oh BOLD where art thou? Evidence for a “mm-scale” match between intracortical and fMRI measures.

A frequently discussed problem with functional magnetic resonance imaging is that we don’t really understand how the hemodynamic ‘activations’ measured by the technique relate to actual neuronal phenomenon. This is because fMRI measures the Blood-Oxygenation-Level Dependent (BOLD) signal, a complex vascular response to neuronal activity. As such, neuroscientists can easily get worried about all sorts of non-neural contributions to the BOLD signal, such as subjects gasping for air, pulse-related motion artefacts, and other generally uninteresting effects. We can even start to worry that out in the lab, the BOLD signal may not actually measure any particular aspect of neuronal activity, but rather some overly diluted, spatially unconstrained filter that simply lacks the key information for understanding brain processes.

Given that we generally use fMRI over neurophysiological methods (e.g. M/EEG) when we want to say something about the precise spatial generators of a cognitive process, addressing these ambiguities is of utmost importance. Accordingly a variety of recent papers have utilized multi-modal techniques, for example combining optogenetics, direct recordings, and FMRI, to assess particularly which kinds of neural events contribute to alterations in the BOLD signal and it’s spatial (mis)localization. Now a paper published today in Neuroimage addresses this question by combining high resolution 7-tesla fMRI with Electrocorticography (ECoG) to determine the spatial overlap of finger-specific somatomotor representations captured by the measures. Starting from the title’s claim that “BOLD matches neuronal activity at the mm-scale”, we can already be sure this paper will generate a great deal of interest.

From Siero et al (In Press)

As shown above, the authors managed to record high resolution (1.5mm) fMRI in 2 subjects implanted with 23 x 11mm intracranial electrode arrays during a simple finger-tapping task. Motor responses from each finger were recorded and used to generate somatotopic maps of brain responses specific to each finger. This analysis was repeated in both ECoG and fMRI, which were then spatially co-registered to one another so the authors could directly compare the spatial overlap between the two methods. What they found appears at first glance, to be quite impressive:
From Siero et al (In Press)

Here you can see the color-coded t-maps for the BOLD activations to each finger (top panel, A), the differential contrast contour maps for the ECOG (middle panel, B), and the maximum activation foci for both measures with respect to the electrode grid (bottom panel, C), in two individual subjects. Comparing the spatial maps for both the index and thumb suggests a rather strong consistency both in terms of the topology of each effect and the location of their foci. Interestingly the little finger measurements seem somewhat more displaced, although similar topographic features can be seen in both. Siero and colleagues further compute the spatial correlation (Spearman’s R) across measures for each individual finger, finding an average correlation of .54, with a range between .31-.81, a moderately high degree of overlap between the measures. Finally the optimal amount of shift needed to reduce spatial difference between the measures was computed and found to be between 1-3.1 millimetres, suggesting a slight systematic bias between ECoG and fMRI foci.

Are ‘We the BOLD’ ready to breakout the champagne and get back to scanning in comfort, spatial anxieties at ease? While this is certainly a promising result, suggesting that the BOLD signal indeed captures functionally relevant neuronal parameters with reasonable spatial accuracy, it should be noted that the result is based on a very-best-case scenario, and that a considerable degree of unique spatial variance remains for the two methods. The data presented by Siero and colleagues have undergone a number of crucial pre-processing steps that are likely to influence their results: the high degree of spatial resolution, the manual removal of draining veins, the restriction of their analysis to grey-matter voxels only, and the lack of spatial smoothing all render generalizing from these results to the standard 3-tesla whole brain pipeline difficult. Indeed, even under these best-case criteria, the results still indicate up to 3mm of systematic bias in the fMRI results. Though we can be glad the bias was systematic and not random– 3mm is still quite a lot in the brain. On this point, the authors note that the stability of the bias may point towards a systematic miss-registration of the ECoG and FMRI data and/or possible rigid-body deformations introduced by the implantation of the electrodes), issues that could be addressed in future studies. Ultimately it remains to be seen whether similar reliability can be obtained for less robust paradigms than finger wagging, obtained in the standard sub-optimal imaging scenarios. But for now I’m happy to let fMRI have its day in the sun, give or take a few millimeters.

