We report three eyetracking experiments that examine the learning procedure used by adults as they pair novel words and visually presented referents over a sequence of referentially ambiguous trials. Successful learning under such conditions has been argued to be the product of a learning procedure in which participants provisionally pair each novel word with several possible referents and use a statistical-associative learning mechanism to gradually converge on a single mapping across learning instances. We argue here that successful learning in this setting is instead the product of a one-trial procedure in which a single hypothesized word-referent pairing is retained across learning instances, abandoned only if the subsequent instance fails to confirm the pairing – more a ‘fast mapping’ procedure than a gradual statistical one. We provide experimental evidence for this Propose-but-Verify learning procedure via three experiments in which adult participants attempted to learn the meanings of nonce words cross-situationally under varying degrees of referential uncertainty. The findings, using both explicit (referent selection) and implicit (eye movement) measures, show that even in these artificial learning contexts, which are far simpler than those encountered by a language learner in a natural environment, participants do not retain multiple meaning hypotheses across learning instances. As we discuss, these findings challenge ‘gradualist’ accounts of word learning and are consistent with the known rapid course of vocabulary learning in a first language.

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Unlike rapid scene and object recognition from brief displays, little is known about recognition of event categories and event roles from minimal visual information. In three experiments, we displayed naturalistic photographs of a wide range of two-participant event scenes for 37 ms and 73 ms followed by a mask, and found that event categories (the event gist, e.g., ‘kicking’, ‘pushing’, etc.) and event roles (i.e., Agent and Patient) can be recognized rapidly, even with various actor pairs and backgrounds. Norming ratings from a subsequent experiment revealed that certain physical features (e.g., outstretched extremities) that correlate with Agent-hood could have contributed to rapid role recognition. In a final experiment, using identical twin actors, we then varied these features in two sets of stimuli, in which Patients had Agent-like features or not. Subjects recognized the roles of event participants less accurately when Patients possessed Agent-like features, with this difference being eliminated with two-second durations. Thus, given minimal visual input, typical Agent-like physical features are used in role recognition but, with sufficient input from multiple fixations, people categorically determine the relationship between event participants.

People interact with entities in the environment in distinct and categorizable ways (e.g., is). We can recognize these action categories across variations in actors, objects, and settings; moreover, we can recognize them from both dynamic and static visual input. However, the neural systems that support action recognition across these perceptual differences are unclear. Here, we used multivoxel pattern analysis of fMRI data to identify brain regions that support visual action categorization in a format-independent way. Human participants were scanned while viewing eight categories of interactions (e.g., ) depicted in two visual formats: (1) visually controlled videos of two interacting actors and (2) visually varied photographs selected from the internet involving different actors, objects, and settings. Action category was decodable across visual formats in bilateral inferior parietal, bilateral occipitotemporal, left premotor, and left middle frontal cortex. In most of these regions, the representational similarity of action categories was consistent across subjects and visual formats, a property that can contribute to a common understanding of actions among individuals. These results suggest that the identified brain regions support action category codes that are important for action recognition and action understanding. Humans tend to interpret the observed actions of others in terms of categories that are invariant to incidental features: whether a girl pushes a boy or a button and whether we see it in real-time or in a single snapshot, it is still Here, we investigated the brain systems that facilitate the visual recognition of these action categories across such differences. Using fMRI, we identified several areas of parietal, occipitotemporal, and frontal cortex that exhibit action category codes that are similar across viewing of dynamic videos and still photographs. Our results provide strong evidence for the involvement of these brain regions in recognizing the way that people interact physically with objects and other people.

A crucial component of event recognition is understanding event roles, i.e. who acted on whom: boy hitting girl is different from girl hitting boy. We often categorize Agents (i.e. the actor) and Patients (i.e. the one acted upon) from visual input, but do we rapidly and spontaneously encode such roles even when our attention is otherwise occupied? In three experiments, participants observed a continuous sequence of two-person scenes and had to search for a target actor in each (the male/female or red/blue-shirted actor) by indicating with a button press whether the target appeared on the left or the right. Critically, although role was orthogonal to gender and shirt color, and was never explicitly mentioned, participants responded more slowly when the target's role switched from trial to trial (e.g., the male went from being the Patient to the Agent). In a final experiment, we demonstrated that this effect cannot be fully explained by differences in posture associated with Agents and Patients. Our results suggest that extraction of event structure from visual scenes is rapid and spontaneous.