Education, tips and tricks to help you conduct better fMRI experiments.
Sure, you can try to fix it during data processing, but you're usually better off fixing the acquisition!

Tuesday, May 22, 2012

Common intermittent EPI artifacts: Subject movement


More fMRI experiments are ruined by subject motion than any other single cause. At least, that is my anecdotal conclusion from a dozen years' performing post-acquisition autopsies on "bad" data. The reasons for this vulnerability are manifold, starting with the type of subjects you're trying to scan. You may be interested in people for whom remaining still is difficult or impossible without sedation of some kind.

However, I think there is another reason why many (most?) fMRIers end up with more subject motion than is practicable: they haven't taken the time to think through the different ways that subjects can thwart your best efforts. In other words, what we are considering is largely experimental technique, or bedside manner as medical types refer to this stuff.

With the possible (and debatable) exception of bite bars, which aren't popular for myriad reasons, there is no panacea for motion. Why? As we shall see, it's not just movement of the head that's a concern. You need to consider a subject's comfort, arousal level, propensity to want to breathe, and many other things that might be peripheral to your task but are very much on the mind of your (often fMRI-naive) subjects.

Now, before we get any farther I need to outline what this post will cover, and what it won't. The focus of this post is on single-shot, unaccelerated gradient echo EPI - the sort of plain vanilla sequence that the majority of sites use for fMRI. I won't be covering the effects of motion on parallel imaging such as GRAPPA, for example. I will also restrict discussion here to the effects of motion on axial slices. Hopefully you can extrapolate to different slice prescriptions. But, rest assured that this isn't the last word in motion, not by a long chalk. Motion has come up before on this blog, e.g. in relation to GRAPPA for EPI, and the ubiquity of the problem implies that the issue will arise in many subsequent posts, too. Take today's post as an introduction to the general problem.

My final caveat on the utility of today's post. As this blog is focused on practical matters I will restrict the bulk of the discussion to things that you'll see and can control online, in real time. There are many tools that can be used to provide useful diagnostics post hoc, some of which I will mention. But this isn't a post aimed at showing you what went wrong. Rather, the intent of this post is to describe what is going wrong, such that you might be able to intercede and fix the situation. Some sites have useful real-time diagnostics that can tell you when (and perhaps how) a subject is moving, but they aren't widespread. Thus, for today's post we shall keep things simple and restrict the discussion to what can be seen in the EPIs themselves, as they are acquired.

WARNING: If you haven't run an fMRI experiment in a while then you might want to stop reading this post here and go and review the earlier post, Understanding fMRI artifacts: "Good" axial data. That post highlights our target: the low motion case.


Eye movements

Let's start simply. Here is a video of a subject intentionally moving his eyes to a target. Saccading is the technical term, I hear. (See Note 1 for experimental details. Parameters were fixed throughout for this post, unless mentioned to the contrary in any section below.) There are twenty volumes played back at a rate of 5 frames/sec: