Partial Directed Coherence (PDC)

Estimates frequency-resolved directed connectivity with Partial Directed Coherence (Baccala & Sameshima 2001), computed from the frequency-domain coefficient matrix \(\bar{A}(f)\) of an MVAR model (PhysioCore::mvarFit()). Unlike DTF, PDC reflects only direct channel-to-channel influences, so a purely indirect pathway gives PDC near zero. The (default) generalized PDC weights each row by the inverse residual standard deviation to make the measure scale-invariant (Baccala 2007). PDC satisfies \(\sum_i \mathrm{PDC}_{ij}(f)^2 = 1\) for each source \(j\) (outflow normalization).

Usage

eegPDC(
  x,
  order = NULL,
  freqs = NULL,
  generalized = TRUE,
  band = NULL,
  method = "ols",
  assay_name = NULL
)

Arguments

x

A PhysioExperiment object with 2D EEG data (time x channels).

order

MVAR model order, or NULL to select automatically.

freqs

Numeric vector of frequencies in Hz (default: 128 points from 0 to the Nyquist frequency).

generalized

Use generalized PDC (default: TRUE).

band

Optional numeric length-2 band in Hz over which to average the stored connectivity matrix (default: all frequencies).

method

MVAR estimator passed to PhysioCore::mvarFit() (default: "ols").

assay_name

Input assay name (default: the default assay).

Value

The PhysioExperiment with metadata(x)$connectivity set as in eegDTF() (a band-averaged directed matrix, the frequency-resolved array, frequencies, and settings).

References

Baccala, L. A., & Sameshima, K. (2001). Partial directed coherence: a new concept in neural structure determination. Biological Cybernetics, 84(6), 463-474.

See also

eegDTF(), eegConditionalGC(), eegConnectivityMatrix()

Examples

if (FALSE) { # \dontrun{
pe <- make_eeg(n_time = 4000, n_channels = 5, sr = 250)
pe <- eegPDC(pe, order = 5)
metadata(pe)$connectivity$matrix
} # }