The present research shows that different localizer task conditions do not appear to alter the variability of the locations of activations in the fusiform gyrus when responding to face stimuli. This is important because it indicates that experimenters have some flexibility in terms of what tasks they employ to define face responsive areas to form ROIs to analyze their tasks of interest. With that said, there are a few caveats to note.
First, we may not be finding differences in localization based on task demands because our experimental tasks may not be sufficiently dissimilar. That is, passive viewing and n-back tasks share many of the same task demands. It is not clear whether performing other more varied tasks on faces would lead to different localization. While we grant that our tasks are not radically dissimilar, they are not particularly similar either. Further, it would be difficult to test the whole task space. We chose these tasks because researchers in the field typically use these tasks to localize face-responsive areas in cortex as our literature review shows (almost all researchers use either a passive viewing or 1-back task). With that said, we find that task demands do not matter much in terms of localizing face responsive areas in FFA as evidenced by our literature review and two experiments. However, comparison stimuli do matter in terms of magnitude, extent and the reliability of activity over the ROI (as found with Pearson correlations), so a researcher should take care to use the same or similar contrasting stimuli for localizer tasks and tasks of interest.
Second, we are not claiming that no differences exist for different localizer tasks. For example, one can obtain a more reliable, robust, and larger activation cluster depending on task and contrasting stimuli. From our data it seems that faces vs. scrambles provide a larger and more robust activation cluster in the FFA compared to faces vs. houses. As such, faces vs. scrambles also produced more variance than faces vs. houses so a researcher must determine which variable is more important (reliability or activation magnitude). Additionally, if the task is more attentionally demanding, like the 1-back task, the activation patterns are more reliable as measured by Pearson correlations. These are important considerations when choosing a localizer task or choosing any task to explore in the magnet. These results also speak to Friston et al.’s (2006)
concerns with using functional localizers. While the same or similar areas of cortex were active for different task demands, magnitudes, extents, and reliabilities of activation patterns may vary based on task context and may interact with various experimental manipulations (e.g. task and comparison stimuli interacted in Experiment 1 for magnitude and extent).
Third, it is important to consider what constitutes a significant difference. For example, if one finds a statistically significant difference in the location of the peak activated voxel for two different tasks, does that mean that the two tasks activated different regions? This is why we believe that using multivoxel pattern/correlation analyses (using Pearson correlation coefficients in this experiment) will become increasingly important, especially given the noise in fMRI data. It seems that when we consider whole patterns, we may find more similarities in our datasets than we might have imagined. Therefore, potentially important differences could emerge, such as differences in activation patterns as a function of different contrasting stimuli. Additionally and importantly, these correlation analyses provide a good measure of the reliability of our localizer tasks. In practice, functional localizers are typically employed by finding peaks (and defining a spherical region of interest around the peak) or thresholding activation maps. So the use of multivoxel correlation analysis at this time may be restricted to evaluating the reliability/reproducibility of the functional localizers rather than defining functionally localized areas. In the future, however, researchers may move to multivariate approaches when defining localized areas.
Lastly, it is not clear whether these results would generalize to other cortical regions, e.g., the visual word form area (McCandliss et al., 2003
), or the extrastriate body area (Downing et al., 2001
) though we do not see any compelling reason for many of these same results not to be found for other ROIs as well. In addition, while we focused on the fusiform gyrus, other brain areas were also active for the experimental conditions. Therefore, we are not advocating that researchers look only within ROIs when performing their fMRI experiments. For example, we found more PFC activations with increasing load in the n-back task, and we also found amygdala activations for face vs. house contrasts. The aim of this paper was to test whether various experimental manipulations alter the locale of FFA activations, not to restrict analyses to ROIs.
In sum, a researcher interested in using the functional localizer approach to localize the FFA should consider matching contrasting stimuli to the experiment of interest, but different localizer tasks seem to activate the same or similar regions of the FFA, which may alleviate many concerns with using the localizer approach (Saxe et al., 2006
; Friston et al., 2006
). If the researcher, however, is using the localizer approach not to define an area from a location standpoint, but to make additional claims, then the concerns of Friston et al., (2006)
come into play, because task demands and contrasting stimuli did interact in terms of the magnitude, extent and the patterns/reliabilities of activations in FFA.