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[[FsFastTutorialV6.0|top]] | [[FsFastTutorialV6.0|previous]]| [[FsFastTutorialV6.0/FsFastDirStruct_freeview|next (Directory Structure)]]
<<TableOfContents>> 		[[FsFastTutorialV6.0|top]] | [[FsFastTutorialV6.0|previous]]| [[FsFastTutorialV6.0/FsFastDirStruct_freeview|next (Directory Structure)]] <<TableOfContents>>
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The functional data were collected as part of the Functional Biomedical Research Network (fBIRN, www.nbirn.net). The functional data were collected as part of the Functional Biomedical Research Network (fBIRN).
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The paradigm was designed to study the effects of emotional stimuli on
the ability to recall items stored in working memory. 		The paradigm was designed to study the effects of emotional stimuli on the ability to recall items stored in working memory.
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  1. Encode (16 sec) - 8 stick figures to remember (no response)
   1. Distractor (16 sec) - 8 distractor images (response whether there is a face in the image)
      a. Emotional - Distractors are emotionally disturbing
      a. Neutral - Distractors are emotionally neutral
  1. Probe (16 sec) - 8 pairs of stick figures. Subject responds as to which of the pair was in the original Encode. 		  1. Encode (16 sec) - 8 stick figures to remember (no response)
  1. Distractor (16 sec) - 8 distractor images (response whether there is a face in the image)
   a. Emotional - Distractors are emotionally disturbing
   a. Neutral - Distractors are emotionally neutral
  1. Probe (16 sec) - 8 pairs of stick figures. Subject responds as to which of the pair was in the original Encode.
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{{attachment:wmparadigm.jpg}}<<BR>>
The above yields 5 conditions:
  1. Encode
  1. Emotional Distractor
  1. Neutral Distractor
  1. Probe following Emotional Distractor
  1. Probe following Neutral Distractor
{{attachment:wmparadigm.jpg}} <<BR>> The above yields 5 conditions:

 1. Encode
 1. Emotional Distractor
 1. Neutral Distractor
 1. Probe following Emotional Distractor
 1. Probe following Neutral Distractor
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'''If you are at a !FreeSurfer Course, continue on to the next page now''' <<BR>><<BR>>
[[FsFastTutorialV6.0|top]] | [[FsFastTutorialV6.0|previous]]| [[FsFastTutorialV6.0/FsFastDirStruct_freeview|next (Directory Structure)]]
'''If you are at a !FreeSurfer Course, continue on to the next page now''' <<BR>><<BR>> [[FsFastTutorialV6.0|top]] | [[FsFastTutorialV6.0|previous]]| [[FsFastTutorialV6.0/FsFastDirStruct_freeview|next (Directory Structure)]]
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= Getting the Data (not necessary for the Boston FreeSurfer Course)  = = Getting the Data (not necessary for the Boston FreeSurfer Course) =
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cd to a place on your network where you have enough space to unpack
the tutorial data. 		cd to a place on your network where you have enough space to unpack the tutorial data.
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You will need to set the TUTORIAL_DATA environment variable. In tcsh
or csh 		You will need to set the TUTORIAL_DATA environment variable. In tcsh or csh
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You will also need to link the FreeSurfer anatomical subjects (data
in fsfast-tutorial.subjects) into your $SUBJECTS_DIR.
You should set the FSFAST output format to be compressed NIFTI (nii.gz): 		You will also need to link the FreeSurfer anatomical subjects (data in fsfast-tutorial.subjects) into your $SUBJECTS_DIR. You should set the FSFAST output format to be compressed NIFTI (nii.gz):

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Contents

  1. FSFAST Tutorial Data Description
  2. Functional Paradigm
  3. Functional Data
  4. Anatomical Data
  5. Getting the Data (not necessary for the Boston FreeSurfer Course)
  6. Organizing the Tutorial (not necessary for the Boston FreeSurfer Course)

1. FSFAST Tutorial Data Description

The functional data were collected as part of the Functional Biomedical Research Network (fBIRN).

  • Working-memory paradigm with distractors
  • 18 subjects
  • Each subject has 1 run (except sess01 which has 4 runs)
  • Collected at MGH Bay 4 (3T Siemens)

  • FreeSurfer anatomical analyses

2. Functional Paradigm

The paradigm was designed to study the effects of emotional stimuli on the ability to recall items stored in working memory.

  • Blocked design
  • Each block consisted of 3 phases
    1. Encode (16 sec) - 8 stick figures to remember (no response)
    2. Distractor (16 sec) - 8 distractor images (response whether there is a face in the image)
      1. Emotional - Distractors are emotionally disturbing
      2. Neutral - Distractors are emotionally neutral
    3. Probe (16 sec) - 8 pairs of stick figures. Subject responds as to which of the pair was in the original Encode.
  • Between each block was a 16 sec scrambled image used as baseline.

wmparadigm.jpg
The above yields 5 conditions:

  1. Encode
  2. Emotional Distractor
  3. Neutral Distractor
  4. Probe following Emotional Distractor
  5. Probe following Neutral Distractor

The scrambled image will be modeled as a baseline, not as a condition.

3. Functional Data

  • Original data: each subject had 8 runs
  • This data: each subject has 1 run (except for sess01 who has 4)
  • Each run lasts 142 time points
  • TR = 2 sec.
  • There is one run of rest data for 13 subjects
  • There is a B0 map for each subject

4. Anatomical Data

  • FreeSurfer analysis has been run for all 18 subjects

If you are at a FreeSurfer Course, continue on to the next page now

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5. Getting the Data (not necessary for the Boston FreeSurfer Course)

You can get the analyzed functional data (10G) from: 

wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/fsfast-functional.tar.gz

You can get the structural data (5G) from: 

wget ftp://surfer.nmr.mgh.harvard.edu/pub/data/fsfast-tutorial.subjects.tar.gz

6. Organizing the Tutorial (not necessary for the Boston FreeSurfer Course)

cd to a place on your network where you have enough space to unpack the tutorial data. 

cd /place/with/space

Untar the data 

tar xvfz fsfast-tutorial.tar.gz
tar xvfz fsfast-tutorial.subjects.tar.gz

You will need to set the TUTORIAL_DATA environment variable. In tcsh or csh 

setenv TUTORIAL_DATA /place/with/space

In bash 

export TUTORIAL_DATA=/place/with/space

You will also need to link the FreeSurfer anatomical subjects (data in fsfast-tutorial.subjects) into your $SUBJECTS_DIR. You should set the FSFAST output format to be compressed NIFTI (nii.gz): 

export FSF_OUTPUT_FORMAT=nii.gz

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FsFastTutorialV6.0/TutorialData (last edited 2018-09-30 09:41:07 by AndrewHoopes)