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= Background =
= Background =


Many cortical areas have a one to one mapping between visual field and cortical location (Bressler and Silver 2010). A natural way to explore this is to have a stimulus that traverses the visual field in some fashion, and then do some type of correlation analysis between visual field location and brain activity. Engel et al.  (1993,1994,1997) were one of the first experimenters to develop a continuos stimuli covers all of the visual space. They showed that by using a traveling wave analysis for a rotating wedge and moving concentric circles stimuli, the visual field maps could be produced in occipital cortex. Figure 1, taken from Wandell et al. 2007 illustrates this method.  
Many cortical areas have a one to one mapping between visual field and cortical location (Bressler and Silver 2010). A natural way to explore this is to have a stimulus that traverses the visual field in some fashion, and then do some type of correlation analysis between visual field location and brain activity. Engel et al.  1994, were one of the first experimenters to develop a continuos stimuli that covers all of the visual space for an fMRI experiment. They showed that by using a traveling wave analysis for a rotating wedge and moving concentric circles stimuli, the visual field maps could be produced in occipital cortex. Figure 1, taken from Wandell et al. 2007 illustrates this method.  




[[File:TravelingWaveIllustration.png‎|thumb|300px|center| Figure 1: Traveling Wave Method for creating retinotopic field maps in occipital cortex. Referred to Wandell et al. 2007 for more details. ]]
[[File:TravelingWaveIllustration.png‎|thumb|500px|center| Figure 1: Traveling Wave Method for creating retinotopic field maps in occipital cortex. Referred to Wandell et al. 2007 for more details. ]]




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[[File:Parietal_rois_silver.png‎|thumb|300px|center| Figure 3:  Topographic Maps Parietal Cortex from Silver and Kastner 2009]]
[[File:Parietal_rois_silver.png‎|thumb|400px|center| Figure 3:  Topographic Maps Parietal Cortex from Silver and Kastner 2009]]




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[[File:Rois.001.jpg | thumb|500px|center| Figure 5: Ventral Visual Field Maps ]]
[[File:Rois.001.jpg | thumb|500px|center| Figure 5: Ventral Visual Field Maps ]]


Figure 5 shows the maps produced using this procedure in ventral visual cortex. Starting in V1, moving dorsally a blue contrast reversal is seen and that marks the start of V2
Figure 5 shows the maps produced using this procedure in ventral visual cortex. Starting in V1, moving dorsally a blue contrast reversal is seen, indicating the end of that hemifield and the marks the start of V2d. The distinction between V2 and V3 is not as marked, but it is there. From V3d there is a clear blue and then red reversal, which marks the start of V4. After V4; VO1, VO2, PHC1 and PHC2 can be easily identified. Also from VO1 all the ROI's follow the colateral sulcus.


[[File:Rois.002.jpg | thumb|500px|center| Figure 6: Dorsal Visual Field Maps ]]
[[File:Rois.002.jpg | thumb|500px|center| Figure 6: Dorsal Visual Field Maps ]]
V2d is defined by continuing dorsally from V1 in the Calcarine sulcus. V2d and V3d were a bit tricky to identify since the reversals were not as marked as in other areas. V3dAB follows V3d by going red to blue, then IPS0 by going blue to red.


[[File:Rois.003.jpg | thumb|500px|center| Figure 7: Parietal Maps ]]
[[File:Rois.003.jpg | thumb|500px|center| Figure 7: Parietal Maps ]]


 
In this subject the parietal field maps are not as clear as the ventral ones. But some of the reversals can still be seen in these areas. Continuing dorsally from IPS0 a red reversal is observed to start IPS1. The start of IPS2 is a bit tricky since there wasn't too much signal. However, maps continue dorsally and this subject showed a very clear SPL1.  
 
