Animal foraging and the evolution of goal-directed cognition

Testing the convergent validity, domain generality, and temporal stability of selected measures of people's tendency to explore

Given the ubiquity of exploration in everyday life, researchers from many disciplines have developed methods to measure exploratory behaviour. There are therefore many ways to quantify and measure exploration. However, it remains unclear whether the different measures (i) have convergent validity relative to one another, (ii) capture a domain general tendency, and (iii) capture a tendency that is stable across time. In a sample of 678 participants, we found very little evidence of convergent validity for the behavioural measures (Hypothesis 1); most of the behavioural measures lacked sufficient convergent validity with one another or with the self-reports. In psychometric modelling analyses, we could not identify a good fitting model with an assumed general tendency to explore (Hypothesis 2); the best fitting model suggested that the different behavioural measures capture behaviours that are specific to the tasks. In a subsample of 254 participants who completed the study a second time, we found that the measures had stability across an 1 month timespan (Hypothesis 3). Therefore, although there were stable individual differences in how people approached each task across time, there was no generalizability across tasks, and drawing broad conclusions about exploratory behaviour from studies using these tasks may be problematic. The Stage 1 protocol for this Registered Report was accepted in principle on 2nd December 2022 https://doi.org/10.6084/m9.figshare.21717407.v1 . The protocol, as accepted by the journal, can be found at https://doi.org/10.17605/OSF.IO/64QJU .

forager: a Python package and web interface for modeling mental search

Analyzing data from the verbal fluency task (e.g., "name all the animals you can in a minute") is of interest to both memory researchers and clinicians due to its broader implications for memory search and retrieval. Recent work has proposed several computational models to examine nuanced differences in search behavior, which can provide insights into the mechanisms underlying memory search. A prominent account of memory search within the fluency task was proposed by Hills et al. (2012), where mental search is modeled after how animals forage for food in physical space. Despite the broad potential utility of these models to scientists and clinicians, there is currently no open-source program to apply and compare existing foraging models or clustering algorithms without extensive, often redundant programming. To remove this barrier to studying search patterns in the fluency task, we created forager, a Python package ( https://github.com/thelexiconlab/forager ) and web interface ( https://forager.research.bowdoin.edu/ ). forager provides multiple automated methods to designate clusters and switches within a fluency list, implements a novel set of computational models that can examine the influence of multiple lexical sources (semantic, phonological, and frequency) on memory search using semantic embeddings, and also enables researchers to evaluate relative model performance at the individual and group level. The package and web interface cater to users with various levels of programming experience. In this work, we introduce forager's basic functionality and use cases that demonstrate its utility with pre-existing behavioral and clinical data sets of the semantic fluency task.

The rising entropy of English in the attention economy

We present evidence that the word entropy of American English has been rising steadily since around 1900. We also find differences in word entropy between media categories, with short-form media such as news and magazines having higher entropy than long-form media, and social media feeds having higher entropy still. To explain these results we develop an ecological model of the attention economy that combines ideas from Zipf's law and information foraging. In this model, media consumers maximize information utility rate taking into account the costs of information search, while media producers adapt to technologies that reduce search costs, driving them to generate higher entropy content in increasingly shorter formats.

Divergent and Convergent Creativity Are Different Kinds of Foraging

According to accounts of neural reuse and embodied cognition, higher-level cognitive abilities recycle evolutionarily ancient mechanisms for perception and action. Here, building on these accounts, we investigate whether creativity builds on our capacity to forage in space ("creativity as strategic foraging"). We report systematic connections between specific forms of creative thinking-divergent and convergent-and corresponding strategies for searching in space. U.S. American adults completed two tasks designed to measure creativity. Before each creativity trial, participants completed an unrelated search of a city map. Between subjects, we manipulated the search pattern, with some participants seeking multiple, dispersed spatial locations and others repeatedly converging on the same location. Participants who searched divergently in space were better at divergent thinking but worse at convergent thinking; this pattern reversed for participants who had converged repeatedly on a single location. These results demonstrate a targeted link between foraging and creativity, thus advancing our understanding of the origins and mechanisms of high-level cognition.

C. elegans foraging as a model for understanding the neuronal basis of decision-making

Animals have evolved to seek, select, and exploit food sources in their environment. Collectively termed foraging, these ubiquitous behaviors are necessary for animal survival. As a foundation for understanding foraging, behavioral ecologists established early theoretical and mathematical frameworks which have been subsequently refined and supported by field and laboratory studies of foraging animals. These simple models sought to explain how animals decide which strategies to employ when locating food, what food items to consume, and when to explore the environment for new food sources. These foraging decisions involve integration of prior experience with multimodal sensory information about the animal's current environment and internal state. We suggest that the nematode Caenorhabditis elegans is well-suited for a high-resolution analysis of complex goal-oriented behaviors such as foraging. We focus our discussion on behavioral studies highlighting C. elegans foraging on bacteria and summarize what is known about the underlying neuronal and molecular pathways. Broadly, we suggest that this simple model system can provide a mechanistic understanding of decision-making and present additional avenues for advancing our understanding of complex behavioral processes.

