Many daily activities, from the mundane to the life critical, require active exploration of the environment while doing tasks that tax a wide range of cognitive capacities. Monitoring, predicting, and augmenting performance in these varied contexts requires understanding the fundamental nature of cognition during active exploration activities. However, traditional experimental approaches investigating cognitive capacities and their neural mechanisms use tightly controlled laboratory experiments in conditions in which participants are stationary and not actively exploring the environment. While these approaches have contributed to significant advances in understanding cognitive capacities, there is a fundamental knowledge gap in understanding these capacities during active, wide area exploration.
The importance of bridging this gap is underscored by neural recordings from awake behaving insects and nonhuman mammals that have shown that the neural coding of information sampled from the environment is altered when an organism is engaged in locomotive behaviors needed for active exploration (e.g., flying, walking) compared to when the organism is stationary. A handful of studies suggest that there are also alterations in human brain activity when engaged in locomotive behaviors, but the impact on cognitive capacities is less clear. Indeed, some studies show enhancements of some stages of information processing, while others show impairments. This project will investigate the scale of these alterations in cognitive capacities when engaged in active exploration. We will take advantage of recent developments in recording brain activity during physically active states (e.g., biking, walking) and in immersive virtual and augmented reality applications that allow for tight control of experimental scenarios during active, wide-area exploration. This combination of tightly controlled studies conducted in the lab and outside is directed at a fundamental knowledge gap that currently limits the fundamental understanding of cognitive capacities in real-world scenarios.