 
 
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 =
= Conclusions =


Here is where you say what your results mean.
The goal of this project was to receive training in how to do retinotopy/ attenotopy using mrVista. I defined a total of 15 maps in ventral visual cortex and in parietal cortex. There is definitely an element of judgement when defining these maps as must of the boundaries are defined by approximating where one thinks the reversal takes place. Moreover, these maps are highly variable across subjects and a good amount of experience is needed in order to be consistant in defining these maps. Nonetheless, I must admit that it is very cool seeing and defining these maps, and also to see how the brain organizes what we observe. Special thanks to Kevin Weiner who helped at every step, from obtaining the data getting everything running, to checking that the ROI's made were not in frontal cortex.
 
= References - Resources and related work =


References
= References =


Software
Bressler DW, Silver MA (2010) Spatial attention improves reliability of fMRI retinotopic mapping signals in occipital and parietal cortex. NeuroImage


= Appendix I - Code and Data =
Brian A. Wandell, Serge O. Dumoulin, Alyssa A. Brewer, Visual Field Maps in Human Cortex, Neuron, Volume 56, Issue 2, 25 October 2007


==Code==
Brian A. Wandell, Jonathan Winawer, Imaging retinotopic maps in the human brain, Vision Research, Volume 51, Issue 7, 13 April 2011
[[File:CodeFile.zip]]


==Data==
Engel SA, Rumelhart DE, Wandell BA, Lee AT, Glover GH, Chichilnisky EJ, Shadlen MN(1994) fmri of human visual cortex. Nature 369:525
[[File:DataFile.zip | zip file with my data]]


= Appendix II - Work partition (if a group project) =
Silver MA, Kastner S (2009) Topographic maps in human frontal and parietal cortex. Trends in Cognitive Sciences
Brian and Bob gave the lectures. Jon mucked around on the wiki.

Latest revision as of 03:42, 16 March 2012

Retinotopy/Attenotopy

This project is about mapping field maps in high level visual areas. Over the last years it has been shown that with a few modifications to the classic retinotopy paradigm and better processing techniques, more maps can be consistently found in more areas in addition to occipital cortex. One version of these paradigm modifications, is making the subject covertly attend to the rotating wedge by having a target detection task, while the subject maintains fixation. This is method is appropriately named attenotopy. Furthermore, evidence shows that there are attention processes occurring in parietal cortex. By having an embedded attention task in the classic retinotopy task, we will be able to map visual fields in parietal cortex in addition to all the other occipital cortex maps.

Background

Many cortical areas have a one to one mapping between visual field and cortical location (Bressler and Silver 2010). A natural way to explore this is to have a stimulus that traverses the visual field in some fashion, and then do some type of correlation analysis between visual field location and brain activity. Engel et al. 1994, were one of the first experimenters to develop a continuos stimuli that covers all of the visual space for an fMRI experiment. They showed that by using a traveling wave analysis for a rotating wedge and moving concentric circles stimuli, the visual field maps could be produced in occipital cortex. Figure 1, taken from Wandell et al. 2007 illustrates this method.


Figure 1: Traveling Wave Method for creating retinotopic field maps in occipital cortex. Referred to Wandell et al. 2007 for more details.


Several other cortical areas have been mapped with fMRI including: V1,V2,V3,V4, V3A, V3B, V6, V7 or IPS0, IPS1, IPS2, IPS3 , IPS4, V01, V02, PHC1,PHC2 among many others (Silver and Kastner 2009), Figure 2 and Figure 3. Not that some of these areas extend beyond what was classically thought to be visual cortex. Visual maps in IPS(0-4) lie on the posterior part of parietal cortex. This particular region has been associated with cognitive processes such as attention and memory (Silver and Kastner 2009, see also Bressler and Silver 2010). Specifically, it is now widely accepted that allocation of attention while doing a retinotopic experiment increases the ability to produce field maps (Wandell and Winawer 2011, Bressler and Silver 2010). To this effect, Bressler and Silver made a quantitative study in order to analyze the gain in terms of SNR of this effect. This project uses the same stimuli as the Bressler study and produces similar maps.


