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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: http://secure-web.cisco.com/1EJiZPvng9zcCEb0OA91-g6prvoE6x8E2RuCN3eRqnJvVyWn...http://secure-web.cisco.com/1EJiZPvng9zcCEb0OA91-g6prvoE6x8E2RuCN3eRqnJvVyWnOZIhlVqHUDwmp2WEJbpju-V9f5K_n7JLkG1IXMgF6ntSJr6Aa91zEsfied2HyjVTkJZCXxMUYkbVQwHF0Z6PuuEgJy0xZF4iWLQMnW1WHJWnTXmRF8Gn92JXWkNX3veeq3YElwnE8vUuXUBgXGmmFtbKV7dJKfvdquLkJq0ApBJuwyNBrhKCoiBCQx4GIbuAfZ0iAsH5aL5xid2f1julAWTaA4EyB2BlTn9hUZcuoJNQPs89B-fNI4SA4inRY7YD67lmo-MehxlSgl0xO/http%3A%2F%2Fwww.uwconnectlab.com Pronouns: she, her, hers
Yes, see https://surfer.nmr.mgh.harvard.edu/fswiki/FsFastParametricModulation
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 http://secure-web.cisco.com/1EJiZPvng9zcCEb0OA91-g6prvoE6x8E2RuCN3eRqnJvVyWnOZIhlVqHUDwmp2WEJbpju-V9f5K_n7JLkG1IXMgF6ntSJr6Aa91zEsfied2HyjVTkJZCXxMUYkbVQwHF0Z6PuuEgJy0xZF4iWLQMnW1WHJWnTXmRF8Gn92JXWkNX3veeq3YElwnE8vUuXUBgXGmmFtbKV7dJKfvdquLkJq0ApBJuwyNBrhKCoiBCQx4GIbuAfZ0iAsH5aL5xid2f1julAWTaA4EyB2BlTn9hUZcuoJNQPs89B-fNI4SA4inRY7YD67lmo-MehxlSgl0xO/http%3A%2F%2Fwww.uwconnectlab.com
Pronouns: she, her, hers
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
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 (https://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg19957.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-bounces@nmr.mgh.harvard.edu on behalf of "Douglas N. Greve" dgreve@mgh.harvard.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edu Date: Thursday, July 28, 2022 at 10:25 AM To: "freesurfer@nmr.mgh.harvard.edu" freesurfer@nmr.mgh.harvard.edu Subject: Re: [Freesurfer] FSFAST first level covariates
Yes, see https://surfer.nmr.mgh.harvard.edu/fswiki/FsFastParametricModulation
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.comhttp://secure-web.cisco.com/1EJiZPvng9zcCEb0OA91-g6prvoE6x8E2RuCN3eRqnJvVyWnOZIhlVqHUDwmp2WEJbpju-V9f5K_n7JLkG1IXMgF6ntSJr6Aa91zEsfied2HyjVTkJZCXxMUYkbVQwHF0Z6PuuEgJy0xZF4iWLQMnW1WHJWnTXmRF8Gn92JXWkNX3veeq3YElwnE8vUuXUBgXGmmFtbKV7dJKfvdquLkJq0ApBJuwyNBrhKCoiBCQx4GIbuAfZ0iAsH5aL5xid2f1julAWTaA4EyB2BlTn9hUZcuoJNQPs89B-fNI4SA4inRY7YD67lmo-MehxlSgl0xO/http%3A%2F%2Fwww.uwconnectlab.com Pronouns: she, her, hers
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Hi Doug,
Nevermind to my first question! I read this post (https://secure-web.cisco.com/1646ymi0_yM9ab72e81bZdCKw_zNbXr9RihxDaiDVPq0_Qd...) 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-bounces@nmr.mgh.harvard.edu on behalf of Angela Fang angfang@uw.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edu Date: Thursday, July 28, 2022 at 1:02 PM To: Freesurfer support list 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 (https://secure-web.cisco.com/11nFbIrJYBqRI1W_4wY-HvfdEF3GG6xLL8So8t0i9yKbcEl...). 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-bounces@nmr.mgh.harvard.edu on behalf of "Douglas N. Greve" dgreve@mgh.harvard.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edu Date: Thursday, July 28, 2022 at 10:25 AM To: "freesurfer@nmr.mgh.harvard.edu" freesurfer@nmr.mgh.harvard.edu Subject: Re: [Freesurfer] FSFAST first level covariates
Yes, see https://secure-web.cisco.com/1vlnv3wLgT6AWyuomHXVnJCfD3bAT8O6KYN-6kv4DVE_Kbs... 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 http://secure-web.cisco.com/1QS44pCsFdNu8nsja7kOq-RG6npJErNuoBZVi-WfWdS_BXx3...http://secure-web.cisco.com/1EJiZPvng9zcCEb0OA91-g6prvoE6x8E2RuCN3eRqnJvVyWnOZIhlVqHUDwmp2WEJbpju-V9f5K_n7JLkG1IXMgF6ntSJr6Aa91zEsfied2HyjVTkJZCXxMUYkbVQwHF0Z6PuuEgJy0xZF4iWLQMnW1WHJWnTXmRF8Gn92JXWkNX3veeq3YElwnE8vUuXUBgXGmmFtbKV7dJKfvdquLkJq0ApBJuwyNBrhKCoiBCQx4GIbuAfZ0iAsH5aL5xid2f1julAWTaA4EyB2BlTn9hUZcuoJNQPs89B-fNI4SA4inRY7YD67lmo-MehxlSgl0xO/http%3A%2F%2Fwww.uwconnectlab.com Pronouns: she, her, hers
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Freesurfer@nmr.mgh.harvard.edumailto:Freesurfer@nmr.mgh.harvard.edu
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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 (https://secure-web.cisco.com/1S2s08xk6_r2FFsEB5S1KdOcfq6G8ToJwyZuNFONdwgOYd8...), it sounds like I should code as follows:
1. SelfOffset 2. Self-ValenceSlope (would the weight in the 4th 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-bounces@nmr.mgh.harvard.edu on behalf of Angela Fang angfang@uw.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edu Date: Monday, August 1, 2022 at 4:35 PM To: Freesurfer support list 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://secure-web.cisco.com/1CMVIrMV5SzmWczLBYJ8wrbs4I4fTd5TDfoZl4aAcMRL9BI...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-bounces@nmr.mgh.harvard.edu on behalf of Angela Fang angfang@uw.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edu Date: Thursday, July 28, 2022 at 1:02 PM To: Freesurfer support list 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://secure-web.cisco.com/1S2s08xk6_r2FFsEB5S1KdOcfq6G8ToJwyZuNFONdwgOYd8...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-bounces@nmr.mgh.harvard.edu on behalf of "Douglas N. Greve" dgreve@mgh.harvard.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edu Date: Thursday, July 28, 2022 at 10:25 AM To: "freesurfer@nmr.mgh.harvard.edu" 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://secure-web.cisco.com/1KeBzFuQ6BmCpgnS7C_rpoVtyJ_2fWtO57IvwDMHqHbicHV...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 http://secure-web.cisco.com/1fQQYQjuvvIyegjwuhG_ZMa3obBJzRDJ-iMMRorbhFwYE1uU...http://secure-web.cisco.com/1EJiZPvng9zcCEb0OA91-g6prvoE6x8E2RuCN3eRqnJvVyWnOZIhlVqHUDwmp2WEJbpju-V9f5K_n7JLkG1IXMgF6ntSJr6Aa91zEsfied2HyjVTkJZCXxMUYkbVQwHF0Z6PuuEgJy0xZF4iWLQMnW1WHJWnTXmRF8Gn92JXWkNX3veeq3YElwnE8vUuXUBgXGmmFtbKV7dJKfvdquLkJq0ApBJuwyNBrhKCoiBCQx4GIbuAfZ0iAsH5aL5xid2f1julAWTaA4EyB2BlTn9hUZcuoJNQPs89B-fNI4SA4inRY7YD67lmo-MehxlSgl0xO/http%3A%2F%2Fwww.uwconnectlab.com Pronouns: she, her, hers
