ASICs Mediate Food Responses in an Enteric Serotonergic Neuron that Controls Foraging Behaviors.

Animals must respond to the ingestion of food by generating adaptive behaviors, but the role of gut-brain signaling in behavioral regulation is poorly understood. Here, we identify conserved ion channels in an enteric serotonergic neuron that mediate its responses to food ingestion and decipher how these responses drive changes in foraging behavior. We show that the C. elegans serotonergic neuron NSM acts as an enteric sensory neuron that acutely detects food ingestion. We identify the novel and conserved acid-sensing ion channels (ASICs) DEL-7 and DEL-3 as NSM-enriched channels required for feeding-dependent NSM activity, which in turn drives slow locomotion while animals feed. Point mutations that alter the DEL-7 channel change NSM dynamics and associated behavioral dynamics of the organism. This study provides causal links between food ingestion, molecular and physiological properties of an enteric serotonergic neuron, and adaptive feeding behaviors, yielding a new view of how enteric neurons control behavior.

The Neuropeptide Corazonin Controls Social Behavior and Caste Identity in Ants.

Social insects are emerging models to study how gene regulation affects behavior because their colonies comprise individuals with the same genomes but greatly different behavioral repertoires. To investigate the molecular mechanisms that activate distinct behaviors in different castes, we exploit a natural behavioral plasticity in Harpegnathos saltator, where adult workers can transition to a reproductive, queen-like state called gamergate. Analysis of brain transcriptomes during the transition reveals that corazonin, a neuropeptide homologous to the vertebrate gonadotropin-releasing hormone, is downregulated as workers become gamergates. Corazonin is also preferentially expressed in workers and/or foragers from other social insect species. Injection of corazonin in transitioning Harpegnathos individuals suppresses expression of vitellogenin in the brain and stimulates worker-like hunting behaviors, while inhibiting gamergate behaviors, such as dueling and egg deposition. We propose that corazonin is a central regulator of caste identity and behavior in social insects.

Epigenetic Regulator CoREST Controls Social Behavior in Ants.

Ants acquire distinct morphological and behavioral phenotypes arising from a common genome, underscoring the importance of epigenetic regulation. In Camponotus floridanus, "Major" workers defend the colony, but can be epigenetically reprogrammed to forage for food analogously to "Minor" workers. Here, we utilize reprogramming to investigate natural behavioral specification. Reprogramming of Majors upregulates Minor-biased genes and downregulates Major-biased genes, engaging molecular pathways fundamental to foraging behavior. We discover the neuronal corepressor for element-1-silencing transcription factor (CoREST) is upregulated upon reprogramming and required for the epigenetic switch to foraging. Genome-wide profiling during reprogramming reveals CoREST represses expression of enzymes that degrade juvenile hormone (JH), a hormone elevated upon reprogramming. High CoREST, low JH-degrader expression, and high JH levels are mirrored in natural Minors, revealing parallel mechanisms of natural and reprogrammed foraging. These results unveil chromatin regulation via CoREST as central to programming of ant social behavior, with potential far-reaching implications for behavioral epigenetics.

Muscle-derived Dpp regulates feeding initiation via endocrine modulation of brain dopamine biosynthesis.

In animals, the brain regulates feeding behavior in response to local energy demands of peripheral tissues, which secrete orexigenic and anorexigenic hormones. Although skeletal muscle is a key peripheral tissue, it remains unknown whether muscle-secreted hormones regulate feeding. In Drosophila, we found that decapentaplegic (dpp), the homolog of human bone morphogenetic proteins BMP2 and BMP4, is a muscle-secreted factor (a myokine) that is induced by nutrient sensing and that circulates and signals to the brain. Muscle-restricted dpp RNAi promotes foraging and feeding initiation, whereas dpp overexpression reduces it. This regulation of feeding by muscle-derived Dpp stems from modulation of brain tyrosine hydroxylase (TH) expression and dopamine biosynthesis. Consistently, Dpp receptor signaling in dopaminergic neurons regulates TH expression and feeding initiation via the downstream transcriptional repressor Schnurri. Moreover, pharmacologic modulation of TH activity rescues the changes in feeding initiation due to modulation of dpp expression in muscle. These findings indicate that muscle-to-brain endocrine signaling mediated by the myokine Dpp regulates feeding behavior.

