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> on behalf of "Douglas
N. Greve" <dgr...@mgh.harvard.edu>
*Reply-To: *Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
*Date: *Sunday, August 14, 2022 at 1:37 PM
*To: *"freesurfer@nmr.mgh.harvard.edu" <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
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www.uwconnectlab.com
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Pronouns: she, her, hers
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