simTSrestingstate: Simulate fMRI resting state time series

View source: R/simTSrestingstate.R

simTSrestingstateR Documentation

Simulate fMRI resting state time series

Description

Synthesizes a single time series x representing resting state activity. The fluctuation frequencies f are limited to a square passband 0.01 Hz <= f <= 0.1 Hz. TR is the repetition time (needed to compute the passband limits), expressed in seconds. N is the required number of samples (needs not be a power of 2).

Usage

simTSrestingstate(nscan, base=0, TR, SNR=NULL, noise = c("none", "white",
	"temporal", "low-frequency", "physiological", "mixture"), 
	type = c("gaussian", "rician"), weights, verbose = TRUE, rho = 0.2,
	freq.low = 128, freq.heart = 1.17, freq.resp = 0.2, vee=1)

Arguments

nscan

Number of scans.

base

Baseline value of the time series.

TR

Repetition time in seconds.

SNR

Signal-to-noise ratio of the time series.

noise

Type of noise (white is default).

type

If noise==white, noise==mixture, type of system noise (gaussian is default).

weights

If noise==mixture, vector of weights to specify the fraction of the noise components.

verbose

Logical indicating if warnings should be returned.

rho

If noise==temporal or noise==mixture, value of autocorrelation coefficients. The length of the vector corresponds to the order of the autoregressive model.

freq.low

If noise==low-frequency or noise==mixture, frequency of the low-frequency drift in seconds.

freq.heart

If noise==physiological or noise==mixture, frequency of heart rate in Hz.

freq.resp

If noise==physiological or noise==mixture, frequency of respiratory rate in Hz.

vee

If type==rician, non-centrality parameter of the distribution.

Value

A vector representing the resting state time series

Author(s)

J. Durnez, G. Verdoolaege, M. Welvaert

References

[1] C.G. Fox, Computers & Geoscience, Vol. 13, pp. 369-374, 1987.

[2] M. Fukunaga, Magnetic Resonance Imaging, Vol. 24, pp. 979-992, 2006.

See Also

simTSfmri

Examples

out <- simTSrestingstate(nscan=50, TR=2, SNR=1, noise="none")
plot(out, type="l")


neuRosim documentation built on Oct. 18, 2023, 5:09 p.m.