Ben Goldacre, psychiatrist, occasional fMRIer and critic of rubbish medical research over at BadScience.net, has produced a radio documentary that covers many of the pitfalls of modern medical science:
Science: From Cradle to Grave
It's aimed at a general audience but there are important reminders for us in fMRI-land.
Confounds abound
Epidemiology is a lot like fMRI when it comes to discriminating correlation from causation. As with many areas of research using human subjects, there are usually limits to the factors that can be controlled between groups, or even across time for an individual subject.
But there are often some simple things that we can measure - like heart and respiration rates during fMRI - and thus control for. Surely we should be measuring (and ideally controlling for) as many parameters as we can get our hands on, especially when the time and expense are comparatively minor. Get as much data as you can!
Friday, August 5, 2011
Resting state fMRI: a motion confound in connectivity studies?
Neuroskeptic has done us a favor and covered a recently accepted paper from Randy Buckner's lab concerning the role of motion when determining connectivity from resting state fMRI. Not only was the amount of motion found to differ systematically between male and female subjects, but this systematic difference was preserved across sessions, suggesting that it is a stable trait. The implications for group studies are discussed in the paper, and Neuroskeptic adds further perspective. It's a warning that all resting state fMRIers should heed.
Non-neural physiology.... again
There are some important limitations to consider, however. While ventricular and white matter regions were used as ways to remove some effects of heart rate and motion, the study did not acquire breathing or heart rate data and so the authors were unable to perform the more advanced BOLD-based model corrections developed by Rasmus Birn and Catie Chang (references below). Instead, they followed what might be considered the "typical" post-processing steps, including global mean signal removal. The methods are fine, my point is to highlight the limitations of the "typical" processing stream in the absence of independent physiological data.
So, could the gender differences be explained with improved physiological corrections? What about the motion correction methods in current use: might they not be up to the job we give them? We'll have to wait for further studies to find out. In the mean time, surely it only makes sense to acquire physiological data with resting state fMRI - heart rate and respiration at the very least, although there are suggestions that time course blood pressure might also be useful - and to try to explain as many confounds as possible before concluding there's a group difference due to brain activity.
References for physiological corrections:
Birn et al., Neuroimage 31: 1536 –1548, 2006.
Birn et al., Neuroimage 40: 644-654, 2008.
Chang & Glover, Neuroimage 47: 1381–1393, 2009. Also 1448 –1459 in the same issue.
Non-neural physiology.... again
There are some important limitations to consider, however. While ventricular and white matter regions were used as ways to remove some effects of heart rate and motion, the study did not acquire breathing or heart rate data and so the authors were unable to perform the more advanced BOLD-based model corrections developed by Rasmus Birn and Catie Chang (references below). Instead, they followed what might be considered the "typical" post-processing steps, including global mean signal removal. The methods are fine, my point is to highlight the limitations of the "typical" processing stream in the absence of independent physiological data.
So, could the gender differences be explained with improved physiological corrections? What about the motion correction methods in current use: might they not be up to the job we give them? We'll have to wait for further studies to find out. In the mean time, surely it only makes sense to acquire physiological data with resting state fMRI - heart rate and respiration at the very least, although there are suggestions that time course blood pressure might also be useful - and to try to explain as many confounds as possible before concluding there's a group difference due to brain activity.
References for physiological corrections:
Birn et al., Neuroimage 31: 1536 –1548, 2006.
Birn et al., Neuroimage 40: 644-654, 2008.
Chang & Glover, Neuroimage 47: 1381–1393, 2009. Also 1448 –1459 in the same issue.
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