From emotional signals to symbols

The quest for the origins of language is a diverse enterprise, where research from a variety of disciplines brings area-specific ideas and area-specific terminology to bear. This variety often results in misunderstandings and misconceptions about communication in various species. In the present paper, we argue for focus on emotional systems as the primary motivators for social signals in animals in general. This focus can help resolve discrepancies of interpretation among different areas of inquiry and can illuminate distinctions among different social signals as well as their phylogenetic origins in animals and especially in humans. We advocate, following Jaak Panksepp, a view wherein the Seeking System, the endogenous tendency to search and explore, is the most fundamental emotional motivation. The Seeking System forms the basis for flexible, voluntary, and exploratory control of motor systems and makes much of learning possible. The relative lack of vocal learning and expression in nonhuman primates contrasted with extensive vocal learning and expression in humans began, we propose, with the evolution in ancient hominins of a necessary foundation for the many subsequent capabilities required for language. That foundation was, according to the reasoning, naturally selected in the form of neurological connections between the Seeking System and mechanisms of glottal/phonatory control. The new connections allowed ancient hominins to develop flexible, endogenous vocal fitness signals produced at very high rates and including large numbers of discrete syllables, recombinable to form syllable combinations with many prosodic variations. The increasing sociality of hominins supported evolution of massive expansion in the utilization of these flexible vocal forms to allow development of words and sentences.

Intermittent Search, Not Strict Lévy Flight, Evolves under Relaxed Foraging Distribution Constraints

AbstractThe survival of an animal depends on its success as a forager, and understanding the adaptations that result in successful foraging strategies is an enduring endeavour of behavioral ecology. Random walks are one of the primary mathematical descriptions of foraging behavior. Power law distributions are often used to model random walks, as they can characterize a wide range of behaviors, including Lévy walks. Empirical evidence indicates the prevalence and efficiency of Lévy walks as a foraging strategy, and theoretical work suggests an evolutionary origin. However, previous evolutionary models have assumed a priori that move lengths are drawn from a power law or other families of distributions. Here, we remove this restriction with a model that allows for the evolution of any distribution. Instead of Lévy walks, our model unfailingly results in the evolution of intermittent search, a random walk composed of two disjoint modes-frequent localized walks and infrequent extensive moves-that consistently outcompeted Lévy walks. We also demonstrate that foraging using intermittent search may resemble a Lévy walk because of interactions with the resources within an environment. These extrinsically generated Lévy-like walks belie an underlying behavior and may explain the prevalence of Lévy walks reported in the literature.

The journey within: mental navigation as a novel framework for understanding psychotherapeutic transformation

BACKGROUND

Despite the demonstrated efficacy of psychotherapy, the precise mechanisms that drive therapeutic transformations have posed a challenge and still remain unresolved. Here, we suggest a potential solution to this problem by introducing a framework based on the concept of mental navigation. It refers to our ability to navigate our cognitive space of thoughts, ideas, concepts, and memories, similar to how we navigate physical space. We start by analyzing the neural, cognitive, and experiential constituents intrinsic to mental navigation. Subsequently, we posit that the metaphoric spatial language we employ to articulate introspective experiences (e.g., "unexplored territory" or "going in circles") serves as a robust marker of mental navigation.

METHODS

Using large text corpora, we compared the utilization of spatial language between transcripts of psychotherapy sessions (≈ 12 M. words), casual everyday conversations (≈ 12 M. words), and fictional dialogues in movies (≈ 14 M. words). We also examined 110 psychotherapy transcripts qualitatively to discern patterns and dynamics associated with mental navigation.

RESULTS

We found a notable increase in the utilization of spatial metaphors during psychotherapy compared to casual everyday dialogues (U = 192.0, p = .001, d = 0.549) and fictional conversations (U = 211, p < .001, d = 0.792). In turn, analyzing the usage of non-spatial metaphors, we did not find significant differences between the three datasets (H = 0.682, p = 0.710). The qualitative analysis highlighted specific examples of mental navigation at play.

CONCLUSION

Mental navigation might underlie the psychotherapy process and serve as a robust framework for understanding the transformative changes it brings about.

