Critical Factors that Underlay Cue Interactions in Human Spatial Navigation

Since the formalisation of the idea of cognitive maps (O’Keefe & Nadel, 1978), numerous experiments have tested whether cue competition phenomena are observed in spatial navigation. Different authors (Gallistel, 1990) suggested that learning about the geometric properties of an environment is processed in an encapsulated module, which prevents boundary information from interacting with non-geometric sources of information (e.g., beacons or landmarks) in wayfinding or reorientation studies. This suggestion has led to the idea that cue competition between landmarks and geometric information should not be observed. Numerous experiments have tested this prediction, and the findings have varied largely, leading to intense theoretical debates about whether spatial cognition follows similar learning principles as other tasks. If this was the case, then cue competition should be observed in spatial learning tasks (Pearce, 2009). However, little is known about what are the factors under which sometimes cue interactions are found and others are not.

This thesis builds on Urcelay’s (2017) previous work which suggests that several factors, such as contingency, relative stimulus duration and contiguity, may determine cue competition along both temporal and spatial dimensions. This is an important question because it begins to address the aforementioned empirical discrepancies. Contiguity and cue duration effects were exhaustively studied together with other factors using virtual learning environments.

Overall, the present work provides evidence that spatial contiguity is a critical determinant of cue competition, and that relative stimulus duration determines the strength of cue competition under strong contiguity. Finally, a fixed starting location and extended training enhance the likelihood of observing cue competition. This was observed across different parametric variations, which suggests that these results are not restricted to a specific set of parameters or learning domains. Instead, the present results should broaden the number of variables that should be taken into account when investigating competition phenomena.