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=== Subjects ===
=== Subjects ===
Subjects were 19 healthy volunteers.
Subjects were 19 healthy, right-handed volunteers.


== Memory Task ==
== Memory Task ==
Line 33: Line 33:
== fMRI Analysis ==
== fMRI Analysis ==
=== MR acquisition ===
=== MR acquisition ===
Data were obtained on a GE scanner. Et cetera.
Imaging data were acquired on a 3.0 T Signa whole-body MRI system with a custom-built head coil (GE Medical Systems, Milwaukee, WI, USA).


=== MR Analysis ===
In total, 2,400 functional volumes were acquired for each participant using a T2*-sensitive gradient echo spiral in/our pulse sequence (Glover and Law, 2001).  Functional imaging parameters were optimized to provide whole brain coverage (TR=2000ms; TE= 30ms; flip angle = 75°; FOV = 22 cm; 3.44 x 3.44 x 4 mm resolution, 30 slices).
The MR data was analyzed using [http://white.stanford.edu/newlm/index.php/MrVista mrVista] software tools.  
 
=== fMRI Analysis ===
The fMRI data was analyzed using [https://github.com/mwaskom/lyman Lyman], [http://nipy.sourceforge.net/nipype/ Nipype],  [https://surfer.nmr.mgh.harvard.edu/ Freesurfer], [http://afni.nimh.nih.gov/afni/ AFNI], and [http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/ FSL] software tools.  


==== Pre-processing ====
==== Pre-processing ====
All data were slice-time corrected, motion corrected, and repeated scans were averaged together to create a single average scan for each subject. Et cetera.
All data went through a standard preprocessing pipeline using Freesurfer and FSL, including motion (RapidART) and slice time correction, realignment (middle volume of each run), skull stripping, temporal filtering (high-pass cutoff 128 Hz), and surface-based coregistration (bbregister). Data were spatially smoothed (6 fwhm, SUSAN -- only averages a given voxel with local voxels that have a similar intensity), scaled grand median of timeseries to 10000, & normalized for group analyses (nonlinear warp to FSL’s MNI152 space). Data were modeled using a double gamma function, and the first 5 frames of each run were discarded.
 
==== PRF model fits ====
PRF models were fit with a 2-gaussian model.
 
==== MNI space ====
After a pRF model was solved for each subject, the model was trasnformed into MNI template space. This was done by first aligning the high resolution t1-weighted anatomical scan from each subject to an MNI template. Since the pRF model was coregistered to the t1-anatomical scan, the same alignment matrix could then be applied to the pRF model. <br>
Once each pRF model was aligned to MNI space, 4 model parameters - x, y, sigma, and r^2 - were averaged across each of the 6 subjects  in each voxel.
 
Et cetera.


= Results =
= Results =

Revision as of 05:00, 29 May 2013


Background

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To add an image, simply put text like this inside double brackets 'MyFile.jpg | My figure caption'. When you save this text and click on the link, the wiki will ask you for the figure.


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Materials and Methods

Subjects

Subjects were 19 healthy, right-handed volunteers.

Memory Task

Figure 1. Morph Stimuli


Figure 2. Task Design

Behavioral Analysis

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fMRI Analysis

MR acquisition

Imaging data were acquired on a 3.0 T Signa whole-body MRI system with a custom-built head coil (GE Medical Systems, Milwaukee, WI, USA).

In total, 2,400 functional volumes were acquired for each participant using a T2*-sensitive gradient echo spiral in/our pulse sequence (Glover and Law, 2001). Functional imaging parameters were optimized to provide whole brain coverage (TR=2000ms; TE= 30ms; flip angle = 75°; FOV = 22 cm; 3.44 x 3.44 x 4 mm resolution, 30 slices).

fMRI Analysis

The fMRI data was analyzed using Lyman, Nipype, Freesurfer, AFNI, and FSL software tools.

Pre-processing

All data went through a standard preprocessing pipeline using Freesurfer and FSL, including motion (RapidART) and slice time correction, realignment (middle volume of each run), skull stripping, temporal filtering (high-pass cutoff 128 Hz), and surface-based coregistration (bbregister). Data were spatially smoothed (6 fwhm, SUSAN -- only averages a given voxel with local voxels that have a similar intensity), scaled grand median of timeseries to 10000, & normalized for group analyses (nonlinear warp to FSL’s MNI152 space). Data were modeled using a double gamma function, and the first 5 frames of each run were discarded.

Results

Behavioral Results

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Figure 3. Recognition Confidence by Morph Type


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Figure 4. dprime by Morph Type


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Figure 5. Recognition Confidence by Morph Type & Previous Trial Confidence

fMRI Results

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Coding Regressors

Highpass Filter Cutoff

Conclusions

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References - Resources and related work

References

Software

Appendix I - Code and Data

Code

File:CodeFile.zip

Data

zip file with my data

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