Print

Print


Hi,

Does anyone have a custom shell script, or know if an FSL tool is planned, to allow easy calculation of the average HDR at the group/multi-session level?  (Or maybe this is in existence and I've overlooked it?)  Reposting as about to spend a lot of time doing this again.

Thanks –

Chris



From: Christopher Benjamin <[log in to unmask]<mailto:[log in to unmask]>>
Date: Mon, 28 Mar 2011 18:53:38 -0400
To: FSL - FMRIB's Software Library <[log in to unmask]<mailto:[log in to unmask]>>
Subject: Re: [FSL] best estimate of the shape of the HDR over repeated runs?

Hi, I've had this difficulty as well and adopted a similar strategy.  It takes a long time, but it makes sense…  I'd be very interested to here if there's a standard or automated way to do this.

Christopher

***
Peri-stimulus data extraction: To directly examine the average BOLD response to stimuli in key contrasts contrasts we examined data from the point of peak difference between the two conditions. Each participant had 2 sessions of data. We first averaged the response to trials of each condition within each session independently. The minimum signal value within each condition was then set to 0 to accommodate baseline session effects. Average BOLD signal response were calculated for these 26 sessions of data, and values for the three conditions of interest were finally normalized such that the values 0 and 1 reflected the minimum and maximum BOLD response for the condition in which contrasts indicated lesser activation.




On Mar 28, 2011, at 12:10 PM, Matthew Ward wrote:
I too have been struggling to generate an HDR that summarizes all of the inputs to a higher-level analysis.  And, given the drift between runs/imaging sessions, the only way I have to do this is to take the PS plots of each individual run, normalize them to 'baseline' and then average across the runs.  However, I run into the issue of slight differences in the temporal sampling in some runs.  Any suggestions as to how to streamline the process would be greatly appreciated.

Best,

Matthew Ward