Hi Doug et al,
*I think this email got lost in the cracks before the holidays, so I am
reposting*
We have been working on a linear regression-type analysis (see attached
analysis.info for analysis and slopepar for a sample paradigm file) that
involves task-related activation in a working memory test. For each
participant, there are four conditions: 1, 3, 5, and 7 items that need to
be remembered. The question that we would like to ask is: for each voxel,
does the slope of activation (i.e., the slope of the best-fit line as you
move from 1 to 3 to 5 to 7 items, as calculated separately for each
subject) differ from zero? The second-level analysis would determine if
there is a significant difference in activation-related slope between
groups.
Based on previous discussion, the way we have been doing this is to modify
the paradigm file to create the following contrast:
Condition 2: activation during working memory, but weighted by condition
so the 1 item condition is weighted as 1, the 3 item condition as 3,
etc.
Condition 0: fixation
The contrast is Condition 2 minus Condition 0.
However, this method of weighting does not appear to answer the question
about slope, but rather focuses on a weighted average.
Consider the following scenario, involving 5 subjects (A through E):
The SLOPE column is calculated using the slope function of the spreadsheet
(i.e., slope of best fit line, using values of 1...3...5...7 for the
x-axis, and, say, for subject A, the values of 2...4...6...8 for the
y-axis).
The WEIGHTED column is calculated in the way that I think FS-FAST is doing
it, which is as follows:
((1 * 1 item activ. value) + (3 * 3 item activ. value) + (5 * 5 item
activ. value) + (7 * 7 item activ. value))/4
The SLOPE and WEIGHTED values (regardless of their different scale) are
not really comparable. For example, for Subject A, the SLOPE value is 1
and the WEIGHTED value is 58, while for Subject E, the SLOPE value is 1.1
and the WEIGHTED value is 28.
So when looking at the paradigm file, take the lines
76.57 2 3.4 5
213.42 2 2.29 7
Does this mean that the activation at the first timepoint is accounted for
5-fold and the second timepoint 7-fold? If this is the case then this
analysis may not best represent what we are looking for.
Is there a way to modify the paradigm file so that the analysis can focus
on slope of the best fit line as opposed to the weighted average?
Thanks,
Josh
Forwarded from:
Adam Nitenson, B.S.
Brain Genomics Lab
Massachusetts General Hospital
nitenson(a)nmr.mgh.harvard.edu
Phone: 617-643-3215