Search

In an unfamiliar environment, searching for and navigating to a target requires that spatial information be acquired, stored, processed, and retrieved. In a study encompassing all of these processes, participants acted as taxicab drivers who learned to pick up and deliver passengers in a series of small virtual towns. We used data from these experiments to refine and validate MAGELLAN, a cognitive map-based model of spatial learning and wayfinding. MAGELLAN accounts for the shapes of participants' spatial learning curves, which measure their experience-based improvement in navigational efficiency in unfamiliar environments. The model also predicts the ease (or difficulty) with which different environments are learned and, within a given environment, which landmarks will be easy (or difficult) to localize from memory. Using just 2 free parameters, MAGELLAN provides a useful account of how participants' cognitive maps evolve over time with experience, and how participants use the information stored in their cognitive maps to navigate and explore efficiently. [ABSTRACT FROM AUTHOR]

The hippocampal formation has been associated with a wide variety of functions including spatial navigation and planning, memory encoding and retrieval, relational processing, novelty detection, and imagination. These functions are dissimilar in terms of their behavioral consequences and modality of representation. Consequently, theoretical standpoints have focused on explaining the role of the hip-pocampal formation in terms of either its spatial or nonspatial functions. Contrary to this dichotomy, we propose that it is essential to look beyond these traditional boundaries between mnemonic and spatial functions and focus instead on the processes that these functions have in common. In this framework, we use electrophysiology data from the spatial domain to predict effects on the systems level, both in spatial and nonspatial domains. We initially outline the results of studies that have used findings from spatial navigation in rodents to predict the patterns of brain activity observable in people who are exploring virtual environments. We discuss how certain properties of space-defining neurons enable space to be represented as a mental map of interconnected locations, which are expressed at multiple spatial scales in separate modules in the hippocampal formation. We then suggest that memories are also organized in networks, characterized by mnemonic and temporal hierarchies. We finish by discussing how virtual-reality techniques can be used to create novel lifelike episodes allowing us to look at episodic memory processes while multivariate analysis tools can be used to explore the organizational structure of mnemonic networks. [ABSTRACT FROM AUTHOR]