Remove TMS pulse and recharge intervals

Replaces sample-exact closed pulse/recharge intervals by a linear or cubic Hermite bridge, or blanks them to zero or a trial-specific baseline. The selected input assay is preserved unless overwrite = TRUE.

Usage

removeTMSpulse(
  x,
  pulse_window_ms = c(-2, 10),
  recharge_windows_ms = NULL,
  method = c("cubic", "linear", "blank"),
  support_ms = 2,
  blank_value = c("baseline", "zero"),
  baseline_window_ms = c(-200, -20),
  epoch_start_ms = 0,
  assay_name = NULL,
  output_assay = "tms_pulse_clean",
  overwrite = FALSE
)

Arguments

x

A PhysioExperiment with time x channel or time x channel x trial data.

pulse_window_ms

Increasing pulse-window limits in milliseconds.

recharge_windows_ms

Optional increasing pair or n x 2 matrix.

method

Exactly "cubic", "linear", or "blank".

support_ms

One positive derivative-support duration for cubic interpolation, in milliseconds.

blank_value

Exactly "baseline" or "zero".

baseline_window_ms

Closed baseline interval in milliseconds.

epoch_start_ms

Time of the first sample relative to the pulse.

assay_name

Optional input assay name.

output_assay

Output assay name.

overwrite

Whether to overwrite the selected input assay.

Value

A modified PhysioExperiment with an appended TMS-EEG audit step.

Details

Closed intervals use round((time_ms - epoch_start_ms) / 1000 * sampling_rate) + 1. Overlapping or sample-adjacent pulse/recharge intervals are merged. Linear and cubic methods require real samples on both sides and never bridge across a second removed interval. Baseline settings do not affect interpolation or zero blanking. Baseline blanking requires at least two samples wholly outside every removed interval. The audit metadata contains the complete altered mask, merged sample ranges, continuity jumps, and robust baseline noise.

References

Rogasch NC, Sullivan C, Thomson RH, et al. (2017). Analysing concurrent transcranial magnetic stimulation and electroencephalographic data. NeuroImage, 147:934-951. doi:10.1016/j.neuroimage.2016.10.031