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Freesurfer@nmr.mgh.harvard.edumailto:Freesurfer@nmr.mgh.harvard.edu
MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be https://secure-web.cisco.com/1jFjqS9IyNOVs3s3Y70hEz0N9lJCQJbdXFa3B531-LTrhGO...https://secure-web.cisco.com/1EIAJa3Vy8ViZunXEQlBqUeh89Z7hfnnmjv7DeFVsTGR2Flz9jn4bCu1dyuSCsHExp1254fEb-3HSfv_I0wnhZVOmxSlCgQ5W60PZLZ4fD7viMK9Vd4bddOCe3voLZt-bfajyrS85ddBk6F4OSk79smF2rXnEb0HPuZuwRHA1trnMRnDI6lw5vKTMZDtUpQ-uTFSKEWRF8-za7m4KgVPY3fvUsg_Vbe7BdVSF7LLb3z9K_jpTuId2AnuH3bM3sjJBCDBRuN-o1kc7VbRHE3c8w26Oh-Q_23VPqL5zPdyWBydZK2cexYD7WJa7ADaeuH6LHpS-9wtePP21o-y_utC43A/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer
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:
- SelfOffset
- Self-ValenceSlope (would the weight in the 4^th column reflect the value of self multiplied by the value of valence for this participant?)
- NonSelfOffset
- 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-bounces@nmr.mgh.harvard.edu on behalf of Angela Fang angfang@uw.edu *Reply-To: *Freesurfer support list freesurfer@nmr.mgh.harvard.edu *Date: *Monday, August 1, 2022 at 4:35 PM *To: *Freesurfer support list 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-bounces@nmr.mgh.harvard.edu on behalf of Angela Fang angfang@uw.edu *Reply-To: *Freesurfer support list freesurfer@nmr.mgh.harvard.edu *Date: *Thursday, July 28, 2022 at 1:02 PM *To: *Freesurfer support list 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-bounces@nmr.mgh.harvard.edu on behalf of "Douglas N. Greve" dgreve@mgh.harvard.edu *Reply-To: *Freesurfer support list freesurfer@nmr.mgh.harvard.edu *Date: *Thursday, July 28, 2022 at 10:25 AM *To: *"freesurfer@nmr.mgh.harvard.edu" 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 <http://secure-web.cisco.com/1EJiZPvng9zcCEb0OA91-g6prvoE6x8E2RuCN3eRqnJvVyWnOZIhlVqHUDwmp2WEJbpju-V9f5K_n7JLkG1IXMgF6ntSJr6Aa91zEsfied2HyjVTkJZCXxMUYkbVQwHF0Z6PuuEgJy0xZF4iWLQMnW1WHJWnTXmRF8Gn92JXWkNX3veeq3YElwnE8vUuXUBgXGmmFtbKV7dJKfvdquLkJq0ApBJuwyNBrhKCoiBCQx4GIbuAfZ0iAsH5aL5xid2f1julAWTaA4EyB2BlTn9hUZcuoJNQPs89B-fNI4SA4inRY7YD67lmo-MehxlSgl0xO/http%3A%2F%2Fwww.uwconnectlab.com> Pronouns: she, her, hers _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://secure-web.cisco.com/1EIAJa3Vy8ViZunXEQlBqUeh89Z7hfnnmjv7DeFVsTGR2Flz9jn4bCu1dyuSCsHExp1254fEb-3HSfv_I0wnhZVOmxSlCgQ5W60PZLZ4fD7viMK9Vd4bddOCe3voLZt-bfajyrS85ddBk6F4OSk79smF2rXnEb0HPuZuwRHA1trnMRnDI6lw5vKTMZDtUpQ-uTFSKEWRF8-za7m4KgVPY3fvUsg_Vbe7BdVSF7LLb3z9K_jpTuId2AnuH3bM3sjJBCDBRuN-o1kc7VbRHE3c8w26Oh-Q_23VPqL5zPdyWBydZK2cexYD7WJa7ADaeuH6LHpS-9wtePP21o-y_utC43A/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer>
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
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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 2nd offset because you suggested to someone else to include it (see https://secure-web.cisco.com/1UvSz7SvjZnlE1QfkdS-VBc1GzXeZMYqUcsOqE3dGoo43an...). 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-bounces@nmr.mgh.harvard.edu on behalf of "Douglas N. Greve" dgreve@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://secure-web.cisco.com/1UvSz7SvjZnlE1QfkdS-VBc1GzXeZMYqUcsOqE3dGoo43an...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 4th 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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Angela Fang angfang@uw.edumailto:angfang@uw.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto:freesurfer@nmr.mgh.harvard.edu Date: Monday, August 1, 2022 at 4:35 PM To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto: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://secure-web.cisco.com/1HVMVTjRAiW9L4gY48Veh_kfiv1-IcKlH19YGnZA4uiivgC...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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Angela Fang angfang@uw.edumailto:angfang@uw.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto:freesurfer@nmr.mgh.harvard.edu Date: Thursday, July 28, 2022 at 1:02 PM To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto: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://secure-web.cisco.com/1UvSz7SvjZnlE1QfkdS-VBc1GzXeZMYqUcsOqE3dGoo43an...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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu on behalf of "Douglas N. Greve" dgreve@mgh.harvard.edumailto:dgreve@mgh.harvard.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto: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.edumailto: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://secure-web.cisco.com/1bgmzz_9tTMWvh4BzMGrwjHQ2D5_roGg0hrYzue5vjRIg8U...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 http://secure-web.cisco.com/1Hp71z1cC-eBlP7rsnRthI3pC6fSTDX71Tdura97djs9Thbh...http://secure-web.cisco.com/1EJiZPvng9zcCEb0OA91-g6prvoE6x8E2RuCN3eRqnJvVyWnOZIhlVqHUDwmp2WEJbpju-V9f5K_n7JLkG1IXMgF6ntSJr6Aa91zEsfied2HyjVTkJZCXxMUYkbVQwHF0Z6PuuEgJy0xZF4iWLQMnW1WHJWnTXmRF8Gn92JXWkNX3veeq3YElwnE8vUuXUBgXGmmFtbKV7dJKfvdquLkJq0ApBJuwyNBrhKCoiBCQx4GIbuAfZ0iAsH5aL5xid2f1julAWTaA4EyB2BlTn9hUZcuoJNQPs89B-fNI4SA4inRY7YD67lmo-MehxlSgl0xO/http%3A%2F%2Fwww.uwconnectlab.com Pronouns: she, her, hers
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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?
