Caroline Heimhofer

Pupil size has been shown to reflect physical effort during brief, discrete motor tasks. It remains unknown whether pupil size similarly scales with effort during sustained repetitive movement, or whether it also reflects the accumulation of motor fatigability, a reduction in motor performance during prolonged movements. In our previous work, sustained maximal tapping induced motor slowing, a subtype of motor fatigability, characterized by decreasing movement speed and associated with increased antagonistic muscle coactivation. Next to these behavioural effects, pupil initially dilated and then gradually decreased over time. Whether this temporal change in pupil size is shaped by physical effort alone or also by motor fatigability remains unclear. Here, we combined a repetitive wrist tapping paradigm with force measurement, electromyography, and pupillometry, and paced participants at three different tapping speeds to dissociate physical effort from motor slowing, which has been shown to be speed-dependent. Fatigability-related motor slowing emerged selectively at the fastest speed. Moreover, we showed that antagonistic muscle coactivation increased more steeply at faster speeds, even in the absence of motor slowing, suggesting it may reflect an early change in motor control. While we found clear evidence that pupil size scaled with overall tapping speed, we did not find evidence that the temporal change of the pupil was pacing-dependent. These findings extend the pupil effort relationship to sustained, dynamic motor tasks and suggest that pupil size is a marker of physical effort but not motor fatigability during sustained repetitive movement.

Finger representations in the sensorimotor cortex can be activated even in the absence of somatosensory input or motor output through mere top-down processes, such as motor imagery. While executed finger movements activate finger representations in the primary sensorimotor cortex that are spatially consistent over time within participants, the stability of top-down activated finger representations remains largely unexplored. Given the increasing use of top-down activated sensorimotor representations to both plan implantation of and control brain-computer interfaces, it is crucial to understand the stability of these representations. Here, we investigated the spatial consistency, and thereby reliability, of finger representations activated through motor imagery in the primary somatosensory cortex over time. To assess this, participants performed imagined and executed individual finger movements in two 3T fMRI sessions that were ~2 weeks apart. We observed highly consistent univariate finger-selective activity clusters and multivariate vertex-wise activity patterns within participants over time in both the motor imagery and motor execution task. Using a multivariate across-tasks decoding approach, we further found that motor execution and motor imagery activate similar finger representations in the primary somatosensory cortex. This demonstrates that motor imagery can be used to identify finger representations related to movement execution. Our findings not only validate the use of top-down processes for brain-computer interface planning and control, but also open up new opportunities for the development of sensorimotor training interventions that do not rely on overt movements.

Reward can enhance motor performance. However, its potential to counteract motor fatigability, a reduction in motor performance during sustained movements, remains underinvestigated. This could be relevant in neurological conditions such as multiple sclerosis, where increased motor fatigability is a prominent symptom. One form of motor fatigability is motor slowing, a decline in movement speed over time evoked by fast, repetitive movements. In this study, we investigated whether the possibility to earn reward attenuates motor slowing, and examined associated changes in muscle activity and pupil size, a putative marker of physical effort. Participants performed a wrist tapping task at maximal voluntary speed with or without the possibility of earning a reward. We found that wrist tapping induced motor slowing and that slowing was significantly reduced by reward. Over time, tapping became more costly as indicated by higher muscle activity and coactivation per tap. This was accompanied by a sustained pupil dilation, which could not solely be explained by tapping speed. These findings suggest that, rather than restoring efficient motor control, reward attenuates motor slowing by allowing participants to access a performance reserve and invest more resources into the task, reflected by increased muscle activation per tap and sustained pupil dilation.

