Localizes the single equivalent current dipole that best explains a scalp
topography, by nonlinearly optimizing the dipole position (a grid search
inside the head sphere refined with Nelder-Mead) while the dipole moment is
the closed-form least-squares fit at each candidate position. Uses the same
forward physics as eegForwardModel() and the electrode positions from
colData / the montage. This is the classic focal-source complement to the
distributed inverses in eegSourceEstimate().
Usage
eegDipoleFit(
x,
time = NULL,
method = c("spherical", "bem_simplified"),
n_grid = 8L,
assay_name = NULL
)Arguments
- x
A
PhysioExperiment.- time
Sample index to fit (a single index), a length-2 range to average over, or
NULL(default) to fit the peak global-field-power sample.- method
Forward physics:
"spherical"(single-sphere) or"bem_simplified"(Berg-Scherg 3-shell).- n_grid
Grid resolution per axis for the initial search (default 8).
- assay_name
Assay to use (default: the object's default assay).
Value
An eeg_dipole_fit object: position (x, y, z in normalized head
radius), moment, orientation (unit), amplitude, gof (goodness of
fit, variance explained), residual, and the fitted/observed topographies.
Examples
pe <- make_eeg(n_time = 100, n_channels = 19, sr = 100)
fit <- eegDipoleFit(pe)
fit$gof
#> [1] 0.3307643