- SelfOffset
- 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-bounces@nmr.mgh.harvard.edu on behalf of "Douglas N. Greve" dgreve@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-bounces@nmr.mgh.harvard.edu> <mailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Angela Fang <angfang@uw.edu> <mailto:angfang@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-bounces@nmr.mgh.harvard.edu> <mailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Angela Fang <angfang@uw.edu> <mailto:angfang@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-bounces@nmr.mgh.harvard.edu> <mailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of "Douglas N. Greve" <dgreve@mgh.harvard.edu> <mailto:dgreve@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 <http://secure-web.cisco.com/1EJiZPvng9zcCEb0OA91-g6prvoE6x8E2RuCN3eRqnJvVyWnOZIhlVqHUDwmp2WEJbpju-V9f5K_n7JLkG1IXMgF6ntSJr6Aa91zEsfied2HyjVTkJZCXxMUYkbVQwHF0Z6PuuEgJy0xZF4iWLQMnW1WHJWnTXmRF8Gn92JXWkNX3veeq3YElwnE8vUuXUBgXGmmFtbKV7dJKfvdquLkJq0ApBJuwyNBrhKCoiBCQx4GIbuAfZ0iAsH5aL5xid2f1julAWTaA4EyB2BlTn9hUZcuoJNQPs89B-fNI4SA4inRY7YD67lmo-MehxlSgl0xO/http%3A%2F%2Fwww.uwconnectlab.com> Pronouns: she, her, hers _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://secure-web.cisco.com/1EIAJa3Vy8ViZunXEQlBqUeh89Z7hfnnmjv7DeFVsTGR2Flz9jn4bCu1dyuSCsHExp1254fEb-3HSfv_I0wnhZVOmxSlCgQ5W60PZLZ4fD7viMK9Vd4bddOCe3voLZt-bfajyrS85ddBk6F4OSk79smF2rXnEb0HPuZuwRHA1trnMRnDI6lw5vKTMZDtUpQ-uTFSKEWRF8-za7m4KgVPY3fvUsg_Vbe7BdVSF7LLb3z9K_jpTuId2AnuH3bM3sjJBCDBRuN-o1kc7VbRHE3c8w26Oh-Q_23VPqL5zPdyWBydZK2cexYD7WJa7ADaeuH6LHpS-9wtePP21o-y_utC43A/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer> _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://secure-web.cisco.com/1kpvIURIF86fQFDWvoqFqGbAI26mDoO1l2wT0G81LGdkV67kjYUgecIaFvo7MFPqYyxgDEs2XDYD5OMVatlurlEpOuw39MYKT4ptAGi6oG9elRrohfOxEkYwMfrkQYF0Bejt06PkUI2Gpy-jr8G9VBAC1Kn-Un8yRxjrqL7q5qzMyblUKiXxUkbswTMq7AejCS0qxUMZE35LH07vxfV6rhgdvfslyIk1rfD_ollHWd5ujp-K7DU1mPld0wBfpRP2smmaVKpViLcpDvEzWATqNXcLyPl8CDoPHdiZ_OPLE_8p9xed9SeN2d_CGvKkwS9RheoDF23zctN6cWmCAAiXlkQ/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer>
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
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-bounces@nmr.mgh.harvard.edu on behalf of "Douglas N. Greve" dgreve@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 2nd 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://secure-web.cisco.com/1sZZR9kggc35UyK7lSAda3dE6il9II_AD7YGowE7cmcitll...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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu on behalf of "Douglas N. Greve" dgreve@mgh.harvard.edumailto:dgreve@mgh.harvard.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto: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.edumailto: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://secure-web.cisco.com/1sZZR9kggc35UyK7lSAda3dE6il9II_AD7YGowE7cmcitll...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 4th 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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Angela Fang angfang@uw.edumailto:angfang@uw.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto:freesurfer@nmr.mgh.harvard.edu Date: Monday, August 1, 2022 at 4:35 PM To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto: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://secure-web.cisco.com/1iwJ9wvsB8w-J1bWqiw97nQRIYudXBcJGIxCHHLF-50obfB...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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Angela Fang angfang@uw.edumailto:angfang@uw.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto:freesurfer@nmr.mgh.harvard.edu Date: Thursday, July 28, 2022 at 1:02 PM To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto: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://secure-web.cisco.com/1sZZR9kggc35UyK7lSAda3dE6il9II_AD7YGowE7cmcitll...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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu on behalf of "Douglas N. Greve" dgreve@mgh.harvard.edumailto:dgreve@mgh.harvard.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto: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.edumailto:freesurfer@nmr.mgh.harvard.edu Subject: Re: [Freesurfer] FSFAST first level covariates
