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Look at Matt Glasser responses: concise, direct and full of useful information. On 1/19/14 4:25 PM, "Watson, Christopher" <[log in to unmask]> wrote: > "Again, a long, not relevant answer to my question." > > You might find you'll have more success in getting help if you stop being so > rude. Particularly to one of the top contributors to the list. > Most people who contribute to this list do so, presumably, because they > believe that for the advancement of science it is important to help others in > their own research. However, you are not *entitled* to receive help, yet you > have already received several long, thoughtful replies. On a Sunday, no less. > > If you truly did read the diffusion textbook and the original research papers, > and still have questions about reduced FA coinciding with increased > connectivity (per probabilistic tractography), then you should re-read the > sources, study the FSL wiki (and the functions' help sections), and read the > literature. This is not a rare topic. > > Chris > ________________________________________ > From: FSL - FMRIB's Software Library [[log in to unmask]] on behalf of Meoded, > Avner (NIH/NINDS) [E] [[log in to unmask]] > Sent: Sunday, January 19, 2014 7:34 AM > To: [log in to unmask] > Subject: Re: [FSL] Values in matrix1 after probtrackx > > Dear Mark > Again, a long, not relevant answer to my question. > What about possible explanations related to probabilistic tractography and > not related to corrected DTI data? From people who deal with probabilistic > tractography every day > > > > Thank you > > Avner > > > On 1/19/14 3:09 AM, "Mark Jenkinson" <[log in to unmask]> wrote: > >> Dear Avner, >> >> I am sorry that you were dissatisfied with my attempts to help you. I >> genuinely try to help everyone that I can on the list. >> >> When working from only a few lines in an email it is hard to not make some >> assumptions, but actually I do not like making assumptions and I try to avoid >> them. I did assume that you work for the NIH (based on your email address >> and >> sign-up name) and therefore were in contact with others in the NIH with >> experience in diffusion imaging and analysis. It is a pity if you do not >> have >> access to such people. >> >> I was not intending to imply that we could not provide you any information, >> but the situation that you described, with unintuitive results in an >> experiment with patients vs controls, requires very careful analysis and >> scrutiny to avoid making incorrect interpretations. This scrutiny would be >> beyond what we could provide in a few paragraphs of an email. Matt has >> explained something about what tractography gives you and provided one >> potential explanation, but as he points out himself there are other >> possibilities and the interpretation is quite challenging. In your case I >> think it is important to carefully investigate all potential factors that >> could drive the results, such as image quality (e.g. SNR), artifacts >> (including what remains after standard artifact correction), the >> anatomy/geometry of the brain areas you are investigating, as well as the >> biology of the particular pathologies involved. Given the many complex issues >> that can arise here, related to diffusion imaging, brain anatomy and biology >> (not just tractography), I recommended that you seek out someone who could >> look carefully through your data and talk to you about issues related to the >> data, the analysis, the anatomy and the biology involved in this particular >> study. >> >> I still recommend that you seek someone out to discuss these issues, since we >> cannot adequately cover these things by email. This is why I was suggesting >> that you find someone in the NIH, but it would not have to be someone from >> there. I make this recommendation because I honestly think it is important >> in >> order to make sure that you get a correct interpretation of your study. If >> you have very specific questions then we are happy to answer them, but I >> strongly encourage you to find someone to discuss your study with in detail. >> >> As for the response from Tim Behrens, I hope that you can appreciate that >> answering emails, writing documentation and textbooks is something that takes >> away from research time and that each of us makes certain sacrifices in order >> to do these things. We all have to decide on the nature and amount to which >> we can undertake such tasks. If we do not limit this time then we would not >> be able to do research, write papers and grants, and therefore stay employed. >> I try to give advice on the list that I feel is of most benefit given the >> limited time I have to answer such queries on what is quite an active email >> list. I hope that you can respect this situation and can believe that my >> emails were really intended to help, even if you were not happy with them. >> >> All the best, >> Mark >> >> >> >> On 18 Jan 2014, at 13:30, "Meoded, Avner (NIH/NINDS) [E]" >> <[log in to unmask]> wrote: >> >>> Dear Mark, >>> >>> I see you like to make assumptions. So let us assume that I am an high >>> school student who does not understand a thing about DTI. Moreover I do not >>> understand the basics of probabilistic tractography. So in order to >>> understand more I read Diffusion MRI book (edited by Berg and Behrens) and >>> also papers that deal with different tractography methods. So now I >>> understand a little bit of tractography but still there are unclear issues >>> that I would like to clarify with the experts in the field- that is the >>> reason I contacted FSL community. >>> If