Animal Behavior and Cognition

eLife Assessment

This important study introduces an advance in multi-animal tracking by reframing identity assignment as a self-supervised contrastive representation learning problem. It eliminates the need for segments of video where all animals are simultaneously visible and individually identifiable, and significantly improves tracking speed, accuracy, and robustness with respect to occlusion. This innovation has implications beyond animal tracking, potentially connecting with advances in behavioral analysis and computer vision. While the strength of support for these advances is solid overall, the presentation could be greatly improved for clarity and broader accessibility; in addition, incorporating more standard metrics in the multi-animal tracking literature would better benchmark the approach against other methods.

eLife Assessment

This manuscript describes a novel approach for assessing cognitive function in freely moving mice in their home-cage, without human involvement. The authors provide convincing evidence in support of the tasks they developed to capture a variety of complex behaviors and demonstrate the utility of a machine learning approach to expedite the acquisition of task demands. This work is important given its potential utility for other investigators interested in studying mouse cognition.

eLife Assessment

This study presents an important finding that ant nest structure and digging behavior depend on ant age demographics for a ground-dwelling ant species (Camponotus fellah). By asking whether ants employ age-polyethism in excavation, the authors address a long-standing question about how individuals in collectives determine the overall state of the task they must perform, and their results may prove to be a key consideration for interpreting results from other studies in the field of social insect behavior. The experimental evidence that the age of the ants and the group composition affect the digging of tunnels is solid, although some aspects of the modeling and certain analyses may benefit from further clarification regarding their added value to the core findings.

eLife Assessment

This important study uses long-term behavioural observations to understand the factors that influence female-on-female aggression in gorilla social groups. The evidence supporting the claims is convincing, as it includes novel methods of assessing aggression and considers other potential factors. The work will be of interest to broad biologists working on the social interactions of animals.

eLife Assessment

This important study presents a new framework (ASBAR) that combines open-source toolboxes for pose estimation and behavior recognition to automate the process of categorizing behaviors in wild apes from video data. The authors present compelling evidence that this pipeline can categorize simple wild ape behaviors from out-of-context video at a similar level of accuracy as previous models, while simultaneously vastly reducing the size of the model. The study's results should be of particular interest to primatologists and other behavioral biologists working with natural populations.

eLife Assessment

This valuable work investigates cooperative behaviors in adolescents using a repeated Prisoner's Dilemma game. The computational modeling approach used in the study is solid and well established, yet evidence supporting certain claims remains incomplete. The work could be strengthened with the consideration of additional experimental contexts, non-linear relationships between age and observed behavior, and modeling details. If these concerns are addressed, the results will be of interest to developmental psychologists, economists, and social psychologists.

eLife Assessment

This fundamental study demonstrates how a left-right bias in the relationship between numerical magnitude and space depends on brain lateralization. The evidence is compelling and will be of interest to researchers studying numerical cognition, brain lateralization, and cognitive brain development more broadly.

eLife Assessment

The open-source software Chromas tracks and analyses cephalopod chromatophore dynamics. The software features a user-friendly interface alongside detailed instructions for its application, with compelling exemplary applications to two widely divergent cephalopod species, a squid and a cuttlefish, over time periods large enough to encompass new chromatophore development among existing ones. It demonstrates accurate tracking of the position and identity of each chromatophore. The software and methods outlined therein will become an important tool for scientists tracking dynamic signaling in animals.

eLife Assessment

This study presents a useful framework to extract the individuality index to predict subjects' behavior in the target tasks. However, the evidence supporting such a framework is somewhat incomplete and would benefit from overall framing and clarity on its approaches. Overall, this study would be of interest to cognitive and AI researchers who work on cognitive models in general.

eLife Assessment

This important work by Malita et al. describes a mechanism by which an intestinal infection causes an increase in daytime sleep through signaling from the gut to the blood-brain barrier. Their findings suggest that cytokines upd3 and upd2 produced by the intestine following infection act on glia of the blood brain barrier to regulate sleep by modulating Allatostatin A signaling. The evidence is compelling and elegantly performed using the ample Drosophila genetic toolbox, making this work appealing for a broad group of neuroscience researchers interested in sleep and gut-brain interactions.