Foraging In Patches Research Articles

Understanding explore-exploit dynamics in child development: current insights and future directions

Examining children's decisions to explore or exploit the environment provides a window into their developing metacognition and reflection capacities. Reinforcement learning, characterized by the balance between exploring new options (exploration) and utilizing known ones (exploitation), is central to this discussion. Children initially exhibit broad and intensive exploration, which gradually shifts toward exploitation as they grow. We review major theories and empirical findings, highlighting two main exploration strategies: random and directed. The former involves stochastic choices without considering information or rewards, while the latter is driven by reducing uncertainty for information gain. Behavioral tasks such as n-armed bandit, horizon, and patch foraging tasks are used to study these strategies. Findings on the n-armed bandit and horizon tasks showed mixed results on whether random exploration decreases over time. Directed exploration consistently decreases with age, but its emergence depends on task difficulty. In patch-foraging tasks, adults tend to overexploit (staying too long in one patch) and children overexplore (leaving too early), whereas adolescents display the most optimal balance. The paper also addresses open questions regarding the mechanisms supporting early exploration and the application of these strategies in real-life contexts like persistence. Future research should further investigate the relation between cognitive control, such as executive function and metacognition, and explore-exploit strategies, and examine their practical implications for adaptive learning and decision-making in children.

Major depression symptom severity associations with willingness to exert effort and patch foraging strategy.

Individuals with major depressive disorder (MDD) can experience reduced motivation and cognitive function, leading to challenges with goal-directed behavior. When selecting goals, people maximize 'expected value' by selecting actions that maximize potential reward while minimizing associated costs, including effort 'costs' and the opportunity cost of time. In MDD, differential weighing of costs and benefits are theorized mechanisms underlying changes in goal-directed cognition and may contribute to symptom heterogeneity. We used the Effort Foraging Task to quantify cognitive and physical effort costs, and patch leaving thresholds in low effort conditions (reflecting perceived opportunity cost of time) and investigated their shared versus distinct relationships to clinical features in participants with MDD (N=52, 43 in-episode) and comparisons (N=27). Contrary to our predictions, none of the decision-making measures differed with MDD diagnosis. However, each of the measures were related to symptom severity, over and above effects of ability (i.e., performance). Greater anxiety symptoms were selectively associated with lower cognitive effort cost (i.e. greater willingness to exert effort). Anhedonia and behavioral apathy were associated with increased physical effort costs. Finally, greater overall depression was related to decreased patch leaving thresholds. Markers of effort-based decision-making may inform understanding of MDD heterogeneity. Increased willingness to exert cognitive effort may contribute to anxiety symptoms such as worry. Decreased leaving thresholds associations with symptom severity is consistent with reward rate-based accounts of reduced vigor in MDD. Future research should address subtypes of depression with or without anxiety, which may relate differentially to cognitive effort decisions.

Competitive integration of time and reward explains value-sensitive foraging decisions and frontal cortex ramping dynamics.

Patch foraging presents a ubiquitous decision-making process in which animals decide when to abandon a resource patch of diminishing value to pursue an alternative. We developed a virtual foraging task in which mouse behavior varied systematically with patch value. Mouse behavior could be explained by a model integrating time and rewards antagonistically, scaled by a latent patience state. The model accounted for deviations from predictions of optimal foraging theory. Neural recordings throughout frontal areas revealed encoding of decision variables from the integrator model, most robustly in frontal cortex. Regression modeling followed by unsupervised clustering identified a subset of ramping neurons. These neurons' firing rates ramped up gradually (up to tens of seconds), were inhibited by rewards, and were better described as a continuous ramp than a discrete stepping process. Together, these results identify integration via frontal cortex ramping dynamics as a candidate mechanism for solving patch foraging problems.

Abundant resources compensate for the uneven distribution of ungulates in desert grassland.

