The Path more Travelled: Time Pressure Increases Reliance on Familiar Route-Based Strategies during Navigation

Abstract

Navigating large-scale environments involves dynamic interactions between the physical world and individuals' knowledge, goals, and strategies. Time pressure can result from self-imposed goals or relatively dynamic situational factors that induce varied constraints. While time pressure is ubiquitous in daily life and has been shown to influence affective states, cost-benefit analyses, and strategy selection, its influence on navigation behaviour is unknown. The present study examined how introducing varied time constraints during virtual urban navigation would influence spatial strategies and impact the efficiency and effectiveness of goal-directed wayfinding. Participants learned a large-scale urban virtual environment by wayfinding between a series of 20 successive landmark goals (e.g., You have reached the Theater. Now find the Bank.). A day later, they again performed the same task, but landmark-to-landmark trials were characterized by conditions of low-, moderate-, or high-pressure time limits as quantified by a pilot experiment. As time pressure increased, participants more likely navigated along previously experienced paths and less likely travelled in the global direction of the destination. Results suggest strategy shifts under time constraints that increase reliance on egocentric, route-based strategies and decrease reliance on global configural knowledge, probably in an attempt to reduce cognitive demands and support performance under pressure.

Lost in Time and Space: States of High Arousal Disrupt Implicit Acquisition of Spatial and Sequential Context Information

“…Presumably due to floor effects, alterations in performance reached significance at a moderate to low level of mnemonic interference. Our behavioral data support the idea that states high in arousal disrupt hippocampus-dependent acquisition of spatial context information (Schwabe et al, 2007 ; Brunyé et al, 2017 ; Vogel et al, 2017 ) as indicated by impaired spatial discrimination ability (Reagh et al, 2014 ; Marshall et al, 2016 ). Consistent with our second hypothesis, high arousal states did not differ in the direction and magnitude they hamper performance, thus excluding a role of their valence, i.e., appetitive or aversive (Mather and Sutherland, 2009 ; Harmon-Jones et al, 2013 ).…”

“…In fact, acute stress is associated with an impairment of spatial working memory in rodents and monkeys (Gamo et al, 2015 ), healthy humans (Moriarty et al, 2014 ; Olver et al, 2015 ) and psychiatric populations (Smith and Lenzenweger, 2013 ), as well as impaired spatial learning in rodents (Akirav et al, 2001 , 2004 ; Herrero et al, 2006 ) and monkeys (Arnsten and Goldman-Rakic, 1998 ). In humans, exposure to stress strengthens reliance on egocentric, route-based strategies at the cost of allocentric, cognitive map-based context information (van Gerven et al, 2016 ; Brunyé et al, 2017 ). Moreover, further research showed that under acute stress, spatial navigation is supported less by a hippocampus-dependent strategy, which maps flexible spatial relations using multiple cues (Schwabe et al, 2007 ; Vogel et al, 2017 ).…”

Spatial decision dynamics during wayfinding: intersections prompt the decision-making process

“…We also assessed wayfinding effectiveness by calculating path efficiency. As in our recent work, we chose to use path efficiency due to its relative invulnerability to stopping behavior, and the fact that path and time efficiency are typically highly correlated (Brunyé et al, 2014 , 2016a; Brunyé, Gardony, Mahoney, & Taylor, 2012 ; Brunyé, Wood, Houck, & Taylor, 2016 b). The present dataset was no exception, with highly correlated time and path efficiency measures (all Pearson r ≥ 0.90).…”

The formation and use of hierarchical cognitive maps in the brain: A neural network model

“…This hierarchical mechanism also appears to produce a preference for familiar routes -those for which the agent has available sequences -as seen in Figure 10. This preference has been experimentally demonstrated in human navigation (Brunyé et al 2017;Payyanadan 2018). It also suggests that, in more complex tasks and environments, the hierarchical mechanism may produce a form of habitual behaviour, where inefficient but familiar solutions are preferred over optimal but planningintensive solutions.…”

“…If frequently-used sequences of state-action combinations are used to speed up the propagation of activity, these familiar sequences may be selected in preference to an optimal route. The preference for known routes has been observed in experimental studies (Brunyé et al 2017;Payyanadan 2018). The model might also display this habitual behaviour in non-navigation tasks.…”