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--></style></head><body lang=NL link=blue vlink="#954F72"><div class=WordSection1><p class=MsoNormal><span lang=EN-GB>Dear Jan-Mathijs, <o:p></o:p></span></p><p class=MsoNormal><span lang=EN-GB><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-GB>Thank you for your quick reply. <o:p></o:p></span></p><p class=MsoNormal><span lang=EN-GB><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-GB>@1R Indeed </span><span lang=EN-GB>ft_connectivityanalysis on individual dipole positions (PCC). Cfg.refindx’ seems not to do anything, are there other options to run a seed-based connectivity analysis? <o:p></o:p></span></p><p class=MsoNormal><span lang=EN-GB>@R2 We indeed performed </span><span lang=EN-GB>source-reconstruction for each subject on a subject-specific grid, that maps onto a template grid in spatially normalized space. <o:p></o:p></span></p><p class=MsoNormal><span lang=EN-GB> I constructed a GA of the individual data and would like to plot these on a standard cortical sheet / brain surface. <o:p></o:p></span></p><p class=MsoNormal><span lang=EN-GB><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-GB>Best <o:p></o:p></span></p><p class=MsoNormal><span lang=EN-GB>Conny <o:p></o:p></span></p><p class=MsoNormal><o:p> </o:p></p><div style='mso-element:para-border-div;border:none;border-top:solid #E1E1E1 1.0pt;padding:3.0pt 0cm 0cm 0cm'><p class=MsoNormal style='border:none;padding:0cm'><b>Van: </b><a href="mailto:jan.schoffelen@donders.ru.nl">Schoffelen, J.M. (Jan Mathijs)</a><br><b>Verzonden: </b>woensdag 24 oktober 2018 10:16<br><b>Aan: </b><a href="mailto:fieldtrip@science.ru.nl">FieldTrip discussion list</a><br><b>Onderwerp: </b>Re: [FieldTrip] seed based SOURCE connectivity analysis betweenGroups - GA, plotting and statistics</p></div><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Hi Conny,<o:p></o:p></p><div><div><div><p class=MsoNormal><o:p> </o:p></p></div><div><p class=MsoNormal>You are a bit short on the details, so it is hard to give to-the-point feedback.<o:p></o:p></p></div><div><p class=MsoNormal><o:p> </o:p></p></div><div><p class=MsoNormal>@1 this depends on the type of connectivity metric you have in mind. You mention the ‘cfg.refindx’ so I assume that you want to use ft_connectivityanalysis. Also, do you use ‘parcellated’ source data, or is the data defined on individual dipole positions?<o:p></o:p></p></div><div><p class=MsoNormal><o:p> </o:p></p></div><div><p class=MsoNormal>@2 this works best if your individual subject source models can be easily compared, e.g. according to <o:p></o:p></p></div><div><p class=MsoNormal><o:p> </o:p></p></div><div><p class=MsoNormal><a href="http://www.fieldtriptoolbox.org/tutorial/sourcemodel#performing_group_analysis_on_3-dimensional_source-reconstructed_data">http://www.fieldtriptoolbox.org/tutorial/sourcemodel#performing_group_analysis_on_3-dimensional_source-reconstructed_data</a><o:p></o:p></p></div><div><p class=MsoNormal><o:p> </o:p></p></div><div><p class=MsoNormal>This allows for averaging/statistics at the low-number-of-sources (before interpolation) and saves a lot of memory.<o:p></o:p></p></div><div><p class=MsoNormal><o:p> </o:p></p></div><div><p class=MsoNormal>Best wishes,<o:p></o:p></p></div><div><p class=MsoNormal><o:p> </o:p></p></div><div><p class=MsoNormal>Jan-Mathijs<o:p></o:p></p></div><div><p class=MsoNormal><o:p> </o:p></p><div><p class=MsoNormal><o:p> </o:p></p></div><div><p class=MsoNormal><br><br><o:p></o:p></p><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><div><p class=MsoNormal>On 23 Oct 2018, at 00:18, Quaedflieg, Conny (PSYCHOLOGY) <<a href="mailto:conny.quaedflieg@maastrichtuniversity.nl">conny.quaedflieg@maastrichtuniversity.nl</a>> wrote:<o:p></o:p></p></div><p class=MsoNormal><o:p> </o:p></p><div><div><p class=MsoNormal> <o:p></o:p></p></div><div><div><p class=MsoNormal><a name="OLE_LINK1"><span style='font-family:"Tahoma",sans-serif'>Dear Fieldtripers,</span></a><span style='mso-bookmark:OLE_LINK1'></span><o:p></o:p></p></div><div><p class=MsoNormal><span style='font-family:"Tahoma",sans-serif'> </span><o:p></o:p></p></div><div><p class=MsoNormal><span lang=EN-GB style='font-family:"Tahoma",sans-serif'>I’m trying to compare 2 groups (n=40 per group) on SOURCE connectivity data using a seed (based on an atlas).