Going Beyond the "Synthetic Method": New Paradigms Cross-Fertilizing Robotics and Cognitive Neuroscience

In so-called ethorobotics and robot-supported social cognitive neurosciences, robots are used as scientific tools to study animal behavior and cognition. Building on previous epistemological analyses of biorobotics, in this article it is argued that these two research fields, widely differing from one another in the kinds of robots involved and in the research questions addressed, share a common methodology, which significantly differs from the "synthetic method" that, until recently, dominated biorobotics. The methodological novelty of this strategy, the research opportunities that it opens, and the theoretical and technological challenges that it gives rise to, will be discussed with reference to the peculiarities of the two research fields. Some broad methodological issues related to the generalization of results concerning robot-animal interaction to theoretical conclusions on animal-animal interaction will be identified and discussed

Zebrafish Adjust Their Behavior in Response to an Interactive Robotic Predator

Zebrafish (Danio rerio) constitutes a valuable experimental species for the study of the biological determinants of emotional responses, such as fear and anxiety. Fear-related test paradigms traditionally entail the interaction between focal subjects and live predators, which may show inconsistent behavior throughout the experiment. To address this technical challenge, robotic stimuli are now frequently integrated in behavioral studies, yielding repeatable, customizable, and controllable experimental conditions. While most of the research has focused on open-loop control where robotic stimuli are preprogrammed to execute a priori known actions, recent work has explored the possibility of two-way interactions between robotic stimuli and live subjects. Here, we demonstrate a “closed-loop control” system to investigate fear response of zebrafish in which the response of the robotic stimulus is determined in real-time through a finite-state Markov chain constructed from independent observations on the interactions between zebrafish and their predator. Specifically, we designed a 3D-printed robotic replica of the zebrafish allopatric predator red tiger Oscar fish (Astronotus ocellatus), instrumented to interact in real-time with live subjects. We investigated the role of closed-loop control in modulating fear response in zebrafish through the analysis of the focal fish ethogram and the information-theoretic quantification of the interaction between the subject and the replica. Our results indicate that closed-loop control elicits consistent fear response in zebrafish and that zebrafish quickly adjust their behavior to avoid the predator's attacks. The augmented degree of interactivity afforded by the Markov-chain-dependent actuation of the replica constitutes a fundamental advancement in the study of animal-robot interactions and offers a new means for the development of experimental paradigms to study fear