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Journal ArticleDOI

Foraging across the life span: is there a reduction in exploration with aging?

17 Apr 2013-Frontiers in Neuroscience (Frontiers)-Vol. 7, pp 53-53
TL;DR: Overall, the evidence suggests that foraging behavior may undergo significant changes across the life span across internal and external search, and finds evidence of a trend toward reduced exploration with increased age.
Abstract: Does foraging change across the life span, and in particular, with aging? We report data from two foraging tasks used to investigate age differences in search in external environments as well as internal search in memory. Overall, the evidence suggests that foraging behavior may undergo significant changes across the life span across internal and external search. In particular, we find evidence of a trend towards reduced exploration with increased age. We discuss these findings in light of theories that postulate a link between aging and reductions in novelty seeking and exploratory behavior.

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Citations
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Journal ArticleDOI
TL;DR: A predictive model of search is built to disentangle the unique contributions of the three hypotheses of developmental differences and found robust and recoverable parameter estimates indicating that children generalize less and rely on directed exploration more than adults.
Abstract: How do children and adults differ in their search for rewards? We considered three different hypotheses that attribute developmental differences to (a) children’s increased random sampling, (b) mor...

64 citations

Journal ArticleDOI
TL;DR: A decision-theoretic outlook on the role of the human hippocampus, amygdala and prefrontal cortex in resolving approach–avoidance conflicts relevant for anxiety and integral for survival is provided.
Abstract: Jointly minimizing multiple threats over extended time horizons enhances survival. Consequently, many tests of approach-avoidance conflicts incorporate multiple threats for probing corollaries of animal and human anxiety. To facilitate computations necessary for threat minimization, the human brain may concurrently harness multiple decision policies and associated neural controllers, but it is unclear which. We combine a task that mimics foraging under predation with behavioural modelling and functional neuroimaging. Human choices rely on immediate predator probability-a myopic heuristic policy-and on the optimal policy, which integrates all relevant variables. Predator probability relates positively and the associated choice uncertainty relates negatively to activations in the anterior hippocampus, amygdala and dorsolateral prefrontal cortex. The optimal policy is positively associated with dorsomedial prefrontal cortex activity. We thus provide a decision-theoretic outlook on the role of the human hippocampus, amygdala and prefrontal cortex in resolving approach-avoidance conflicts relevant for anxiety and integral for survival.

37 citations

Journal ArticleDOI
TL;DR: Although intellectual engagement is a significant factor associated with adult cognitive health, it is unclear what it includes, why and how it declines across the lifespan, and importantly, whether it is reversible as discussed by the authors.
Abstract: Although intellectual engagement is a significant factor associated with adult cognitive health, it is unclear what it includes, why and how it declines across the lifespan, and importantly, whether i

33 citations

Journal ArticleDOI
TL;DR: This model proposes that novel objects encountered late in life will be perceived as being relatively rare, so the value of information from investigating their properties will be estimated to be low, and develops an exploration–exploitation (‘bandit’) model, in which agents must decide whether to explore or ignore a novel object that it has just encountered.

28 citations


Cites background from "Foraging across the life span: is t..."

  • ...Intuitively, one might expect that organisms are selected to engage in behaviours that help them gain information early in life (exploration) and then, having learned much of what is to be learned, switch to using this information late in life (exploitation) (see Mata et al., 2013)....

