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Continuous Feature Term

Source: R/feature.R
feature.Rd

Specify a continuously sampled feature (for example RMS energy) to be convolved with an HRF via fmrihrf::feature_regressor(). Unlike hrf(), this is a time series, not a list of trials.

Usage

feature(
  x,
  dt = NULL,
  times = NULL,
  start = 0,
  center = TRUE,
  scale = c("none", "sd"),
  mask = NULL,
  basis = "spmg1",
  nbasis = 1,
  lag = 0,
  span = NULL,
  precision = NULL,
  id = NULL,
  name = NULL,
  prefix = NULL
)

Arguments

x

Numeric vector, matrix (samples x features), or a list of those (one per run).

dt

Positive sampling interval in seconds. Mutually exclusive with times.

times

Sample times in seconds, or a list of per-run time vectors. Mutually exclusive with dt.

start

Start time in seconds used only when dt is supplied. Defaults to 0.

center, scale, mask, span

Passed to fmrihrf::feature_regressor(). Centering and scaling are applied per run.

basis, nbasis, lag

HRF specification, as in hrf().

precision

Optional evaluation precision in seconds. When NULL (default), the event-model precision is used, then tightened to min(precision, dt).

id, name, prefix

Term identifier used for column names. If omitted, the name of x is used.

Value

A featurespec object for use on the RHS of an event_model() formula or in the list interface.

Details

x may be a numeric vector or a samples-by-features matrix (one run), or a list of those with one element per sampling_frame block. Supply exactly one of dt or times. Feature-only models are allowed: event_model(~ feature(x, dt = 0.1, id = "rms"), sampling_frame = sframe).

See also

fmrihrf::feature_regressor(), hrf(), event_model()

Examples

dt <- 0.5
rms <- abs(sin(seq(0, 20, by = dt)))
sframe <- sampling_frame(blocklens = 15, TR = 2)
emod <- event_model(
  ~ feature(rms, dt = dt, id = "rms", center = FALSE, scale = "none"),
  sampling_frame = sframe
)
ncol(design_matrix(emod))
#> [1] 1