Strategically managing livestock grazing in arid regions optimizes land use and reduces the damage caused by overgrazing. Controlled grazing preserves the grassland ecosystem and fosters sustainability despite resource limitations. However, uneven resource distribution can lead to diverse grazing patterns and land degradation, particularly in undulating terrains. In this study, we developed a herbivore foraging algorithm based on a resource selection function model to analyze foraging distribution patterns, predict the probability of foraging, and identify the determinants of foraging probability in cattle. The study area was a complex desert landscape encompassing dunes and interdunes. Data on cattle movements and resource distribution were collected and analyzed to model and predict foraging behavior. Our findings revealed that cattle prefer areas with abundant vegetation in proximity to water sources and avoid higher elevations. However, abundant resource availability mitigated these impacts and enhanced the role of water points, particularly during late grazing periods. The analysis showed that available resources primarily determine foraging distribution patterns and lessen the effects of landforms and water distance on patch foraging. The results suggest that thoughtful water source placement and the subdivision of pastures into areas with varied terrain are crucial for sustainable grazing management. By strategically managing these factors, land degradation can be minimized, and the ecological balance of grassland ecosystems can be maintained. Further research is needed to refine the model and explore its applicability in other arid regions.

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.

Understanding patch foraging strategies across development.

Patch foraging is a near-ubiquitous behaviour across the animal kingdom and characterises many decision-making domains encountered by humans. We review how a disposition to explore in adolescence may reflect the evolutionary conditions under which hunter-gatherers foraged for resources. We propose that neurocomputational mechanisms responsible for reward processing, learning, and cognitive control facilitate the transition from exploratory strategies in adolescence to exploitative strategies in adulthood - where individuals capitalise on known resources. This developmental transition may be disrupted by psychopathology, as there is emerging evidence of biases in explore/exploit choices in mental health problems. Explore/exploit choices may be an informative marker for mental health across development and future research should consider this feature of decision-making as a target for clinical intervention.

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.

Quitting while you're ahead: Patch foraging and temporal cognition.

Theoretical models of foraging are based on the maximization of food intake rate. Remarkably, foragers often hew close to the predictions of rate maximization, except for a frequently observed bias to remain in patches for too long. By sticking with depleting options beyond the optimal patch residence time-a phenomenon referred to as overharvesting or overstaying-foragers miss out on food they could have earned had they sought a new option elsewhere. Here, we review potential causes of overstaying and consider the role that temporal cognition might play in this phenomenon. We first consider how an explicit, internal sense of time might inform foraging behaviors, and next examine patch-leaving choices from the perspective of intertemporal decision-making. Finally, we identify promising areas for future research that will provide a better understanding of how foraging decisions are made, and what factors drive the tendency to overharvest patches. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Rat Anterior Cingulate Cortex Continuously Signals Decision Variables in a Patch Foraging Task.

In patch foraging tasks, animals must decide whether to remain with a depleting resource or to leave it in search of a potentially better source of reward. In such tasks, animals consistently follow the general predictions of optimal foraging theory (the marginal value theorem; MVT): to leave a patch when the reward rate in the current patch depletes to the average reward rate across patches. Prior studies implicate an important role for the anterior cingulate cortex (ACC) in foraging decisions based on MVT: within single trials, ACC activity increases immediately preceding foraging decisions, and across trials, these dynamics are modulated as the value of staying in the patch depletes to the average reward rate. Here, we test whether these activity patterns reflect dynamic encoding of decision-variables and whether these signals are directly involved in decision-making. We developed a leaky accumulator model based on the MVT that generates estimates of decision variables within and across trials, and tested model predictions against ACC activity recorded from male rats performing a patch foraging task. Model predicted changes in MVT decision variables closely matched rat ACC activity. Next, we pharmacologically inactivated ACC in male rats to test the contribution of these signals to decision-making. ACC inactivation had a profound effect on rats' foraging decisions and response times (RTs) yet rats still followed the MVT decision rule. These findings indicate that the ACC encodes foraging-related variables for reasons unrelated to patch-leaving decisions.SIGNIFICANCE STATEMENT The ability to make adaptive patch-foraging decisions, to remain with a depleting resource or search for better alternatives, is critical to animal well-being. Previous studies have found that anterior cingulate cortex (ACC) activity is modulated at different points in the foraging decision process, raising questions about whether the ACC guides ongoing decisions or serves a more general purpose of regulating cognitive control. To investigate the function of the ACC in foraging, the present study developed a dynamic model of behavior and neural activity, and tested model predictions using recordings and inactivation of ACC. Findings revealed that ACC continuously signals decision variables but that these signals are more likely used to monitor and regulate ongoing processes than to guide foraging decisions.