The foraging Gene and Its Behavioral Effects: Pleiotropy and Plasticity.

The Drosophila melanogaster foraging (for) gene is a well-established example of a gene with major effects on behavior and natural variation. This gene is best known for underlying the behavioral strategies of rover and sitter foraging larvae, having been mapped and named for this phenotype. Nevertheless, in the last three decades an extensive array of studies describing for's role as a modifier of behavior in a wide range of phenotypes, in both Drosophila and other organisms, has emerged. Furthermore, recent work reveals new insights into the genetic and molecular underpinnings of how for affects these phenotypes. In this article, we discuss the history of the for gene and its role in natural variation in behavior, plasticity, and behavioral pleiotropy, with special attention to recent findings on the molecular structure and transcriptional regulation of this gene.

Smart active particles learn and transcend bacterial foraging strategies.

Throughout evolution, bacteria and other microorganisms have learned efficient foraging strategies that exploit characteristic properties of their unknown environment. While much research has been devoted to the exploration of statistical models describing the dynamics of foraging bacteria and other (micro-) organisms, little is known, regarding the question of how good the learned strategies actually are. This knowledge gap is largely caused by the absence of methods allowing to systematically develop alternative foraging strategies to compare with. In the present work, we use deep reinforcement learning to show that a smart run-and-tumble agent, which strives to find nutrients for its survival, learns motion patterns that are remarkably similar to the trajectories of chemotactic bacteria. Strikingly, despite this similarity, we also find interesting differences between the learned tumble rate distribution and the one that is commonly assumed for the run and tumble model. We find that these differences equip the agent with significant advantages regarding its foraging and survival capabilities. Our results uncover a generic route to use deep reinforcement learning for discovering search and collection strategies that exploit characteristic but initially unknown features of the environment. These results can be used, e.g., to program future microswimmers, nanorobots, and smart active particles for tasks like searching for cancer cells, micro-waste collection, or environmental remediation.

Abundant resources can trigger reduced consumption: Unveiling the paradox of excessive scrounging.

In ecological contexts, it is conventionally expected that increased food availability would boost consumption, particularly when animals prioritize maximizing their food intake. This paper challenges this conventional wisdom by conducting an in-depth game-theoretic analysis of a basic foraging model, in which animals must choose between intensive food searching as producers or moderate searching while relying on group members as scroungers. Our study reveals that, under certain circumstances, increasing food availability can amplify the inclination to scrounge to such an extent that it leads to a reduction in animals' food consumption compared to scenarios with limited food availability. We further illustrate a similar phenomenon in a model capturing free-riding dynamics among workers in a company. We demonstrate that, under certain reward mechanisms, enhancing workers' production capacities can inadvertently trigger a surge in free-riding behavior, leading to both diminished group productivity and reduced individual payoffs. Our findings provide intriguing insights into the complex relationships between individual and group performances, as well as the intricate mechanisms underlying the emergence of free-riding behavior in competitive environments.

Brain mechanism of foraging: Reward-dependent synaptic plasticity versus neural integration of values.

During foraging behavior, action values are persistently encoded in neural activity and updated depending on the history of choice outcomes. What is the neural mechanism for action value maintenance and updating? Here, we explore two contrasting network models: synaptic learning of action value versus neural integration. We show that both models can reproduce extant experimental data, but they yield distinct predictions about the underlying biological neural circuits. In particular, the neural integrator model but not the synaptic model requires that reward signals are mediated by neural pools selective for action alternatives and their projections are aligned with linear attractor axes in the valuation system. We demonstrate experimentally observable neural dynamical signatures and feasible perturbations to differentiate the two contrasting scenarios, suggesting that the synaptic model is a more robust candidate mechanism. Overall, this work provides a modeling framework to guide future experimental research on probabilistic foraging.