Crossover fatigability (CF) refers to the phenomenon in which fatigability is observed in the non-exercised homologous muscle. As the debate about the existence of CF and its underlying mechanisms is still ongoing and may be protocol-dependent, our study investigated whether CF can be evoked using fast repetitive movements at maximal speed, which have been shown to induce fatigability on the supraspinal level. These rapidly repeating movements induce motor slowing, an involuntary decrease in movement speed. We evoke fatigability through maximal speed finger tapping with one hand and subsequently assessed fast finger tapping performance of the contralateral hand. In two independent cohorts ( n = 16, n = 30), we demonstrated that CF can indeed be induced using a motor slowing paradigm. Our findings show that CF manifests as a reduced initial tapping speed in the other, non-exercised hand and as a reduced “movement reserve.” Notably, even a brief 10 s period of maximal speed finger tapping was sufficient to evoke this CF effect. Based on our current results and on previous findings, we suggest that CF evoked by motor slowing is unlikely to emerge peripherally and most likely reflects supraspinal mechanisms.

Reward can enhance motor performance. However, its potential to counteract motor fatigability, a reduction in motor performance during sustained movements, remains underinvestigated. This could be particularly relevant in neurological conditions such as multiple sclerosis, where increased motor fatigability is a prominent symptom. One form of motor fatigability is motor slowing, a decline in movement speed over time evoked by fast, repetitive movements. In this study, we investigated whether the possibility to earn reward attenuates motor slowing, and examined associated changes in muscle activity and pupil size, a putative marker of physical effort. Participants performed a wrist tapping task at maximal voluntary speed with or without the possibility of earning a reward. We found that wrist tapping induced motor slowing and that slowing was significantly reduced by reward. Over time, tapping became more costly as indicated by higher muscle activity and coactivation per tap. This was accompanied by a sustained pupil dilation, which could not solely be explained by tapping speed. These findings suggest that, rather than restoring efficient motor control, reward attenuates motor slowing by allowing participants to access a performance reserve and invest more resources into the task, reflected by increased muscle activation per tap and sustained pupil dilation.

Neurofeedback (NF) training based on motor imagery is increasingly used in neurorehabilitation with the aim to improve motor functions. However, the neuroplastic changes underpinning these improvements are poorly understood. Here, we used mental “finger individuation,” i.e., the selective facilitation of single finger representations without producing overt movements, as a model to study neuroplasticity induced by NF. To enhance mental finger individuation, we used transcranial magnetic stimulation (TMS)-based NF training. During motor imagery of individual finger movements, healthy female and male human participants were provided visual feedback on the size of motor evoked potentials, reflecting their finger-specific corticospinal excitability. We found that TMS-NF improved the mental activation of finger-specific representations. First, intracortical inhibitory circuits in the primary motor cortex were tuned after training such that inhibition was selectively reduced for the finger that was mentally activated. Second, motor imagery finger representations in areas of the sensorimotor system assessed with functional MRI became more distinct after training. Together, our results indicate that the neural underpinnings of finger individuation, a well-known model system for neuroplasticity, can be modified using TMS-NF guided motor imagery training. These findings demonstrate that TMS-NF induces neuroplasticity in the sensorimotor system, highlighting the promise of TMS-NF on the recovery of fine motor function.

Finger representations in the sensorimotor cortex can be activated even in the absence of somatosensory input or motor output through mere top-down processes, such as motor imagery. While executed finger movements activate finger representations in the primary sensorimotor cortex that are spatially consistent over time within participants, the stability of top-down activated finger representations remains largely unexplored. Given the increasing use of top-down activated sensorimotor representations to both plan implantation of and control brain-computer interfaces, it is crucial to understand the stability of these representations. Here, we investigated the spatial consistency, and thereby reliability, of finger representations activated through motor imagery in the primary somatosensory and primary motor cortex over time. To assess this, participants performed imagined and executed individual finger movements in two 3T fMRI sessions that were ∼2 weeks apart. We observed highly consistent univariate finger-selective activity clusters and multivariate vertex-wise activity patterns within participants over time in both the motor imagery and motor execution task. Using a multivariate across-task decoding approach, we further found that motor execution and motor imagery activate similar finger representations in both the primary somatosensory and primary motor cortex. This demonstrates that motor imagery can be used to identify finger representations related to movement execution. Our findings not only validate the use of top-down processes for brain-computer interface planning and control, but also open up new opportunities for the development of sensorimotor training interventions that do not rely on overt movements.