Siero, J. C. W., Hermes, D., Hoogduin, H., Luijten, P. R., Ramsey, N. F., & Petridou, N. (2014). BOLD matches neuronal activity at the mm scale: A combined 7T fMRI and ECoG study in human sensorimotor cortex. NeuroImage. doi:10.1016/j.neuroimage.2014.07.002

 

A defense of vegetarian fMRI (1/2)

Recently there’s been much ado about a newly published fMRI study of empathetic responding in vegetarians, vegans, and omnivores. The study isn’t perfect, which the authors admit, but I find it interesting and relatively informative for an fMRI paper. The Neurocritic doesn’t, rather he raises some seemingly serious issues with the study. I promised on twitter I’d defend my claim that the study is good (and that neurocritic could do better). But first, a motivated ramble to distract and confuse you.

As many of you might realize, neuroscience could be said to be going through something like puberty. While the public remains infatuated with every poorly worded research report, researchers within the neurosciences have to view brain mapping through an increasingly skeptical lens. This is a good thing: science progresses through the introduction and use of new technologies and the eventual skeptical refinement of their products.

And certainly there is plenty of examples shoddy neuroscience out there, whether it’s reports of voodoo correlations or inconsistencies between standard fMRI analyses packages. Properly executed, attention to these issues and a healthy skepticism of the methods will ultimately result in a refined science. Yet we must also be careful to apply the balm of skepticism in a refined manner: neuroscientists are people to, and we work in an increasingly competitive field where there are few well-defined standards and even less clarity.

Take an example from my lab that happened just today.  We’re currently analyzing some results from a social cognition experiment my colleague Kristian Tylen and I conducted last year. Like many fMRI results, our hypotheses (which were admitable a bit vague when we made them) were not exactly supported by our findings. Rather we ended up with a scattered series of blobs that appeared to mostly center on early visual areas. This is obviously boring and unpublishable, and after some time we decided to do a small volume correction on some areas we’d discussed in a published paper. This finally revealed some interesting findings somewhere around the TPJ, which brings me to the point of this story.

My research has thus far mostly focused on motor and prefrontal regions. We in neuroimaging can often fall victim to what I call ‘blob blind sight’ where we focus so greatly on a single area or handful of areas that we forget there’s’ a wide world of cortex out there. Imagine my surprise when I tried to get clear about whether our finding was situated in exactly the pSTS, TPJ, or nearby inferior parietal lobule (IPL) only to discover that these three areas are nearly indistinguishable from one another anatomically.

All of these regions are involved in different aspects of social cognition, and across the literature there are no clear anatomical differentiation between them. In many cases, researchers will just lump them together as pSTS/TPJ, regardless of the fact that a great deal of research has gone on explicitly differentiating them. Now what does one do with a blob that lands somewhere in the middle, overlapping all three? More specifically, imagine the case where your activation foci lands smack dab in the middle, or a few voxels to the left. Is it TPJ? Or IPL? Or is it really the conjunction of all three, and if so, how does one make sense of that given the wide array of functions and connectivity patterns for these areas. IPL is a part of the default mode, whereas TPJ and pSTS are not. It’s really quite a mess, and the answer you choose will likely depend upon the interpretation you give, given the vast variety of functions allocated to these three regions.

The point of all this, which begins to lead to my critique of TNC critique, is that it is not a simple matter of putting ones foot down and claiming that the lack of an expected activation or the presence of an unexpected one is damning or indicative of bad science. It’s an inherent problem in a field where hundreds of papers are published monthly with massive tables of activation foci. To say that a study has gone awry because they don’t report your favorite area misses the point. What’s more important is to evaluate the methods and explain the totality of the findings reported.

So that’s one huge issue confronting most researchers. Although there are some open source ‘foci databases’ out there, they are underused and hard to rely on. One can of course try to pinpoint the exact area, but in reality the chance that you’ll have such a focused blob is pretty unlikely. Rather, researchers have to rely on extra-scanner measures and common sense to make any kind of interesting theoretical inferences from fMRI. This post was meant to be a response to The Neurocritic, who took issue with my taking issue of his taking issue with a certain vegetarian fmri study… but I’m already an hour late coming home from work and I’m afraid I’ve failed to deliver. I did take the time this afternoon to go thoroughly through both the paper and TNC’s response however, and I think I’ve got a pretty compelling argument. Next time: why the neurocritic is plain wrong 😉