Stochastic dynamics of social patch foraging decisions.

Animals typically forage in groups. Social foraging can help animals avoid predation and decrease their uncertainty about the richness of food resources. Despite this, theoretical mechanistic models of patch foraging have overwhelmingly focused on the behavior of single foragers. In this study, we develop a mechanistic model that accounts for the behavior of individuals foraging together and departing food patches following an evidence accumulation process. Each individual’s belief about patch quality is represented by a stochastically accumulating variable, which is coupled to another’s belief to represent the transfer of information. We consider a cohesive group, and model information sharing by considering both intermittent pulsatile coupling (only communicate decision to leave) and continuous diffusive coupling (communicate throughout the deliberation process). Groups employing pulsatile coupling can obtain higher foraging efficiency, which depends more strongly on the coupling parameter compared to those using diffusive coupling. Conversely, groups using diffusive coupling are more robust to changes and heterogeneities in belief weighting and departure criteria. Efficiency is measured by a reward rate function that balances the amount of energy accumulated against the time spent in a patch, computed by solving an ordered first passage time problem for the patch departures of each individual. Using synthetic departure time data, we can distinguish between the two modes of communication and identify the model parameters. Our model establishes a social patch foraging framework to identify deliberative decision strategies and forms of social communication, and to allow model fitting to field data from foraging animal groups.

Delay discounting and under-valuing of recent information predict poorer adherence to social distancing measures during the COVID-19 pandemic

The COVID-19 pandemic has brought about unprecedented global changes in individual and collective behaviour. To reduce the spread of the virus, public health bodies have promoted social distancing measures while attempting to mitigate their mental health consequences. The current study aimed to identify cognitive predictors of social distancing adherence and mental health symptoms, using computational models derived from delay discounting (the preference for smaller, immediate rewards over larger, delayed rewards) and patch foraging (the ability to trade-off between exploiting a known resource and exploring an unknown one). In a representative sample of the UK population (N = 442), we find that steeper delay discounting predicted poorer adherence to social distancing measures and greater sensitivity to reward magnitude during delay discounting predicted higher levels of anxiety symptoms. Furthermore, under-valuing recently sampled information during foraging independently predicted greater violation of lockdown guidance. Our results suggest that those who show greater discounting of delayed rewards struggle to maintain social distancing. Further, those who adapt faster to new information are better equipped to change their behaviour in response to public health measures. These findings can inform interventions that seek to increase compliance with social distancing measures whilst minimising negative repercussions for mental health.

Are adolescents more optimal decision-makers in novel environments? Examining the benefits of heightened exploration in a patch foraging paradigm.

Adolescence is a period of heightened exploration relative to adulthood and childhood. This predisposition has been linked with negative behaviours related to risk-taking, including dangerous driving, substance misuse and risky sexual practices. However, recent models have argued that adolescents' heightened exploration serves a functional purpose within the lifespan, allowing adolescents to develop experiential knowledge of their surroundings. Yet, there is limited evidence that heightened exploration in adolescence is associated with positive outcomes. To address this, the present pre-registered study utilised a foraging paradigm with a sample of adolescents aged 16-17 (N=68) and of adults aged 21 and above (N=69). Participants completed a patch foraging task, which required them to choose between exploiting a known resource which gradually yields fewer rewards, and exploring a novel, unknown resource with a fresh distribution of rewards. Findings demonstrated that adolescents explored more than adults, which - in the context of the current task-represented more optimal patch foraging behaviour. These findings indicate that adolescents' heightened exploration can be beneficial, as they were able to effectively navigate unknown environments and accrue rewards more successfully than adults. This provides evidence that heightened exploration in adolescence, relative to adulthood, can lead to positive outcomes and contributes to our understanding of the role increased novelty-seeking plays at this point in the lifespan.