you see the title of my mail it is "Values in matrix1 after probtrackx"; >>> The specific question I have is what those values mean? Probabilistic >>> tractography aim to quantify uncertainty on the PDD and build a connectivity >>> distribution. Now if you go and check matrix obtained from network1 option >>> in probrackx2 you will see that the matrix contain values in the range of >>> 1-1,000,000 and beyond. You mentioned in you last e-mail that: "Uncertainty >>> in direction at any point in the brain will enhance the uncertainty in the >>> tractography from that point onwards for any tracks that pass through that >>> point." How can we learn about this uncertainty from the matrix values? >>> >>> Indeed at the NIH there are many experts who are always available for >>> discussion about all aspects of health and science. However, is >>> FSL/Probtrakcx a NIH application??? >>> >>> Finally I would like to show Timothy Behrens's response to my question : >>> >>> "if you have posted it to the FSL list then you should get an answer soon. >>> It is a very effective community forum. You will understand that with more >>> than 5000 users, there is no way I can personally answer every question and >>> hope to maintain a research career!" >>> >>> This is the answer from the researcher who is the first author on the >>> NeuroImage paper from 2007 about probabilistic tractography, and also the >>> one who wrote the chapter MR diffusion tractography with Saad Jbadi in the >>> book mentioned above. >>> >>> >>> >>> >>> Avner >>> >>> >>> On 1/18/14 4:58 AM, "Mark Jenkinson" <[log in to unmask]> wrote: >>> >>>> Hi, >>>> >>>> Artifact "correction" methods don't fully remove all artifacts, so you >>>> cannot >>>> rule out the possibility that artifacts are causing the things you are >>>> seeing >>>> just because you have run artifact correction. Such methods remove a lot >>>> of >>>> the effect of artifacts but not absolutely everything. >>>> >>>> I'm not sure what you mean by "steps" but the samples in probtrack refer to >>>> individual streamlines (that are selected from the probability distribution >>>> of >>>> possible streamlines). Uncertainty in direction at any point in the brain >>>> will enhance the uncertainty in the tractography from that point onwards >>>> for >>>> any tracks that pass through that point. >>>> >>>> You definite cannot make categorical statements such as "more samples >>>> mean[s] >>>> more disease". >>>> As I said, there are a *lot* of things that can influence tractography >>>> results >>>> and you really should discuss you particular case, with your particular >>>> subjects and you particular data acquisition, with someone who is >>>> experienced >>>> with tractography. There certainly should be such people in the NIH. >>>> >>>> All the best, >>>> Mark >>>> >>>> >>>> On 17 Jan 2014, at 13:10, "Meoded, Avner (NIH/NINDS) [E]" >>>> <[log in to unmask]> wrote: >>>> >>>>> Hi >>>>> The raw DTI data was corrected for artifacts. >>>>> As you mentioned less uncertainty may enhance measures of connectivity. >>>>> But >>>>> in my case I documented reduced FA and not increased FA, the latter is >>>>> seen >>>>> perhaps in regions with reduced crossing fibers. >>>>> Now my question is specific to probabilistic tractography: number of >>>>> samples >>>>> obtained from probtrackx between to regions mean number of "steps" track >>>>> does; are those "steps" depends on the uncertainty? So at the end more >>>>> samples mean more disease? >>>>> >>>>> Thank you >>>>> >>>>> Avner >>>>> >>>>> On 1/17/14 7:39 AM, "Mark Jenkinson" <[log in to unmask]> wrote: >>>>> >>>>>> Hi, >>>>>> >>>>>> These are not simple questions and it will depend a lot on the nature of >>>>>> your >>>>>> data - SNR, artefacts, amount of movement, etc. There are also some >>>>>> potential >>>>>> biological possibilities, such as reduction in crossing tracts, which can >>>>>> enhance measures of connectivity (since there is less uncertainty in the >>>>>> crossing region) without meaning that the axonal tract is biologically >>>>>> "stronger". You should look very critically at your data and show it to >>>>>> people who are experienced with diffusion analysis. >>>>>> >>>>>> All the best, >>>>>> Mark >>>>>> >>>>>> >>>>>> On 16 Jan 2014, at 18:08, "Meoded, Avner (NIH/NINDS) [E]" >>>>>> <[log in to unmask]> wrote: >>>>>> >>>>>>> Dear FSL users >>>>>>> >>>>>>> I conducted a study with network1 option and then did structural >>>>>>> connectome >>>>>>> analysis, in patients affected with neurodegenerative disease. >>>>>>> I also performed TBSS and found reduced FA values in different areas in >>>>>>> patients compared to controls. >>>>>>> The problem is that I have higher values stored in the connectivity >>>>>>> matrices >>>>>>> in patients compared to controls, and hence after connectome analyses I >>>>>>> obtained networks that are more connected in patients. Now I know that >>>>>>> these >>>>>>> values cannot represent axons, but how you can explain reduced FA in >>>>>>> patients >>>>>>> and more streamlines evaluated in probtrackx? Or what are the numbers >>>>>>> stored >>>>>>> in the matrix mean? (after running seed to seed network 1) >>>>>>> >>>>>>> Is this because in patients (with white matter disease, lower FA) there >>>>>>> is >>>>>>> more uncertainty in voxels between roi1 and roi2 and therefore we get >>>>>>> more >>>>>>> samples so basically tracts tend to spread more and as a results more >>>>>>> sample? >>>>>>> so at the end more samples which represents more uncertainty (disease) >>>>>>> Should I normalize the matrices in some way >>>>>>> >>>>>>> >>>>>>> Thank you >>>>>>> >>>>>>> Avner