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A crucial step for validating the utility of an immersive virtual reality (iVR) buffet to study eating behavior is to determine whether variations in food characteristics such as portion size (PS) are relevant predictors of food selection in an iVR buffet. We tested whether manipulating PS in an iVR buffet affects the weight of food selected, and whether this response to PS is similar to participants' measured intake when PS varies at laboratory meals. In a randomized crossover design, 91 adults (18-71 y; 64 females; BMI = 25.3 ± 5.7) used their iVR remote to select lunch and dinner portions from an iVR buffet before consuming a standardized lab meal at two visits separated by one week. The PS in the iVR buffet and lab meals varied between a standard PS and a large PS. This design enabled comparisons of PS effects between iVR and lab settings, despite the scale difference in food weight between the environments. Portion size significantly affected food selection and food intake (p < 0.001). Subjects selected an additional 350 g in iVR and consumed an additional 154 g of food in the lab meals when offered the large portion compared to the small portion. The effect of PS showed a similar percentage increase in iVR (36.5%) and lab meals (39.2%). There was no significant difference in the effect of PS between iVR and lab meals after accounting for scale differences in food weight between the environments. The response to PS was not influenced by subject characteristics such as body mass index, sex, or age. These results demonstrate the utility of iVR for replicating real-world eating behaviors and enhancing our understanding of the intricate dynamics of food-related behaviors in a variety of contexts., Competing Interests: Declaration of competing interest None, (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Background: Investigating the relationship between the human body and its spatial environment is a critical component in understanding the process of acquiring spatial knowledge. However, few empirical evaluations have looked at how the visual accessibility of an environment affects spatial learning. To address this gap, this paper focuses on geographic scale, defined as the spatial extent visually accessible from a single viewpoint. We present two experiments in which we manipulated geographic scale using two perspectives, a ground level and an elevated view, in order to better understand the scale effect on spatial learning. Learning outcomes were measured using estimates of direction and self-reports of mental workload., Results: In contrast to our hypothesis, we found few differences in spatial learning when comparing different perspectives. However, our analysis of pointing errors shows a significant interaction effect between the scale and spatial ability: The elevated perspective reduced the differences in pointing errors between low and high spatial ability participants in contrast to when participants learned the environment at ground level alone. Bimodal pointing distributions indicate that participants made systematic errors, for example, forgetting turns or segments. Modeling these errors revealed a unified alternative representation of the environment and further suggests that low spatial ability participants benefited more from the elevated perspective in terms of spatial learning compared to high spatial ability participants., Conclusions: We conclude that an increased geographic scale, which was accessible through an elevated perspective in this study, can help bridge the performance gap in spatial learning between low and high spatial ability participants.

In the current study, we investigated the ways in which the acquisition and transfer of spatial knowledge were affected by (a) the type of spatial relations predominately experienced during learning (routes determined by walkways vs. straight-line paths between locations); (b) environmental complexity; and (c) the availability of rotational body-based information. Participants learned the layout of a virtual shopping mall by repeatedly searching for target storefronts located in 1 of the buildings. We created 2 novel learning conditions to encourage participants to use either route knowledge (paths on walkways between buildings) or survey knowledge (straight-line distances and directions from storefront to storefront) to find the target, and measured the development of route and survey knowledge in both learning conditions. Environmental complexity was manipulated by varying the alignment of the buildings with the enclosure, and the visibility within space. Body-based information was manipulated by having participants perform the experiment in front of a computer monitor or using a head-mounted display. After navigation, participants pointed to various storefronts from a fixed position and orientation. Results showed that the frequently used spatial knowledge could be developed similarly across environments with different complexities, but the infrequently used spatial knowledge was less developed in the complex environment. Furthermore, rotational body-based information facilitated spatial learning under certain conditions. Our results suggest that path integration may play an important role in spatial knowledge transfer, both from route to survey knowledge (cognitive map construction), and from survey to route knowledge (using cognitive map to guide wayfinding). (PsycINFO Database Record (c) 2019 APA, all rights reserved).

To navigate through daily life, humans use their ability to conceptualize spatio-temporal information, which ultimately leads to a system of categories. Likewise, the spatial sciences rely heavily on conceptualization and categorization as means to create knowledge when they process spatio-temporal data. In the spatial sciences and in related branches of artificial intelligence, an approach has been developed for processing spatio-temporal data on the level of coarse categories: qualitative spatio-temporal representation and reasoning (QSTR). Calculi developed in QSTR allow for the meaningful processing of and reasoning with spatio-temporal information. While qualitative calculi are widely acknowledged in the cognitive sciences, there is little behavioral assessment whether these calculi are indeed cognitively adequate. This is an astonishing conundrum given that these calculi are ubiquitous, are often intended to improve processes at the human-machine interface, and are on several occasions claimed to be cognitively adequate. We have systematically evaluated several approaches to formally characterize spatial relations from a cognitive-behavioral perspective for both static and dynamically changing spatial relations. This contribution will detail our framework, which is addressing the question how formal characterization of space can help us understand how people think with, in, and about space.

This article discusses an approach to characterizing movement patterns (paths/trajectories) of individual agents that allows for relating aspects of cognitive conceptualization of movement patterns with formal spatial characterizations. To this end, we adopt a perspective of characterizing movement patterns on the basis of perceptual and conceptual invariants that we term movement choremes (MCs). MCs are formally grounded by behaviorally validating qualitative spatio-temporal calculi. Relating perceptual and cognitive aspects of space and formal theories of spatial information has shown promise to foster understanding of the semantics of movement patterns. Specifically, we discuss our approach in relation to existing qualitative formalisms such as the region connection calculus and the Egenhofer's intersection formalisms. We show that the MC approach is compatible with these approaches but offers additional opportunities to improve the cognitive adequacy of these formalisms. We summarize this paper using a movement taxonomy that also provides guidance for future research., (Copyright © 2011 Cognitive Science Society, Inc.)

The human factors in GIScience Laboratory (Human Factors Lab) of The Pennsylvania State University's Department of Geography is located in University Park, PA (USA). University Park and bordering State College, PA are found in the heart of PA between the cities of New York City, NY, Philadelphia, PA, and Pittsburgh, PA. The laboratory is directed by Dr. Alexander Klippel and is part of the GeoVISTA Center. The Human Factors Lab contributes to Penn State Geography's strong tradition as a leader in research on map perception, spatial cognition, and behavior in spatial environments. This report focuses upon basic research topics in spatial cognition, including: (1) perceptual and cognitive factors in map symbolization and design, (2) the creation of cognitively ergonomic route directions for next generation location based services (LBS), (3) You-Are-Here maps and the creation of a sense of place through map-like representations, (4) the conceptualization and representation of dynamic phenomena (i.e., geographic movement pattern), and (5) the relationship between linguistic and non-linguistic conceptualization.