On 7/10/2025 3:51 PM, Isabella Rossellini wrote:
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Thank you! I found some significant results/regions in the negative direction.
Does this mean that time impacts cortical thickness? So, there is a
time x thickness effect, and with longer time/treatment, the cortical
thickness decreases in those regions?
Yes, though it is usually not stated as "time-by-thickness effect" since
time is an independent variable and thickness is a dependent variable.
Additionally, I wanted to visualize the thickness changes over time.
In other words, I was hoping to extract and visualize cortical
thickness values at these time points.
What would be the best way to do this?
You could make an average at each time point.
Sincerely,
Isa Rosselini
On Fri, Jun 20, 2025 at 3:19 PM Isabella Rossellini
<[email protected]> wrote:
Dear Douglas,
Thank you for your kind help and advice!
Good to know that a two-stage model is not needed for one subject. So
I should not run the longitudinal preprocessing either, right?
Following your advice, I created this FSGD file below for subjid1 with
5 timepoints (0, 3, 6, 9, 12).
Name of the imaging files: subjid1_base, subjid1_3mo, subjid1_6mo,
subjid1_9mo, subjid1_12mo
GroupDescriptorFile 1
Title Onesubject
Class Class1
Variables TimePoint
Input subjid1_base Class1 0
Input subjid1_3mo Class1 3
#Input subjid1_6mo Class1 6
Input subjid1_9mo Class1 9
Input subjid1_12mo Class1 12
Does this look okay to you?
You also wrote that I should "remove the mean of the time points from the time
point number number". (The mean is 6 in our case) I wonder why?
Does this mean that the TimePoint variables should be -6 -3 0 3 6
instead? (and not 0 3 6 9 12)
GroupDescriptorFile 1
Title Onesubject
Class Class1
Variables TimePoint
Input subjid1_base Class1 -6
Input subjid1_3mo Class1 -3
#Input subjid1_6mo Class1 0
Input subjid1_9mo Class1 3
Input subjid1_12mo Class1 6
Sincerely,
Isa Rosselini
On Thu, Apr 17, 2025 at 5:37 PM Isabella Rossellini
<[email protected]> wrote:
Dear Douglas,
I am sorry for the late response. I did not see your message up until now.
I would like to see how the brain changes for a patient with anxiety
who got better gradually (again, we have 5-time points (0, 3, 6, 9,
12). And then do the same for another participant who did not get
better up until 12 months.
That is the reason I would like to look at patients one by one.
I ran the mri_glmfit analysis but I received an error message:
ERROR: DOF=0
Is this because I tried to run it on one participant?
Sincerely,
Isa Rosselini
Date: Mon, 3 Feb 2025 09:20:40 -0500
From: "Douglas N. Greve" <[email protected]>
Subject: Re: [Freesurfer] longitudinal analysis on one subject
To: [email protected]
Message-ID: <[email protected]>
Content-Type: text/plain; charset="utf-8"
The glm can be run on this data in theory. With only 5 time points, you
probably won't have much power though. What are you trying to test?
On Sat, Feb 1, 2025 at 11:56 PM Isabella Rossellini
<[email protected]> wrote:
Hello Freesurfer users/experts,
I am working with Freesurfer 7.4.1 on a MacStudio (macOS 15.2) and I would like
to ask your opinion about the following.
Basically, we had an anxiety treatment study and I would like to analyze one
subject who has 5-time points (0, 3, 6, 9, 12) with a longitudinal pipeline,
two-stage model.
Is it possible to run this on one person only and see the changes between these
time points?
I have never done this before on one subject so I am not sure what the best
approach would be to look at the changes.
After running the longitudinal preprocessing (base, long), should I generate
the tables of freesurfer parcellation/segmentation stats data
(aparcstats2table, asegstats2table)?
Or can I just follow the two stage model steps? Maybe glm only works on a group
of subjects.
https://secure-web.cisco.com/1oKKNLruyxLrTLstwDHVKJ7dOdikOj62Ii7jaQSAHbttB7p8ks9bcl-vEjP7-e6vh1gYOEnAIxijKUhVHc92WJSus_MJxaMZ062AtGYNA1mxkE4efzSwj6B7LmYGdcIiVclaugebZHuJre6iS1mzcWgzUN_bcES0r9aKlnoVkd7ERg4u8bGGQl89NxiCOSeguwZDX_jzDL7cYrnOmBbkVLYrYzZUkcopXMc0uUj8ovTFiQmN683FQrXgd-jPjLAy9rn-Fb8PAAHuQFuCIzmCp_S_KHHrGUppDV20DCOyuNRi1xINz9-V4ieoeFaPmircjOC-W_jf1A4ZqqBOmV6wTcg/https%3A%2F%2Fsurfer.nmr.mgh.harvard.edu%2Ffswiki%2FLongitudinalTwoStageModel
(We have 9 more subjects - 10 in total - so I was hoping to visualize the
pattern of changes one by one, in each subject, since these patients showed
different changes in anxiety based on self-reported
questionnaires)
Sincerely,
Isa Rosselini
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