Summary: Deep sleep oscillations are proposed to be central in restoring brain function and to affect different aspects of motor performance such as facilitating the consolidation of motor sequences resulting in faster and more accurate sequence tapping. Yet, whether deep sleep modulates performance fatigability during fatiguing tasks remains unexplored. We investigated overnight changes in tapping speed and resistance against performance fatigability via a finger tapping task. During fast tapping, fatigability manifests as a reduction in speed (or “motor slowing”) which affects all tapping tasks, including motor sequences used to study motor memory formation. We further tested whether overnight changes in performance fatigability are influenced by enhancing deep sleep oscillations using auditory stimulation. We found an overnight increase in tapping speed alongside a reduction in performance fatigability and perceived workload. Auditory stimulation led to a global enhancement of slow waves and both slow and fast spindles during the stimulation window and a local increase in slow spindles in motor areas across the night. However, overnight performance improvements were not significantly modulated by auditory stimulation and changes in tapping speed or performance fatigability were not predicted by individual changes in deep sleep oscillations. Our findings demonstrate overnight changes in fatigability but revealed no evidence suggesting that this effect is causally linked to temporary augmentation of slow waves or sleep spindles. Our results are important for future studies using tapping tasks to test the relationship between sleep and motor memory consolidation, as overnight changes in objectively measured and subjectively perceived fatigue likely impact behavioural outcomes.

Introduction: Increased motor fatigability is a symptom of many neuromuscular and neurodegenerative disorders. However, it is difficult to pinpoint pathological motor fatigability, since the phenomena has not yet been fully characterized in the healthy population. In this study, we investigate how motor fatigability differs across age. Given that many disorders involve supraspinal components, we characterize motor fatigability with a paradigm that has previously been associated with supraspinal mechanisms. Finger tapping at maximal speed results in a rapid decrease in movement speed, which is a measure of motor fatigability.Methods: We collected finger tapping data in a field experiment from the general population with a smartphone app, and we investigated age differences in maximal tapping speed, as well as the decrease in tapping speed for the index, middle, and little fingers.Results: We found that the maximal tapping speed differed significantly between young (18–30 years, n = 194) and aged (50–70 years, n = 176), whereas the fatigability-induced relative decrease in movement speed did not differ between the age groups (average decrease: 17.0% ± 6.9% (young) vs. 16.5% ± 7.5% (aged) decrease). Furthermore, tapping speed and motor fatigability depended on which finger was used.Discussion: These findings might relate to dexterity, with more dexterous movements being more resistant to fatigue. In this study, we provide a characterization of motor fatigability in the general population which can be used as a comparison for clinical populations in the future.

Motor fatigability emerges when challenging motor tasks must be maintained over an extended period of time. It is frequently observed in everyday life and affects patients as well as healthy individuals. Motor fatigability can be measured using simple tasks like finger tapping at maximum speed for 30 s. This typically results in a rapid decrease of tapping frequency, a phenomenon called motor slowing. In a previous study (Bächinger et al, eLife, 8 (September), https://doi.org/10.7554/eLife.46750, 2019), we showed that motor slowing goes hand in hand with a gradual increase in blood oxygen level dependent signal in the primary sensorimotor cortex (SM1), supplementary motor area (SMA), and dorsal premotor cortex (PMd). It is unclear what drives the activity increase in SM1 caused by motor slowing and whether motor fatigability affects the dynamic interactions between SM1, SMA, and PMd. Here, we performed dynamic causal modelling (DCM) on data of 24 healthy young participants collected during functional magnetic resonance imaging to answer this question. The regions of interest (ROI) were defined based on the peak activation within SM1, SMA, and PMd. The model space consisted of bilateral connections between all ROI, with intrinsic self-modulation as inhibitory, and driving inputs set to premotor areas. Our findings revealed that motor slowing was associated with a significant reduction in SM1 self-inhibition, as uncovered by testing the maximum à posteriori against 0 (t(23)=-4.51, p < 0.001). Additionally, the model revealed a significant decrease in the driving input to premotor areas (t(23) > 2.71, p < 0.05) suggesting that structures other than cortical motor areas may contribute to motor fatigability.