Oh, I think I see now. In realty, each trial is either self or not self
and then you have a separate valence measure, so your coding should be
1. Self-offset
2. SelfValence
3. NoSelf-offset
4. NoSelfValence
Where 1+2 are used for a self event and 3+4 are used for a noself event.
If you want to test for the difference between self and noself valence
slope, then you would just use -a 2 -c 4
On 8/29/2022 12:08 PM, Angela Fang wrote:
External Email - Use Caution
Great, thanks so much Doug- this setup makes sense to me. However,
isn’t it a problem that the brain regions associated with the contrast
for -a 3 and the contrast for -a 4 would be the same for trials that
subjects rate as 1 (self-relevant) vs 0 (not self-relevant)? Could we
code it as 2 (self-relevant) and 1 (not self-relevant)?
Many thanks!!
*From: *<freesurfer-boun...@nmr.mgh.harvard.edu> on behalf of "Douglas
N. Greve" <dgr...@mgh.harvard.edu>
*Reply-To: *Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
*Date: *Sunday, August 28, 2022 at 1:07 PM
*To: *"freesurfer@nmr.mgh.harvard.edu" <freesurfer@nmr.mgh.harvard.edu>
*Subject: *Re: [Freesurfer] FSFAST first level covariates
I was under the impression that Self and Valence were ratings from the
same event (in that mail archive, they were different events and so
needed different offsets). If Self and Valence are from the same
event, then you would have something like
1. Offset
2. Self
3. Valence
4. Self*Valence
I've never tried the interaction (self*valence). You might have to
demean before computing the product
On 8/14/2022 4:58 PM, Angela Fang wrote:
* External Email - Use Caution *
The two coding schemes are different because the second one does
include the self*valence variable you’re talking about, whereas
the first one doesn’t. I only included the 2^nd offset because you
suggested to someone else to include it (see *MailScanner has
detected a possible fraud attempt from "secure-web.cisco.com"
claiming to be*
https://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg19957.html
<https://secure-web.cisco.com/1UvSz7SvjZnlE1QfkdS-VBc1GzXeZMYqUcsOqE3dGoo43anjoKIpvfs4NnozgTlCx23dB10wC_oFWTi8Zyazh1v1oufO7QQBf9hJanKAiwbu0cr4NfMvGMSOSaaOt5nSATHi-J-55MTqcCUhjz8_rRM1YuYWhtxzDVrlNJ5mD3QlEmdQlhRlYoneii_5mWjAZB1gcbpR_0Zl1nUaCy9BfmpcQRNLpIdfE1NMjg7OnqHOX5jAdPz1gGqxVTKgstTqx8RhxmTkDYOQPLc6hC3by-Atu2VfBnloD3GbZOzG04LjV1Of0uYaB6pk6oSsZFULTsifcwPSiwh1m9gKSg5lD7Q/https%3A%2F%2Fwww.mail-archive.com%2Ffreesurfer%40nmr.mgh.harvard.edu%2Fmsg19957.html>).
If we don’t need it, would it just be 2 conditions, as follows?
1. SelfOffset
2. Self*ValenceSlope
But then I’m not clear how to get the main effect of valence
(brain regions that scale with increasing emotion valence, while
holding self-relevance constant)?
*From: *<freesurfer-boun...@nmr.mgh.harvard.edu>
<mailto:freesurfer-boun...@nmr.mgh.harvard.edu> on behalf of
"Douglas N. Greve" <dgr...@mgh.harvard.edu>
<mailto:dgr...@mgh.harvard.edu>
*Reply-To: *Freesurfer support list
<freesurfer@nmr.mgh.harvard.edu>
<mailto:freesurfer@nmr.mgh.harvard.edu>
*Date: *Sunday, August 14, 2022 at 1:37 PM
*To: *"freesurfer@nmr.mgh.harvard.edu"
<mailto:freesurfer@nmr.mgh.harvard.edu>
<freesurfer@nmr.mgh.harvard.edu>
<mailto:freesurfer@nmr.mgh.harvard.edu>
*Subject: *Re: [Freesurfer] FSFAST first level covariates
Those look like they are the same coding scheme. What is
different? You can only have one offset. The Self vs Valence -a 2
-a 4 is not testing for an interaction. If you want an interaction
you have to create a new variable which is SelfRating*ValenceRating.
