Acquisition and consolidation of hierarchical representations of space

Navigation – the ability to reach targets which are no visible from the current position - depends on the correct recall of the desired target and the environment between one's current position and this target. The content of these representations are subject to influences from different modalities, e.g. vision, and language. A place can be recognized through different cues, e.g. due to a salient object, but also because of the angles of the routes at an intersection, or a name. The location of places as well as the routes connecting them can be integrated and memorized in an allocentric, survey-like representation. Depending on the amount of detail, the granularity level of a representation can be coarser or finer; the different levels are organized hierarchically. Characteristics of a superordinate category, like a region, can affect the perception of its constituting elements, the places; an inheritance of qualities from region to place levels is possible. The formation of superordinate categories depends both on environmental factors as well as individual ones: what is recognized, what is remembered, and which predictions are drawn from this representation? In this dissertation I examine the acquisition of representations of space, in order to identify features that are well suited for being remembered and auxiliary for navigation. I have two research foci: First, I examine the impact of language by using different hierarchically structured naming schemes as place names. Wiener & Mallot (2003) found that characterizing places only with landmarks belonging to different semantic categories influenced route choice as well as the representations of space. I compare these findings to the impact of different naming schemes. I show that there are naming schemes that may influence behavior in a similar way as a landmark does, but that seeing something and reading its name is by far the same thing. The second part focuses on the content of representations established during navigation. With three different navigation experiments, I examine the content of the concepts of space that are acquired during navigation. What is remembered - the location of places, the routes, or the hierarchical structure of the experimental environment? Are there features that are more likely to be consolidated during sleep, e.g., the transfer of concrete knowledge about places and routes into an abstract, survey-like representation? I show that there are improvements in one wayfinding task correlated to sleep. In the other experiments, learning effects were found for both groups. I also address the question of suitable parameters for measuring survey knowledge

Evidence from London taxi drivers of hierarchical route planning in a real-world environment

The ability to navigate a spatial environment strongly depends on how well individuals learn, represent and make use of their knowledge about the environment. In the past, research investigated these aspects separately and often in a virtual environment. The current work studied these three aspects of navigation in a real-real world setting to understand how humans navigate naturally in a complex, urban environment like London, UK. Of particular interest was to determine if there was evidence of hierarchical representations during route planning as found in previous behavioural, neuroscientific or computational studies. Most past studies have explored knowledge for simplistic environments or fragmented knowledge of real-world environments. By contrast, licensed London taxi drivers acquire a unique, almost perfect mental representation of the street network, the location of places and the traffic rules that apply to it. Here, the rare knowledge of these navigation experts was explored in three studies with novel approaches. First, to gain an understanding of the training process of unqualified taxi drivers, information from an interview with a teacher, training lessons and study material was collected, summarised and reported. A range of learning strategies was identified that was linked to theoretical, map-based learning and practical, in-situ experiences of London and pointed towards a segmented planning of routes through subgoal selection. Second, a potential mental segregation of London was studied with qualified taxi drivers through boundary drawings of specific London districts with a paper map to understand a potential hierarchical representation. Higher agreement was found for geographical structures and topically distinct districts surrounded by a linear, almost rectangular street network, whereas agreement was lowest for irregularly shaped districts with similarities to neighbouring areas. Finally, taxi drivers were asked to plan and then verbally recall each street they would take along routes between selected origin destination pairs. Audio recordings of these routes made it possible to relate the response times between individual streets to specific street network properties. The analysis using a linear mixed model indicated slower responses at upcoming turns and entering main roads, whereas boundary streets were recalled faster, as were finial streets when compared to initial street. No effects of Euclidean distance or detours were found. Observations from the training process indicate that a potential segregation of the environment, which might impact on later route planning, might be formed already through specific learning strategies. Faster response times for boundary streets support models in which planning is hierarchical. These findings extend past work on route planning in lab-based networks to real-world city street networks and highlight avenues for future research to explore and make use of real-world data

