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While scene context is known to facilitate object recognition, little is known about which contextual “ingredients” are at the heart of this phenomenon. Here, we address the question of whether the materials that frequently occur in scenes (e.g., tiles in a bathroom) associated with specific objects (e.g., a perfume) are relevant for the processing of that object. To this end, we presented photographs of consistent and inconsistent objects (e.g., perfume vs. pinecone) superimposed on scenes (e.g., a bathroom) and close-ups of materials (e.g., tiles). In Experiment 1, consistent objects on scenes were named more accurately than inconsistent ones, while there was only a marginal consistency effect for objects on materials. Also, we did not find any consistency effect for scrambled materials that served as color control condition. In Experiment 2, we recorded event-related potentials and found N300/N400 responses—markers of semantic violations—for objects on inconsistent relative to consistent scenes. Critically, objects on materials triggered N300/N400 responses of similar magnitudes. Our findings show that contextual materials indeed affect object processing—even in the absence of spatial scene structure and object content—suggesting that material is one of the contextual “ingredients” driving scene context effects.
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.
We wish to make the following correction to the published paper 'Effects of Transient Loss of Vision on Head and Eye Movements during Visual Search in a Virtual Environment'. We have identified a flaw in the implementation of a latency mitigation strategy for our gaze-contingent protocol written in Unity3D. As a result, the maximum latency is now estimated to be 30 ms instead of 15 ms, which should not affect any of the results originally published but should be noted for further reference.