The trajectory of thought: Heavy-tailed distributions in memory foraging promote efficiency

Free-recall tasks suggest human memory foraging may follow a heavy-tailed distribution, such as a Lévy flight, patch foraging, or area-restricted search - walk procedures that are common in other activities of cognitive agents, such as food foraging in both animals and humans. To date, research merely equates memory foraging with hunting in the physical world based on similarities in statistical structure. The current work supports that memory foraging follows a heavy-tailed distribution by using categories with quantitative distances between each item: countries, which have physical distances, and animals, from which cognitive distances can be derived using a multidimensional scaling (MDS) procedure. Likewise, inter-item lag times follow a heavy-tailed distribution. The current work also demonstrates that inter-item distances and times are positively correlated, suggesting the organization of items in memory may be akin to the organization of a physical landscape. Finally, both studies show that participants' original, heavy-tailed lists of countries and animal names produce shorter overall distances traveled than random selection. Human memory foraging follows the same pattern as foraging in the natural world - perhaps because exposure to ecological settings informs our inner cognitive experience - leading to a processing and retrieval time benefit.

Behavioural responses to unexpected changes in reward quality

Successive negative contrast (SNC) effects are changes in anticipatory or consummatory behaviour when animals unexpectedly receive a lower value reward than they have received previously. SNC effects are often assumed to reflect frustration and appear to be influenced by background affective state. However, alternative explanations of SNC, such as the functional-search hypothesis, do not necessarily imply an aversive affective state. We tested 18 dogs in a SNC paradigm using a patch foraging task. Dogs were tested in two conditions, once with the low value reward in all of five trials (unshifted) and once when reward value was altered between high and low (shifted). Following a reward downshift, subjects showed a SNC effect by switching significantly more often between patches compared to the unshifted condition. However, approach latency, foraging time and quantity consumed did not differ between conditions, suggesting non-affective functional search behaviour rather than frustration. There was no relationship between strength of SNC and anxiety-related behaviours as measured in a novel object test and a personality questionnaire (C-BARQ). However, associations with the C-BARQ scores for Trainability and Stranger directed aggression suggest a possible link with behavioural flexibility and coping style. While reward quality clearly affects incentive motivation, the relationship between SNC, frustration and background affective state requires further exploration.

Unusual foraging patterns of the barn owl,Tyto alba(Strigiformes: Tytonidae), on small islets from the Pityusic archipelago (Western Mediterranean Sea)

Research on the diet of barn owls on some of the lesser Pityusic Islands (Formentera, s'Espalmador and s'Espartar) reveals a previously undescribed opportunistic trophic behaviour based on regular foraging in patches of territory separated by relatively broad sea channels. Individually, small islets with reduced human influence do not usually provide enough food for the barn owl. Consequently, the species expands its home range to include multiple islands or islets. This study is the first to document the regular crossing of broad sea channels (one of which exceeds 4.5 km) by barn owls in order to hunt. The islets provide the barn owls with prey otherwise considered as marginal (such as Oryctolagus cuniculus and Hydrobates pelagicus).

Forensic foraging of change detection in opponent strategies with a neural model of the interactions between temporal and prefrontal cortex

Abstract Change detection, and which information to attend to, are key research problems relevant to understanding adaptive behavior. Rational analyses of change detection have been developed in optimal foraging theory ( McNamara and Houston, 1987 , Stephens, 1987 ) and psychology ( Gallistel, Krishan, Liu, Miller, & Latham, 2014 ). Information foraging models ( Pirolli, 2007 ) have been developed to predict the optimal choice of information, and when to terminate collecting additional information. Optimal performance depend crucially on changing behavior when the world changes. For example, intelligence analysts track the dynamically changing strategies of adversaries and must choose information to weigh the utility of alternate actions regarding these agents. Neurobiologically-plausible descriptions of these behaviors have thus far been fragmentary (cf., Hayden, Pearson, & Platt, 2011 ). Here, behavioral and mechanistic differences in belief updating about an agent’s strategy, and information foraging choices were investigated in a variant of the patch foraging task. Human subjects typically displayed non-normative updating and information foraging decisions which influenced future belief updating and foraging behaviors. To explore the biological basis of these behaviors, a neural model which forages, processes, and updates the beliefs of competing hypotheses was created. Strategy updating and information foraging behaviors were modeled in the temporal and prefrontal cortices consistent with theories of human cognitive processing during adversarial game play. The neural model reproduced human behaviors observed in foraging, belief updating, and change detection. These results highlight the importance of updating strategy, foraging, and fatigue behaviors and provide a simulation framework for future studies to investigate other high-level cognitive behaviors.