</span><o:p></o:p></p></div><div><p class=MsoNormal><span lang=EN-GB style='font-family:"Tahoma",sans-serif'>Based on the help function this should be possible using<span class=apple-converted-space> </span>cfg.refindx.<span class=apple-converted-space> </span></span><o:p></o:p></p></div><div><p class=MsoNormal><span lang=EN-GB style='font-family:"Tahoma",sans-serif'> </span><o:p></o:p></p></div><div><p class=MsoNormal><span lang=EN-GB style='font-family:"Tahoma",sans-serif'>Though, the analysis looks exactly the same with and without the refindx specified.</span><o:p></o:p></p></div><div><p class=MsoNormal><span lang=EN-GB style='font-family:"Tahoma",sans-serif'> </span><o:p></o:p></p></div><div><p class=MsoNormal><span lang=EN-GB style='font-family:"Tahoma",sans-serif'>I would be really grateful with help on the following</span><o:p></o:p></p></div><ol style='margin-top:0cm' start=1 type=1><li class=MsoListParagraph style='margin-top:0cm;margin-bottom:0cm;margin-bottom:.0001pt;mso-list:l0 level1 lfo1'><span lang=EN-GB style='font-family:"Tahoma",sans-serif'>Ideas how to run a seed based source analysis</span><o:p></o:p></li><li class=MsoListParagraph style='margin-top:0cm;margin-bottom:0cm;margin-bottom:.0001pt;mso-list:l0 level1 lfo1'><span lang=EN-GB style='font-family:"Tahoma",sans-serif'>How can I combine source data of several pp’s and plot the grand averages and run statistics over it?</span><o:p></o:p></li></ol><div style='margin-left:36.0pt'><p class=MsoNormal><span lang=EN-GB style='font-family:"Tahoma",sans-serif'>I tried this with ft_sourcegandaverage though when interpolating the data to the MRI I get error messages that the data is too large and that it wil take too long.</span><o:p></o:p></p></div><div><p class=MsoNormal><span lang=EN-GB style='font-family:"Tahoma",sans-serif'> </span><o:p></o:p></p></div><div><p class=MsoNormal><span lang=EN-GB style='font-family:"Tahoma",sans-serif'>Best</span><o:p></o:p></p></div></div><div><p class=MsoNormal> <o:p></o:p></p></div><p class=MsoNormal style='margin-bottom:12.0pt'><span lang=EN-GB>Conny Quaedflieg, PhD</span></p><div><p class=MsoNormal><span lang=EN-GB style='color:#7F7F7F'>Assistant Professor<br>Department of Clinical Psychological Science<br>Faculty of Psychology and Neuroscience<br>UNS 40, Room A3731a</span><o:p></o:p></p></div><div><p class=MsoNormal><span style='color:#7F7F7F'>043-883164</span><o:p></o:p></p></div><p class=MsoNormal style='margin-bottom:12.0pt'><br><br><br><o:p></o:p></p><div><p class=MsoNormal> <o:p></o:p></p></div><p class=MsoNormal><span style='font-size:10.5pt;font-family:"Helvetica",sans-serif'>_______________________________________________<br>fieldtrip mailing list<br></span><a href="https://mailman.science.ru.nl/mailman/listinfo/fieldtrip"><span style='font-size:10.5pt;font-family:"Helvetica",sans-serif'>https://mailman.science.ru.nl/mailman/listinfo/fieldtrip</span></a><span style='font-size:10.5pt;font-family:"Helvetica",sans-serif'><br></span><a href="https://doi.org/10.1371/journal.pcbi.1002202"><span style='font-size:10.5pt;font-family:"Helvetica",sans-serif'>https://doi.org/10.1371/journal.pcbi.1002202</span></a><o:p></o:p></p></div></blockquote></div><p class=MsoNormal><o:p> </o:p></p></div></div><p class=MsoNormal style='margin-bottom:12.0pt'><o:p> </o:p></p></div><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><o:p> </o:p></p></div></body></html>