Network structure of the human musculoskeletal system shapes neural interactions on multiple timescales

Abstract

Human motor control requires the coordination of muscle activity under the anatomical constraints imposed by the musculoskeletal system. Interactions within the central nervous system are fundamental to motor coordination, but the principles governing functional integration remain poorly understood. We used network analysis to investigate the relationship between anatomical and functional connectivity amongst 36 muscles. Anatomical networks were defined by the physical connections between muscles and functional networks were based on intermuscular coherence assessed during postural tasks. We found a modular structure of functional networks that was strongly shaped by the anatomical constraints of the musculoskeletal system. Muscle networks exhibited a multilayer architecture with functional interactions at distinct timescales. Changes in postural tasks were associated with a frequency-dependent reconfiguration of the coupling between functional modules. Combined, these findings suggest these spectral modes may signify a coordinative structure for flexibly organising muscle activity during postural control. More broadly, our multi-level network approach to the motor system offers a unique window into the coordinated neural circuitry that generates synergistic input to muscles in different behaviours.not peer-reviewed)

Anatomical network analysis of the musculoskeletal system reveals integration loss and parcellation boost during the fins-to-limbs transition

“…Here, we formalized the anatomical organization of fins and limbs using network models that capture the basic physical relationships among bones and muscles. Working with network models of the musculoskeletal anatomy of appendages allows us to directly compare forms with incomplete homologies , to integrate skeletal and muscular data Molnar et al 2017;Santos et al 2017), and to quantify patterns of morphological complexity, integration, and modularity in a manner not available for comparative methods that focus on shape and size (Kerkman et al 2017; Esteve-Altava 2017a; Murphy et al 2018).…”

Information decomposition of multichannel EMG to map functional interactions in the distributed motor system

“…We previously showed that intermuscular coherence between postural muscles at different frequencies revealed distinct network topologies, which indicate the functioning of a multiplex network organization (Kerkman et al, 2018). Multivariate frequencydomain analysis of coupled processes can be used to assess frequency-dependent causal interactions in physiological time series (Faes and Nollo, 2011) and we have applied to assess frequency-dependent directed muscle networks (Boonstra et al, 2015).…”

“…Moreover, information measures provide a compact description of the dynamics which subsumes oscillatory behaviors in different frequency bands. For instance, an increased information storage, such as that observed in the AL muscles perturbing postural stability, likely reflects the emergence of dominant oscillatory activity in specific frequency bands, which is also related to higher intermuscular coherence (Kerkman et al, 2018).…”

“…We used multi-channel EMG data that was acquired from fourteen healthy participants (seven males and seven females; mean age, 25 ± 8 years; ten right-handed and four left-handed) while standing upright (Kerkman et al, 2018). The experiment was approved by the Ethics Committee Human Movement Sciences of the Vrije Universiteit Amsterdam (reference ECB 2014-78) and participants gave informed consent before participation.…”

“…We apply this approach to EMG activity recorded from multiple muscles distributed across the body while participants performed postural tasks. We previously used intermuscular coherence to map undirected functional muscle networks in this data (Kerkman et al, 2018). Here, we use conditional transfer entropy to map directed interactions between muscles and investigate their contribution in the coordination of the neuromuscular system during postural control.…”