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Humans and other animals often seek instrumental information to strategically improve their decisions in the present. Our curiosity also leads us to acquire non-instrumental information that is not immediately useful but can be encoded in memory and stored for use in the future by means of episodic recall. Despite its adaptive benefits and central role in human cognition, questions remain about the cognitive mechanisms and evolutionary origins that underpin curiosity. Here, we comparatively review recent empirical studies that some authors have suggested reflects curiosity in nonhuman animals. We focus on findings from laboratory tasks in which individuals can choose to gain advanced information about uncertain future outcomes, even though the information cannot be used to increase future rewards and is often costly. We explore the prevalence of preferences in these tasks across animals, discuss the theoretical advances that they have promoted, and outline some limitations in contemporary research. We also discuss several features of human curiosity that can guide future empirical research aimed at characterising and understanding curiosity in animals. Though the prevalence of curiosity in animals is actively debated, we surmise that investigating behavioural candidates for curiosity-motivated behaviour in a broader range of species and contexts, should help promote theoretical advances in our understanding of cognitive principles and evolutionary pressures that support curiosity-driven behaviour., (© 2024. The Author(s).)

As the most species-rich vertebrate group, fish provide an array of opportunities to investigate the link between ecological interactions and the evolution of behavior and cognition, yet, as an animal model, they are relatively underutilized in studies of comparative cognition. To address this gap, we developed a fully automated platform for behavioral experiments in aquatic species, GoFish. GoFish includes closed-loop control of task contingencies using real-time video tracking, presentation of visual stimuli, automatic food reward dispensers, and built-in data acquisition. The hardware is relatively inexpensive and accessible, and all software components of the platform are open-source. GoFish facilitates experimental automation, allowing for customization of high-throughput protocols and the efficient acquisition of rich behavioral data. We hope this platform proves to be a useful tool for the research community, facilitating refined, reproducible behavioral experiments on aquatic species in comparative cognition, behavioral ecology, and neuroscience., (© 2024 The Author(s). Journal of Fish Biology published by John Wiley & Sons Ltd on behalf of Fisheries Society of the British Isles.)

Fish are the most species-rich vertebrate group, displaying vast ecological, anatomical and behavioural diversity, and therefore are of major interest for the study of behaviour and its evolution. However, with respect to other vertebrates, fish are relatively underrepresented in psychological and cognitive research. A greater availability of easily accessible, flexible, open-source experimental platforms that facilitate the automation of task control and data acquisition may help to reduce this bias and improve the scalability and refinement of behavioural experiments in a range of different fish species. Here we present GoFish, a fully automated platform for behavioural experiments in aquatic species. GoFish includes real-time video tracking of subjects, presentation of stimuli in a computer screen, an automatic feeder device, and closed-loop control of task contingencies and data acquisition. The design and software components of the platform are freely available, while the hardware is open-source and relatively inexpensive. The control software, Bonsai, is designed to facilitate rapid development of task workflows and is supported by a growing community of users. As an illustration and test of its use, we present the results of two experiments on discrimination learning, reversal, and choice in goldfish (Carassius auratus). GoFish facilitates the automation of high-throughput protocols and the acquisition of rich behavioural data. Our platform has the potential to become a widely used tool that facilitates complex behavioural experiments in aquatic species., (© 2023. The Author(s).)

Signals that reduce uncertainty can be valuable because well-informed decision-makers can better align their preferences to opportunities. However, some birds and mammals display an appetite for informative signals that cannot be used to increase returns. We explore the role that reward-predictive stimuli have in fostering such preferences, aiming at distinguishing between two putative underlying mechanisms. The 'information hypothesis' proposes that reducing uncertainty is reinforcing per se, somewhat consistently with the concept of curiosity: a motivation to know in the absence of tractable extrinsic benefits. In contrast, the 'conditioned reinforcement hypothesis', an associative account, proposes asymmetries in secondarily acquired reinforcement: post-choice stimuli announcing forthcoming rewards (S + ) reinforce responses more than stimuli signalling no rewards (S - ) inhibit responses. In three treatments, rats faced two equally profitable options delivering food probabilistically after a fixed delay. In the informative option (Info), food or no food was signalled immediately after choice, whereas in the non-informative option (NoInfo) outcomes were uncertain until the delay lapsed. Subjects preferred Info when (1) both outcomes were explicitly signalled by salient auditory cues, (2) only forthcoming food delivery was explicitly signalled, and (3) only the absence of forthcoming reward was explicitly signalled. Acquisition was slower in (3), when food was not explicitly signalled, showing that signals for positive outcomes have a greater influence on the development of preference than signals for negative ones. Our results are consistent with an elaborated conditioned reinforcement account, and with the conjecture that both uncertainty reduction and conditioned reinforcement jointly act to generate preference., (© 2022. The Author(s).)