This would be a great outcome of this discussion.
With recent versions of SPM12, there is already an export to
NIDM-Results available through a right-click in the results table. An
implementation of a direct upload to NeuroVault exists but the option is
not offered in the interface yet for some boring technical reasons that
will hopefully be resolved soon. A manual upload should be rather
straightforward though.
Best wishes,
Guillaume.
On 07/09/17 16:42, [log in to unmask] wrote:
> Thanks for the link Guillaume.
>
> As the original poster I was never happy about reporting peaks, especially in large clusters.
>
> After all this discussion I think it is time to focus my own work on a more open approach to results sharing such as suggested in the article, and encourage my colleagues as well. Particularly I would love to see more people sharing maps in a way that would allow me more directly compare the topography of my results with others.
>
> Hopefully this discussion pushes a few researchers into more open data approaches.
>
>
> Colin Hawco, PhD
> Neuranalysis Consulting
> Neuroimaging analysis and consultation
> www.neuranalysis.com
> [log in to unmask]
>
>
>
>
> -----Original Message-----
> From: Guillaume Flandin [mailto:[log in to unmask]]
> Sent: September-07-17 11:20 AM
> To: [log in to unmask]
> Cc: [log in to unmask]
> Subject: Re: [SPM] R: [SPM] reporting cluster-corrected results
>
> Dear Colin,
>
> I agree with you and it was the direction of my perhaps slightly cryptic previous email in this thread.
>
> To report a significant cluster, you report its size (in voxels, mm3, resels, as this is the statistic you made an inference on) and its associated p-value adjusted for the search space. Then unless you present a list of the coordinates of all the voxels subtending the cluster, you are making a selective reporting. As you mention, there are now several ways to store statistical maps online that you can link to in your publications, NeuroVault being one of them:
>
> https://neurovault.org/
> https://www.ncbi.nlm.nih.gov/pubmed/25869863
>
> There is also an emerging standard called NIDM to capture all of the neuroimaging statistical results (for AFNI, FSL, SPM):
>
> https://www.nature.com/articles/sdata2016102
>
> This is particularly relevant for image-based meta-analyses (as opposed to coordinate-based).
>
> Best regards,
> Guillaume.
>
>
> On 06/09/17 19:52, Colin Hawco wrote:
>> Another option which hasn't really been raised is to supplement with online imaging data, with the t-maps reported in the papers overlaid on an anatomical (low-res if you want to be truly honest as to the spatial specificity of your fMRI group maps). A growing number of online platforms exist for this, or journals that allow for uploading this sort of info. Or even post the t-map on a source like github and let interested readers make their own assessments based on the actual data rather than a summary table.
>>
>> This isn't yet common practice but maybe it should be.
>>
>> At the end, the presented options are all rather inadequate ways to represent the complexity of our imaging findings. Presenting a peak is in a lot of ways misleading, presenting a large number of sub-peaks can be too much information to be useful to a reader, center of mass works well for blobular clusters but not complex shapes, reporting regions (via atlas or whatever) is prone to mislabelling and can depend on the atlas and also how general the region reported is (e.g. mid-frontal gyrus as opposed BA 46).
>>
>> Amongst a group of inadequate options for summary table, providing access to the group tmap provides the most accurate and detailed result.
>>
>> Colin Hawco, PhD
>> Neuranalysis Consulting
>> Neuroimaging analysis and consultation www.neuranalysis.com
>> [log in to unmask]
>>
>>
>>
>> -----Original Message-----
>> From: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]]
>> On Behalf Of Donald McLaren
>> Sent: September-06-17 9:39 AM
>> To: [log in to unmask]
>> Subject: Re: [SPM] R: [SPM] reporting cluster-corrected results
>>
>> Hi Luca,
>>
>> I generally suggest reporting all peaks separated by a specified distance. If you have a lot of peaks, then add a supplemental table. This will also benefit anyone who wants to use your data for a meta-analysis.
>>
>> Keep in mind that SPM only reports the top 3 peaks in each cluster, so you may need any alternative program to get all the peaks or change SPM settings.
>>
>> Best,
>> Donald
>>
>>> On Sep 6, 2017, at 4:42 AM, PRESOTTO LUCA <[log in to unmask]> wrote:
>>>
>>> Dear Helmut and other experts,
>>>
>>> I was pondering about the same things as Bianca.
>>>
>>> I've attached two pretty standard pattern that I find in my analyses (in both cases they're thresholded at p<0.05, FEW). One it's a (pretty standard and known) group analysis of DLB patients vs controls in PET, the other it's a correlation study between PET methabolism and a neuropsychological score.
>>>
>>> I'd find that reporting the cluster peak location would be extremely misleading in both cases, as the effect can be seen in very large (and specific) brain regions and not in a "point".
>>>
>>> In which way would you describe the observed results in a paper?
>>>
>>>
>>> Thank you,
>>> Luca
>>>
>>> -----Messaggio originale-----
>>> Da: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]]
>>> Per conto di MRI More
>>> Inviato: lunedì 4 settembre 2017 16:26
>>> A: [log in to unmask]
>>> Oggetto: Re: [SPM] reporting cluster-corrected results
>>>
>>> Dear Bianca,
>>>
>>>> though I am still worried that this practice of reporting of
>>>> cluster-peaks leads to misunderstandings on the nature of cluster correction (and leads people/readers to infer spatial specificity that is not there).
>>>
>>> Also don't forget the smoothing. Peaks, clusters are usually labeled based on unsmoothed maximum probability maps (same for region of interest analyses), and T maps are often mapped onto unsmoothed anatomical high-res data, which implies anatomical precision that simply doesn't exist and can also be very misleading in case the geometric artefacts in the EPIs are rather large (e.g. OFC). It's an established routine though. It's also established to present thresholded data, hiding the rest.
>>>
>>>> In the past, I have used my strategy 1 for this, but this then means
>>>> no coordinates are reported
>>>
>>> IMO this is bad. In case one wants to find out the exact location of
>>> the cluster one has to rely on figures then, which can be very
>>> misleading (especially surface renderings). For the gross
>>> localization labels can do it, but their use is limited as well as
>>> parcellations can differ quite a bit (e.g. how many frontal or cingulate regions).
>>> Thus one would also have to consult the corresponding atlas file
>>> first, which might not be implemented in the default software. Thus
>>> I'd suggest to report *some* coordinates, be it peak coordinates or
>>> center of mass. In that case the reader only has to find out which
>>> MNI version you are refering to and/or whether preprocessing has led
>>> to any deviations (e.g. a non-MNI Dartel template) ;)
>>>
>>>> where I have no cluster-peaks to report
>>>
>>> I would report the center of the mass then, which might be sufficient in most instances. In case the center came to lie outside the cluster I'd prefer a different measure though. For larger clusters the range seems to make sense, although it might be very difficult to infer the exact form of the cluster without an additional figure.
>>>
>>> Best regards
>>>
>>> Helmut
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> --
> Guillaume Flandin, PhD
> Wellcome Trust Centre for Neuroimaging
> University College London
> 12 Queen Square
> London WC1N 3BG
>
--
Guillaume Flandin, PhD
Wellcome Trust Centre for Neuroimaging
University College London
12 Queen Square
London WC1N 3BG
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