Back

The Towers Foraging Park: A Flexible Naturalistic Framework to Study Learning, Decision-Making, and Motor Control in Freely Moving Mice

Schaffhauser, M.; Orjollet-Lacomme, T.; Amroune, K.; Morvan, T.; Fortoul, A.; Lechelon, M.; Robbe, D.

2025-09-11 animal behavior and cognition
10.1101/2025.09.09.675194 bioRxiv
Show abstract

Adaptive behavior depends on a variety of brain functions, such as learning, decision-making, spatial navigation and motor control, which have been studied using two main strategies. Trial-based tasks allow their mechanistic dissection but tend to generate highly stereotypical behavior, whereas open-field investigations capture naturalistic dynamics with less experimental control. To leverage the strengths of both approaches, we developed a behavioral framework which recreates dilemmas faced by animals during patch foraging. In the Tower Foraging Park (TFP), mice harvest rewards along square towers (patches) by making quarter-turns around them in a single direction (exploit) and alternating between towers (explore) as patches eventually deplete. Within a couple of sessions, naive mice performed quarter-turns in the rewarded direction with increasing vigor and reduced variability, and switched towers after short exploitation bouts. When the harvest direction was reversed, mice rapidly adapted their turning direction, with quarter-turn trajectory variability and speed becoming decoupled. Mice subjected to daily reversals adapted progressively faster, revealing meta-learning. When the next rewarding tower became harder to locate, all trained mice increased exploitation duration, although metalearners outperformed animals trained under stable contingencies. Altogether, the TFP produced behavior consistent with foraging theory and revealed new processes facilitating flexible foraging: meta-learning and the decoupling of movement variability and speed. Moreover, because the TFP accommodates diverse protocol variants, adheres to FAIR principles, and is fully compatible with modern neurophysiological techniques, it provides a promising platform for mechanistic investigations of brain functions underlying adaptive behavior while maintaining ethological validity.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.