Hampapur: Difference between revisions
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MNI is an abbreviation for [http://en.wikipedia.org/wiki/Montreal_Neurological_Institute Montreal Neurological Institute]. | MNI is an abbreviation for [http://en.wikipedia.org/wiki/Montreal_Neurological_Institute Montreal Neurological Institute]. | ||
= Methods = | = Methods = | ||
Revision as of 17:45, 14 March 2012
Background
You can use subsections if you like.
Below is an example of a retinotopic map. Or, to be precise, below will be an example of a retinotopic map once the image is uploaded. 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.
MNI space
MNI is an abbreviation for Montreal Neurological Institute.
Methods
Measuring retinotopic maps
Retinotopic maps were obtained in 5 subjects using Population Receptive Field mapping methods Dumoulin and Wandell (2008). These data were collected for another research project in the Wandell lab. We re-analyzed the data for this project, as described below.
Subjects
Subjects were 5 healthy volunteers.
MR acquisition
Data were obtained on a GE scanner. Et cetera.
MR Analysis
The MR data was analyzed using mrVista software tools.
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.
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.
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.