<div dir="ltr">Hi Alessandra<br><div class="gmail_extra"><div class="gmail_quote"><div> </div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex"><div dir="ltr"><div><div><div><div><div><div><span><span>I was wondering how streamtrack work in generating and selecting tracks. As far as I could see from mailing list, number of streamlines generated are usually higher than actually selected. Both commands can be set by -maxnum and -number options.<br>Reasons for excluding a streamline depend basically on tract length, inclusion or exclusion rois used.<br></span></span></div><span><span>To get somehow a sense of the probability to get a connection one could divide number of selected streamlines to the number of generated ones.<br></span></span></div></div></div></div></div></div></blockquote><div><br></div><div>Yes, that is one option, but I'd stress that you really want to avoid any interpretation of that number as a measure of actual probability. This is the reason why Geoff Parker talks about a <a href="http://www.ncbi.nlm.nih.gov/pubmed/12884338">probabilistic index of connectivity (PICo)</a> rather than actual probabilities - there are far too many factors that come into it, see for example <a href="http://www.ncbi.nlm.nih.gov/pubmed/22846632">Derek Jones' excellent paper on the topic</a>.</div><div> </div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex"><div dir="ltr"><div><div><div><div><div><span><span></span></span></div><span><span>Looking at the messages in the archives, during probabilistick tracking, seed points are randomly
selected within the seed mask, then a direction is chosen and eventually
stream process starts if amplitude in that direction is higher than
initcutoff.</span></span><br><span><span><span><span>From my point of view an approach where a certain
number of attempts are made from each voxel in brain mask would make a
lot of sense to provide meaningful probability results related to
"existence" of a connection; giving the opportunity to choice output
number could be potentially dangerous, expecially when making connectomics
analyses. </span></span></span></span></div></div></div></div></div></blockquote><div><br></div><div>Well, I'd disagree to some extent with the word 'meaningful' in this context, but yes, this is a common request. This option is actually available in MRtrix3 (along with lots of other approaches to seeding). Unfortunately, we have no plans to back-port that feature to the MRtrix 0.2 version.</div><div> </div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex"><div dir="ltr"><div><div><div><div>I see there exists an option in streamtrack, -trials. How it does work precisely?<br></div></div><span><span>I tried with a single voxel seed, fixing maxnum and number (100 or 500) and varying trials parameter. Considering i have set a negligible cutoff for minlength (1mm), what i see is that results strongly depend on trials parameter. Really small trials (5) cause all tracts terminating quite close to seed point; with higher number of trials, results get better. On the other side, the larger this number, the higher the likely to get spurious connections. <br>Is it correct to say, due to request of a certain number of streamlines, a lot of seed points are initializied within that unique seed voxel, and only after that trial parameter gets effective?<br></span></span></div></div></div></blockquote><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex"><div dir="ltr"><div><div><span><span>I am asking because I am not interested in making whole brain analysis, hence I want to carefully inspect how these parameters work. In the light of that, what could be a good compromise when handling trials, number and maxnum parameters?<br></span></span></div></div></div></blockquote><div><br></div><div><div><div>The -trials option is unrelated to what you're interested in - it's to do with the rejection sampling used during probabilistic tracking, and really shouldn't need to be adjusted. What you want in this scenario is to set -maxnum and -number to the same value. </div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex"><div dir="ltr"><div></div></div></blockquote></div><div><br></div><div>I would say if you need finer control over the seeding strategy, you'll want to try <a href="https://github.com/MRtrix3/mrtrix3">MRtrix3</a> instead. And if you're seriously interested in connectomics, I recommend you think about including <a href="http://www.ncbi.nlm.nih.gov/pubmed/22705374">ACT</a> & <a href="http://www.ncbi.nlm.nih.gov/pubmed/23238430">SIFT</a> to generate connectomes with meaningful track counts - both of which are available in MRtrix3 and documented in their respective wiki entries (<a href="https://github.com/MRtrix3/mrtrix3/wiki/Anatomically-Constrained-Tractography-%28ACT%29">ACT</a>, <a href="https://github.com/MRtrix3/mrtrix3/wiki/SIFT">SIFT</a>), along with our r<a href="https://github.com/MRtrix3/mrtrix3/wiki/Structural-connectome-construction">ecommendations regarding connectomic analysis</a>.</div><div><br></div><div>Hope that helps,</div><div>Donald.</div><div><br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex"><div dir="ltr"><div></div></div></blockquote></div><div> </div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex"><div dir="ltr"><div><div><span><span><br></span></span></div><span><span>Best,<br></span></span></div><span><span>Alessandro<span class=""><font color="#888888"><br clear="all"></font></span></span></span><span class=""><font color="#888888"><div><div><div><div><div><div><div><div><div><div><div><div><div><br>-- <br><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr">Alessandro Calamuneri, M.Sc., PhD<br><div>Department of Neurosciences, University of Messina, Italy</div>
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<br></blockquote></div><br><br clear="all"><div><br></div>-- <br><div class="gmail_signature"><div dir="ltr"><b><font color="#990000">Dr J-Donald Tournier (PhD)</font></b><br><div><font color="#990000"><br></font></div><i><font color="#990000">Senior Lecturer, </font></i><i><font color="#990000">Biomedical Engineering</font></i><div><i><font color="#990000">Division of Imaging Sciences & Biomedical Engineering<br>King's College London</font></i><div><i><font color="#990000"><br></font></i></div><div><i><font color="#990000"><b style="font-family:Calibri,sans-serif;font-size:15px"><span style="font-size:10pt">A:</span></b><span style="font-family:Calibri,sans-serif;font-size:10pt"> Department of Perinatal Imaging & Health, 1<sup>st</sup> Floor South Wing, St Thomas' Hospital, London. SE1 7EH</span><br></font></i></div><div><i><font color="#990000"><b>T:</b> +44 (0)20 7188 7118 ext 53613</font></i></div></div><div><i><font color="#990000"><b>W:</b> <a href="http://www.kcl.ac.uk/medicine/research/divisions/imaging/departments/biomedengineering" target="_blank">http://www.kcl.ac.uk/medicine/research/divisions/imaging/departments/biomedengineering</a></font></i><br></div></div></div>
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