nirs.modules.default_modules.FIR_model

See also nirs.modules.default_modules.basic_processing,
nirs.modules.default_modules.FIR_model,
nirs.modules.default_modules.group_analysis,
nirs.modules.default_modules.image_recon,
nirs.modules.default_modules.single_subject_dOD, and
nirs.modules.default_modules.single_subject.

Untitled

nirs.modules.default_modules.FIR_model

This module runs a default modules to get group level statistical analysis.
The following modules are included in this default: nirs.modules.RemoveStimLess, nirs.modules.FixNaNs, nirs.modules.Resample, nirs.modules.OpticalDensity, nirs.modules.TrimBaseLine, nirs.modules.AR_IRLS, and nirs.modules.MixedEffects.
Example Usage:
for i = 1:10
raw(i) = nirs.testing.simData([], @(t)nirs.testing.blockedStimDesign(t,15,25,2));
% task-based 15s duration, 25s between onset, and 2 conditions
end
 
job = nirs.modules.default_modules.FIR_model();
GroupStats = job.run(raw);
Import data module skipped: Data provided Hb created in workspace ……………………….Finished 1 of 10. ……………………….Finished 2 of 10. ……………………….Finished 3 of 10. ……………………….Finished 4 of 10. ……………………….Finished 5 of 10. ……………………….Finished 6 of 10. ……………………….Finished 7 of 10. ……………………….Finished 8 of 10. ……………………….Finished 9 of 10. ……………………….Finished 10 of 10. SubjStats created in workspace GroupStats created in workspace
 
% a contrast window based on time
GroupStats.ttest({‘A[3:8s]’}).draw(‘tstat’,[],‘p<0.05’)
ans =
1×2 Figure array: Figure Figure
 
% a contrast window using a tapered shape (based on the canonical model)
GroupStats.ttest({‘A[canonical]’}).draw(‘tstat’,[],‘p<0.05’,[],[],‘hbo’);
 
% a contast window based on the sample point (2-8 is the 2nd through 8th
% beta term and requires knowledge of the FIR binwidth).
GroupStats.ttest({‘A[2:8]’}).draw
ans =
1×2 Figure array: Figure Figure