[color=#000000]Dear Marko,[/color]
[color=#000000]Using CONN for preprocessing and denoising your data before SPM-based functional activation analyses is perfectly fine (particularly since CONN's preprocessing steps rely heavily on SPM12 procedures). T[/color]he recommended approach in that scenario is described in https://web.conn-toolbox.org/fmri-methods/denoising-pipeline, and it simply consists on running the following command:
conn_module( 'preprocessing', ...
'structurals', {'/data/anat.nii'}, ...
'functionals', {'/data/func.nii'}, ...
'steps', {'default_mni', 'functional_regression', 'functional_bandpass'}, ...
'reg_names', {'realignment','scrubbing','White Matter','CSF'}, ...
'reg_dimensions',[inf, inf, 5, 5], ...
'reg_deriv', [1, 0, 0, 0], ...
'bp_filter', [0.008 inf] )
[color=#000000] [/color]
[color=#000000]changing the structurals/functionals lines to point to your subject(s) structural/functional data (see "help conn_module" for details about how to enter multi-subject / multi-session data in these fields)[/color]
[color=#000000]Hope this helps[/color]
[color=#000000]Alfonso
[/color]
[i]Originally posted by Marko Rajkovic:[/i][quote]Dear Conn Community,
I have a specific issue and would appreciate<span style="white-space: pre;"> </span>your input and your experience on this topic. I was recently introduced to the Conn Toolbox and I find the GUI Design to be very helpful and clear especially for preprocessing fMRI data. However, having looked into the manual and the GUI itself there are still some things that are not yet clear to me.
Maybe a quick summary of our Design and paradigm will be useful: we are interested in investigating differences in pattern separation between young healthy adults and healthy elders using a pattern separation paradigm. During the task participants had to discern whether a stimulus following a specific cue (either auditory or visual) was the same (pattern completion), different (pattern separation) or a lure (pattern similarity). Both groups had to do the same task once (1 session). Thus, At the moment we are only interested in comparing both groups using multivariate analyses and not (yet) effective connectivity.
1. Can one use the Conn Toolbox even if it is only for the purpose of preprocessing data? In other words is it advisable to use different toolboxes for different steps of ones analyses and is this advisable? (e.g. Preprocessing via Conn-Toolbox and performing multivariate analyses using spm12)
2. Should one use the Denoising function for task related fMRI or is this step more suited for resting-state analyses? Is it perhaps better to just use rp files that are generated through the motion corrections stage of preprocessing?
Thank you all in advance.
Kind regards,
Marko[/quote]
[color=#000000]Using CONN for preprocessing and denoising your data before SPM-based functional activation analyses is perfectly fine (particularly since CONN's preprocessing steps rely heavily on SPM12 procedures). T[/color]he recommended approach in that scenario is described in https://web.conn-toolbox.org/fmri-methods/denoising-pipeline, and it simply consists on running the following command:
conn_module( 'preprocessing', ...
'structurals', {'/data/anat.nii'}, ...
'functionals', {'/data/func.nii'}, ...
'steps', {'default_mni', 'functional_regression', 'functional_bandpass'}, ...
'reg_names', {'realignment','scrubbing','White Matter','CSF'}, ...
'reg_dimensions',[inf, inf, 5, 5], ...
'reg_deriv', [1, 0, 0, 0], ...
'bp_filter', [0.008 inf] )
[color=#000000] [/color]
[color=#000000]changing the structurals/functionals lines to point to your subject(s) structural/functional data (see "help conn_module" for details about how to enter multi-subject / multi-session data in these fields)[/color]
[color=#000000]Hope this helps[/color]
[color=#000000]Alfonso
[/color]
[i]Originally posted by Marko Rajkovic:[/i][quote]Dear Conn Community,
I have a specific issue and would appreciate<span style="white-space: pre;"> </span>your input and your experience on this topic. I was recently introduced to the Conn Toolbox and I find the GUI Design to be very helpful and clear especially for preprocessing fMRI data. However, having looked into the manual and the GUI itself there are still some things that are not yet clear to me.
Maybe a quick summary of our Design and paradigm will be useful: we are interested in investigating differences in pattern separation between young healthy adults and healthy elders using a pattern separation paradigm. During the task participants had to discern whether a stimulus following a specific cue (either auditory or visual) was the same (pattern completion), different (pattern separation) or a lure (pattern similarity). Both groups had to do the same task once (1 session). Thus, At the moment we are only interested in comparing both groups using multivariate analyses and not (yet) effective connectivity.
1. Can one use the Conn Toolbox even if it is only for the purpose of preprocessing data? In other words is it advisable to use different toolboxes for different steps of ones analyses and is this advisable? (e.g. Preprocessing via Conn-Toolbox and performing multivariate analyses using spm12)
2. Should one use the Denoising function for task related fMRI or is this step more suited for resting-state analyses? Is it perhaps better to just use rp files that are generated through the motion corrections stage of preprocessing?
Thank you all in advance.
Kind regards,
Marko[/quote]