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Journal ArticleDOI
TL;DR: These findings highlight the utility of considering foraging-like problems when investigating the mechanisms of economic choice, and suggest that many animal decision-makers have difficulty making two-option choices, and use degenerate strategies evolved to solve foraging problems.
Abstract: The papers that accompany this Research Topic fall at the intersection of foraging theory and neuroscience. Why does such a topic merit a Research Topic in Frontiers in Decision Neuroscience? And what does foraging theory have to do with decision neuroscience? Foraging theory was created in the 1960's, as behavioral ecologists began to absorb the intellectual advances in microeconomic theory of the 1940's and 50's, and apply its principles to their research. Early foraging theorists realized that animals can be thought of as economic decision-makers that thrive by learning to maximize benefits and minimize costs. A key insight was that adaptive fitness—the main driving influence in Darwinian evolution—behaves mathematically like any other economic good, and that we can analyze behavior by assuming animals seek to maximize it (McNamara and Houston, 1986; Stephens and Krebs, 1986). While economics focuses on human problems, such selecting a brand of peanut butter or choosing a retirement plan, foraging theory focuses on animal problems. Early foraging theorists identified two major abstract problems: whether to accept or reject a prey item (the diet selection problem) and, when foraging in a prey-rich patch, when to leave it and move on to another one (the patch-leaving problem, Stephens and Krebs, 1986). Of course, these problems apply to humans as well, from the hunter-gatherer foraging for small animals to the internet surfer looking for interesting articles to pass the time. In the diet selection problem, an animal (e.g., a fox) must decide, on encountering a prey (e.g., a pheasant) whether to pursue it or pass it up (Krebs et al., 1977). Foraging theorists realized that animals should integrate the costs and benefits of pursuit (presumably learned through experience) into a single decision variable and then compare that to specific threshold (also learned). The realization that the optimal strategy is a step-function and the method for computing this threshold were major early discoveries. Importantly, the threshold is a “background variable” that represents the marginal intake rate associated with the overall environment. In economic terms, it is the opportunity cost of pursuit. This example illustrates three key features of foraging problems: (1) they are fundamentally optimization problems that can be solved through cost-benefit analyses, (2) they are modeled after problems encountered by animals, and (3) decisions are usually framed as a foreground (pursue) vs. background (ignore), rather than as two simultaneously presented alternatives as in standard economic tasks. Several scholars have suggested that foreground-background decisions, even if they are mathematically identical to two-option choices common in economics, are mediated by distinct mental operations (Stephens, 2002). Indeed, it has been suggested that many animal decision-makers have difficulty making two-option choices, and use degenerate strategies evolved to solve foraging problems (Pavlic and Passino, 2010; Kacelnik et al., 2011). Furthermore, there is evidence that human decision-making is framed in terms or a default and an alternative, and that values of these options may be associated with specific brain regions (Kolling et al., 2012; Boorman et al., 2013). These findings highlight the utility of considering foraging-like problems when investigating the mechanisms of economic choice. Indeed, results obtained in foraging conditions are often different from those obtained in economic tasks. For example, consider intertemporal choice tasks, in which animals choose between a large reward available after a long delay or a smaller reward available sooner. Animals typically reject the larger gains if the delay is more than a few seconds. This seemingly impulsive behavior has often been used to argue that most animal species discount future rewards heavily (Rachlin, 2000; Heilbronner et al., 2008; Kalenscher and Pennartz, 2008; Stevens and Stephens, 2008). Puzzlingly, however, in foraging tasks, animals discount only weakly or not at all (Stephens and Anderson, 2001; Hayden et al., 2011). Some scholars have suggested that the two-option structure of the standard intertemporal choice task is confusing for animals and that, because they misunderstand its structure, it produces highly biased estimates of discounting rates. In contrast, foraging tasks, with their naturally-inspired structure, do not (Bateson and Kacelnik, 1996; Kacelnik, 1997; Stephens, 2002; Pearson et al., 2010; Blanchard et al., 2013; Blanchard and Hayden, 2014). Another example comes in the context of risky choice. Foraging theory emphasizes the serial and long-term strategic nature of risky choice, and thus suggests that decisions ought to be studied not solely in terms of non-linear utility—in other words, the prospect of an immediate gain or loss multiplied by its likelihood—but in terms of discontinuities between short and long-term strategies (Hayden and Platt, 2007; Heilbronner and Hayden, 2013). Whereas, economic theory often categorically classifies organisms into those that are risk seeking or are risk-averse, studies that look at repeated choices with uncertain outcomes find that both humans and other animals can adapt their choice strategies depending on the state of the environment, their current needs, and their long-term goals (Real and Caraco, 1986; Kolling et al., 2014). Foraging theory's emphasis on adaptive significance allows us to consider each species within its own ecological niche. For instance, most nutrition a rodent will encounter is at ground level; danger will likely come from above. Rodent superior colliculus (SC) maps precisely this distinction, with visual input from the upper quadrant of the visual field accessing the medial SC, which mediates defense responses, whereas the lower quadrant projects more strongly to lateral SC, stimulation of which results in approach behaviors (Comoli et al., 2012). The manual dexterity and trichromatic binocular vision of primates, and ultimately potentially the development of the prefrontal cortex, can also be related to their need to forage for ripe fruit and tender leaves in a visually complex, cluttered, and volatile environment (Passingham and Wise, 2012). As we neuroscientists try to collate fine-grained research from fruit flies and zebra fish to genetically modified rodents and primates, such ecological considerations will become increasingly pressing. The papers included in this collection serve as an introduction to some of the major ideas that have influenced the nascent field of neural foraging. The most basic step in deriving a complete understanding of the neural basis of foraging is to understand the neural basis of the building blocks of foraging, food consumption, and executive control of decision-making. One goal is to make foraging theory more biological; whereas we assume that food consumption—often considered simply as “reward” in many neuroscience paradigms—is a “frictionless” process, it is in fact a very real and complex one. To understand it we must understand how it works (Caracheo et al., 2013; Horst and Laubach, 2013), and how it interacts with decision-making (Murray and Rudebeck, 2013). Simultaneously, foraging involves complex cognitive processes, and understanding how those work is critical for understanding the way that our minds constrains foraging decisions (Sallet et al., 2013). These include understanding of the neural representation of variables that are psychologically relevant to foraging decisions, like effort and risk (Miller et al., 2013), as well as social factors (Pearson et al., 2013). Traditional foraging theory tends to ignore factors that affect animal decisions like aging (Mata et al., 2013). Future work will also point toward linking economic ideas to foraging ideas, especially in the domain of time and risk (Bixter and Luhmann, 2013).

25 citations


Cites background from "Foraging across the life span: is t..."

  • ...Traditional foraging theory tends to ignore factors that affect animal decisions like aging (Mata et al., 2013)....