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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 http://secure-web.cisco.com/18HOOX9hfVRQEKQOQbgg8UwdgpOwQEz96iMd0DkXNhr8_ric...http://secure-web.cisco.com/1EJiZPvng9zcCEb0OA91-g6prvoE6x8E2RuCN3eRqnJvVyWnOZIhlVqHUDwmp2WEJbpju-V9f5K_n7JLkG1IXMgF6ntSJr6Aa91zEsfied2HyjVTkJZCXxMUYkbVQwHF0Z6PuuEgJy0xZF4iWLQMnW1WHJWnTXmRF8Gn92JXWkNX3veeq3YElwnE8vUuXUBgXGmmFtbKV7dJKfvdquLkJq0ApBJuwyNBrhKCoiBCQx4GIbuAfZ0iAsH5aL5xid2f1julAWTaA4EyB2BlTn9hUZcuoJNQPs89B-fNI4SA4inRY7YD67lmo-MehxlSgl0xO/http%3A%2F%2Fwww.uwconnectlab.com Pronouns: she, her, hers
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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-bounces@nmr.mgh.harvard.edu on behalf of "Douglas N. Greve" dgreve@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
- Offset
- Self
- Valence
- 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-bounces@nmr.mgh.harvard.edu> <mailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of "Douglas N. Greve" <dgreve@mgh.harvard.edu> <mailto:dgreve@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-bounces@nmr.mgh.harvard.edu> <mailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Angela Fang <angfang@uw.edu> <mailto:angfang@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-bounces@nmr.mgh.harvard.edu> <mailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Angela Fang <angfang@uw.edu> <mailto:angfang@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-bounces@nmr.mgh.harvard.edu> <mailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of "Douglas N. Greve" <dgreve@mgh.harvard.edu> <mailto:dgreve@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 <http://secure-web.cisco.com/1EJiZPvng9zcCEb0OA91-g6prvoE6x8E2RuCN3eRqnJvVyWnOZIhlVqHUDwmp2WEJbpju-V9f5K_n7JLkG1IXMgF6ntSJr6Aa91zEsfied2HyjVTkJZCXxMUYkbVQwHF0Z6PuuEgJy0xZF4iWLQMnW1WHJWnTXmRF8Gn92JXWkNX3veeq3YElwnE8vUuXUBgXGmmFtbKV7dJKfvdquLkJq0ApBJuwyNBrhKCoiBCQx4GIbuAfZ0iAsH5aL5xid2f1julAWTaA4EyB2BlTn9hUZcuoJNQPs89B-fNI4SA4inRY7YD67lmo-MehxlSgl0xO/http%3A%2F%2Fwww.uwconnectlab.com> Pronouns: she, her, hers _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://secure-web.cisco.com/1EIAJa3Vy8ViZunXEQlBqUeh89Z7hfnnmjv7DeFVsTGR2Flz9jn4bCu1dyuSCsHExp1254fEb-3HSfv_I0wnhZVOmxSlCgQ5W60PZLZ4fD7viMK9Vd4bddOCe3voLZt-bfajyrS85ddBk6F4OSk79smF2rXnEb0HPuZuwRHA1trnMRnDI6lw5vKTMZDtUpQ-uTFSKEWRF8-za7m4KgVPY3fvUsg_Vbe7BdVSF7LLb3z9K_jpTuId2AnuH3bM3sjJBCDBRuN-o1kc7VbRHE3c8w26Oh-Q_23VPqL5zPdyWBydZK2cexYD7WJa7ADaeuH6LHpS-9wtePP21o-y_utC43A/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer> _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://secure-web.cisco.com/1kpvIURIF86fQFDWvoqFqGbAI26mDoO1l2wT0G81LGdkV67kjYUgecIaFvo7MFPqYyxgDEs2XDYD5OMVatlurlEpOuw39MYKT4ptAGi6oG9elRrohfOxEkYwMfrkQYF0Bejt06PkUI2Gpy-jr8G9VBAC1Kn-Un8yRxjrqL7q5qzMyblUKiXxUkbswTMq7AejCS0qxUMZE35LH07vxfV6rhgdvfslyIk1rfD_ollHWd5ujp-K7DU1mPld0wBfpRP2smmaVKpViLcpDvEzWATqNXcLyPl8CDoPHdiZ_OPLE_8p9xed9SeN2d_CGvKkwS9RheoDF23zctN6cWmCAAiXlkQ/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer> _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://secure-web.cisco.com/1baPxzF3OOPXMGMKlDUSToUGtXmZmXs1NV_eR9tJozBEesYxYl4BPvyM-dh7LBWCb7khf-uECadRZwtCvQJ-Y8v5UKWYVxnuvYakLo0u3pWD5fFwaEvMS1db4fhFfyfI_klxJRpmUTHzOOORzQYhBlxcouqCUAGbwl1T-7IMbZBTJLBWA9xD8j1GRSjaaDh3qoIXRI7ScaoKF_j5qBsSzOG3WVi0L0jqJPJ30zhrQ3wRV1Tr4Pvpz2J9ZmbLIzIc7dyDMvU7mLa9KUb3x0CV9UD-xevTdnaB4e9AeTz7CCFUi3dF2t4fUZDRo4Vsu0i3NpJrzzLFnXE_zwLgsS_zAJg/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer>
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That makes sense! And if we wanted to identify brain regions associated with valence (across self/non-self) that is unique from condition 2, can we add a 5th condition? Maybe we can code self as 2 and non-self as 1 so that condition 2 (self*valence) would be different from condition 5 (valence ratings only)?
Incredibly helpful, Doug- thank you so much!
