Four on-road studies were conducted in the Clifton area of Nottingham, UK, aiming to explore the relationships between driver workload and environmental engagement associated with ‘active’ and ‘passive’ navigation systems. In a between-subjects design, a total of 61 experienced drivers completed two experimental drives comprising the same three routes (with overlapping sections), staged one week apart. Drivers were provided with the navigational support of a commercially-available navigation device (‘satnav’), an informed passenger (a stranger with expert route knowledge), a collaborative passenger (an individual with whom they had a close, personal relationship) or a novel interface employing a conversational natural language ‘NAV-NLI’ (Navigation Natural Language Interface). The NAV-NLI was created by curating linguistic intercourse extracted from the earlier conditions and delivering this using a ‘Wizard-of-Oz’ technique. This term describes a research experiment in which subjects interact with a computer system that they believe to be autonomous, but which is actually being operated or partially operated by an unseen human being. The different navigational methods were notable for their varying interactivity and the preponderance of environmental landmark information within route directions. Participants experienced the same guidance on each of the two drives to explore changes in reported and observed behaviour. Results show that participants who were more active in the navigation task (collaborative passenger or NAV-NLI) demonstrated enhanced environmental engagement (landmark recognition, route-learning and survey knowledge) allowing them to reconstruct the route more accurately post-drive, compared to drivers using more passive forms of navigational support (SatNav or informed passenger). Workload measures (the Tactile Detection Task (TDT) and the National Aeronautical and Space Administration Task Load Index (NASA-TLX)) indicated no differences between conditions, although SatNav users and collaborative passenger drivers reported lower workload during their second drive. The research demonstrates clear benefits and potential for a navigation system employing two-way conversational language to deliver instructions. This could help support a long-term perspective in the development of spatial knowledge, enabling drivers to become less reliant on the technology and begin to re-establish associations between viewing an environmental feature and the related navigational manoeuvre.

Theories of spatial cognition are derived from many sources. Psychologists are concerned with determining the features of the mind which, in combination with external inputs, produce our spatialized experience. A review of philosophical and other approaches has convinced us that the brain must come equipped to impose a three-dimensional Euclidean framework on experience – our analysis suggests that object re-identification may require such a framework. We identify this absolute, nonegocentric, spatial framework with a specific neural system centered in the hippocampus.

A consideration of the kinds of behaviours in which such a spatial mapping system would be important is followed by an analysis of the anatomy and physiology of this system, with special emphasis on the place-coded neurons recorded in the hippocampus of freely moving rats. A tentative physiological model for the hippocampal cognitive map is proposed. A review of lesion studies, in tasks as diverse as discrimination learning, avoidance, and extinction, shows that the cognitive map notion can adequately explain much of the data.

The model is extended to humans by the assumption that spatial maps are built in one hemisphere, semantic maps in the other. The latter provide a semantic deep structure within which discourse comprehension and production can be achieved. Evidence from the study of amnesic patients, briefly reviewed, is consistent with this extension.

We argue that a map is meaningless unless we have a process for using it. Thus, in this paper, we not only offer the world graph as a representation of relationships among situations the animal has encountered and may encounter again, but we also offer algorithms for how the information encoded in the world graph may be used by the animal in determining its behavior. Each node of the graph encodes a recognizable situation in the animal's world, but a given place may well be encoded in a number of different nodes. Nodes not only require algorithms for the recognition of the situation; they store information about drive reduction associated with the encoded situation. We note that the use of graphs as a basis for exploring some search space is well known in artificial intelligence (AI), but we stress the importance of the animal's exploration of its environment for growing the graph, as distinct from the mathematically described potential nodes frequent in AI search spaces. To explore a number of hypotheses about the way information in the world graph is used to guide the animal's movement, we recall a number of classical experiments on maze exploration by animals, and use them to argue for the nonlocal hypothesis (selection of a path does not depend only upon information about the immediate environment of the animal) and the competing nodes hypothesis (more than one drive may enter into the determination of the animal's behavior at any time). An important feature of the model is that it yields exploration and latent learning without the introduction of an exploratory drive. We also note that the performance exhibited by the model appears to be state-dependent when the animal operates under high drive levels. The drive-interaction matrix is offered as a subject for future research.

We complement the presentation of the world graph model, its drive dynamics, and how these are constrained by experiments on maze behavior, with a brief analysis of maps in the brain. We distinguish egocentric maps–which we relate to the many visual systems–from allocentric maps. We offer a somewhat unconventional view of short-term and long-term memory. We examine cooperative computation in somatotopically organized networks, relating this to visually guided behavior in the frog, and to the interaction of colliculus and cortex in the control of eye movements. We examine, but do not advocate, the hypothesis that the hippocampus is a cognitive map. We do stress that if it is a cognitive map, it must be seen as a chart of the local neighborhood, rather than the whole atlas; and we note that the cognitive map hypothesis would lead one to expect the region to exhibit activation of place cells before the animal leaves the previous place.