On 8/10/2022 2:38 PM, Angela Fang wrote:
* External Email - Use Caution *
Hello,
Just re-sending my question below. If I have a variable with 2
levels (yes/no) and another variable that is continuous, based
on this post (*MailScanner has detected a possible fraud
attempt from "secure-web.cisco.com" claiming to be*
https://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg19957.html
<https://secure-web.cisco.com/1S2s08xk6_r2FFsEB5S1KdOcfq6G8ToJwyZuNFONdwgOYd87JJkB-uznJW2pelg24KQwX3lweVOmFs99TCKitjbJOqKWgEH_UW7wir5JQ113csODerDntanBrEibOdt6Mxs2QeQ5D7n69Ds6NaOSOJIbLFeMjuoaTXCkNccNydn7jvjmVd0zW2YhEXG9JtLxMNVIYt8q48ZK0sJUt8sjTP6xuCzA1pzB19MUHA078Zgygtns0YVgn1n5Sg41ZbVZ3jWciX5ZF34AejW5nWj1Z4mWO1Xyd_7RwNbKkVMPeDwG6K9W59gzBf_t0G-AzmUhxGC8zfKM0bxA9hhZv4GR2BQ/https%3A%2F%2Fwww.mail-archive.com%2Ffreesurfer%40nmr.mgh.harvard.edu%2Fmsg19957.html>),
it sounds like I should code as follows:
1. SelfOffset
2. Self-ValenceSlope (would the weight in the 4^th column
reflect the value of self multiplied by the value of
valence for this participant?)
3. NonSelfOffset
4. NonSelf-ValenceSlope
If the other way of modifying the paradigm file is also
acceptable to test the interaction (as I describe below), that
would also be helpful to know.
Thanks!
Angela
*From: *<freesurfer-boun...@nmr.mgh.harvard.edu>
<mailto:freesurfer-boun...@nmr.mgh.harvard.edu> on behalf of
Angela Fang <angf...@uw.edu> <mailto:angf...@uw.edu>
*Reply-To: *Freesurfer support list
<freesurfer@nmr.mgh.harvard.edu>
<mailto:freesurfer@nmr.mgh.harvard.edu>
*Date: *Monday, August 1, 2022 at 4:35 PM
*To: *Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
<mailto:freesurfer@nmr.mgh.harvard.edu>
*Subject: *Re: [Freesurfer] FSFAST first level covariates
* External Email - Use Caution *
Hi Doug,
Nevermind to my first question! I read this post (*MailScanner
has detected a possible fraud attempt from
"secure-web.cisco.com" claiming to be*
https://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg32235.html
<https://secure-web.cisco.com/1646ymi0_yM9ab72e81bZdCKw_zNbXr9RihxDaiDVPq0_Qd4EXYgDmO56zQdi9l_AyV3uyyiURXHoYWQmiu56CbMuIGdZz8EH0gbsnVrAz9KwunZAwLzh0kh-jzVwHtlbEdd1ExEJYHT7o7JtUWg2GM484JTyL0VZJymRuGRyD0ag1nQ_0BPPjQHxPCqNHEU4Y_seBsq9XsUROgyR-bX-tHVXxhshVUHgneudw6tEB2lIVYfYrL3srRbjy1QN9Bq_e3_WaNCDhkXdixnae24i41HHYwJfn3KwsmNoZ2RxLoh3SMkXXwVntAewl8PeldBY0s3UxoEPiFbDdXXuJLUjlw/https%3A%2F%2Fwww.mail-archive.com%2Ffreesurfer%40nmr.mgh.harvard.edu%2Fmsg32235.html>)
and realized that we always include a subject-specific par
file in each run for first-level analyses.
However, I’m still confused about how to modify my paradigm
file. I also need to model the trials of non-interest, so
would it be as follows?
0 1 2.5 1.0 SelfOffset
0 2 2.5 1.0 SelfSlope (equal to
subject’s rating of self-relevance)
0 3 2.5 1.0 ValenceOffset
0 4 2.5 3.0 ValenceSlope (equal to
subject’s rating of valence)
2.5 0 2.5 1.0 FIXATION
5.0 1 2.5 1.0 SelfOffset
5.0 2 2.5 0 SelfSlope
(equal to subject’s rating of self-relevance, in this case
subject responded 0, or non-relevant)
5.0 3 2.5 1.0 ValenceOffset
5.0 4 2.5 2.0 ValenceSlope
(equal to subject’s rating of valence)
7.5 5 2.5 1.0 OTHER
Do these contrasts look correct to you?
Self vs Fixation -a 1 -c 0 (main effect of self)
Valence vs Fixation -a 3 -c 0 (main effect of valence)
Self vs Valence -a 2 -a 4 (interaction between self x valence)
Thank you so much for your help!
Angela
*From: *<freesurfer-boun...@nmr.mgh.harvard.edu>
<mailto:freesurfer-boun...@nmr.mgh.harvard.edu> on behalf of
Angela Fang <angf...@uw.edu> <mailto:angf...@uw.edu>
*Reply-To: *Freesurfer support list
<freesurfer@nmr.mgh.harvard.edu>
<mailto:freesurfer@nmr.mgh.harvard.edu>
*Date: *Thursday, July 28, 2022 at 1:02 PM
*To: *Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
<mailto:freesurfer@nmr.mgh.harvard.edu>
*Subject: *Re: [Freesurfer] FSFAST first level covariates
Thanks Doug. This wiki page is extremely helpful. However, my
question is about individual subject responses. I could see
how you could include a summary (e.g., average) value of the
parametric variable across subjects in your “weight” column
but it’s not clear to me how you could integrate individual
subject responses to each word in the parametric modulation
paradigm file? I’m imagining something like the FSGD file
where a value is given for each subject, but for first-level
analysis.
