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Anselme, P.

Publications and source records attributed to Anselme, P..

2 recordsLinked to original sources

Continuous foraging behavior shapes patch-leaving decisions in pigeons: A 3D tracking study

Optimal foraging behavior is a key component of successful adaptations to natural environments. Understanding how animals decide to stay near food or to leave it for another food patch gives us insights into the underlying cognitive mechanisms that govern adaptive behaviors. 3D pose tracking was used to determine how pigeons exploit a 4 square meter arena with two separate platforms (i.e. food patches) whose absolute and relative elevations were manipulated. Detailed kinematic features of foraging and traveling behaviors were quantified using automated video tracking, without a need for manual coding. Our computational approach captured continuous, high-dimensional movement patterns and enabled precise quantification of travel costs between patches. Combined with mixed-effects survival analysis, our fine-grained behavioral tracking provided detailed insight into the moment-by-moment dynamics of patch-leaving decisions of pigeons. As expected from behavior optimization models, our results showed a preference to visit a ground food platform first, and longer latencies to leave an elevated platform. Foraging activity significantly decreased throughout the session, with shorter visits, less pecks per visit, and a decrease in inter-peck variability. However, a mixed-effects Cox regression modeled pigeons patch-leaving probability, demonstrating that current and cumulative foraging parameters between patches significantly enhanced the models predictive power beyond patch accessibility (i.e., beyond travel costs). This suggests that pigeons integrate both current environmental cues and their individual foraging history when making patch-leaving decisions. Our findings are discussed in relation to the marginal value theorem and optimal foraging theory.

animal behavior and cognition↗

A New Method to Quantify the Causal Effects of Reinforcement in Terms of Behavioral Selection

We present a new methodology to partition different sources of behavior change within a selectionist framework based on the Price equation - the Multilevel Model of Behavioral Selection (MLBS). The MLBS provides a theoretical background to describe behavior change in terms of operant selection. Operant selection is formally captured by the covariance based law of effect (CLOE) and accounts for all changes in individual behavior that involve a covariance between behavior and predictors of evolutionary fitness (e.g., food). In this article we show how the CLOE may be applied to different components of operant behavior (e.g., allocation, speed, and accuracy of responding), thereby providing quantitative estimates for various selection effects affecting behavior change using data from a published learning experiment in pigeons.

animal behavior and cognition↗