved synergy across different pre-surgery days? This might help inform whether the changes post-surgery are within a normal variation or whether they reflect important changes in how the muscles are being used over time.

Last, and maybe most difficult (and possibly out of scope for this work): I would have ideally liked to see some theoretical modeling of the biomechanics so I could more easily understand what the tendon transfer did or how specific synergies affect hand kinematics before and after the surgery. Especially given that the synergies remained consistent, such an analysis could be highly instructive for a reader or to suggest future perturbations to further probe the effects of tendon transfer on long-term learning.

Author response:

Thank you for the thorough assessment and insightful reviews of our manuscript, "Multi-timescale neural adaptation underlying long-term musculoskeletal reorganization." We are very encouraged by the positive evaluation – particularly the recognition of the study as "important" with "solid" evidence – and we appreciate the constructive feedback provided in the public reviews.

As requested, we would like to provide this provisional author response to accompany the first version of the Reviewed Preprint. While we plan to provide a detailed point-by-point response upon submission of the revised manuscript, this email outlines our overall revision plan based on the public reviews.

We found the reviewers' comments to be extremely helpful and largely aligned with our own assessment of areas for clarification and strengthening. We plan a full revision that will address all points raised.

Regarding Interpretations and Clarity:

Several comments focused on clarifying key interpretations. We agree with these suggestions and have already incorporated significant textual revisions into the manuscript to:

More explicitly articulate the proposed multi-timescale model that reconciles the smooth behavioral recovery with the abrupt neural shifts (addressing a core point from R1).

Refine the interpretation of the compensatory tenodesis strategy, clarifying the distinct neural implementations observed in each monkey and the crucial role of temporal re-timing versus amplitude scaling (addressing points from R1 and R2).

Correct our interpretation regarding the apparent differences in the "arms race" phenomenon, framing it more parsimoniously in terms of observational windows and individual adaptation rates (addressing R1).

Ensure consistent and unambiguous terminology (e.g., using "activation profiles") throughout the text and figure captions (addressing R1).

Carefully adjust language to distinguish between direct empirical findings and interpretations regarding concepts like energetic cost and the drivers of adaptation (addressing R2).

Explicitly address the potential confound of physical tendon healing, clarifying in the Methods and Discussion why our surgical technique allows us to interpret the findings primarily in terms of neural learning (addressing R3).

Regarding New Analyses and Data Presentation:

The reviewers also provided excellent suggestions for new analyses to enhance the rigor and depth of our findings. We plan to undertake these analyses for the full revision, including:

Adding measures of trial-to-trial variability (e.g., SEM envelopes) and time-lag analysis to our cross-correlation results (addressing R1).

Performing a point-by-point statistical comparison to better characterize the subtle differences between pre-surgery and final recovered synergy profiles (addressing R1).

Formally quantifying the baseline behavioral variability between the monkeys (addressing R1).

Creating a new kinematic plot visualizing the refinement of the tenodesis skill over time (addressing R1).

Establishing a baseline for normal day-to-day synergy variability by analyzing pre-surgery data (addressing R3).

Incorporating additional behavioral/kinematic data (pull times and grasp aperture) into Figure 5 to provide a clearer link between neural changes and functional recovery (addressing R2).

We have also noted the reviewers' suggestions regarding figure clarity and plan improvements where possible. We have already addressed some specific recommendations (e.g., elaborating captions for Figs 6 & 7, adding a supplementary table for muscle acronyms).

We plan to address the 'Recommendations for the authors' thoroughly during the preparation of the revised manuscript. We are very grateful for all these recommendations, as we are confident they will significantly improve the quality, clarity, and impact of our work. We hope that these comprehensive revisions might also strengthen the final eLife assessment.