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About hmrDeconvHRF_drift(Homer2)  


Ku
Posts: 3
 Ku
Customer
Topic starter
(@kuu)
New Member
Joined: 1 month ago

Hello, I’m Kuu.

Could you tell me what number should be input in “ParamsBasis”?

I use the GUI with MatlabRuntime and there is a little explanation of parameters.

So I cannot understand why the initial value are ”0.1 3.0 10.0 1.8 3.0 10.0” and how did you decide that?

Would somebody please tell me that.

 

Kind regards,

Thank you.

4 Replies
Meryem Yücel
Posts: 8
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(@mayucel)
Member
Joined: 6 months ago

Hi Kuu,

 

Please check out the below link:

 

https://github.com/BUNPC/Homer3/wiki/hmrR_GLM

 

 

Meryem

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1 Reply
Ku
 Ku
Customer
(@kuu)
Joined: 1 month ago

New Member
Posts: 3

@mayucel

Hello Meryem,

I have checked it. Thank you.

 

Kuu.

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David Boas
Posts: 42
(@dboas)
Eminent Member
Joined: 4 months ago

If you go into the processing stream GUI from the tool menu you can find the help for this function. I copy it below for your convenience.

Note that in Homer3 we now call this function hmrR_GLM and all the processing functions are documented on the wiki here as well as in the function help that you can find in the file itself or through the processing stream GUI.

The paramBasis options are described in the help. Please see below.

As described those are the values for % idxBasis=2 - [tau sigma T] applied to both HbO and HbR or [tau1 sigma1 T1 tau2 sigma2 T2]. Those parameters are used in the temporal basis function % 2 - a modified gamma function convolved with a square-wave of duration T. Set T=0 for no convolution. The modified gamma function is (exp(1)*(t-tau).^2/sigma^2) .* exp(-(tHRF-tau).^2/sigma^2)

I hope this helps.

David

 

% [yavg, yavgstd, tHRF, nTrials, ynew, yresid, ysum2, beta, R] =
% hmrDeconvHRF_DriftSS(y, s, t, SD, Aaux, tIncAuto, trange, glmSolveMethod, idxBasis, paramsBasis, rhoSD_ssThresh, flagSSmethod, driftOrder, flagMotionCorrect )
%
% UI NAME:
% GLM_HRF_Drift_SS
%
% This script estimates the HRF with options to specify the temporal basis
% function type and corresponding parameters, whether or not to perform
% simultaneous regression of short separation channels, drift order, and
% whether or not to correct for motion artifacts. You can also choose the
% method for solving the GLM matrix equation.
%
% INPUTS:
% y - this is the concentration data with dimensions #time points x [HbO/HbR/HbT] x #channels
% s - stimulation vector (# time points x #conditions)=1 at stim onset otherwise =0
% t - time vector corresponding with y and s
% SD - source detector stucture (units should be consistent with rhoSD_ssThresh)
% Aaux - A matrix of auxilliary regressors (#time points x #Aux channels)
% tIncAuto - a vector (#time points x 1) indicating which data time points
% are motion (=0) or not (=1)
% trange - defines the range for the block average [tPre tPost]
% glmSolveMethod - this specifies the GLM solution method to use
% 1 - use ordinary least squares (Ye et al (2009). NeuroImage, 44(2), 428?447.)
% 2 - use iterative weighted least squares (Barker,
% Aarabi, Huppert (2013). Biomedical optics express, 4(8), 1366?1379.)
% Note that we suggest driftOrder=0 for this method as
% otherwise it can produce spurious results.
% idxBasis - this specifies the type of basis function to use for the HRF
% 1 - a consecutive sequence of gaussian functions
% 2 - a modified gamma function convolved with a square-wave of
% duration T. Set T=0 for no convolution.
% The modified gamma function is
% (exp(1)*(t-tau).^2/sigma^2) .* exp(-(tHRF-tau).^2/sigma^2)
% 3 - a modified gamma function and its derivative convolved
% with a square-wave of duration T. Set T=0 for no convolution.
% 4- GAM function from 3dDeconvolve AFNI convolved with
% a square-wave of duration T. Set T=0 for no convolution.
% (t/(p*q))^p * exp(p-t/q)
% Defaults: p=8.6 q=0.547
% The peak is at time p*q. The FWHM is about 2.3*sqrt(p)*q.
% paramsBasis - Parameters for the basis function depends on idxBasis
% idxBasis=1 - [stdev step] where stdev is the width of the
% gaussian and step is the temporal spacing between
% consecutive gaussians
% idxBasis=2 - [tau sigma T] applied to both HbO and HbR
% or [tau1 sigma1 T1 tau2 sigma2 T2]
% where the 1 (2) indicates the parameters for HbO (HbR).
% idxBasis=3 - [tau sigma T] applied to both HbO and HbR
% or [tau1 sigma1 T1 tau2 sigma2 T2]
% where the 1 (2) indicates the parameters for HbO (HbR).
% idxBasis=4 - [p q T] applied to both HbO and HbR
% or [p1 q1 T1 p2 q2 T2]
% where the 1 (2) indicates the parameters for HbO (HbR).
% rhoSD_ssThresh - max distance for a short separation measurement. Set =0
% if you do not want to regress the short separation measurements.
% Follows the static estimate procedure described in Gagnon et al (2011).
% NeuroImage, 56(3), 1362?1371.
% flagSSmethod - 0 if short separation regression is performed with the nearest
% short separation channel.
% 1 if performed with the short separation channel with the
% greatest correlation.
% 2 if performed with average of all short separation channels.
% driftOrder - Polynomial drift correction of this order
% flagMotionCorrect - set to 1 to baseline correct between motion epochs indicated in tIncAuto, otherwise set to 0
%
% gstd - std for gaussian shape temporal basis function (sec)
% gms - mean for gaussian shape temporal basis function (sec)
%
% OUTPUTS:
% yavg - the averaged results
% ystd - the standard deviation across trials
% tHRF - the time vector
% nTrials - the number of trials averaged for each condition
% ynew - the model of the HRF with the residual. That is, it is the data y
% with the nuasance model parameters removed.
% yresid - the residual between the data y and the GLM fit
% ysum2 - an intermediate matrix for calculating stdev across runs
% beta - the coefficients of the temporal basis function fit for the HRF
% (#coefficients x HbX x #Channels x #conditions)
% R - the correlation coefficient of the GLM fit to the data
% (#Channels x HbX)
%
% LOG:

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Ku
Posts: 3
 Ku
Customer
Topic starter
(@kuu)
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Joined: 1 month ago

 

Hi David

 

Thank you for your response.

Your explanation really helped.

 

Kuu

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