Amy Lynne Shelton - US grants

Humans use spatial memory to successfully navigate in familiar environments on a daily basis, such as finding car keys or getting to the office. However, perhaps everyone has the experience of ending up at the wrong destination at some point in their lifetime. What has gone wrong in our memory system when this happens? Our understanding of navigation from memory in the past has relied on research with animals. For example, research has shown two distinct learning strategies that may explain both the flexible and habitual nature of navigation from memory: fast, flexible place learning in the hippocampus of the brain, but slow, rigid learning of specific patterns of response in the striatum. How such research findings from the animal population can apply to human spatial memory is so far unclear. With support from the National Science Foundation, the investigator will use behavioral and brain imaging techniques (e.g., functional magnetic resonance imaging) to study place learning and response learning and to bridge the domains of animal spatial learning and human spatial cognition. The goals of the project are to test whether and how humans engage place and response learning mechanisms, link those mechanisms to predicted neural correlates, and establish their functional significance. The investigator has designed a series of behavioral and neuroscience experiments to achieve these goals.

This work represents a transformative step in the study of human learning and memory. Linking findings from non-human animals to studies of human behavior and brain mechanisms has the potential to significantly advance our understanding of human spatial cogntion by building connections among psychology, neurobiology, and genetics. The work also provides an essential bridge to broader issues of human memory and individual differences in learning styles by considering how and under what conditions humans might learn differently. Such results could lead to better strategies for enhancing teaching and learning in a wide range of applications. This grant will readily support educational outreach by providing training opportunities at the undergraduate, graduate, and post-doctoral levels, and by making relevant materials and demos accessible to the public.

The objective of this research is to enable more effective design and use of virtual worlds. Virtual worlds are important in many domains, including architecture, education, medicine, simulation, and training. However, when compared to the real world, virtual worlds are hard to move through effectively, and pose challenges to effective navigation. If virtual worlds are going to be widely deployed - particularly for applications in education, training, and simulation - then these problems must be solved. This work will generate essential discoveries improving the process of wayfinding (orienting and navigating from place to place) and locomoting through immersive virtual worlds. It thus provides a critical and synergistic complement to the recent advent of low-cost commodity-level virtual reality equipment.

This research is multi-disciplinary and employs methods from computer science, cognitive science, and geographical information science in accomplishing these objectives. A transformation of wayfinding and navigation for large immersive virtual worlds can be accomplished by studying locomotion modes in conjunction with the spatial characteristics of virtual worlds and individual differences and abilities of the users of the virtual environments. In this work, virtual worlds are described and analyzed in terms of their connectivity, visual access, and integration using formal measures summarized as space syntax. Likewise, individuals traveling through virtual worlds may navigate and reason about space quite differently, and these differences can be quantified and measured. The goal is to develop locomotion modes that take into account both characteristics described by space syntax and individual attributes of users. Truly effective design and use of virtual worlds depend on an understanding of how an individual's abilities relate to the characteristics of the virtual world and the mechanisms for moving about in them. This interdisciplinary approach examines wayfinding and navigation in a multi-factor way, combining a focus on locomotion modes, a focus on spatial syntax (characteristics) of the virtual world, and a focus on the abilities and differences of individual users. In addition to improving the design and use of virtual worlds, this work will impact multiple disciplines: it not only advances computer graphics and virtual reality, but also informs the fields of cognitive science and geographical information science.

The ability to understand and reason about the spatial relationships among objects supports children's academic readiness and achievements in math and reading yet, we know little about when they emerge or how to improve them during early development. One of the earliest and most accessible windows into spatial skills is children's block play--building structures with physical blocks. Building with blocks is surprisingly complex, which makes it difficult to characterize in detail how children build structures, why they sometimes struggle, and what can be done to improve their skills. Drawing on traditional observational methods and advancements in computer science, this project creates detailed, robust, and automatic techniques for characterizing children's building behaviors and articulating the different building paths taken by "novice" and "expert" child builders. Its multidisciplinary approach advances the frontiers of understanding about how people learn, and how they might use their STEM knowledge more effectively. The tools produced by the project will offer new ways to measure spatial skills in formal and informal learning settings, and has the potential to change the way we think about early block-building as a marker for learning. In this way the project reflects NSF's investments in promising developments that build a coherent, cumulative knowledge base, focusing on high-leverage topics.

Spatial skills represent a fundamental aspect of human knowledge, supporting a wide range of cognitive functions including our ability to create and understand 2- and 3-D spatial representations of information. This project focuses on one of the earliest developing yet highly complex spatial skills--block building--which has garnered attention in both cognitive and educational arenas due to its accessibility and adaptability for young children in formal and informal learning contexts. Consistent with the Education and Human Resources Core Research program's mission of supporting fundamental research on learning in STEM that combines theory, techniques, and perspectives from a wide range of disciplines and contexts, the spatial skills coding system developed in this project combines video and motion tracking of children's block building. This will allow researchers to gather and characterize data from much larger numbers of children than ever before, to relate these data on block-building to other academically-relevant skills, and to use the characterization of child "expert" performance as instructional input to "novice" builders. Its use of traditional cognitive methods along with machine learning techniques to characterize the process of children's block building and how it develops will generate scalable tools that can be used by scientists and educators to characterize, analyze, and promote development of spatial skills in our youngest learners.