The evolution of early hominin food production and sharing.

How did humans evolve from individualistic to collective foraging with sex differences in production and widespread sharing of plant and animal foods? While current evolutionary scenarios focus on meat, cooking, or grandparental subsidies, considerations of the economics of foraging for extracted plant foods (e.g., roots, tubers), inferred to be important for early hominins (∼6 to 2.5 mya), suggest that early hominins shared such foods with offspring and others. Here, we present a conceptual and mathematical model of early hominin food production and sharing, prior to the emergence of frequent hunting, cooking, and increased lifespan. We hypothesize that extracted plant foods were vulnerable to theft, and that male mate guarding protected females from food theft. We identify conditions favoring extractive foraging and food sharing across mating systems (i.e., monogamy, polygyny, promiscuity), and we assess which system maximizes female fitness with changes in the profitability of extractive foraging. Females extract foods and share them with males only when: i) extracting rather than collecting plant foods pays off energetically; and ii) males guard females. Males extract foods when they are sufficiently high in value, but share with females only under promiscuous mating and/or no mate guarding. These results suggest that if early hominins had mating systems with pair-bonds (monogamous or polygynous), then food sharing by adult females with unrelated adult males occurred before hunting, cooking, and extensive grandparenting. Such cooperation may have enabled early hominins to expand into more open, seasonal habitats, and provided a foundation for the subsequent evolution of human life histories.

Overharvesting in human patch foraging reflects rational structure learning and adaptive planning.

Patch foraging presents a sequential decision-making problem widely studied across organisms-stay with a current option or leave it in search of a better alternative? Behavioral ecology has identified an optimal strategy for these decisions, but, across species, foragers systematically deviate from it, staying too long with an option or "overharvesting" relative to this optimum. Despite the ubiquity of this behavior, the mechanism underlying it remains unclear and an object of extensive investigation. Here, we address this gap by approaching foraging as both a decision-making and learning problem. Specifically, we propose a model in which foragers 1) rationally infer the structure of their environment and 2) use their uncertainty over the inferred structure representation to adaptively discount future rewards. We find that overharvesting can emerge from this rational statistical inference and uncertainty adaptation process. In a patch-leaving task, we show that human participants adapt their foraging to the richness and dynamics of the environment in ways consistent with our model. These findings suggest that definitions of optimal foraging could be extended by considering how foragers reduce and adapt to uncertainty over representations of their environment.

Foraging synchrony drives resilience in human-dolphin mutualism.

Interactions between humans and nature have profound consequences, which rarely are mutually beneficial. Further, behavioral and environmental changes can turn human-wildlife cooperative interactions into conflicts, threatening their continued existence. By tracking fine-scale behavioral interactions between artisanal fishers and wild dolphins targeting migratory mullets, we reveal that foraging synchrony is key to benefiting both predators. Dolphins herd mullet schools toward the coast, increasing prey availability within the reach of the net-casting fishers, who gain higher foraging success-but only when matching the casting behavior with the dolphins' foraging cues. In turn, when dolphins approach the fishers' nets closely and cue fishers in, they dive for longer and modify their active foraging echolocation to match the time it takes for nets to sink and close over mullets-but only when fishers respond to their foraging cues appropriately. Using long-term demographic surveys, we show that cooperative foraging generates socioeconomic benefits for net-casting fishers and ca. 13% survival benefits for cooperative dolphins by minimizing spatial overlap with bycatch-prone fisheries. However, recent declines in mullet availability are threatening these short- and long-term benefits by reducing the foraging success of net-casting fishers and increasing the exposure of dolphins to bycatch in the alternative fisheries. Using a numerical model parametrized with our empirical data, we predict that environmental and behavioral changes are pushing this traditional human-dolphin cooperation toward extinction. We propose two possible conservation actions targeting fishers' behavior that could prevent the erosion of this century-old fishery, thereby safeguarding one of the last remaining cases of human-wildlife cooperation.

