In my opinion, there are some advantages to ft_read_cifti. I personally
have not run into bugs with ft_read_cifti in my applications and am able to
go back and forth between wb_view and matlab with vertices and voxels in
the correct ordering. The main benefit of ft_read_cifti is that it reads in
additional information, for example, reading the rs-fMRI data results in
subject=num2str(100206);
subjLR1 = ft_read_cifti(['~/HCP_rs/Subjects/' subject
'/rfMRI_REST1_LR_Atlas_MSMAll_hp2000_clean.dtseries.nii']);
subjLR1
subjLR1 =
dimord: 'pos_time'
time: [1x1200 double]
hdr: [1x1 struct]
unit: 'mm'
brainstructure: [96854x1 double]
brainstructurelabel: {1x21 cell}
dim: [91 109 91]
pos: [96854x3 double]
transform: [4x4 double]
dtseries: [96854x1200 double]
and in particular .brainstructure and .brainstructurelabel can be used to
extract subcortical regions easily.
In contrast, ciftiopen returns a gifti object containing a single array
>> subjLR1_ciftiopen = ciftiopen(['~/HCP_rs/Subjects/' subject
'/rfMRI_REST1_LR_Atlas_MSMAll_hp2000_clean.dtseries.nii'],...
'/home/samsi/Applications2/workbench/bin_linux64/wb_command');
subjLR1_ciftiopen
subjLR1_ciftiopen =
cdata: [91282x1200 single]
I just made this example of how to get the data to match up:
subject=num2str(100206);
subjLR1 = ft_read_cifti(['~/HCP_rs/Subjects/' subject
'/rfMRI_REST1_LR_Atlas_MSMAll_hp2000_clean.dtseries.nii']);
subjLR1
% optional:
subjLR1.dtseries = single(subjLR1.dtseries);
subjLR1_ciftiopen = ciftiopen(['~/HCP_rs/Subjects/' subject
'/rfMRI_REST1_LR_Atlas_MSMAll_hp2000_clean.dtseries.nii'],...
'/home/samsi/Applications2/workbench/bin_linux64/wb_command');
subjLR1_ciftiopen
nomedialwall = ~isnan(subjLR1.dtseries(:,1));
test = subjLR1.dtseries(nomedialwall,:);
size(test)
all(subjLR1_ciftiopen.cdata(:)==test(:))
norm(subjLR1_ciftiopen.cdata - test,'fro')
If people have other thoughts on ft_read_cifti or concerns with anything
above, maybe we can get a new thread going.
Best,
Ben
On Tue, Oct 25, 2016 at 6:20 PM, Glasser, Matthew <[email protected]>
wrote:
> ciftiopen uses single precision. I remain puzzled where people are
> getting the idea to use ft_read_cifti from for MRI data.
>
> Peace,
>
> Matt.
>
> From: <[email protected]> on behalf of Timothy
> Coalson <[email protected]>
> Date: Tuesday, October 25, 2016 at 3:55 PM
> To: "Harms, Michael" <[email protected]>
> Cc: "[email protected]" <[email protected]>
> Subject: Re: [HCP-Users] Problem with handling dense FC matrix
>
> The ciftiopen option of matlab cifti support should allow you to load the
> file, though I think it loads as double, and you'd need to convert it to
> single to reclaim some memory (which comes close to your memory+swap cap,
> as it needs the double and single versions allocated simultaneously in
> order to do the conversion).
>
> One possibility, if you don't really need a 90k x 90k network, is
> downsampling or parcellating the dense connectome, see http://www.
> humanconnectome.org/software/workbench-command.php?
> function=-cifti-parcellate .
>
> If you do need the 90k x 90k resolution, and can work in c++ instead of
> matlab, you could use CiftiLib for reading the file (can read single rows
> from disk, rather than the entire matrix into memory), or code up a new
> command for wb_command (same support for cifti, but also support for other
> file types, access to other algorithms).
>
> Tim
>
>
> On Tue, Oct 25, 2016 at 3:21 PM, Harms, Michael <[email protected]> wrote:
>
>>
>> If you’re talking about some sort of community/modularity analysis, then,
>> no, there aren’t any tools for doing that directly in workbench.
>>
>> Maybe Tim C. will have some suggestions. I believe that the dconn is
>> stored as a single precision float. Have you tried using ‘ciftiopen’? I’m
>> not sure if that preserves the single precision format of the data, or if
>> it balloons by a factor of 2 due to conversion to matlab’s default double
>> precision format. If you can keep it as single precision in matlab, you
>> might be able to work with it provided Matlab has access to a lot of RAM.
>>
>> cheers,
>> -MH
>>
>> --
>> Michael Harms, Ph.D.
