Reply-To: | | [log in to unmask][log in to unmask]> wrote: >> Many thanks Donald, >> >> Ok this makes sense now to me. However how about having the same voxel being significant in the linear term as well as the quadratic one even when looking at them individually (ie performinga t test at the linear regressor only and another one at the quadratic regressors only). This also even when the regressors are orthogonal ? >> >> Kind regards >> >> Aser >> >>> On 30 Sep 2015, at 18:45, "MCLAREN, Donald" <[log in to unmask]> wrote: >>> >>> If I follow you have the PPI term, you have the the linear PM PPI term, and you have a quadratic PM PPI term. You found that only the quadratic PM PPI was non-zero. This is certainly possible. It means that the connectivity doesn't change with the task at the mean PM value, but increases as the PM value gets lower or higher. This would be a U-shaped effect of connectivity. If you look at y=x^2, then you can think of y being connectivity and and X being your PM. >>> >>> Best Regards, >>> Donald McLaren, PhD >>> >>> >>>> On Wed, Sep 30, 2015 at 1:36 PM, Aser A <[log in to unmask]> wrote: >>>> Hi Donald, >>>> >>>> I have another question related to the PM result. I sometime get activations in the PPI of the PM but these activations are not significant in the 0 order or the main effect result. Is this possible or usual ? How this is can be explained ? >>>> >>>> Thanks >>>> >>>> Aser >>>> >>>>> On Mon, Sep 28, 2015 at 11:19 AM, Aser A <[log in to unmask]> wrote: >>>>> Many thanks Donald, >>>>> >>>>> I have to admit that I did not quite get the method of the plot. But many thanks for the other comments >>>>> >>>>>> On Fri, Sep 25, 2015 at 1:37 AM, MCLAREN, Donald <[log in to unmask]> wrote: >>>>>> See below. >>>>>> >>>>>> Best Regards, >>>>>> Donald McLaren, PhD >>>>>> >>>>>> >>>>>>> On Thu, Sep 24, 2015 at 4:28 PM, Aser A <[log in to unmask]> wrote: >>>>>>> Many thanks Donald. I saw in the article you mentioned a diagram that I did not understood it well. The one that shows the 25 % 50 or 75% connectivity in circles. >>>>>>> >>>>>>> From this I have these questions : >>>>>>> >>>>>>> - What does not mean and how it can be created ? >>>>>> >>>>>> I would suggest that you read my recent paper on the flexible modulation of connectivity in AD (McLaren et al. 2014 in NeuroImage), it has a better example. I've also sent my OHBM presentation on the topic in a separate email. Briefly, >>>>>> (1) Select the top N% of voxels in the brain, >>>>>> (2) Count the number of voxels selected from step (1) in each ROI parcellation (in the Swallowing paper, we used AAL regions); >>>>>> (3) Divide by the total number of voxels in each ROI parcellation. >>>>>> Plot the results using the radar plot function in Excel (or your favorite graphing program) >>>>>> >>>>>>> >>>>>>> - Say that I found using gPPI, that more than one region are connected with region X. How can I tell or get indication of which of those two regions has sèÅâ‚g |