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Revision as of 22:17, 18 March 2013
Back to Psych 221 Projects 2013
Background
Methods
Expectation Maximization
Probability Map
Subjects were 5 healthy volunteers.
2D FFT
Data were obtained on a GE scanner. Et cetera.
Similarity Measure
The MR data was analyzed using mrVista software tools.
Thresholding
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.
Results
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.
See wikimedia help on formulas for help.
This example of equation use is copied and pasted from wikipedia's article on the DFT.
The sequence of N complex numbers x0, ..., xN−1 is transformed into the sequence of N complex numbers X0, ..., XN−1 by the DFT according to the formula:
where i is the imaginary unit and 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 Xk can thus be viewed as coefficients of x in an orthonormal basis.)
The transform is sometimes denoted by the symbol , as in or or .
The inverse discrete Fourier transform (IDFT) is given by
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
Data
Appendix II - Work partition (if a group project)
Brian and Bob gave the lectures. Jon mucked around on the wiki.