The dynamics of categorization: Unraveling rapid categorization.

Abstract

We explore a puzzle of visual object categorization: Under normal viewing conditions, you spot something as a dog fastest, but at a glance, you spot it faster as an animal. During speeded category verification, a classic basic-level advantage is commonly observed (Rosch, Mervis, Gray, Johnson, & Boyes-Braem, 1976), with categorization as a dog faster than as an animal (superordinate) or Golden Retriever (subordinate). A different story emerges during ultra-rapid categorization with limited exposure duration (<30ms), with superordinate categorization faster than basic or subordinate categorization (Thorpe, Fize, & Marlot, 1996). These two widely cited findings paint contrary theoretical pictures about the time course of object categorization, yet no study has previously investigated them together. Over five experiments, we systematically examined two experimental factors that could explain the qualitative difference in categorization across the two paradigms: exposure duration and category trial context. Mapping out the time course of object categorization by manipulating exposure duration and the timing of a post-stimulus mask revealed that brief exposure durations favor superordinate-level categorization, but with more time a basic-level advantage emerges. But this superordinate advantage was modulated significantly by target category trial context. With randomized target categories, the superordinate advantage was eliminated; and with “blocks” of only four repetitions of superordinate categorization within an otherwise randomized context, the advantage for the basic-level was eliminated. Contrary to some theoretical accounts that dictate a fixed priority for certain levels of abstraction in visual processing and access to semantic knowledge, the dynamics of object categorization are flexible, depending jointly on the level of abstraction, time for perceptual encoding, and category context.

Visual category learning

“…There is growing recognition in psychology and neuroscience that inappropriate statistical tests, questionable statistical practices, and low statistical power can impede scientific progress . Similarly, methodological choices, limitations, and confounds can profoundly impact empirical results and their theoretical implications in behavioral and brain imaging research on visual category learning, as reviewed here, as well as other aspects of visual categorization and recognition . Our message here is not that it is impossible to draw conclusions from category learning experiments because seemingly inconsequential methodological details may matter.…”

“…[145][146][147][148] Similarly, methodological choices, limitations, and confounds can profoundly impact empirical results and their theoretical implications in behavioral and brain imaging research on visual category learning, as reviewed here, as well as other aspects of visual categorization and recognition. 70,[149][150][151][152] Our message here is not that it is impossible to draw conclusions from category learning experiments because seemingly inconsequential methodological details may matter. Rather, we emphasize the importance of paying careful attention to all procedural details, even those that may on first blush appear tangential or inconsequential.…”

Perceiving animacy from shape

“…For example, in speededcategorization tasks with limited exposure duration, categorization of animacy (i.e., the detection of animals) is easier and faster than basic-level categorization (e.g., Macé, Joubert, Nespoulous, & Fabre-Thorpe, 2009;Praß, Grimsen, Ko¨nig, & Fahle, 2013;Wu, Crouzet, Thorpe, & Fabre-Thorpe, 2014). This suggests there might be dedicated neural hardware to distinguish animals from other objects very quickly, based on early, and relatively coarse, image representations (Cauchoix, Crouzet, Fize, & Serre, 2016;Fabre-Thorpe, 2011;Mack & Palmeri, 2015; and not based on simple low-level image statistics; e.g., Cichy, Pantazis, Citation: Schmidt, F., Hegele, M., & Fleming, R. W. (2017). Perceiving animacy from shape.…”

The Time-Course of Ultrarapid Categorization: The Influence of Scene Congruency and Top-Down Processing

“…This consistent behavioral effect in ultrarapid categorization tasks is denoted as the superordinate advantage and seems robust for increased presentation time (PT) of the stimuli ( Poncet & Fabre-Thorpe, 2014 ). Furthermore, recent findings suggest that this perceptual categorization of rapidly presented information is also influenced by the chosen experimental trial context ( Mack & Palmeri, 2015 ; Palmeri & Mack, 2015). Specifically, the superordinate advantage disappeared when a randomized target category design was used, in which superordinate- or basic-level categorization always changed after a few consecutive trials (e.g., maximum of four repetitions).…”