## 5 Discussion
### Limitations of the Present Study  
Each methodological choice comes with its inherent limitations. Beyond the limitations of our tasks and image types (see previous sections), we also need to consider limitations of our stimulus material, the experimental design, the data analysis procedures as well as conceptual limitations. A first limitation concerns the generalizability of the present findings given our selection of stimuli. We only used six categories and a small set of similar image exemplars within each category. For instance, our objects were long vertical buildings, usually embedded in a natural scene. Given this specificity, can our results be generalized to other objects in other contexts? Actually, our reasoning has never been about all objects merely by virtue of being an object. A close-up view of a flower petal spanning the entire image would also be considered an object. However, this image would actually be more similar to our landscapes in terms of scene structure and thus the resulting attention maps should also be quite dispersed. Therefore, our three image types should not be taken too literally. They should be interpreted in terms of the purpose they fulfil: differentiating between images that can be categorized by means of singular diagnostic objects, object-to-object relations or global scene properties. That is, our conceptualization of image types is based on categorization requirements. Within these requirement-based image types, future studies should investigate whether our results generalize to a larger set of categories and exemplars and critically test the boundaries of such generalization. A second limitation concerns the effects of our fixed task order, which induced systematic dependencies between tasks. We held task order constant because we wanted to keep spontaneous gaze unconditional on viewing history and minimize the need to scan the image during gaze-pointing. Still, repeated viewing might account for some of our results. For instance, the two eye movement tasks produced highly similar attention maps. Did participants simply revisit the areas they had previously identified? Indeed, studies that repeatedly exposed participants to the same scenes reported similarities in their scan-paths [70; 71]. However, similarity in these studies was quite low, although it reliably differed from chance. Other studies found that when people viewed the same scenes repeatedly, they made progressively fewer and longer fixations, shorter saccades and spent less time on meaningful areas [72]. This suggests that our methodological choice to always place gaze-pointing second might confound task effects with preview and practice effects. We are more optimistic that the fixed task order had no relevant impact on drawing. Manual selection is a highly intentional task and participants could take as much time as they wanted. Presumably, it does not matter whether familiarization with an image is spread across three instances of viewing it versus one instance of viewing it longer. Still, this assumption remains untested. Thus, future studies could explicitly control for task order effects, either by varying it systematically or by manipulating tasks between participants. Third, our metrics used for comparing attention maps deserve a critical evaluation. Dice scores and cross-correlations have complementary benefits and costs, as discussed above. However, there are problems that neither of them can fix. For instance, they do not control for central fixation bias, do not take the spatial distance between selected areas into account and do not differentiate between false positives and false negatives. These issues can be addressed by other metrics [66]. For instance, the Kullback-Leibler Divergence and Similarity penalize false negatives (misses) more than false positives (misdetections). Thus, human-CNN similarity should decrease if the XAI method fails to highlight information that humans considered to be highly relevant.