Reward expectations direct learning and drive operant matching in Drosophila.

Foraging animals must use decision-making strategies that dynamically adapt to the changing availability of rewards in the environment. A wide diversity of animals do this by distributing their choices in proportion to the rewards received from each option, Herrnstein's operant matching law. Theoretical work suggests an elegant mechanistic explanation for this ubiquitous behavior, as operant matching follows automatically from simple synaptic plasticity rules acting within behaviorally relevant neural circuits. However, no past work has mapped operant matching onto plasticity mechanisms in the brain, leaving the biological relevance of the theory unclear. Here, we discovered operant matching in Drosophila and showed that it requires synaptic plasticity that acts in the mushroom body and incorporates the expectation of reward. We began by developing a dynamic foraging paradigm to measure choices from individual flies as they learn to associate odor cues with probabilistic rewards. We then built a model of the fly mushroom body to explain each fly's sequential choice behavior using a family of biologically realistic synaptic plasticity rules. As predicted by past theoretical work, we found that synaptic plasticity rules could explain fly matching behavior by incorporating stimulus expectations, reward expectations, or both. However, by optogenetically bypassing the representation of reward expectation, we abolished matching behavior and showed that the plasticity rule must specifically incorporate reward expectations. Altogether, these results reveal the first synapse-level mechanisms of operant matching and provide compelling evidence for the role of reward expectation signals in the fly brain.

Neural evidence of switch processes during semantic and phonetic foraging in human memory.

Humans may retrieve words from memory by exploring and exploiting in "semantic space" similar to how nonhuman animals forage for resources in physical space. This has been studied using the verbal fluency test (VFT), in which participants generate words belonging to a semantic or phonetic category in a limited time. People produce bursts of related items during VFT, referred to as "clustering" and "switching." The strategic foraging model posits that cognitive search behavior is guided by a monitoring process which detects relevant declines in performance and then triggers the searcher to seek a new patch or cluster in memory after the current patch has been depleted. An alternative body of research proposes that this behavior can be explained by an undirected rather than strategic search process, such as random walks with or without random jumps to new parts of semantic space. This study contributes to this theoretical debate by testing for neural evidence of strategically timed switches during memory search. Thirty participants performed category and letter VFT during functional MRI. Responses were classified as cluster or switch events based on computational metrics of similarity and participant evaluations. Results showed greater hippocampal and posterior cerebellar activation during switching than clustering, even while controlling for interresponse times and linguistic distance. Furthermore, these regions exhibited ramping activity which increased during within-patch search leading up to switches. Findings support the strategic foraging model, clarifying how neural switch processes may guide memory search in a manner akin to foraging in patchy spatial environments.

Effort Foraging Task reveals positive correlation between individual differences in the cost of cognitive and physical effort in humans.

Effort-based decisions, in which people weigh potential future rewards against effort costs required to achieve those rewards involve both cognitive and physical effort, though the mechanistic relationship between them is not yet understood. Here, we use an individual differences approach to isolate and measure the computational processes underlying effort-based decisions and test the association between cognitive and physical domains. Patch foraging is an ecologically valid reward rate maximization problem with well-developed theoretical tools. We developed the Effort Foraging Task, which embedded cognitive or physical effort into patch foraging, to quantify the cost of both cognitive and physical effort indirectly, by their effects on foraging choices. Participants chose between harvesting a depleting patch, or traveling to a new patch that was costly in time and effort. Participants' exit thresholds (reflecting the reward they expected to receive by harvesting when they chose to travel to a new patch) were sensitive to cognitive and physical effort demands, allowing us to quantify the perceived effort cost in monetary terms. The indirect sequential choice style revealed effort-seeking behavior in a minority of participants (preferring high over low effort) that has apparently been missed by many previous approaches. Individual differences in cognitive and physical effort costs were positively correlated, suggesting that these are perceived and processed in common. We used canonical correlation analysis to probe the relationship of task measures to self-reported affect and motivation, and found correlations of cognitive effort with anxiety, cognitive function, behavioral activation, and self-efficacy, but no similar correlations with physical effort.