Figure 2: Topographic Maps in Ventral Visual Cortex from Silver and Kastner 2009


Figure 3: Topographic Maps Parietal Cortex from Silver and Kastner 2009


Methods

Stimuli

As mentioned before the stimuli used was as in Bressler and Silver 2010, Figure 2. A flickering checkerboard rotating wedge traverses the visual field in clockwise fashion. The wedge is 45 degrees wide, and extends 0.5 degrees to 10.9 degrees from a central fixation. The wedge rotates 22.5 deg locked to the scanner's TR at 2.13s. It takes the wedge 34.13 seconds to complete a cycle and there are 8 cycles that go into the analysis. A target appears with 50% probability inside the wedge. The subject is instructed to respond when a target appears, while maintaining fixation. Refer to Bressler and Silver 2010 for more details.

Figure 4: Rotating Wedge with an embedded target detection task.

Preprocessing

For this project only one subject was analyzed, and only the right hemisphere is presented here. mrVista was used for data preprocessing and analysis. Traditional retinotopy analyzes were used, i.e. the coherence between the frequency produced by a stimulus cycle of 34.13s and the average fMRI time series for each voxel was calculated (Engel et al. 1994). The resulting maps are transformed into an inflated 3D cortical view. In this view the regions of interest were defined and stored.

Analysis and Results

Visual field maps were defined following Wandell et al. 2007 definitions. Briefly, a visual field area should: 1) represent a substantial portion of the visual field, 2) it must do so in an orderly fashion, 3) the basic features should be consistant within subjects. Starting from V1 (easily identified by the Calcarine Sulcus) contrast reversals are followed dorsally and ventrally to define the rest of the maps. The results are shown in the following figures.

Figure 5: Ventral Visual Field Maps

Figure 5 shows the maps produced using this procedure in ventral visual cortex. Starting in V1, moving dorsally a blue contrast reversal is seen, indicating the end of that hemifield and the marks the start of V2d. The distinction between V2 and V3 is not as marked, but it is there. From V3d there is a clear blue and then red reversal, which marks the start of V4. After V4; VO1, VO2, PHC1 and PHC2 can be easily identified. Also from VO1 all the ROI's follow the colateral sulcus.

Figure 6: Dorsal Visual Field Maps

V2d is defined by continuing dorsally from V1 in the Calcarine sulcus. V2d and V3d were a bit tricky to identify since the reversals were not as marked as in other areas. V3dAB follows V3d by going red to blue, then IPS0 by going blue to red.

Figure 7: Parietal Maps

In this subject the parietal field maps are not as clear as the ventral ones. But some of the reversals can still be seen in these areas. Continuing dorsally from IPS0 a red reversal is observed to start IPS1. The start of IPS2 is a bit tricky since there wasn't too much signal. However, maps continue dorsally and this subject showed a very clear SPL1.

Conclusions

The goal of this project was to receive training in how to do retinotopy/ attenotopy using mrVista. I defined a total of 15 maps in ventral visual cortex and in parietal cortex. There is definitely an element of judgement when defining these maps as must of the boundaries are defined by approximating where one thinks the reversal takes place. Moreover, these maps are highly variable across subjects and a good amount of experience is needed in order to be consistant in defining these maps. Nonetheless, I must admit that it is very cool seeing and defining these maps, and also to see how the brain organizes what we observe. Special thanks to Kevin Weiner who helped at every step, from obtaining the data getting everything running, to checking that the ROI's made were not in frontal cortex.

References

Bressler DW, Silver MA (2010) Spatial attention improves reliability of fMRI retinotopic mapping signals in occipital and parietal cortex. NeuroImage

Brian A. Wandell, Serge O. Dumoulin, Alyssa A. Brewer, Visual Field Maps in Human Cortex, Neuron, Volume 56, Issue 2, 25 October 2007

Brian A. Wandell, Jonathan Winawer, Imaging retinotopic maps in the human brain, Vision Research, Volume 51, Issue 7, 13 April 2011

Engel SA, Rumelhart DE, Wandell BA, Lee AT, Glover GH, Chichilnisky EJ, Shadlen MN(1994) fmri of human visual cortex. Nature 369:525

Silver MA, Kastner S (2009) Topographic maps in human frontal and parietal cortex. Trends in Cognitive Sciences

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