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Build an inter-muscle coordination network with a chosen estimator

Source: R/emg-network.R
coordinationNetwork.Rd

A single entry point over the four inter-muscle connectivity estimators (emgCoherenceNetwork(), emgPartialCoherenceNetwork(), emgWPLINetwork(), emgDirectedGCNetwork()): builds the coordination network of a multi-muscle EMG recording with the chosen method and routes the relevant parameters to the underlying estimator. Use it (with splitHalfStability()) to answer "which muscles co-activate, and is that structure real?".

Usage

coordinationNetwork(
  x,
  method = c("coherence", "partial_coherence", "wpli", "directed_gc"),
  freq_band = NULL,
  channels = NULL,
  nperseg = 256L,
  noverlap = NULL,
  max_lag = 10L,
  debiased = FALSE,
  assay_name = NULL,
  ...
)

Arguments

x

A PhysioExperiment holding a multi-channel EMG assay.

method

Estimator: "coherence" (magnitude-squared coherence), "partial_coherence" (coherence with shared influence removed), "wpli" (weighted phase-lag index), or "directed_gc" (directed Granger causality).

freq_band

Optional c(low, high) Hz band for the spectral estimators.

channels

Optional integer channel indices to include (default all).

nperseg, noverlap

Welch segment length / overlap for the spectral estimators (coherence / partial coherence / wPLI).

max_lag

Model order for directed Granger causality.

debiased

Use the debiased wPLI estimator.

assay_name

Assay to build the network from (default: the default assay).

...

Passed through to the underlying estimator.

Value

The estimator's network object – a list whose $network is the inter-muscle adjacency matrix.

See also

splitHalfStability(), emgCoordinationStructure(), emgCoherenceNetwork()

Examples

pe <- make_emg(n_time = 2000, n_channels = 4, sr = 1000)
net <- coordinationNetwork(pe, method = "coherence", freq_band = c(20, 150))
net$network
#>           EMG1      EMG2      EMG3      EMG4
#> EMG1 1.0000000 0.1807600 0.1152781 0.1406955
#> EMG2 0.1807600 1.0000000 0.1248851 0.1637571
#> EMG3 0.1152781 0.1248851 1.0000000 0.1360003
#> EMG4 0.1406955 0.1637571 0.1360003 1.0000000