Research ArticleNEUROSCIENCE

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

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Science Advances  27 Jun 2018:
Vol. 4, no. 6, eaat0497
DOI: 10.1126/sciadv.aat0497
  • Fig. 1 Community structure of the anatomical muscle network.

    (A) Topological representation of the anatomical network. The nodes of the network represent the muscles, and the edges represent the anatomical connections between muscles that are attached to the same bone or connective tissue. The five modules are color-coded. (B) Spatial representation of anatomical muscle network displayed on the human body (53). The size of each node represents the number of other nodes it is connected to.

  • Fig. 2 Community structure of multiplex functional muscle networks.

    (A) Frequency spectra of the four components obtained using NNMF. (B) Multiplex community structure of functional muscle network across frequencies and conditions. The dominant hand of all participants is displayed on the right side of the human body. (C) Spatial representation of the average muscle network displayed on the human body (53). The size of the nodes represents the number of other nodes it is connected to and the width of the edges the number of edges across layers. (D) Binary muscle networks for each layer.

  • Fig. 3 Relationship between functional connectivity and anatomical distance.

    (A) Adjacency and distance matrix of the anatomical muscle network. The maximum anatomical distance (path length) is 4. (B) Percentage of functional edges of thresholded networks across experimental conditions as a function of anatomical distance. (C) Distribution of edge weights of functional networks as a function of anatomical distance for each layer. Weights were averaged across experimental conditions. Edges connecting muscles within the same module are color-coded (rUA, right upper arm; FA, bilateral forearms; T, torso; rUL, right upper leg; lUL, left upper leg; and LL, bilateral lower legs), and gray dots represent edges between modules.

  • Fig. 4 Clustered graphs of functional muscle networks across conditions.

    (A) Clustered graphs in the nine experimental conditions (columns) and the four frequency components (rows). The nodes are the modules identified using multiplex modularity analysis. Node size represents the network density within, and the width of the edges represents the connection density between modules. (B) Spatial representation of the functional modules on the human body: right upper arm (rUA), bilateral forearms (FA), torso (T), right upper leg (rUL), left upper leg (lUL), and bilateral lower legs (LL). We used toolboxes for geometry processing to generate the colored meshes (54) and display them on the human body (53). (C) Significant differences in the connectivity of the clustered graphs between the stability conditions. Two contrasts were assessed: normal stability–anterior-posterior instability and normal stability–medial-lateral instability. A permutation test was used, and family-wise error control was maintained using Bonferroni correction (84 comparisons). Significant differences (Pcorrected < 0.05) are color-coded: Red depicts an increase and blue depicts a decrease in the average weights. Colored edges and nodes depict significant changes in connectivity between and within modules, respectively. (D) Significant differences in the connectivity of the clustered graphs between the pointing conditions. Two contrasts were assessed: no pointing–unimanual pointing and no pointing–bimanual pointing.

  • Table 1 List of muscles.
    MuscleAbbreviation
    Tibialis anteriorTA
    Gastrocnemius caput medialeGM
    SoleusSOL
    Rectus femorisRF
    Biceps femorisBF
    Vastus lateralisVL
    Adductor longusAL
    Obliquus externus abdominisEO
    Pectoralis majorPMA
    SternocleidomastoideusSMA
    LongissimusLO
    Latissimus dorsiLD
    TrapeziusTZ
    DeltoideusD
    Biceps brachiiBB
    Triceps brachiiTRB
    Extensor digitorumED
    Flexor digitorum superficialisFDS
  • Table 2 Origin and insertion of muscles.

    Origin and insertion are based on gross human anatomy as described by Martini et al. (2), hence ignoring potential individual differences between participants.

    MuscleOrigin 1Origin 2Origin 3Insertion 1Insertion 2
    TATibiaOs cuneiforme medialeOssa metatarsi
    GMFemurCalcaneus
    SOLFibulaTibiaCalcaneus
    RFOs coxae*Os ilium*Tibia
    BFFemurOs ischii*FibulaTibia
    VLFemurTibia
    ALOs pubis*Femur
    EOCostae†‡Linea albaOs ilium*
    PMAClaviculaCostae†‡Sternum†‡Humerus
    SMAClaviculaSternum†‡Os temporale†§
    LOLigamentum sacrospinale*VertebraCostae†‡Vertebra
    LDCostae†‡Fascia thoracolumbalisVertebraHumerus
    TZLigamentum nuchaeOs occipitale†§VertebraClaviculaScapula
    DClaviculaScapulaHumerus
    BBScapulaRadius
    TRBHumerusScapulaUlna
    EDHumerusOssa digitorum
    FDSHumerusRadiusUlnaOssa digitorum

    *Part of the pelvis.

    †Connective structure on the midline of the body connecting bilateral muscles.

    ‡Part of the skeleton thoracis.

    §Part of the ossa cranii.

    Supplementary Materials

    • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/4/6/eaat0497/DC1

      section S1. Alternative anatomical muscle network

      section S2. Spinal nerve network

      section S3. Weighted functional networks

      fig. S1. The adjacency matrix of anatomical muscle networks.

      fig. S2. Community structure of the spinal nerve network.

      fig. S3. Community structure of weighted functional network.

      table S1. Spinal nerve innervation.

    • Supplementary Materials

      This PDF file includes:

      • section S1. Alternative anatomical muscle network
      • section S2. Spinal nerve network
      • section S3. Weighted functional networks
      • fig. S1. The adjacency matrix of anatomical muscle networks.
      • fig. S2. Community structure of the spinal nerve network.
      • fig. S3. Community structure of weighted functional network.
      • table S1. Spinal nerve innervation.

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