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help > RE: Movement
Nov 19, 2014 06:11 AM | Alfonso Nieto-Castanon - Boston University
RE: Movement
Hi Brad,
Yes, having a large proportion of the BOLD signal variance explained by the combination of confounding effects is perfectly normal/expected (motion and physiological effects can be very large compared to the neural sources in the BOLD signal).
Also you are right that the interpretation of the percentage variance explained by each confounding effect was a bit counter-intuitive (this has also been changed in more recent versions). In older versions the effects shown in these Denoising plots represented the "unique variance" explained by each factor (the total variance explained by that factor alone, after removing all that could be explained by the other factors), while in newer versions this plot has been changed to represent the "unique&shared variance" explained by each factor (the total variance explained by that factor, even if some portion of that variance would also be explained by other factors). The combination/addition of the "unique variance" of several factors is always smaller that the total variance explained by all factors combined, and the combination of the "unique&shared variance" of several factors is always larger than the total variance explained by all factors combined (and we were hoping that using the latter would perhaps make it a bit more intuitive interpreting these plots).
Hope this helps
Alfonso
Originally posted by Bradley Taber-Thomas:
Yes, having a large proportion of the BOLD signal variance explained by the combination of confounding effects is perfectly normal/expected (motion and physiological effects can be very large compared to the neural sources in the BOLD signal).
Also you are right that the interpretation of the percentage variance explained by each confounding effect was a bit counter-intuitive (this has also been changed in more recent versions). In older versions the effects shown in these Denoising plots represented the "unique variance" explained by each factor (the total variance explained by that factor alone, after removing all that could be explained by the other factors), while in newer versions this plot has been changed to represent the "unique&shared variance" explained by each factor (the total variance explained by that factor, even if some portion of that variance would also be explained by other factors). The combination/addition of the "unique variance" of several factors is always smaller that the total variance explained by all factors combined, and the combination of the "unique&shared variance" of several factors is always larger than the total variance explained by all factors combined (and we were hoping that using the latter would perhaps make it a bit more intuitive interpreting these plots).
Hope this helps
Alfonso
Originally posted by Bradley Taber-Thomas:
Great, thanks, the new version works as you
described.
A lot of subjects have their "TOTAL Confounds" explaining most of the variance, as in the screen shot attached to that previous post. Does that look normal to you? The Total doesn't seem to be a combination of the individual confounds, and it is certainly a lot of the variance (e.g., for some subjects the Total confounds explain >0.9 variance for the whole brain).
Best,
Brad
A lot of subjects have their "TOTAL Confounds" explaining most of the variance, as in the screen shot attached to that previous post. Does that look normal to you? The Total doesn't seem to be a combination of the individual confounds, and it is certainly a lot of the variance (e.g., for some subjects the Total confounds explain >0.9 variance for the whole brain).
Best,
Brad
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| Title | Author | Date |
|---|---|---|
| Kaylah Curtis | Jul 23, 2014 | |
| Mary Newsome | Apr 2, 2015 | |
| Alfonso Nieto-Castanon | Apr 6, 2015 | |
| Alfonso Nieto-Castanon | Jul 29, 2014 | |
| Xiaozhen You | Mar 31, 2015 | |
| Fred Uquillas | Mar 31, 2015 | |
| Xiaozhen You | Apr 1, 2015 | |
| Fred Uquillas | Apr 1, 2015 | |
| Alfonso Nieto-Castanon | Apr 2, 2015 | |
| Xiaozhen You | Apr 2, 2015 | |
| Ekaterina Shcheglova | Mar 26, 2023 | |
| Fred Uquillas | Apr 24, 2015 | |
| Alfonso Nieto-Castanon | Apr 28, 2015 | |
| Fred Uquillas | May 6, 2015 | |
| Arkan A | May 6, 2015 | |
| Alfonso Nieto-Castanon | May 6, 2015 | |
| Arkan A | May 7, 2015 | |
| Alfonso Nieto-Castanon | May 8, 2015 | |
| Arkan A | May 8, 2015 | |
| Bradley Taber-Thomas | Sep 30, 2014 | |
| Alfonso Nieto-Castanon | Oct 1, 2014 | |
| Bradley Taber-Thomas | Oct 1, 2014 | |
| Alfonso Nieto-Castanon | Nov 19, 2014 | |
| Kaylah Curtis | Jul 29, 2014 | |
| Alfonso Nieto-Castanon | Jul 30, 2014 | |
| Alexander Drobyshevsky | Oct 21, 2014 | |
| Alfonso Nieto-Castanon | Nov 19, 2014 | |
| Kaylah Curtis | Jul 30, 2014 | |
| Aleksandra Herman | Oct 23, 2014 | |