From: freesurfer-bounces@nmr.mgh.harvard.edu on behalf of "Douglas N. Greve" dgreve@mgh.harvard.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edu Date: Tuesday, August 30, 2022 at 7:38 AM To: "freesurfer@nmr.mgh.harvard.edu" freesurfer@nmr.mgh.harvard.edu Subject: Re: [Freesurfer] FSFAST first level covariates
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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu on behalf of "Douglas N. Greve" dgreve@mgh.harvard.edumailto:dgreve@mgh.harvard.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto:freesurfer@nmr.mgh.harvard.edu Date: Sunday, August 28, 2022 at 1:07 PM To: "freesurfer@nmr.mgh.harvard.edu"mailto:freesurfer@nmr.mgh.harvard.edu freesurfer@nmr.mgh.harvard.edumailto: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 2nd 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://secure-web.cisco.com/1axFb8Uk3EidN7RU3PxCMFcOtbS8C3cmNULxUDXhNgudqc2...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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu on behalf of "Douglas N. Greve" dgreve@mgh.harvard.edumailto:dgreve@mgh.harvard.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto: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.edumailto: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://secure-web.cisco.com/1axFb8Uk3EidN7RU3PxCMFcOtbS8C3cmNULxUDXhNgudqc2...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 4th 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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Angela Fang angfang@uw.edumailto:angfang@uw.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto:freesurfer@nmr.mgh.harvard.edu Date: Monday, August 1, 2022 at 4:35 PM To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto: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://secure-web.cisco.com/1x486JnVcuVKZFlKc9lnM17mkutiyvGdWJ7I2FV8fwW_DW3...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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Angela Fang angfang@uw.edumailto:angfang@uw.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto:freesurfer@nmr.mgh.harvard.edu Date: Thursday, July 28, 2022 at 1:02 PM To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto: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://secure-web.cisco.com/1axFb8Uk3EidN7RU3PxCMFcOtbS8C3cmNULxUDXhNgudqc2...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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu on behalf of "Douglas N. Greve" dgreve@mgh.harvard.edumailto:dgreve@mgh.harvard.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto: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.edumailto: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://secure-web.cisco.com/1xgmi0XbR7WrIE4BfzR740s181TIOvSTjcUq-Rk-z13hN0I...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 http://secure-web.cisco.com/1jmqvstywIOSDQi7lL5fFrNGMQ7tbzvHu9YyNypnTBOqEwq6...http://secure-web.cisco.com/1EJiZPvng9zcCEb0OA91-g6prvoE6x8E2RuCN3eRqnJvVyWnOZIhlVqHUDwmp2WEJbpju-V9f5K_n7JLkG1IXMgF6ntSJr6Aa91zEsfied2HyjVTkJZCXxMUYkbVQwHF0Z6PuuEgJy0xZF4iWLQMnW1WHJWnTXmRF8Gn92JXWkNX3veeq3YElwnE8vUuXUBgXGmmFtbKV7dJKfvdquLkJq0ApBJuwyNBrhKCoiBCQx4GIbuAfZ0iAsH5aL5xid2f1julAWTaA4EyB2BlTn9hUZcuoJNQPs89B-fNI4SA4inRY7YD67lmo-MehxlSgl0xO/http%3A%2F%2Fwww.uwconnectlab.com Pronouns: she, her, hers
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https://secure-web.cisco.com/1YVm7hDB3GJiC8FqZUeSmNQqYOZano_RsH2quxJj481Alnt...
sorry, you lost me there ...
On 8/31/2022 12:39 PM, Angela Fang wrote:
External Email - Use Caution
That makes sense! And if we wanted to identify brain regions associated with valence (across self/non-self) that is unique from condition 2, can we add a 5^th condition? Maybe we can code self as 2 and non-self as 1 so that condition 2 (self*valence) would be different from condition 5 (valence ratings only)?
Incredibly helpful, Doug- thank you so much!
*From: *freesurfer-bounces@nmr.mgh.harvard.edu on behalf of "Douglas N. Greve" dgreve@mgh.harvard.edu *Reply-To: *Freesurfer support list freesurfer@nmr.mgh.harvard.edu *Date: *Tuesday, August 30, 2022 at 7:38 AM *To: *"freesurfer@nmr.mgh.harvard.edu" freesurfer@nmr.mgh.harvard.edu *Subject: *Re: [Freesurfer] FSFAST first level covariates
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
- Self-offset
- SelfValence
- NoSelf-offset