Ventral Pallidum and Amygdala Cooperate to Restrain Reward Approach under Threat.

Foraging decisions involve assessing potential risks and prioritizing food sources, which can be challenging when confronted with changing and conflicting circumstances. A crucial aspect of this decision-making process is the ability to actively overcome defensive reactions to threats and focus on achieving specific goals. The ventral pallidum (VP) and basolateral amygdala (BLA) are two brain regions that play key roles in regulating behavior motivated by either rewards or threats. However, it is unclear whether these regions are necessary in decision-making processes involving competing motivational drives during conflict. Our aim was to investigate the requirements of the VP and BLA for foraging choices in conflicts involving overcoming defensive responses. Here, we used a novel foraging task and pharmacological techniques to inactivate either the VP or BLA or to disconnect these brain regions before conducting a conflict test in male rats. Our findings showed that BLA is necessary for making risky choices during conflicts, whereas VP is necessary for invigorating the drive to obtain food, regardless of the presence of conflict. Importantly, our research revealed that the connection between VP and BLA is critical in controlling risky food-seeking choices during conflict situations. This study provides a new perspective on the collaborative function of VP and BLA in driving behavior, aimed at achieving goals in the face of dangers.

Insectivorous bats form mobile sensory networks to optimize prey localization: The case of the common noctule bat.

Animals that depend on ephemeral, patchily distributed prey often use public information to locate resource patches. The use of public information can lead to the aggregation of foragers at prey patches, a mechanism known as local enhancement. However, when ephemeral resources are distributed over large areas, foragers may also need to increase search efficiency, and thus apply social strategies when sampling the landscape. While sensory networks of visually oriented animals have already been confirmed, we lack an understanding of how acoustic eavesdropping adds to the formation of sensory networks. Here we radio-tracked a total of 81 aerial-hawking bats at very high spatiotemporal resolution during five sessions over 3 y, recording up to 19 individuals simultaneously. Analyses of interactive flight behavior provide conclusive evidence that bats form temporary mobile sensory networks by adjusting their movements to neighboring conspecifics while probing the airspace for prey. Complementary agent-based simulations confirmed that the observed movement patterns can lead to the formation of mobile sensory networks, and that bats located prey faster when networking than when relying only on local enhancement or searching solitarily. However, the benefit of networking diminished with decreasing group size. The combination of empirical analyses and simulations elucidates how animal groups use acoustic information to efficiently locate unpredictable and ephemeral food patches. Our results highlight that declining local populations of social foragers may thus suffer from Allee effects that increase the risk of collapses under global change scenarios, like insect decline and habitat degradation.

A reinforcement-based mechanism for discontinuous learning.

Problem-solving and reasoning involve mental exploration and navigation in sparse relational spaces. A physical analogue is spatial navigation in structured environments such as a network of burrows. Recent experiments with mice navigating a labyrinth show a sharp discontinuity during learning, corresponding to a distinct moment of "sudden insight" when mice figure out long, direct paths to the goal. This discontinuity is seemingly at odds with reinforcement learning (RL), which involves a gradual build-up of a value signal during learning. Here, we show that biologically plausible RL rules combined with persistent exploration generically exhibit discontinuous learning. In tree-like structured environments, positive feedback from learning on behavior generates a "reinforcement wave" with a steep profile. The discontinuity occurs when the wave reaches the starting point. By examining the nonlinear dynamics of reinforcement propagation, we establish a quantitative relationship between the learning rule, the agent's exploration biases, and learning speed. Predictions explain existing data and motivate specific experiments to isolate the phenomenon. Additionally, we characterize the exact learning dynamics of various RL rules for a complex sequential task.