The impossible puzzle: No global embedding in environmental space memory

We live in compartmentalized, clustered environments and have to deal with spatial information scattered across rooms, streets, neighborhoods, and cities every day of our life. Yet, we are able to piece this information together in our head, for example, in order to find our way from our flat to our workplace, even when faced with construction work and blocked streets. Furthermore, we can point out the direction to the supermarket to a pedestrian without having direct visual access to it. My thesis is concerned with the question of how our memory for spatial relations of places in navigable space (also called survey knowledge) is actually structured. In four consecutive studies, I contrasted two major theo-retical approaches that try to explain how we represent survey knowledge, namely, Euclidean map and enriched graph approaches. Euclidean map approaches assume that spatial locations are represented in a map-like, globally embedded, Euclidean format. Enriched graph approaches propose a partitioned, unitwise representation of places connected in a network. These local units are not required to be globally consistent. In each study, I used different virtual environments, sometimes single rooms, mostly navigable multi-corridor environ-ments, once even an impossible non-Euclidean environment. Participants learned spatial relations between objects spread across these environments and solved survey tasks afterward (e.g., pointing to object locations from memory). Their performance yielded multiple effects. In short, the most prominent effects were: (1) Pointing latency increased with increasing number of places along the route towards the target, (2) facilitated recall along the direction of the initially experienced path walked within the environment, (3) globally incoherent point-ing behavior following the local metrics experienced from place to place, (4) facilitated performance upon alignment with local corridor geometry but also (5) upon alignment with regional geometry and a global main orientation, and (6) decreased pointing latency when pointing beyond regional boundaries. Interpreting these effects jointly implies that human survey knowledge is not repre-sented in the form of a Euclidean mental map embedding all encountered places in a uniform, globally consistent format. Instead, just as the environment we experience, also our memory of it seems to be compartmentalized, consisting of a network of local places connected by directed links that specify how to get from one place to another (rotation and translation) without directly requiring a global calibration. Survey estimates have to be constructed incrementally following this graph structure along the memorized connectivity, thereby relying on the local metrics that enrich the graph entities. These estimates are generally transient but can be retained for a limited amount of time for aiding subsequent estimates. In addition to the local entities of the enriched graph representation, it seems that general reference directions can be acquired during learning a navigable multi-compartment space. Such a reference direction can be understood as a mental “north”, a main direction that is tried to be main-tained and propagated across multiple local places and represented supplemen-tary in memory. It might be limited to only a sub-group of local units, thereby forming regional clusters, or it can cover the entire environment that was encountered. Such a general reference direction can aid the coordination of the local memory units during the construction of survey estimates, however, it does not require a global embedding of all place information into a coherent Euclidean map format. In sum, our representation of navigable space seems to be best described as an impossible puzzle where the memorized pieces and connec-tions do not necessarily match up on a global scale

Simulated cognitive topologies: automatically generating highly contextual maps for complex journeys

As people traverse complex journeys, they engage in a number of information interactions across spatial scales and levels of abstraction. Journey complexity is characterised by factors including the number of actions required, and by variation in the contextual basis of reasoning such as a transition between different modes of transport. The high-level task of an A to B journey decomposes into a sequence of lower-level navigational sub-tasks, with the representation of geographic entities that support navigation during, between and across sub-tasks, varying relative to the nature of the task and the character of the geography. For example, transitioning from or to a particular mode of transport has a direct bearing on the natural level of representational abstraction that supports the task, as well as on the overall extent of the task’s region of influence on the traveller’s focus. Modern mobile technologies send data to a device that can in theory be context-specific in terms of explicitly reflecting a traveller’s heterogeneous information requirements, however the extent to which context is explicitly reflected in the selection and display of navigational information remains limited in practice, with a rigid, predetermined scale-based hierarchy of cartographic views remaining the underlying representational paradigm. The core subject of the research is the context-dependent selection and display of navigational information, and while there are many and varied considerations in developing techniques to address selection and display, the central challenge can simply be articulated as how to determine the probability, given the traveller’s current context, that a feature should be in the current map view. Clearly this central challenge extends to all features in the spatial extent, and so from a practical perspective, research questions centre around the initial selection of a subset of features, and around determining an overall probability distribution over the subset given the significance of features within the hierarchically ordered sequence of tasks. In this thesis research is presented around the use of graph structures as a practical basis for modeling urban geography to support heterogenous selections across viewing scales, and ultimately for displaying highly context-specific cartographic views. Through an iterative, empirical research methodology, a formalised approach based on routing networks is presented, which serves as the basis for modeling, selection and display. Findings are presented from a series of 7 situated navigation studies that included research with an existing navigation application as well as experimental research stimuli. Hypotheses were validated and refined over the course of the studies, with a focus on journey-specific regions that form around the navigable network. Empirical data includes sketch maps, textual descriptions, video and device interactions over the course of complex navigation exercises. Study findings support the proposed graph architecture, including subgraph classes that approximate cognitive structures central to natural comprehension and reasoning. Empirical findings lead to the central argument of a model based on causal mechanisms, in which relations are formalised between task, selection and abstraction. A causal framework for automatically determining map content for a given journey context is presented, with the approach involving a conceptual shift from treating geographic features as spatially indexed records, to treating them as variables with a finite number of possible states. Causal nets serve as the practical basis of reasoning, with geographic features being represented by variables in these causal structures. The central challenge of finding the probability that a variable in a causal net is in a particular state is addressed through a causal model in which journey context serves as the evidence that propagates over the net. In this way, complex heterogeneous selections for interactive multi-scale information spaces are expressed as probability distributions determined through message propagation. The thesis concludes with a discussion around the implications of the approach for the presentation of navigational information, and it is shown how the framework can support context-specific selection and disambiguation of map content, demonstrated through the central use case of navigating complex urban journeys