Task-Dependent Motor Unit Recruitment and Rate Coding Reveal Redistribution of Neural Drive in the Human Hand

Reviewer #1 (Public review):

Summary:

Osswald and colleagues aim to show how motor units of the first dorsal interosseous (FDI) are flexibly recruited across two functionally different movements: index finger abduction and index finger flexion. They motivate this by arguing that FDI is the prime mover in abduction but acts as a synergist in flexion, alongside flexor digitorum profundus (FDP) and flexor digitorum superficialis (FDS) as the prime movers. This is a worthwhile question because it speaks to how descending neural inputs to the spinal cord flexibly control movement.

The authors claim that recruitment order and recruitment threshold of FDI motor units differ between abduction and flexion, and that beta-band intramuscular coherence is reduced when FDI acts as a synergist. However, there are significant methodological concerns that undermine the results and conclusions.

Strengths:

The study certainly aims to address a central question in motor neuroscience - how flexible recruitment of motor units occurs across movements where the same muscle changes its functional role. They correctly identify the FDI as a multi-functional muscle and use intramuscular high-density EMG arrays to record several motor units simultaneously, which is a major technical strength. They also track individual motor units between conditions and, therefore, have generated a potentially valuable dataset for studying spinal motor control across different movements.

Weaknesses:

The key limitation comes from the authors' interpretation of "neural drive" to FDI. The authors acknowledge that global EMG during flexion is smaller than that during abduction (for the same force), and surmise that the FDI receives different amounts of neural drive between these two movements, which is a potential confound for their analyses. To match the neural drive (i.e., global EMG), the authors ask participants to generate the same global EMG in flexion as in abduction; the forces generated by FDI are significantly different (2-3N for abduction and 1-8-6.2 for flexion). From this, they find changes in recruitment order, recruitment threshold, and beta coherence. However, different FDI motor units (and different muscle fibres) are active during abduction versus flexion. Using global EMG as a proxy for neural drive ignores this spatial separation of EMG generation during abduction and flexion, such that some amount of global EMG generated by one part of FDI (during abduction) is considered the same (from a neural drive perspective) as the same amount of EMG generated by a completely different part of FDI (during flexion). But these two global EMGs (during abduction and flexion) are not biologically equivalent because they are generated by different motor units and muscle fibres. Consequently, neural drive during flexion and abduction is not equivalent, which makes biological interpretation less clear. Furthermore, it is difficult to tell if abduction-versus-flexion differences are due to task role (prime mover vs synergist) or differences in force/mechanical demands, multi-muscle coordination, and spatial sampling limits of intramuscular recordings.

As mentioned, we think that the question asked is a very interesting one and framed appropriately to investigate the behaviour of motor units during prime mover and synergist roles. Simultaneously recording the prime movers for index flexion (FDP and FDS) would significantly improve the completeness of the study and allow for multi-muscle comparisons that are more relevant to how the motor system resolves prime mover vs synergist roles.

The authors use motor unit action potential as a proxy for motor unit size. This is not suitable because muscle fibres closer to the electrode will appear larger, independent of their true size. We advise that the authors remove analyses pertaining to motor unit size if it cannot be accurately measured.

Finally, several mechanistic interpretations in the discussion (e.g., spinal interneuronal suppression, reduced corticospinal input, proprioceptive mechanisms) read as more speculative than the current data can support without added controls or citations.

Reviewer #2 (Public review):

In this study, the authors examine whether the structure of motor unit (MU) recruitment and firing varies across movement directions in the human first dorsal interosseous (FDI) muscle. While task-dependent changes in MU recruitment have been reported previously (e.g., Thomas et al. 1986), these findings were largely based on recordings from a limited number of isolated single motor units. By applying high-density intramuscular electromyography and decomposition techniques, the authors demonstrate similar phenomena at the level of larger MU populations, thereby providing a useful consolidation of prior observations. In addition, they show that recruitment thresholds shift across tasks while the inverse relationship between discharge rate and recruitment threshold (the "onion-skin" organization) is preserved, suggesting that the overall structure of inputs to the motoneuron pool remains stable despite changes in recruitment order. Furthermore, by analyzing intramuscular coherence across MU firing, the authors attempt to characterize differences in the extent of synchronization among frequency components of neural inputs between abduction and flexion of the index finger. In particular, they report reduced beta-band coherence during flexion compared to abduction, indicating decreased synchronization in this frequency range (13-30Hz). This observation is noteworthy, as it points to potential differences in the neural inputs underlying these task-dependent changes.

A key strength of the study is that it extends prior work on task-dependent MU recruitment to larger populations using state-of-the-art recording and decomposition approaches. This represents a meaningful technical and conceptual advance over earlier studies limited to small numbers of units. The finding that recruitment shifts between flexion and abduction occur consistently across MUs, independent of motor unit size, further strengthens the robustness and generality of the observed phenomenon. Together, these results provide convincing evidence that MU recruitment is not strictly fixed by a rigid size principle across functional contexts and thus make a valuable contribution to the literature on motor control.

However, several aspects of the mechanistic interpretation are less well supported. The authors interpret their findings as reflecting a "redistribution" of net excitatory input to the motoneuron pool across tasks. While this is a plausible interpretation of the observed changes in recruitment thresholds and recruitment order, it is not directly demonstrated by the analyses presented. The current data do not clearly distinguish redistribution of inputs from alternative explanations, such as task-dependent modulation of shared versus independent inputs, or changes in the effective gain of existing pathways. As such, the evidence for a specific redistribution of input remains incomplete.

The interpretation of the intramuscular coherence analysis represents a further key weakness. By computing frequency-specific coherence across MUs during abduction (as a prime mover) and flexion (as a synergist), the authors report reduced beta-band coherence during flexion and interpret this as evidence for attenuated corticospinal input and increased involvement of spinal circuits. However, the relationship between changes in downstream coherence and the magnitude of upstream neural drive is not well established. Coherence reflects the synchronization of inputs rather than their net strength, and therefore, a reduction in coherence cannot be directly interpreted as a decrease in input from a specific source. Moreover, coherence measures alone do not permit identification of the origin of the inputs, and thus do not provide sufficient evidence to attribute the observed differences to descending or spinal pathways. While the difference between tasks is clear and potentially informative, the mechanistic interpretation appears overstated and should be treated more cautiously.

A related issue concerns the interpretation of the preserved RT-DR relationship. While this finding supports the presence of a stable common input structure across tasks, the additional claim that proprioceptive feedback contributes significantly to maintaining this organization is not clearly justified by the presented data. No direct evidence is provided to dissociate afferent from descending inputs, and the absence of task-dependent differences in lower-frequency coherence further limits support for this interpretation. As such, the proposed role of proprioceptive feedback appears speculative.

Overall, the authors successfully achieve their primary aim of demonstrating task-dependent flexibility in MU recruitment at the population level, and the results provide useful empirical support for this phenomenon using modern techniques. The study is likely to be of interest to researchers in motor control and neuromuscular physiology, particularly given the increasing relevance of MU-level analyses in both basic and applied contexts. However, the broader mechanistic conclusions regarding the nature and origin of the underlying neural inputs are not fully supported by the data and would benefit from more cautious interpretation or additional experimental evidence.