The generality of cryptic dietary niche differences in diverse large-herbivore assemblages.

Ecological niche differences are necessary for stable species coexistence but are often difficult to discern. Models of dietary niche differentiation in large mammalian herbivores invoke the quality, quantity, and spatiotemporal distribution of plant tissues and growth forms but are agnostic toward food plant species identity. Empirical support for these models is variable, suggesting that additional mechanisms of resource partitioning may be important in sustaining large-herbivore diversity in African savannas. We used DNA metabarcoding to conduct a taxonomically explicit analysis of large-herbivore diets across southeastern Africa, analyzing ∼4,000 fecal samples of 30 species from 10 sites in seven countries over 6 y. We detected 893 food plant taxa from 124 families, but just two families-grasses and legumes-accounted for the majority of herbivore diets. Nonetheless, herbivore species almost invariably partitioned food plant taxa; diet composition differed significantly in 97% of pairwise comparisons between sympatric species, and dissimilarity was pronounced even between the strictest grazers (grass eaters), strictest browsers (nongrass eaters), and closest relatives at each site. Niche differentiation was weakest in an ecosystem recovering from catastrophic defaunation, indicating that food plant partitioning is driven by species interactions, and was stronger at low rainfall, as expected if interspecific competition is a predominant driver. Diets differed more between browsers than grazers, which predictably shaped community organization: Grazer-dominated trophic networks had higher nestedness and lower modularity. That dietary differentiation is structured along taxonomic lines complements prior work on how herbivores partition plant parts and patches and suggests that common mechanisms govern herbivore coexistence and community assembly in savannas.

Linking pollen limitation and seed dispersal effectiveness.

Seed production and dispersal are crucial ecological processes impacting plant demography, species distributions and community assembly. Plant-animal interactions commonly mediate both seed production and seed dispersal, but current research often examines pollination and seed dispersal separately, which hinders our understanding of how pollination services affect downstream dispersal services. To fill this gap, we propose a conceptual framework exploring how pollen limitation can impact the effectiveness of seed dispersal for endozoochorous and myrmecochorous plant species. We summarize the quantitative and qualitative effects of pollen limitation on plant reproduction and use Optimal Foraging Theory to predict its impact on the foraging behaviour of seed dispersers. In doing so, we offer a new framework that poses numerous hypotheses and empirical tests to investigate links between pollen limitation and seed dispersal effectiveness and, consequently, post-dispersal ecological processes occurring at different levels of biological organization. Finally, considering the importance of pollination and seed dispersal outcomes to plant eco-evolutionary dynamics, we discussed the implications of our framework for future studies exploring the demographic and evolutionary impacts of pollen limitation for animal-dispersed plants.

Nonrandom foraging and resource distributions affect the relationships between host density, contact rates and parasite transmission.

Nonrandom foraging can cause animals to aggregate in resource dense areas, increasing host density, contact rates and pathogen transmission, but when should nonrandom foraging and resource distributions also have density-independent effects? Here, we used a factorial experiment with constant resource and host densities to quantify host contact rates across seven resource distributions. We also used an agent-based model to compare pathogen transmission when host movement was based on random foraging, optimal foraging or something between those states. Nonrandom foraging strongly depressed contact rates and transmission relative to the classic random movement assumptions used in most epidemiological models. Given nonrandom foraging in the agent-based model and experiment, contact rates and transmission increased with resource aggregation and average distance to resource patches due to increased host movement in search of resources. Overall, we describe three density-independent mechanisms by which host behaviour and resource distributions alter contact rate functions and pathogen transmission.