Biology subjects

Esteve-Agraz, J.

Publications and source records attributed to Esteve-Agraz, J..

3 recordsLinked to original sources

bioRxiv2025

Reward-based prosocial choices in mice

Prosocial behaviors, actions that benefit others, are an essential part of the social life of humans and other animals, by promoting bonding and cohesion among individuals and groups. Here we present a new behavioural paradigm to assess prosociality in food foraging contexts in laboratory mice, based in our paradigm previously developed for rats. In this task, the decision-maker can choose between two options, one that will only provide rewards to itself (selfish choice) or one that will reward both itself and its cagemate (prosocial choice). Our work reveals that prosocial choices in male mice are not widespread and are only observed in a small proportion of animals. Using detailed analysis of behavior, we describe that recipients of help express different social cues in prosocial and selfish trials, but decision makers do not take them into account to guide their choices. Furthermore, we assess how the level of individual training and the physical layout of the paradigm might affect the performance in this social task. Only those mice with increased social attention (16% of the animals) display prosocial preferences, suggesting these to be rooted in similar behavioural factors and social interactions that we previously described in other work with rats.

neuroscience↗

bioRxiv2022

Multimodal cues displayed by submissive rats promote prosocial choices by dominants

Animals often display prosocial behaviours, performing actions that benefit others. Although prosociality is essential for social bonding and cooperation, we still know little about how animals integrate behavioural cues from those in need to make decisions that increase their wellbeing. To address this question, we used a two-choice task where rats can provide rewards to a conspecific in the absence of self-benefit, and interrogated which conditions promote prosociality by manipulating the social context of the interacting animals. While sex or degree of familiarity did not affect prosocial choices in rats, social hierarchy revealed to be a potent modulator, with dominant decision-makers showing faster emergence and higher levels of prosocial choices towards their submissive cage-mates. Leveraging quantitative analysis of multimodal social dynamics prior to choice, we identified that pairs with dominant decision-makers exhibited more proximal interactions. Interestingly, these closer interactions were driven by submissive animals that modulated their position and movement following their dominants and whose 50kHz vocalisation rate correlated with dominants prosociality. Moreover, Granger causality revealed stronger bidirectional influences in pairs with dominant focals and submissive recipients, indicating increased behavioural coordination. Finally, multivariate analysis highlighted body language as the main information dominants use on a trial-by-trial basis to learn that their actions have effects on others. Our results provide a refined understanding of the behavioural dynamics that rats use for action-selection upon perception of socially relevant cues and navigate social decision-making.

neuroscience↗

bioRxiv2021

pyControl: Open source, Python based, hardware and software for controlling behavioural neuroscience experiments.

Laboratory behavioural tasks are an essential research tool. As questions asked of behaviour and brain activity become more sophisticated, the ability to specify and run richly structured tasks becomes more important. An increasing focus on reproducibility also necessitates accurate communication of task logic to other researchers. To these ends we developed pyControl, a system of open source hardware and software for controlling behavioural experiments comprising; a simple yet flexible Python-based syntax for specifying tasks as extended state machines, hardware modules for building behavioural setups, and a graphical user interface designed for efficiently running high throughput experiments on many setups in parallel, all with extensive online documentation. These tools make it quicker, easier and cheaper to implement rich behavioural tasks at scale. As important, pyControl facilitates communication and reproducibility of behavioural experiments through a highly readable task definition syntax and self-documenting features. ResourcesDocumentation: https://pycontrol.readthedocs.io Repositories: https://github.com/pyControl User support: https://groups.google.com/g/pycontrol

neuroscience↗