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From Psych 221 Image Systems Engineering
Revision as of 02:40, 4 June 2013 by imported>Psych204B (→‎Appendix I - Code and Data)
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Background

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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