Disentangling diagnostic object properties for human scene categorization.

It usually only takes a single glance to categorize our environment into different scene categories (e.g. a kitchen or a highway). Object information has been suggested to play a crucial role in this process, and some proposals even claim that the recognition of a single object can be sufficient to categorize the scene around it. Here, we tested this claim in four behavioural experiments by having participants categorize real-world scene photographs that were reduced to a single, cut-out object. We show that single objects can indeed be sufficient for correct scene categorization and that scene category information can be extracted within 50 ms of object presentation. Furthermore, we identified object frequency and specificity for the target scene category as the most important object properties for human scene categorization. Interestingly, despite the statistical definition of specificity and frequency, human ratings of these properties were better predictors of scene categorization behaviour than more objective statistics derived from databases of labelled real-world images. Taken together, our findings support a central role of object information during human scene categorization, showing that single objects can be indicative of a scene category if they are assumed to frequently and exclusively occur in a certain environment.

What makes a scene? Fast scene categorization as a function of global scene information at different resolutions.

The ability to quickly and accurately categorize our environment into meaningful scene categories has been linked to the fast processing of global scene properties. Here, we causally tested this claim by reducing scene images to different sets of global scene properties with varying degrees of spatial resolution. In Experiment 1, human observers reached above-chance categorization accuracy for most stimulus conditions, indicating that images reduced to global scene properties indeed allow for correct categorization. In Experiment 2, we demonstrated that these features can be extracted from only 30 ms of stimulus presentation. However, accuracy in both experiments was far below performance on unmanipulated images and differed strongly between conditions. Images with higher resolutions yielded better performance than those with lower resolutions. In Experiment 3, we related this performance advantage to the identification of single objects in stimuli with higher resolutions which supports the notion that object information is used for scene categorization. Taken together, we show that global scene properties are useful but not sufficient for fast scene categorization. Instead, localized information is crucial in this process, presumably because it conveys object identities. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Flexible time course of spatial frequency use during scene categorization.

Human observers can quickly and accurately categorize scenes. This remarkable ability is related to the usage of information at different spatial frequencies (SFs) following a coarse-to-fine pattern: Low SFs, conveying coarse layout information, are thought to be used earlier than high SFs, representing more fine-grained information. Alternatives to this pattern have rarely been considered. Here, we probed all possible SF usage strategies randomly with high resolution in both the SF and time dimensions at two categorization levels. We show that correct basic-level categorizations of indoor scenes are linked to the sampling of relatively high SFs, whereas correct outdoor scene categorizations are predicted by an early use of high SFs and a later use of low SFs (fine-to-coarse pattern of SF usage). Superordinate-level categorizations (indoor vs. outdoor scenes) rely on lower SFs early on, followed by a shift to higher SFs and a subsequent shift back to lower SFs in late stages. In summary, our results show no consistent pattern of SF usage across tasks and only partially replicate the diagnostic SFs found in previous studies. We therefore propose that SF sampling strategies of observers differ with varying stimulus and task characteristics, thus favouring the notion of flexible SF usage.

Manual motor reaction while being absorbed into popular music.

In three experiments, we investigated the behavioral consequences of being absorbed into music on performance in a concurrent task. We tested two competing hypotheses: Based on a cognitive load account, captivation of attention by the music and state absorption might slow down reactions in the decisional task. Alternatively, music could induce spontaneous motor activity, and being absorbed in music might result in a more autonomous, flow-driven behavior with quicker motor reactions. Participants performed a simple, visual, two-alternative forced-choice task while listening to popular musical excerpts. Subsequently, they rated their subjective experience using a short questionnaire. We presented music in four tempo categories (between 80 and 140 BPM) to account for a potential effect of tempo and an interaction between tempo and absorption. In Experiment 1, absorption was related to decreased reaction times (RTs) in the visual task. This effect was small, as expected in this setting, but replicable in Experiment 2. There was no effect of the music's tempo on RTs but a tendency of mind wandering to relate to task performance. After slightly changing the study setting in Experiment 3, flow predicted decreased RTs, but absorption alone - as part of the flow construct - did not predict RTs. To sum up, we demonstrated that being absorbed in music can have the behavioral consequence of speeded manual reactions in specific task contexts, and people seem to integrate the music into an active, flow-driven and therefore enhanced performance. However, shown relations depend on task settings, and a systematic study of context is necessary to understand how induced states and their measurement contribute to the findings.