One reason to present at conferences is to hear criticisms from your colleagues.
Rankin McGugin and Ana Beth Van Gulick were recently presenting their work at the SfN meeting in NewOrleans, in a very interesting Nanosymposium organized by Ido Davidesco on Extrastriate Cortex: Functional Organization Faces and Objects. Since the work they were presenting argues against the idea that face perception is a “cognitive function with its own piece of real-estate in the brain”, namely the FFA, it is particularly interesting to hear what Nancy Kanwisher has to say about this since she is known as the strongest advocate of this position.
Rankin recently published part of her dissertation in PNAS, a study scanning 51 subjects at 7T and relating responses to cars in the FFA to car expertise. While Rankin and Ana Beth’s talks were about unpublished follow-up experiments, they both mentioned the study, and thus Kanwisher’s question mentioned that study.
The question was, from memory: “I am confused, are you now changing the definition of what a car expertise effect is? I thought that it was supposed to be a stronger response to cars than objects in car experts and in your PNAS paper you do not get that”. Our answer at the time was “no we aren’t –changing the definition- and yes we are – finding more activity for cars than objects in car experts” but I doubt it came out very clearly.
Here I hope to unpack our answer, for those who care:
1- Are we changing the definition of an expertise effect?
This requires an answer, because everybody knows that a scientific hypothesis that requires conveniently changing one’s definition to match the data isn’t much of a hypothesis at all. If we did this, without making it clear what justifies it, we’d be pretty bad scientists.
However, the definition of an expertise effect has never been “a stronger response to objects of expertise than to other objects” and it’s important to explain why.
Let’s start with the first car and bird expertise study I conducted as a post doctoral project with Nancy Kanwisher.
The plot shows the response in FFA for Birds – Cars on the Y axis, and the X axis shows behavioral expertise for Birds – Cars. The definition of an expertise effect was “the correlation between behavioral expertise and the response to objects of expertise”, here r=.75 and r=.82, within samples of car experts and bird experts. This plot illustrates something interesting: more of the bird experts have more activity for birds than cars than car experts have more activity to cars than birds. This is likely because animals, as reported many times since then, generally produce a large response in FFA, even in novices. Would we on this basis suggest that the expertise effect is larger for birds than cars? I would suggest we would not: it is the correlation that matters. Conceptually, it is easy to imagine comparing the response to cars or birds to other things that lead to smaller responses in FFA, like shoes or houses, and as long as the response to these objects does not depend on car or bird expertise, the correlation would remain the same, and the values on the Y axis would simply be shifted.
Perhaps best illustrating that the main effect of objects of expertise relative to the baseline as never been critical to the definition of expertise, we have often used faces as a baseline. Since expertise for faces is likely to be higher than for most other categories, even an expertise account would predict more activity for faces – this is *exactly* what the expertise account says: that faces engage the FFA more than most other things because most people we scan are very good at face recognition.
For instance in a paper in 2005, using another small sample of people varying on car expertise (on the X axis) we found a similar correlation with the response in FFA for cars, relative to faces this time. Clearly, most car experts will still have more activation for faces than cars in FFA and this is shown in the figure. Note that the best car expert’s FFA responded more to cars than faces.
2- Do we find more activity for cars than other objects in the FFA in McGugin’s 2012 PNAS paper?
Yes we do. Here is one of the several figures in the paper that show this.
The X-axis is behavioral car expertise. The Y-axis now is plotting Car da. What is that? It is basically an effect size measure, calculated like Cohen’s d. In this case, it is the response to cars – the response to all other categories we used (faces, animals, planes), divided by the pooled variance. If da is positive, there is more activity for cars than the average of other objects. And in the present case, this happens for a subset of our subjects, those with more car expertise. But is this a critical feature of our results? It really isn’t, because where the mean falls on the Y -axis completely depends on the choice of baseline, and the baseline is not what varies with expertise.
What matters in the measurement of expertise effects is the relation between performance and the response to objects of expertise relative to a baseline. The baseline needs to be high level (fixation is not good, because in that case we’d be measuring each brain’s general BOLD response to any visual image, which tends to vary quite a bit) but it does not matter whether it is one category of objects, faces or the average of many categories. As long as the baseline does not correlate with expertise for the category of interest, the correlation should be the same.
McGugin et al. (2012) is strong evidence that the kind of expertise effects we have reported for years in the FFA overlap with face-selective responses in the very center of the FFA, even in the most face selective high resolution voxels. There is a large proportion of cognitive neuroscience studies that use faces because the strong response in the FFA and its associated network make many questions easier to study: McGugin et al. (2012) suggests the results of such studies speak to processes relevant to face recognition *and* to processes relevant to many other visual skills.