- 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-bounces@nmr.mgh.harvard.edu> <mailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of "Douglas N. Greve" <dgreve@mgh.harvard.edu> <mailto:dgreve@mgh.harvard.edu> *Reply-To: *Freesurfer support list <freesurfer@nmr.mgh.harvard.edu> <mailto:freesurfer@nmr.mgh.harvard.edu> *Date: *Sunday, August 28, 2022 at 1:07 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 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-bounces@nmr.mgh.harvard.edu> <mailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of "Douglas N. Greve" <dgreve@mgh.harvard.edu> <mailto:dgreve@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-bounces@nmr.mgh.harvard.edu> <mailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Angela Fang <angfang@uw.edu> <mailto:angfang@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-bounces@nmr.mgh.harvard.edu> <mailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Angela Fang <angfang@uw.edu> <mailto:angfang@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-bounces@nmr.mgh.harvard.edu> <mailto:freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of "Douglas N. Greve" <dgreve@mgh.harvard.edu> <mailto:dgreve@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 <http://secure-web.cisco.com/1EJiZPvng9zcCEb0OA91-g6prvoE6x8E2RuCN3eRqnJvVyWnOZIhlVqHUDwmp2WEJbpju-V9f5K_n7JLkG1IXMgF6ntSJr6Aa91zEsfied2HyjVTkJZCXxMUYkbVQwHF0Z6PuuEgJy0xZF4iWLQMnW1WHJWnTXmRF8Gn92JXWkNX3veeq3YElwnE8vUuXUBgXGmmFtbKV7dJKfvdquLkJq0ApBJuwyNBrhKCoiBCQx4GIbuAfZ0iAsH5aL5xid2f1julAWTaA4EyB2BlTn9hUZcuoJNQPs89B-fNI4SA4inRY7YD67lmo-MehxlSgl0xO/http%3A%2F%2Fwww.uwconnectlab.com> Pronouns: she, her, hers _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://secure-web.cisco.com/1EIAJa3Vy8ViZunXEQlBqUeh89Z7hfnnmjv7DeFVsTGR2Flz9jn4bCu1dyuSCsHExp1254fEb-3HSfv_I0wnhZVOmxSlCgQ5W60PZLZ4fD7viMK9Vd4bddOCe3voLZt-bfajyrS85ddBk6F4OSk79smF2rXnEb0HPuZuwRHA1trnMRnDI6lw5vKTMZDtUpQ-uTFSKEWRF8-za7m4KgVPY3fvUsg_Vbe7BdVSF7LLb3z9K_jpTuId2AnuH3bM3sjJBCDBRuN-o1kc7VbRHE3c8w26Oh-Q_23VPqL5zPdyWBydZK2cexYD7WJa7ADaeuH6LHpS-9wtePP21o-y_utC43A/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer> _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://secure-web.cisco.com/1kpvIURIF86fQFDWvoqFqGbAI26mDoO1l2wT0G81LGdkV67kjYUgecIaFvo7MFPqYyxgDEs2XDYD5OMVatlurlEpOuw39MYKT4ptAGi6oG9elRrohfOxEkYwMfrkQYF0Bejt06PkUI2Gpy-jr8G9VBAC1Kn-Un8yRxjrqL7q5qzMyblUKiXxUkbswTMq7AejCS0qxUMZE35LH07vxfV6rhgdvfslyIk1rfD_ollHWd5ujp-K7DU1mPld0wBfpRP2smmaVKpViLcpDvEzWATqNXcLyPl8CDoPHdiZ_OPLE_8p9xed9SeN2d_CGvKkwS9RheoDF23zctN6cWmCAAiXlkQ/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer> _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://secure-web.cisco.com/1baPxzF3OOPXMGMKlDUSToUGtXmZmXs1NV_eR9tJozBEesYxYl4BPvyM-dh7LBWCb7khf-uECadRZwtCvQJ-Y8v5UKWYVxnuvYakLo0u3pWD5fFwaEvMS1db4fhFfyfI_klxJRpmUTHzOOORzQYhBlxcouqCUAGbwl1T-7IMbZBTJLBWA9xD8j1GRSjaaDh3qoIXRI7ScaoKF_j5qBsSzOG3WVi0L0jqJPJ30zhrQ3wRV1Tr4Pvpz2J9ZmbLIzIc7dyDMvU7mLa9KUb3x0CV9UD-xevTdnaB4e9AeTz7CCFUi3dF2t4fUZDRo4Vsu0i3NpJrzzLFnXE_zwLgsS_zAJg/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer> _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://secure-web.cisco.com/1YVm7hDB3GJiC8FqZUeSmNQqYOZano_RsH2quxJj481AlntnLRefYlE9kjoEeGt-gqA6RsAdbgjPhr3wwZfx4rEgRXoj06J-SGFMFiSbQLbKYPSby80T2idt0EoIdV3oj2GH7OUEl7nsmsIv9UQJ9mSBowr4LnVf1hWw2T6XlHKGCWFm6ZZPo0Q8dmsDjQkiGFJlwXLfpOaOBBX0O_C7M2inizHY1H8wESXwUCYCCFhhRo8U4dKBB3RQmfV2SsWReXAEHulIBsXU0p5URqQNItB8GESOZHTsc0pvkguOY-7Vn0f0vtsEEW74WljePRe3NnEbhSgMX5B39AnuNTWqr_A/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer>
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Sorry if I was unclear. The analysis we have set up will allow me to test for the difference between self and non self valence slope, but I’m also interested in testing for the slope of valence alone (identifying the brain regions associated with increasing valence ratings). Can I add another condition for valence, and if so, how do we make the weights different from the self*valence condition (because self is always coded 1 so the weights for self*valence and valence only will be identical)?
On Aug 31, 2022, at 8:08 PM, Douglas N. Greve dgreve@mgh.harvard.edu wrote:
sorry, you lost me there ...
On 8/31/2022 12:39 PM, Angela Fang wrote:
External Email - Use Caution That makes sense! And if we wanted to identify brain regions associated with valence (across self/non-self) that is unique from condition 2, can we add a 5th condition? Maybe we can code self as 2 and non-self as 1 so that condition 2 (self*valence) would be different from condition 5 (valence ratings only)?
Incredibly helpful, Doug- thank you so much!
