Patrick Govoni

Patrick Govoni, Pawel Romanczuk

Navigation for social organisms rarely is a fully independent activity. Group structure and dynamics, as well as embodied interactions, critically influence useful behavior. Individual neural network controlled agents are trained to navigate in different social contexts, where social dependence and behavioral strategy learned is determined by relative task performance and spatial effect. Increasing high quality social information drives phase transitions from individual to following navigational strategy, and to collision avoidance in response to a crowded foraging patch. Predictable, nonstationary environmental dynamics drive behavioral hybridization between individual and social navigation, far and near the patch. Our findings challenge the approach of only inspecting individual behavior for social organisms and highlight the importance of taking a bottom-up approach in understanding how organisms behave.

Patrick Govoni, Pawel Romanczuk

Navigation is believed to be controlled by at least two partially dissociable systems in the brain. The cognitive map informs an organism of its location and bearing, updated by integrating vestibular self-motion or predicting distances to landmarks. Route-based navigation, on the other hand, directly evaluate sequential movement decisions from immediate percepts. Here we demonstrate the sufficiency of visual route-based decision-making in a classic open field navigation task often assumed to require a cognitive map. Three distinct strategies emerge to robustly navigate to a hidden goal, each conferring contextual tradeoffs analyzed at both neural and behavioral scales, as well as qualitatively aligning with behavior observed across the biological spectrum. We propose reframing navigation from the bottom-up, through an egocentric episodic perspective without assuming online access to computationally expensive top-down representations, to better explain behavior under energetic or attentional constraints.