Task-Dependent Neural Drive Modulation in the Deltoid: Insights from High-Density EMG Mapping
Poster No:
1733
Submission Type:
Abstract Submission
Authors:
Giacomo Nardese1, Yuyao Ma2, Wolbert van den Hoorn1, Graham Kerr1, Paul Hodges2
Institutions:
1Queensland University of Technology, Brisbane, Queensland, 2University of Queensland, Brisbane, Queensland
First Author:
Co-Author(s):
Introduction:
Whether the motor cortex (M1) provides neural drive (ND) to specific motoneuron pools (MN) is rigidly or flexibly wired depending on task constraints remains unclear. Classic M1 mapping derived from motor-evoked potentials (MEPs) using transcranial magnetic stimulation (TMS) has limited spatial resolution. High-density electromyography (HDsEMG) might provide extensive insights into muscle activity patterns and their organisation over M1, especially in muscles with complex functions (e.g., deltoid muscle (DM)) (Gallina et al., 2017). We hypothesised that different motor tasks would induce changes in excitability across DM: certain M1 regions might evoke task-specific responses, reflecting the specialised roles of M1. Conversely, other M1 regions might steadily evoke MEPs irrespective of tasks, suggesting shared functions (Masse-Alarie et al., 2017).
Methods:
Anterior (AD), Middle (MD) and Posterior (PD) DM regions were mapped with TMS in 20 right-handed healthy adults. They performed isometric shoulder abduction (ABD) at 90°. In separate trials, they were provided with a 5% MVC feedback (FB) from each DM region. Hotspot and Active motor threshold (aMT) were identified for each region. Three series of 42 stimuli were delivered over a 7x6 cm M1 cortical grid at 120% aMT of the targeted portion. An HDsEMG muscle map was generated for each cortical grid site (Figure 1). After normalisation to MVC, differences between trials with FB from each DM region (i.e., AD-MD, PD-MD and AD-PD) were determined (example in Figure 2). HDsEMG grid locations are labelled as 1, 0 or -1 depending on whether the difference between FB pairs is >5% (i.e., excitability in the first FB is greater than the second FB; e.g., ADMD1), between 5 and -5% (i.e., no change between FBs; e.g. ADMD0) or <-5% (excitability in the first FB is lesser than the second FB; e.g., ADMD_1). A ±5% threshold is chosen to account for inter-trial and inter-subject MEP amplitude variability. An RM-ANOVA assessed the differences in HDsEMG grid locations label's amount across FBs. Significance level was set at 0.05 and Bonferroni correction was applied for post-hoc analysis.
Results:
Changes in excitability were not uniformly distributed across the HDsEMG grid and were task-dependent (Figure 1). MEP amplitude did not change in ~40% of HDsEMG grid locations irrespective of how the muscle was driven (ADMD0 vs PDMD0 vs ADPD0, F(1.468) = 0.762, p = 0.474). Different FBs affected how the excitability changed across HDsEMG grid locations (F(2.013) = 25.41, p < 0.001). AD and PD similarly increased the % of HDsEMG grid locations (ADMD1: 49.9(29.1)%; PDMD1: 53.0(28.2)%; p = 1.0) and to a greater extent when compared to MD (ADMD_1: 6.4(8.6)%, p < 0.001; PDMD_1: 6.7(10.5)%, p < 0.001). When compared, AD and PD show a similar % of HDsEMG grid locations (ADPD1: 31.8(28.7)%, 32(26.4)%, p = 0.985) even though in different locations (Figure 2).
Conclusions:
Excitability did not change for ~40% of the HDsEMG grid locations, suggesting that the three DM portions receive a common drive, regardless of the task. However, in the remaining ~60%, excitability changed according to the motor strategy, although with a different magnitude, suggesting that the CNS modulates ND based on the task requirement. DM was overall more excitable when driven by AD and PD compared to MD. This could be because AD and PD have lesser biomechanical advantages for pure ABD when compared to MD. Task-specific increases in excitability were spatially located in different HDsEMG locations, suggesting that the ND modulation might be associated with separate efferent pathways. Those results support previous findings that indicate that some MN pools are always involved in muscle control, but other MN pools are engaged in a task-specific manner (Gordon et al., 2023; Masse-Alarie et al., 2017).
Brain Stimulation:
TMS 2
Motor Behavior:
Motor Planning and Execution
Motor Behavior Other
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Cortical Anatomy and Brain Mapping 1
Novel Imaging Acquisition Methods:
Imaging Methods Other
Keywords:
Cortex
Motor
Plasticity
Transcranial Magnetic Stimulation (TMS)
Other - Mapping
1|2Indicates the priority used for review
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Provide references using APA citation style.
Gordon, E. M., Chauvin, R. J., Van, A. N., Rajesh, A., Nielsen, A., Newbold, D. J., Lynch, C. J., Seider, N. A., Krimmel, S. R., Scheidter, K. M., Monk, J., Miller, R. L., Metoki, A., Montez, D. F., Zheng, A., Elbau, I., Madison, T., Nishino, T., Myers, M. J., . . . Dosenbach, N. U. F. (2023). A somato-cognitive action network alternates with effector regions in motor cortex. Nature, 617(7960), 351-359. https://doi.org/10.1038/s41586-023-05964-2
Masse-Alarie, H., Bergin, M. J. G., Schneider, C., Schabrun, S., & Hodges, P. W. (2017). "Discrete peaks" of excitability and map overlap reveal task-specific organization of primary motor cortex for control of human forearm muscles. Hum Brain Mapp, 38(12), 6118-6132. https://doi.org/10.1002/hbm.23816