>> -----------------------------------------------------------
>> Conte Center for the Neuroscience of Mental Disorders
>> Washington University School of Medicine
>> Department of Psychiatry, Box 8134
>> 660 South Euclid Ave.Tel: 314-747-6173
>> St. Louis, MO 63110Email: [email protected]
>>
>> From: "GLOMB, KATHARINA" <[email protected]>
>> Date: Tuesday, October 25, 2016 at 10:35 AM
>> To: Michael Harms <[email protected]>
>> Subject: Re: [HCP-Users] Problem with handling dense FC matrix
>>
>> Hi Michael,
>>
>> wow, thank you for this lightning speed reply! I want to run some network
>> analysis on this matrix.I don't need the whole matrix, I would just need
>> the unique entries (off-diagonal upper or lower triangular, squareform() in
>> Matlab) - maybe that would help? Can workbench help me in any way to do
>> this?
>>
>> Or do you have any other ideas?
>>
>> Thank you!
>> Katharina
>>
>> On Tue, Oct 25, 2016 at 5:21 PM, Harms, Michael <[email protected]> wrote:
>>
>>>
>>> What are you trying to do with the file in workbench? Have you reviewed
>>> the tutorial, because it includes examples (and a scene to help you along)
>>> of using that file.
>>>
>>> Trying to load/work with that file in matlab is probably going to cause
>>> loads of pain. It is just too large to load the entire thing into matlab.
>>>
>>> cheers,
>>> -MH
>>>
>>> --
>>> Michael Harms, Ph.D.
>>> -----------------------------------------------------------
>>> Conte Center for the Neuroscience of Mental Disorders
>>> Washington University School of Medicine
>>> Department of Psychiatry, Box 8134
>>> 660 South Euclid Ave.Tel: 314-747-6173
>>> St. Louis, MO 63110Email: [email protected]
>>>
>>> From: <[email protected]> on behalf of "GLOMB,
>>> KATHARINA" <[email protected]>
>>> Date: Tuesday, October 25, 2016 at 10:15 AM
>>> To: "[email protected]" <[email protected]>
>>> Subject: [HCP-Users] Problem with handling dense FC matrix
>>>
>>> Hello HCP users,
>>>
>>> I am new to HCP so please excuse me if I'm asking something that should
>>> be obvious. I've tried to find a solution but haven't been successful so
>>> far. I am trying to use the file
>>> HCP_S900_820_rfMRI_MSMAll_groupPCA_d4500ROW_zcorr.dconn.nii
>>> which to my understanding should contain a full FC matrix that is an
>>> average of 820 subjects. I want to feed this matrix into a Matlab function.
>>> Of course, this is problematic because of the memory requirements. I have
>>> tried to read the file using ft_read_cifti from fieldtrip, but Matlab
>>> crashes at 112 GB of memory. So clearly, this is not the way.
>>>
>>> I know I am supposed to be able to use workbench for that, but can't
>>> make it work so far. Can someone point me in the right direction? Is what
>>> I'm trying to do impossible?
>>>
>>> I am using a cluster that can handle up to 132 GB of memory per cpu
>>> (RAM+swap) and runs Debian.
>>>
>>> Thank you!!
>>> Katharina
>>>
>>> --
>>> PhD candidate <http://www.cns.upf.edu/katharina>
>>> Computational Neuroscience Group <http://www.cns.upf.edu/>
>>> Center for Brain and Cognition <http://cbc.upf.edu/>
>>> Universitat Pompeu Fabra <http://www.upf.edu/>
>>> Barcelona, Spain
>>>
>>> I am funded by the INDIREA <http://www.indirea.eu/> Marie Curie Initial
>>> Training Network.
>>>
>>> _______________________________________________
>>> HCP-Users mailing list
>>> [email protected]
>>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users
>>>
>>>
>>> ------------------------------
>>>
>>> The materials in this message are private and may contain Protected
>>> Healthcare Information or other information of a sensitive nature. If you
>>> are not the intended recipient, be advised that any unauthorized use,
>>> disclosure, copying or the taking of any action in reliance on the contents
>>> of this information is strictly prohibited. If you have received this email
>>> in error, please immediately notify the sender via telephone or return mail.
>>>
>>
>>
>>
>> --
>> PhD candidate <http://www.cns.upf.edu/katharina>
>> Computational Neuroscience Group <http://www.cns.upf.edu/>
>> Center for Brain and Cognition <http://cbc.upf.edu/>
>> Universitat Pompeu Fabra <http://www.upf.edu/>
>> Barcelona, Spain
>>
>> I am funded by the INDIREA <http://www.indirea.eu/> Marie Curie Initial
>> Training Network.
>>
>>
>> ------------------------------
>>
>> The materials in this message are private and may contain Protected
>> Healthcare Information or other information of a sensitive nature. If you
>> are not the intended recipient, be advised that any unauthorized use,
>> disclosure, copying or the taking of any action in reliance on the contents
>> of this information is strictly prohibited. If you have received this email
>> in error, please immediately notify the sender via telephone or return mail.
>>
>> _______________________________________________
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>> [email protected]
>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users
>>
>
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> The materials in this message are private and may contain Protected
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> disclosure, copying or the taking of any action in reliance on the contents
> of this information is strictly prohibited. If you have received this email
> in error, please immediately notify the sender via telephone or return mail.
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