From: freesurfer-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu on behalf of "Douglas N. Greve" dgreve@mgh.harvard.edumailto:dgreve@mgh.harvard.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto:freesurfer@nmr.mgh.harvard.edu Date: Tuesday, August 30, 2022 at 7:38 AM To: "freesurfer@nmr.mgh.harvard.edu"mailto:freesurfer@nmr.mgh.harvard.edu freesurfer@nmr.mgh.harvard.edumailto:freesurfer@nmr.mgh.harvard.edu Subject: Re: [Freesurfer] FSFAST first level covariates
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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu on behalf of "Douglas N. Greve" dgreve@mgh.harvard.edumailto:dgreve@mgh.harvard.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto:freesurfer@nmr.mgh.harvard.edu Date: Sunday, August 28, 2022 at 1:07 PM To: "freesurfer@nmr.mgh.harvard.edu"mailto:freesurfer@nmr.mgh.harvard.edu freesurfer@nmr.mgh.harvard.edumailto: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 2nd 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://secure-web.cisco.com/1ibJu9DNCEQ80IS8XnYQe64G3qUwBk_mJpSfJiHpiFjdObD... [secure-web.cisco.com]https://secure-web.cisco.com/1n9NaxxOQGYBn2vf8MJ5Y3HsNwtbaKNPmxR056SHywqcZ1M5Pr3EmrcpD5GO7Bz4VWqz0_QYUglcetQzxo3XfZo52OzpC1h-OFx-iNmhdpBsBWhahZ6gq3wTQ-7drXxoKE3PW6bJvfRmwtp6ttZtwroM5e7FgTaNR0-rYAe7OULwrxMTvFRHcwUT9ZBRYZA_hbtEv0-G0ytcUWEDBddCevIKtYVhpgVwLLS0Exk_XdFbnAvvT1GZTg2WfFucz-ljQluQXurRZBZ6pXaLlq0MOQtFA2RGTM46p_WEB8ZrlOwRc4pLoR-O7EzXnBEQFv2P0/https%3A%2F%2Furldefense.com%2Fv3%2F__https%3A%2F%2Fsecure-web.cisco.com%2F1UvSz7SvjZnlE1QfkdS-VBc1GzXeZMYqUcsOqE3dGoo43anjoKIpvfs4NnozgTlCx23dB10wC_oFWTi8Zyazh1v1oufO7QQBf9hJanKAiwbu0cr4NfMvGMSOSaaOt5nSATHi-J-55MTqcCUhjz8_rRM1YuYWhtxzDVrlNJ5mD3QlEmdQlhRlYoneii_5mWjAZB1gcbpR_0Zl1nUaCy9BfmpcQRNLpIdfE1NMjg7OnqHOX5jAdPz1gGqxVTKgstTqx8RhxmTkDYOQPLc6hC3by-Atu2VfBnloD3GbZOzG04LjV1Of0uYaB6pk6oSsZFULTsifcwPSiwh1m9gKSg5lD7Q%2Fhttps*3A*2F*2Fwww.mail-archive.com*2Ffreesurfer*40nmr.mgh.harvard.edu*2Fmsg19957.html__;JSUlJSUl!!K-Hz7m0Vt54!ji6For-hJmPcW17cpltXyyzEnXZRMzaxRMDE33CdvLR4Q_kP7EegDZ6_SSQVOXEDDzrFFGPTAepz1z3dcedA$). 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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu on behalf of "Douglas N. Greve" dgreve@mgh.harvard.edumailto:dgreve@mgh.harvard.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto: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.edumailto: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://secure-web.cisco.com/1ibJu9DNCEQ80IS8XnYQe64G3qUwBk_mJpSfJiHpiFjdObD... [secure-web.cisco.com]https://secure-web.cisco.com/1XE1lL3vmTF46oAiDk9Xq4syS4ojNt6KjHMyIui8XDeKx440vAVGsBjxCnJ5NKK-7D5KOREbOcJQdZ_l9bAZrNttu8VH1ziXmbZ4wZYMFEJKhheOv_cG0AzLR5JjhRd-3-v-Z7Wlt7tTBp_9dLpWbs0hieBt2GgpTPeZgOOk3R8VdGuid_CVA2VQSSmc0eUzYZT0fsyR2jJduzUy726NkNykVFMjzvUinop_I14uJgRoDSvEs7pANMqp7FT5tITbE-NP8VP8InzX_rrHH3Cj8040MZtmQrZ7fPHU4dpe2yPkC0lGZ_YWgnhGTlJNePPxw/https%3A%2F%2Furldefense.com%2Fv3%2F__https%3A%2F%2Fsecure-web.cisco.com%2F1S2s08xk6_r2FFsEB5S1KdOcfq6G8ToJwyZuNFONdwgOYd87JJkB-uznJW2pelg24KQwX3lweVOmFs99TCKitjbJOqKWgEH_UW7wir5JQ113csODerDntanBrEibOdt6Mxs2QeQ5D7n69Ds6NaOSOJIbLFeMjuoaTXCkNccNydn7jvjmVd0zW2YhEXG9JtLxMNVIYt8q48ZK0sJUt8sjTP6xuCzA1pzB19MUHA078Zgygtns0YVgn1n5Sg41ZbVZ3jWciX5ZF34AejW5nWj1Z4mWO1Xyd_7RwNbKkVMPeDwG6K9W59gzBf_t0G-AzmUhxGC8zfKM0bxA9hhZv4GR2BQ%2Fhttps*3A*2F*2Fwww.mail-archive.com*2Ffreesurfer*40nmr.mgh.harvard.edu*2Fmsg19957.html__;JSUlJSUl!!K-Hz7m0Vt54!ji6For-hJmPcW17cpltXyyzEnXZRMzaxRMDE33CdvLR4Q_kP7EegDZ6_SSQVOXEDDzrFFGPTAepz16TQhQby$), it sounds like I should code as follows:
1. SelfOffset 2. Self-ValenceSlope (would the weight in the 4th 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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Angela Fang angfang@uw.edumailto:angfang@uw.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto:freesurfer@nmr.mgh.harvard.edu Date: Monday, August 1, 2022 at 4:35 PM To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto: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://secure-web.cisco.com/1lzAEwThLlT3bBG3eW3SRuXVXVR9ztiSjluhYifpJ7hPKt8... [secure-web.cisco.com]https://secure-web.cisco.com/12yTQcAEwE0LLr2bz8JobkPJ9I_dBbtqgz3UJWAQpQ4AEnVBa_m4iLPtlvWx1c99LyF92qh1qt2SofAjj90QErdyLZJ3smSx6UBm0POSraAGxPBN6eo-DJWNDgYOiuk-X-2OqshBsoygPcUO-sKIiMwhvztLBWH0NUxMyVJERdmHhyFFEI3wgOVNl9qxFC6alT9udjRe8thAV35kuPhqRcjA7YFhfTcx6T6vaz4KO91yIqwBVrPmgvL2h_4h44RcGFpy8T73dJKKZ04-jT6515S3z9oSbzrpxP6X-qQdNIfeJc61jmcqhlBSBk_6H8KLx/https%3A%2F%2Furldefense.com%2Fv3%2F__https%3A%2F%2Fsecure-web.cisco.com%2F1646ymi0_yM9ab72e81bZdCKw_zNbXr9RihxDaiDVPq0_Qd4EXYgDmO56zQdi9l_AyV3uyyiURXHoYWQmiu56CbMuIGdZz8EH0gbsnVrAz9KwunZAwLzh0kh-jzVwHtlbEdd1ExEJYHT7o7JtUWg2GM484JTyL0VZJymRuGRyD0ag1nQ_0BPPjQHxPCqNHEU4Y_seBsq9XsUROgyR-bX-tHVXxhshVUHgneudw6tEB2lIVYfYrL3srRbjy1QN9Bq_e3_WaNCDhkXdixnae24i41HHYwJfn3KwsmNoZ2RxLoh3SMkXXwVntAewl8PeldBY0s3UxoEPiFbDdXXuJLUjlw%2Fhttps*3A*2F*2Fwww.mail-archive.com*2Ffreesurfer*40nmr.mgh.harvard.edu*2Fmsg32235.html__;JSUlJSUl!!K-Hz7m0Vt54!ji6For-hJmPcW17cpltXyyzEnXZRMzaxRMDE33CdvLR4Q_kP7EegDZ6_SSQVOXEDDzrFFGPTAepz1-csL2qz$) 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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Angela Fang angfang@uw.edumailto:angfang@uw.