27,259 research outputs found

    Neural codes for one’s own position and direction in a real-world “vista” environment

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    Humans, like animals, rely on an accurate knowledge of one’s spatial position and facing direction to keep orientated in the surrounding space. Although previous neuroimaging studies demonstrated that scene-selective regions (the parahippocampal place area or PPA, the occipital place area or OPA and the retrosplenial complex or RSC), and the hippocampus (HC) are implicated in coding position and facing direction within small-(room-sized) and large-scale navigational environments, little is known about how these regions represent these spatial quantities in a large open-field environment. Here, we used functional magnetic resonance imaging (fMRI) in humans to explore the neural codes of these navigationally-relevant information while participants viewed images which varied for position and facing direction within a familiar, real-world circular square. We observed neural adaptation for repeated directions in the HC, even if no navigational task was required. Further, we found that the amount of knowledge of the environment interacts with the PPA selectivity in encoding positions: individuals who needed more time to memorize positions in the square during a preliminary training task showed less neural attenuation in this scene-selective region. We also observed adaptation effects, which reflect the real distances between consecutive positions, in scene-selective regions but not in the HC. When examining the multi-voxel patterns of activity we observed that scene-responsive regions and the HC encoded both spatial information and that the RSC classification accuracy for positions was higher in individuals scoring higher to a self-reported questionnaire of spatial abilities. Our findings provide new insight into how the human brain represents a real, large-scale “vista” space, demonstrating the presence of neural codes for position and direction in both scene-selective and hippocampal regions, and revealing the existence, in the former regions, of a map-like spatial representation reflecting real-world distance between consecutive positions

    Sculpture and Space

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    What is distinctive about sculpture as an artform? I argue that it is related to the space around it as painting and the other pictorial arts are not. I expound and develop Langer's suggestive comments on this issue, before asking what the major strengths and weaknesses of that position might be

    Embodiment and embodied design

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    Picture this. A preverbal infant straddles the center of a seesaw. She gently tilts her weight back and forth from one side to the other, sensing as each side tips downward and then back up again. This child cannot articulate her observations in simple words, let alone in scientific jargon. Can she learn anything from this experience? If so, what is she learning, and what role might such learning play in her future interactions in the world? Of course, this is a nonverbal bodily experience, and any learning that occurs must be bodily, physical learning. But does this nonverbal bodily experience have anything to do with the sort of learning that takes place in schools - learning verbal and abstract concepts? In this chapter, we argue that the body has everything to do with learning, even learning of abstract concepts. Take mathematics, for example. Mathematical practice is thought to be about producing and manipulating arbitrary symbolic inscriptions that bear abstract, universal truisms untainted by human corporeality. Mathematics is thought to epitomize our species’ collective historical achievement of transcending and, perhaps, escaping the mundane, material condition of having a body governed by haphazard terrestrial circumstance. Surely mathematics is disembodied

    Tangible user interfaces : past, present and future directions

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    In the last two decades, Tangible User Interfaces (TUIs) have emerged as a new interface type that interlinks the digital and physical worlds. Drawing upon users' knowledge and skills of interaction with the real non-digital world, TUIs show a potential to enhance the way in which people interact with and leverage digital information. However, TUI research is still in its infancy and extensive research is required in or- der to fully understand the implications of tangible user interfaces, to develop technologies that further bridge the digital and the physical, and to guide TUI design with empirical knowledge. This paper examines the existing body of work on Tangible User In- terfaces. We start by sketching the history of tangible user interfaces, examining the intellectual origins of this field. We then present TUIs in a broader context, survey application domains, and review frame- works and taxonomies. We also discuss conceptual foundations of TUIs including perspectives from cognitive sciences, phycology, and philoso- phy. Methods and technologies for designing, building, and evaluating TUIs are also addressed. Finally, we discuss the strengths and limita- tions of TUIs and chart directions for future research

    Evaluation of Multi-Level Cognitive Maps for Supporting Between-Floor Spatial Behavior in Complex Indoor Environments

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    People often become disoriented when navigating in complex, multi-level buildings. To efficiently find destinations located on different floors, navigators must refer to a globally coherent mental representation of the multi-level environment, which is termed a multi-level cognitive map. However, there is a surprising dearth of research into underlying theories of why integrating multi-level spatial knowledge into a multi-level cognitive map is so challenging and error-prone for humans. This overarching problem is the core motivation of this dissertation. We address this vexing problem in a two-pronged approach combining study of both basic and applied research questions. Of theoretical interest, we investigate questions about how multi-level built environments are learned and structured in memory. The concept of multi-level cognitive maps and a framework of multi-level cognitive map development are provided. We then conducted a set of empirical experiments to evaluate the effects of several environmental factors on users’ development of multi-level cognitive maps. The findings of these studies provide important design guidelines that can be used by architects and help to better understand the research question of why people get lost in buildings. Related to application, we investigate questions about how to design user-friendly visualization interfaces that augment users’ capability to form multi-level cognitive maps. An important finding of this dissertation is that increasing visual access with an X-ray-like visualization interface is effective for overcoming the disadvantage of limited visual access in built environments and assists the development of multi-level cognitive maps. These findings provide important human-computer interaction (HCI) guidelines for visualization techniques to be used in future indoor navigation systems. In sum, this dissertation adopts an interdisciplinary approach, combining theories from the fields of spatial cognition, information visualization, and HCI, addressing a long-standing and ubiquitous problem faced by anyone who navigates indoors: why do people get lost inside multi-level buildings. Results provide both theoretical and applied levels of knowledge generation and explanation, as well as contribute to the growing field of real-time indoor navigation systems

    An evaluation tool for design quality: PFI sheltered housing

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    The complex procurement process entailed by the private finance initiative (PFI) means that clients need new capacities to manage their relationships with bidders and to assess project proposals if the desired level of design quality is to be achieved. To assist local authorities in their client role, a new Architectural Design Quality Evaluation Tool was developed. The aim was to improve the quality of design in residential sheltered housing, procured through the PFI. The tool was developed for and applied to a programme that will see the replacement of a local authority's entire sheltered housing stock. The tool has two functions: (1) to inform the client's assessment process and assist with the selection of the preferred bidding consortium through a series of stages in the PFI process; and (2) to improve the quality of all the submitted designs through an iterative process. Although several existing mechanisms are available for evaluating the performance attributes of buildings, few also tackle the less tangible amenity attributes, which are vital to the feeling of home. The new tool emphasizes the amenity attributes without neglecting performance

    Knowledge-based vision and simple visual machines

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    The vast majority of work in machine vision emphasizes the representation of perceived objects and events: it is these internal representations that incorporate the 'knowledge' in knowledge-based vision or form the 'models' in model-based vision. In this paper, we discuss simple machine vision systems developed by artificial evolution rather than traditional engineering design techniques, and note that the task of identifying internal representations within such systems is made difficult by the lack of an operational definition of representation at the causal mechanistic level. Consequently, we question the nature and indeed the existence of representations posited to be used within natural vision systems (i.e. animals). We conclude that representations argued for on a priori grounds by external observers of a particular vision system may well be illusory, and are at best place-holders for yet-to-be-identified causal mechanistic interactions. That is, applying the knowledge-based vision approach in the understanding of evolved systems (machines or animals) may well lead to theories and models that are internally consistent, computationally plausible, and entirely wrong
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