Photon Calculator: Difference between revisions

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<br>
 
= 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.
<br>
[[File:Example.jpg | Figure 1]]
 
Below is another example of a reinotopic map in a different subject.
<br>
[[File:Example2.jpg | Figure 2]]
 
Once you upload the images, they look like this. Note that you can control many features of the images, like whether to show a thumbnail, and the display resolution.
[[File:Example3.jpg |thumb|300px|center| Figure 3]]
<br>
 
== MNI space ==
 
MNI is an abbreviation for [http://en.wikipedia.org/wiki/Montreal_Neurological_Institute Montreal Neurological Institute].
 
= Methods =
== Measuring retinotopic maps ==
Retinotopic maps were obtained in 5 subjects using Population Receptive Field mapping methods [http://white.stanford.edu/~brian/papers/mri/2007-Dumoulin-NI.pdf Dumoulin and Wandell (2008)]. These data were collected for another [http://www.journalofvision.org/9/8/768/ 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 [http://white.stanford.edu/newlm/index.php/MrVista 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. <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 - What you found =
 
== Retinotopic models in native space ==
Some text. Some analysis. Some figures.
 
== Retinotopic models in individual subjects transformed into MNI space ==
Some text. Some analysis. Some figures.
 
== Retinotopic models in group-averaged data on the MNI template brain ==
Some text. Some analysis. Some figures. Maybe some equations.
 
 
=== Equations===
If you want to use equations, you can use the same formats that are use on wikipedia. <br>
''See wikimedia help on  [http://meta.wikimedia.org/wiki/Help:Displaying_a_formula formulas] for help.'' <br>
This example of equation use is copied and pasted from [http://en.wikipedia.org/wiki/Discrete_Fourier_transform wikipedia's article on the DFT].
 
The [[sequence]] of ''N'' [[complex number]]s ''x''<sub>0</sub>, ..., ''x''<sub>''N''−1</sub> is transformed into the  sequence of ''N'' complex numbers ''X''<sub>0</sub>, ..., ''X''<sub>''N''−1</sub> by the DFT according to the formula:
 
:<math>X_k = \sum_{n=0}^{N-1} x_n e^{-\frac{2 \pi i}{N} k n} \quad \quad k = 0, \dots, N-1</math> 
           
where i is the imaginary unit and <math>e^{\frac{2 \pi i}{N}}</math>  is a primitive N'th [[root of unity]]. (This expression can also be written in terms of a [[DFT matrix]]; when scaled appropriately it becomes a [[unitary matrix]] and the ''X''<sub>''k''</sub> can thus be viewed as coefficients of ''x'' in an [[orthonormal basis]].)
 
The transform is sometimes denoted by the symbol <math>\mathcal{F}</math>, as in <math>\mathbf{X} = \mathcal{F} \left \{ \mathbf{x} \right \} </math> or <math>\mathcal{F} \left ( \mathbf{x} \right )</math> or <math>\mathcal{F} \mathbf{x}</math>. 
 
The '''inverse discrete Fourier transform (IDFT)''' is given by
 
:<math>x_n = \frac{1}{N} \sum_{k=0}^{N-1} X_k e^{\frac{2\pi i}{N} k n} \quad \quad n = 0,\dots,N-1.</math>
 
== Retinotopic models in group-averaged data projected back into native space ==
Some text. Some analysis. Some figures.
 
 
= Conclusions =
 
Here is where you say what your results mean.
 
= References - Resources and related work =
 
References
 
Software
 
= Appendix I - Code and Data =
 
==Code==
[[File:CodeFile.zip]]
 
==Data==
[[File:DataFile.zip | zip file with my data]]
 
= Appendix II - Work partition (if a group project) =
Brian and Bob gave the lectures. Jon mucked around on the wiki.

Latest revision as of 04:50, 19 March 2013

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