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto:freesurfer@nmr.mgh.harvard.edu Date: Thursday, July 28, 2022 at 1:02 PM To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto: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://secure-web.cisco.com/1ibJu9DNCEQ80IS8XnYQe64G3qUwBk_mJpSfJiHpiFjdObD... [secure-web.cisco.com]https://secure-web.cisco.com/1T3b2JFQFteTd3ZHOhc-K8C4AWhG6kni3BhDpBpGRvTN_v5ibRII1RFrWawlH6ObiwQbNDFqe1AJeYJMyTz7Fi7q3MmkOxlTVfjZ-OxSHft7hjS69Ml-Oy13NnY5_ykht0XQdLqJV1oeSJ02P98_bFFhUhSN2HYw1gmAS9kpgxgqueDnyaFJkAtcmUgYj_AUIbwY9HWqnin-gxmS73pvBbUOcy3R9DXdESGZqaIWpTwaHffwR6AHFWJR5zpu7RJSrLXzJiH3I2ieXBZSXtUEn0lMsm0HXZHzUiXY00rTMt0QRlBabg_Qlr3Ds7JRlGzK-/https%3A%2F%2Furldefense.com%2Fv3%2F__https%3A%2F%2Fsecure-web.cisco.com%2F11nFbIrJYBqRI1W_4wY-HvfdEF3GG6xLL8So8t0i9yKbcElVyl_nJoDI6XedAGY2kKd_eP-dnsWeccOw2qajd375GRCeiUjqaXv3C7vOkrGEOiSiqfcPQ9y73ROdtl0jJIGemdoYQDd3GcX-dKx6qDwBcPE_qNlqxB0ZTcsDfTwK88OkoVtftMo1zKBWSiZBV9p0GO2erUcSoXtVI-AITDr9jULRDzVL_IzxtPdtuSBrYXMASRi7ex2oKftjJjyG_HMgygf_ULhSYIsHviihCwfx4uO5_zrvh8H84AxAsv33zsFjOaYeZ826JkD3E99hxrAKW3jYr3PjfN-zNZjQLJA%2Fhttps*3A*2F*2Fwww.mail-archive.com*2Ffreesurfer*40nmr.mgh.harvard.edu*2Fmsg19957.html__;JSUlJSUl!!K-Hz7m0Vt54!ji6For-hJmPcW17cpltXyyzEnXZRMzaxRMDE33CdvLR4Q_kP7EegDZ6_SSQVOXEDDzrFFGPTAepz12r6CnwK$). 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-bounces@nmr.mgh.harvard.edumailto:freesurfer-bounces@nmr.mgh.harvard.edu on behalf of "Douglas N. Greve" dgreve@mgh.harvard.edumailto:dgreve@mgh.harvard.edu Reply-To: Freesurfer support list freesurfer@nmr.mgh.harvard.edumailto: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.edumailto: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://secure-web.cisco.com/16JnG3GJYlcUCXLphmkob7-0y2zD1d2QdT8BOvp_3Vfispu... [secure-web.cisco.com]https://secure-web.cisco.com/1bJytgY3pTn4h9-AVD-z9s6U3gneDrAnZFJvNX7_t2eumq0k9WGG4rV-P-dxcgtl9YCYpAiBAu2GUPu4uIMzaJm3XG2pfhXKkqYwD6torh5q0Z2e3v7Te2mNCSfId9dhi3cr2qPvzrulOkxdHwcvucb2IR917PJ6EbAiEqYz7WgMXDQV04yJeddCboG7nKBGSrzGVk8I4y_tJJFf-E6r5zzixSkfSGsWy2-nAitjWQJl2DSpGr6_lPPLpzp_wKwIU2IWWap3qqftLPbsN7CNsTssfCPVeZNlrNNpIni06j3eesfURiOjYfu9smlt63vwz/https%3A%2F%2Furldefense.com%2Fv3%2F__https%3A%2F%2Fsecure-web.cisco.com%2F1vlnv3wLgT6AWyuomHXVnJCfD3bAT8O6KYN-6kv4DVE_Kbs9JwI6WLDqHM7UN7cfJ1TP0eQKgCtR-KXf01ehJnqsV2jW5XmAXQr0QnOlGk4--dT54zncT2aoK1njMKmN9ayqCJ_tFar2vbW-JGXSkTcg6gdUPh_mngiG7m6SxtOvACvAKVHKQXKhe7-xx2QsCh6VDDkv9vQZNEkvMseg2bTElAE9tBG4Nyws1TeLoT6NRejWCSL4Hnke9bOJGLYp7gY561tg-SfXXlzjCNawo6cgCBAIxSsMzwLR8sWZndlid_nZ0aZqf85_HgcVXWUXEoKCbQCJ_Hs2G69KcjGr8yg%2Fhttps*3A*2F*2Fsurfer.nmr.mgh.harvard.edu*2Ffswiki*2FFsFastParametricModulation__;JSUlJSU!!K-Hz7m0Vt54!ji6For-hJmPcW17cpltXyyzEnXZRMzaxRMDE33CdvLR4Q_kP7EegDZ6_SSQVOXEDDzrFFGPTAepz19uin7Lk$ 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 http://secure-web.cisco.com/1GKMv6rs2jdfQljvbF6OAGPHkb3n6iIyiGTlh3DdC-uaGjD5... [secure-web.cisco.com]https://secure-web.cisco.com/13UyNto3NJxwgTzBd-ANCABF-aBhNvcyCbi0Q9MsSIsJ6LlUj7pyiZ_qwRrH4ueCbe16NQ9OcptL9OLtxkAX8OQm5mzT-D1VXpBL2I3z5aBL6VoefyTtcT7InRYBWPVQB-idhMnio_ZXorisd02SksfF-s8HANoONmc2pqhhUYcN62isMesm_OUPbO4AfrfCPCXvErLN6q0b9Ke0EbL60Wi6ipk93pqgu8hE-rjOyH1atsKyoz3-zxtQSxv733IoxlBfp5mBDiXk8ZIow4OInsexsfAP1yS_f82vXM9N-llM9p_TsEAfUt6bpRMsfrc7v/https%3A%2F%2Furldefense.com%2Fv3%2F__http%3A%2F%2Fsecure-web.cisco.com%2F1EJiZPvng9zcCEb0OA91-g6prvoE6x8E2RuCN3eRqnJvVyWnOZIhlVqHUDwmp2WEJbpju-V9f5K_n7JLkG1IXMgF6ntSJr6Aa91zEsfied2HyjVTkJZCXxMUYkbVQwHF0Z6PuuEgJy0xZF4iWLQMnW1WHJWnTXmRF8Gn92JXWkNX3veeq3YElwnE8vUuXUBgXGmmFtbKV7dJKfvdquLkJq0ApBJuwyNBrhKCoiBCQx4GIbuAfZ0iAsH5aL5xid2f1julAWTaA4EyB2BlTn9hUZcuoJNQPs89B-fNI4SA4inRY7YD67lmo-MehxlSgl0xO%2Fhttp*3A*2F*2Fwww.uwconnectlab.com__;JSUl!!K-Hz7m0Vt54!ji6For-hJmPcW17cpltXyyzEnXZRMzaxRMDE33CdvLR4Q_kP7EegDZ6_SSQVOXEDDzrFFGPTAepz19AfYyUQ$ Pronouns: she, her, hers
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freesurfer@nmr.mgh.harvard.edu
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Angela Fang -
Douglas N. Greve