Categories help us generalize across experience. However, not all categories are created equally. Consider the feline images on the right: these objects can be validly called an animal, a mammal, a cat, or a domestic orange tabby cat (left), people tend to use a mid-level of specificity (cat). Furthermore, even though both animals are cats, why do observers agree that the cat on the left is a better example of a cat than the one on the right?
Along with my colleagues, I have been investigating the neural correlates of these category structures. We have found evidence for entry-level object grouping in the object-selective lateral occipital complex (LOC, Iordan et al, JoCN 2015). Furthermore, the LOC is also sensitive to the typicality of an object within its entry-level category (Iordan et al, NeuroImage 2016).
Does categorization come automatically when one recognizes an object? To test this, I examined both object and scene categorization using a modified Stroop paradigm. Observers classified printed words that were written on top of photos of objects and scenes. Although the images were irrelevant to the task, observers could not inhibit their categorization: they were faster and more accurate in categorizing words with congruent pictures (Greene & Fei-Fei, JoV 2014).