A variable refractory period increases collective performance in noisy environments.

Synchronized oscillations are found in all living systems, from cellsto ecosystems and on varying time scales. A generic principlebehind the production of oscillations involves a delay in theresponse of one entity to stimulations from the others in the sys-tem. Communication among entities is required for the emergenceof synchronization, but its efficacy can be impaired by surroundingnoise. In the social spiderAnelosimus eximius, individuals coordi-nate their activity to catch large prey that are otherwise inaccessi-ble to solitary hunters. When hunting in groups, dozens of spidersmove rhythmically toward their prey by synchronizing movingand stopping phases. We proposed a mechanistic model imple-menting individual behavioral rules, all derived fromfield experi-ments, to elucidate the underlying principles of synchronization.We showed that the emergence of oscillations in spiders involvesa refractory state, the duration of which depends on the relativeintensity of prey versus conspecific signals. Thisflexible behaviorallows individuals to rapidly adapt to variations in their vibrationallandscapes. Exploring the model reveals that the benefits of syn-chronization resulting from improved accuracy in prey detectionand reduced latency to capture prey more than offset the cost ofthe delay associated with immobility phases. Overall, our studyshows that a refractory period whose duration is variable anddependent on information accessible to all entities in the systemcontributes to the emergence of self-organized oscillations innoisy environments. Ourfindings may inspire the design of artifi-cial systems requiring fast andflexible synchronization betweentheir components.

The short neuropeptide F regulates appetitive but not aversive responsiveness in a social insect.

The neuropeptide F (NPF) and its short version (sNPF) mediate food- and stress-related responses in solitary insects. In the honeybee, a social insect where food collection and defensive responses are socially regulated, only sNPF has an identified receptor. Here we increased artificially sNPF levels in honeybee foragers and studied the consequences of this manipulation in various forms of appetitive and aversive responsiveness. Increasing sNPF in partially fed bees turned them into the equivalent of starved animals, enhancing both their food consumption and responsiveness to appetitive gustatory and olfactory stimuli. Neural activity in the olfactory circuits of fed animals was reduced and could be rescued by sNPF treatment to the level of starved bees. In contrast, sNPF had no effect on responsiveness to nociceptive stimuli. Our results thus identify sNPF as a key modulator of hunger and food-related responses in bees, which are at the core of their foraging activities.

Fruit flies can learn non-elemental olfactory discriminations.

Associative learning allows animals to establish links between stimuli based on their concomitance. In the case of Pavlovian conditioning, a single stimulus A (the conditional stimulus, CS) is reinforced unambiguously with an unconditional stimulus (US) eliciting an innate response. This conditioning constitutes an 'elemental' association to elicit a learnt response from A+ without US presentation after learning. However, associative learning may involve a 'complex' CS composed of several components. In that case, the compound may predict a different outcome than the components taken separately, leading to ambiguity and requiring the animal to perform so-called non-elemental discrimination. Here, we focus on such a non-elemental task, the negative patterning (NP) problem, and provide the first evidence of NP solving in Drosophila. We show that Drosophila learn to discriminate a simple component (A or B) associated with electric shocks (+) from an odour mixture composed either partly (called 'feature-negative discrimination' A+ versus AB-) or entirely (called 'NP' A+B+ versus AB-) of the shock-associated components. Furthermore, we show that conditioning repetition results in a transition from an elemental to a configural representation of the mixture required to solve the NP task, highlighting the cognitive flexibility of Drosophila.

Inhibitory learning of phototaxis by honeybees in a passive-avoidance task.

Honeybees are a standard model for the study of appetitive learning and memory. Yet, fewer attempts have been performed to characterize aversive learning and memory in this insect and uncover its molecular underpinnings. Here, we took advantage of the positive phototactic behavior of bees kept away from the hive in a dark environment and established a passive-avoidance task in which they had to suppress positive phototaxis. Bees placed in a two-compartment box learned to inhibit spontaneous attraction to a compartment illuminated with blue light by associating and entering into that chamber with shock delivery. Inhibitory learning resulted in an avoidance memory that could be retrieved 24 h after training and that was specific to the punished blue light. The memory was mainly operant but involved a Pavlovian component linking the blue light and the shock. Coupling conditioning with transcriptional analyses in key areas of the brain showed that inhibitory learning of phototaxis leads to an up-regulation of the dopaminergic receptor gene Amdop1 in the calyces of the mushroom bodies, consistently with the role of dopamine signaling in different forms of aversive learning in insects. Our results thus introduce new perspectives for uncovering further cellular and molecular underpinnings of aversive learning and memory in bees. Overall, they represent an important step toward comparative learning studies between the appetitive and the aversive frameworks.

Scalable rules for coherent group motion in a gregarious vertebrate.

Individuals of gregarious species that initiate collective movement require mechanisms of cohesion in order to maintain advantages of group living. One fundamental question in the study of collective movement is what individual rules are employed when making movement decisions. Previous studies have revealed that group movements often depend on social interactions among individual members and specifically that collective decisions to move often follow a quorum-like response. However, these studies either did not quantify the response function at the individual scale (but rather tested hypotheses based on group-level behaviours), or they used a single group size and did not demonstrate which social stimuli influence the individual decision-making process. One challenge in the study of collective movement has been to discriminate between a common response to an external stimulus and the synchronization of behaviours resulting from social interactions. Here we discriminate between these two mechanisms by triggering the departure of one trained Merino sheep (Ovis aries) from groups containing one, three, five and seven naïve individuals. Each individual was thus exposed to various combinations of already-departed and non-departed individuals, depending on its rank of departure. To investigate which individual mechanisms are involved in maintaining group cohesion under conditions of leadership, we quantified the temporal dynamic of response at the individual scale. We found that individuals' decisions to move do not follow a quorum response but rather follow a rule based on a double mimetic effect: attraction to already-departed individuals and attraction to non-departed individuals. This rule is shown to be in agreement with an adaptive strategy that is inherently scalable as a function of group size.

Use of radio-tagging to map spatial organization and social interactions in insects.

Understanding of the organization of animal societies often requires knowledge of the identity of group members and their spatial location. We propose an original experimental design to track automatically the position of individuals using radio frequency identification technology (RFID). Ants equipped with passive transponders were detected by a reader mounted on a mobile arm moving across the nest surface. We developed an algorithm to accurately extract the positions of individuals moving in two dimensions. Our method was validated on synthetic test cases and then used for characterization of the spatial distribution of ants within nests. This approach provides an amenable system for monitoring large populations of individuals over long periods of time.