Ratio‐ and Predator‐Dependent Functional Forms for Predators Optimally Foraging in Patches

Functional forms of predator-prey interactions are developed for predators optimally foraging on prey distributed in patches. The model uses mean free-path-length theory to develop functional forms for two idealized behaviors of prey in patches. For congregating prey that maintain a fixed density, for example, fish schools, the predation rate has a ratio-dependent form, and predator interference depends only on predator density. For sessile prey, which maintain a fixed patch size, a new predator-dependent form emerges in which predator interference depends on both prey and predator densities. The Beddington-DeAngelis equation is a special case of the sessile form. The model provides behavioral and biological criteria with which to select the functional form and ranges of coefficients appropriate for a particular food web. Finally, the model illustrates that behavior is an essential factor in predator-prey dynamics.

A guide to central place effects in foraging

We develop a general patch-use model of central place foraging, which subsumes and extends several previous models. The model produces a catalog of central place effects predicting how distance from a central place influences the costs and benefits of foraging, load-size, quitting harvest rates, and giving-up densities. In the model, we separate between costs that are load-size dependent, i.e. a direct effect of the size of the load, and load-size independent effects, such as correlations between distance and patch qualities. We also distinguish between predictions of between- and within-environment comparisons. Foraging costs, giving-up densities and quitting harvest rates should almost always increase with distance with these effects amplified by increases in metabolic costs, predation risk and load-costs. With respect to load-size: when comparing foraging in patches within an environment, we should often expect smaller loads to be taken from distant patches (negative distance–load correlation). However, when comparing between environments, there should be a positive correlation between average distance and load-size.

A simpler, more general method of finding the optimal foraging strategy for Bayesian birds

Oaten's (1977)stochastic model for optimal foraging in patches has been solved for a number of particular cases. A few cases, such as Poisson prey distribution and either systematic or random search, are easy to solve. In other cases, such as binomial prey distribution and random search, the form of the optimal strategy may be found using a theorem of McNamara, although more work is required to find which particular rule of the proper form is actually best. More generally (but not completely generally), optimal strategies may be found using dynamic programming. This requires that the number of prey found up to a particular time is a sufficient statistic for the number of prey remaining in a patch. This requirement cannot be dispensed with, but other simplifying assumptions that were used in the past are not necessary. In particular, it is not necessary, even for the sake of convenience, to assume that prey distribution has a form convenient for Bayesian analysis, such as a beta mixture of binomials or a gamma mixture of Poissons. Any prey distribution may be used if whatever prey are in a patch are located at random, and if search either is systematic for discrete time or for continuous time, or is random for continuous time. In earlier work, some pains had to be taken to find the rate of finding prey achieved by a given candidate strategy, but this is not necessary if expected gains and expected times are calculated routinely for each potential stopping point during dynamic programming. A new, simple method of finding optimal strategies is illustrated for discrete time and systematic search. This paper is based on a talk given at the Fifth Hans Kristiansson Symposium held in Lund, Sweden in August, 2003. The subject of the symposium was Bayesian foraging.

Substrate discrimination and preference in foraging fish

Increasing substrate structural complexity has been linked to higher densities of various refuge-seeking aquatic macroinvertebrates, many of which constitute major prey species in a variety of freshwater communities. We investigated (1) whether the three-spined stickleback, Gasterosteus aculeatus, a predator of such macroinvertebrates and an established model organism in studies of animal behaviour, is capable of discriminating between structurally complex and simple substrates, and (2) whether they show a substrate preference when foraging. Hunger-motivated sticklebacks presented with a choice of simple and complex substrate types preferentially foraged over complex substrates. This was seen when the prey density was equal on both substrate types, and when it was greater on the complex substrate. Where prey density was greater on the simple substrate, fish showed no preference for either. The preference for complex substrates existed in both the allocation of time spent foraging and in the direction and frequency of feeding strikes. No substrate preferences were seen in fish that were satiated, or when prey were absent from both substrates. This ruled out refuge as an explanation for the observed preference. We discuss the results in the context of the relative usefulness of substrate discrimination in effective patch foraging in fish.