Detect slow oscillations

Detects slow oscillations (SOs) in EEG channels using a zero-crossing approach in the delta band (0.5–2 Hz), following the algorithm described in Mölle et al. (2002) and implemented in YASA (Vallat & Walker, 2021).

Usage

compute_slow_oscillations(
  psg,
  channel = NULL,
  stages = NULL,
  freq_so = c(0.5, 2),
  amp_ptp_threshold_uv = c(75, 500),
  duration_pos_s = c(0.1, 1),
  duration_neg_s = c(0.1, 1.5)
)

Arguments

psg

An mrpheus_psg object from prepare_psg().

channel

Character. EEG channel label. If NULL (default), the first non-bad EEG channel is used.

stages

Integer vector or NULL. Epoch indices restricted to N2/N3. If NULL, detection runs across all epochs.

freq_so

Numeric vector of length 2. SO frequency band (Hz). Default c(0.5, 2).

amp_ptp_threshold_uv

Numeric vector of length 2. Min and max acceptable peak-to-peak amplitude (µV). Default c(75, 500).

duration_pos_s

Numeric vector of length 2. Min and max positive half- wave duration (s). Default c(0.1, 1.0).

duration_neg_s

Numeric vector of length 2. Min and max negative half- wave duration (s). Default c(0.1, 1.5).

Value

A tibble with one row per detected slow oscillation:

epoch

Integer.

start_s

Numeric. Onset (s) relative to epoch start.

end_s

Numeric. Offset (s) relative to epoch start.

duration_s

Numeric.

neg_peak_uv

Numeric. Negative peak amplitude (µV).

pos_peak_uv

Numeric. Positive peak amplitude (µV).

ptp_uv

Numeric. Peak-to-peak amplitude (µV).

channel

Character.

References

Mölle, M., Marshall, L., Gais, S., & Born, J. (2002). Grouping of spindle activity during slow oscillations in human non-rapid eye movement sleep. Journal of Neuroscience, 22(24), 10941–10947.

Vallat, R., & Walker, M. P. (2021). An open-source, high-performance tool for automated sleep staging. eLife, 10, e70092. doi:10.7554/eLife.70092