We have a similar design as someone else who posted a similar
question (*MailScanner has detected a possible fraud attempt
from "secure-web.cisco.com" claiming to be*
https://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg19957.html
<https://secure-web.cisco.com/11nFbIrJYBqRI1W_4wY-HvfdEF3GG6xLL8So8t0i9yKbcElVyl_nJoDI6XedAGY2kKd_eP-dnsWeccOw2qajd375GRCeiUjqaXv3C7vOkrGEOiSiqfcPQ9y73ROdtl0jJIGemdoYQDd3GcX-dKx6qDwBcPE_qNlqxB0ZTcsDfTwK88OkoVtftMo1zKBWSiZBV9p0GO2erUcSoXtVI-AITDr9jULRDzVL_IzxtPdtuSBrYXMASRi7ex2oKftjJjyG_HMgygf_ULhSYIsHviihCwfx4uO5_zrvh8H84AxAsv33zsFjOaYeZ826JkD3E99hxrAKW3jYr3PjfN-zNZjQLJA/https%3A%2F%2Fwww.mail-archive.com%2Ffreesurfer%40nmr.mgh.harvard.edu%2Fmsg19957.html>).
We have an event-related experiment presenting trait
adjectives in terms of whether they describe themselves (SELF
condition) or someone else (OTHER condition). We are
interested in testing a 2x2 ANOVA to examine an interaction
between self-relevance x emotional valence. Assuming you can’t
integrate individual subject responses to each word in the
paradigm file, would we set it up as follows?
“Usual” paradigm file:
0 1 2.5 1.0 SELF
2.5 0 2.5 1.0 FIXATION
5.0 1 2.5 1.0 SELF
7.5 2 2.5 1.0 OTHER
Parametric modulation paradigm file:
0 1 2.5 1.0 SELFoffset
0 2 2.5 0.8 SELFslope
0 3 2.5 1.0 VALENCEoffset
0 4 2.5 2.0 VALENCEslope
(where 0.8 reflects the percentage of time the word was
endorsed as self-relevant and 2.0 is the average valence
rating given for that word)
And then create a contrast of 2 vs 4 to test the interaction?
Would testing contrast 1 vs 0 be a test of the main effect of
self-relevance and contrast 3 vs 0 the main effect of valence?
Thanks so much for your help!
Angela
*From: *<freesurfer-boun...@nmr.mgh.harvard.edu>
<mailto:freesurfer-boun...@nmr.mgh.harvard.edu> on behalf of
"Douglas N. Greve" <dgr...@mgh.harvard.edu>
<mailto:dgr...@mgh.harvard.edu>
*Reply-To: *Freesurfer support list
<freesurfer@nmr.mgh.harvard.edu>
<mailto:freesurfer@nmr.mgh.harvard.edu>
*Date: *Thursday, July 28, 2022 at 10:25 AM
*To: *"freesurfer@nmr.mgh.harvard.edu"
<mailto:freesurfer@nmr.mgh.harvard.edu>
<freesurfer@nmr.mgh.harvard.edu>
<mailto:freesurfer@nmr.mgh.harvard.edu>
*Subject: *Re: [Freesurfer] FSFAST first level covariates
Yes, see *MailScanner has detected a possible fraud attempt
from "secure-web.cisco.com" claiming to be*
https://surfer.nmr.mgh.harvard.edu/fswiki/FsFastParametricModulation
<https://secure-web.cisco.com/1vlnv3wLgT6AWyuomHXVnJCfD3bAT8O6KYN-6kv4DVE_Kbs9JwI6WLDqHM7UN7cfJ1TP0eQKgCtR-KXf01ehJnqsV2jW5XmAXQr0QnOlGk4--dT54zncT2aoK1njMKmN9ayqCJ_tFar2vbW-JGXSkTcg6gdUPh_mngiG7m6SxtOvACvAKVHKQXKhe7-xx2QsCh6VDDkv9vQZNEkvMseg2bTElAE9tBG4Nyws1TeLoT6NRejWCSL4Hnke9bOJGLYp7gY561tg-SfXXlzjCNawo6cgCBAIxSsMzwLR8sWZndlid_nZ0aZqf85_HgcVXWUXEoKCbQCJ_Hs2G69KcjGr8yg/https%3A%2F%2Fsurfer.nmr.mgh.harvard.edu%2Ffswiki%2FFsFastParametricModulation>
On 7/25/2022 6:56 PM, Angela Fang wrote:
* External Email - Use Caution *
Hi Freesurfer community,
I have run participants through an event-related fMRI task
in which subjects rate whether trait adjectives are
descriptive of themselves or not, and afterwards asked
them to rate each trait word on emotional valence. Is it
possible to include these individual level subjective
ratings of emotional valence as covariates in the first
level contrast in FSFAST? If so, how?
Thanks,
Angela
---
Angela Fang, Ph.D.
Assistant Professor
Department of Psychology
University of Washington
Lab website: *MailScanner has detected a possible fraud
attempt from "secure-web.cisco.com" claiming to be*
www.uwconnectlab.com
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Pronouns: she, her, hers
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