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References
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Book
01 Jan 1988
TL;DR: This book provides a clear and simple account of the key ideas and algorithms of reinforcement learning, which ranges from the history of the field's intellectual foundations to the most recent developments and applications.
Abstract: Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability. The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

37,989 citations


"Foraging across the life span: is t..." refers background in this paper

  • ...Exploration is an adaptive first step because it allows one to acquire information about the environment that will later lead to successful exploitation (Sutton and Barto, 1998)....

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Book ChapterDOI
TL;DR: The analysis of censored failure times is considered in this paper, where the hazard function is taken to be a function of the explanatory variables and unknown regression coefficients multiplied by an arbitrary and unknown function of time.
Abstract: The analysis of censored failure times is considered. It is assumed that on each individual arc available values of one or more explanatory variables. The hazard function (age-specific failure rate) is taken to be a function of the explanatory variables and unknown regression coefficients multiplied by an arbitrary and unknown function of time. A conditional likelihood is obtained, leading to inferences about the unknown regression coefficients. Some generalizations are outlined.

28,264 citations

Journal ArticleDOI
TL;DR: A theory is proposed that increased age in adulthood is associated with a decrease in the speed with which many processing operations can be executed and that this reduction in speed leads to impairments in cognitive functioning because of what are termed the limited time mechanism and the simultaneity mechanism.
Abstract: A theory is proposed to account for some of the age-related differences reported in measures of Type A or fluid cognition. The central hypothesis in the theory is that increased age in adulthood is associated with a decrease in the speed with which many processing operations can be executed and that this reduction in speed leads to impairments in cognitive functioning because of what are termed the limited time mechanism and the simultaneity mechanism. That is, cognitive performance is degraded when processing is slow because relevant operations cannot be successfully executed (limited time) and because the products of early processing may no longer be available when later processing is complete (simultaneity). Several types of evidence, such as the discovery of considerable shared age-related variance across various measures of speed and large attenuation of the age-related influences on cognitive measures after statistical control of measures of speed, are consistent with this theory.

5,094 citations


"Foraging across the life span: is t..." refers background in this paper

  • ...…times have been suggested to capture reliable individual differences in search (Dougherty and Harbison, 2007), any reaction-time based measure poses interpretational problems regarding exploratory tendencies with aging due to overall age differences in motor and cognitive speed (Salthouse, 1996)....

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Journal ArticleDOI
TL;DR: The present study used meta-analytic techniques to determine the patterns of mean-level change in personality traits across the life course and showed that people increase in measures of social dominance, conscientiousness, and emotional stability in young adulthood and decrease in both of these domains in old age.
Abstract: The present study used meta-analytic techniques (number of samples = 92) to determine the patterns of mean-level change in personality traits across the life course. Results showed that people increase in measures of social dominance (a facet of extraversion), conscientiousness, and emotional stability, especially in young adulthood (age 20 to 40). In contrast, people increase on measures of social vitality (a 2nd facet of extraversion) and openness in adolescence but then decrease in both of these domains in old age. Agreeableness changed only in old age. Of the 6 trait categories, 4 demonstrated significant change in middle and old age. Gender and attrition had minimal effects on change, whereas longer studies and studies based on younger cohorts showed greater change.

2,791 citations


"Foraging across the life span: is t..." refers background in this paper

  • ...Research on humans suggests that openness and novelty seeking declines over the life span as measured by self-report (Roberts et al., 2006; Lucas and Donnellan, 2011)....

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  • ...But what evidence is there of age differences in novelty seeking and exploratory behavior? Research on humans suggests that openness and novelty seeking declines over the life span as measured by self-report (Roberts et al., 2006; Lucas and Donnellan, 2011)....

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Posted Content
TL;DR: This article presented a psychometric scale that assesses risk taking in various content domains: financial decisions, health/safety, recreational, ethical, and social decisions, and found that respondents' degree of risk taking was highly domain-specific, i.e. not consistently risk-averse or consistently riskseeking across all content domains.
Abstract: We present a psychometric scale that assesses risk taking in five content domains: financial decisions (separately for investing versus gambling), health/safety, recreational, ethical, and social decisions. Respondents rate the likelihood that they would engage in domain-specific risky activities (Part I). An optional Part II assesses respondents’ perceptions of the magnitude of the risks and expected benefits of the activities judged in Part I. The scale’s construct validity and consistency is evaluated for a sample of American undergraduate students. As expected, respondents’ degree of risk taking was highly domain-specific, i.e. not consistently risk-averse or consistently risk-seeking across all content domains. Women appeared to be more risk-averse in all domains except social risk. A regression of risk taking (likelihood of engaging in the risky activity) on expected benefits and perceived risks suggests that gender and content domain differences in apparent risk taking are associated with differences in the perception of the activities’ benefits and risk, rather than with differences in attitude towards perceived risk.

2,340 citations


"Foraging across the life span: is t..." refers background in this paper

  • ...…= 99) completed a number of questionnaire measures that we reasoned could be related to exploratory behavior, including risk-taking in the investment and gambling domain (Weber et al., 2002), maximization tendencies (Schwartz et al., 2002), and future time perspective (Lang and Carstensen, 2002)....

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