Exploration versus exploitation decisions in the human brain: A systematic review of functional neuroimaging and neuropsychological studies

Thoughts and actions are often driven by a decision to either explore new avenues with unknown outcomes, or to exploit known options with predictable outcomes. Yet, the neural mechanisms underlying this exploration-exploitation trade-off in humans remain poorly understood. This is attributable to variability in the operationalization of exploration and exploitation as psychological constructs, as well as the heterogeneity of experimental protocols and paradigms used to study these choice behaviours. To address this gap, here we present a comprehensive review of the literature to investigate the neural basis of explore-exploit decision-making in humans. We first conducted a systematic review of functional magnetic resonance imaging (fMRI) studies of exploration-versus exploitation-based decision-making in healthy adult humans during foraging, reinforcement learning, and information search. Eleven fMRI studies met inclusion criterion for this review. Adopting a network neuroscience framework, synthesis of the findings across these studies revealed that exploration-based choice was associated with the engagement of attentional, control, and salience networks. In contrast, exploitation-based choice was associated with engagement of default network brain regions. We interpret these results in the context of a network architecture that supports the flexible switching between externally and internally directed cognitive processes, necessary for adaptive, goal-directed behaviour. To further investigate potential neural mechanisms underlying the exploration-exploitation trade-off we next surveyed studies involving neurodevelopmental, neuropsychological, and neuropsychiatric disorders, as well as lifespan development, and neurodegenerative diseases. We observed striking differences in patterns of explore-exploit decision-making across these populations, again suggesting that these two decision-making modes are supported by independent neural circuits. Taken together, our review highlights the need for precision-mapping of the neural circuitry and behavioural correlates associated with exploration and exploitation in humans. Characterizing exploration versus exploitation decision-making biases may offer a novel, trans-diagnostic approach to assessment, surveillance, and intervention for cognitive decline and dysfunction in normal development and clinical populations.

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.

Exploratory preferences explain the human fascination for imaginary worlds in fictional stories

Imaginary worlds are present and often central in many of the most culturally successful modern narrative fictions, be it in novels (e.g., Harry Potter), movies (e.g., Star Wars), video games (e.g., The Legend of Zelda), graphic novels (e.g., One Piece) and TV series (e.g., Game of Thrones). We propose that imaginary worlds are popular because they activate exploratory preferences that evolved to help us navigate the real world and find new fitness-relevant information. Therefore, we hypothesize that the attraction to imaginary worlds is intrinsically linked to the desire to explore novel environments and that both are influenced by the same underlying factors. Notably, the inter-individual and cross-cultural variability of the preference for imaginary worlds should follow the inter-individual and cross-cultural variability of exploratory preferences (with the personality trait Openness-to-experience, age, sex, and ecological conditions). We test these predictions with both experimental and computational methods. For experimental tests, we run a pre-registered online experiment about movie preferences (N = 230). For computational tests, we leverage two large cultural datasets, namely the Internet Movie Database (N = 9424 movies) and the Movie Personality Dataset (N = 3.5 million participants), and use machine-learning algorithms (i.e., random forest and topic modeling). In all, consistent with how the human preference for spatial exploration adaptively varies, we provide empirical evidence that imaginary worlds appeal more to more explorative people, people higher in Openness-to-experience, younger individuals, males, and individuals living in more affluent environments. We discuss the implications of these findings for our understanding of the cultural evolution of narrative fiction and, more broadly, the evolution of human exploratory preferences.

Bayesian approximations to the theory of visual attention (TVA) in a foraging task

Foraging as a natural visual search for multiple targets has increasingly been studied in humans in recent years. Here, we aimed to model the differences in foraging strategies between feature and conjunction foraging tasks found by Á. Kristjánsson et al. Bundesen proposed the theory of visual attention (TVA) as a computational model of attentional function that divides the selection process into filtering and pigeonholing. The theory describes a mechanism by which the strength of sensory evidence serves to categorise elements. We combined these ideas to train augmented Naïve Bayesian classifiers using data from Á. Kristjánsson et al. as input. Specifically, we attempted to answer whether it is possible to predict how frequently observers switch between different target types during consecutive selections (switches) during feature and conjunction foraging using Bayesian classifiers. We formulated 11 new parameters that represent key sensory and bias information that could be used for each selection during the foraging task and tested them with multiple Bayesian models. Separate Bayesian networks were trained on feature and conjunction foraging data, and parameters that had no impact on the model's predictability were pruned away. We report high accuracy for switch prediction in both tasks from the classifiers, although the model for conjunction foraging was more accurate. We also report our Bayesian parameters in terms of their theoretical associations with TVA parameters, πj (denoting the pertinence value), and βi (denoting the decision-making bias).

Using Gaze for Behavioural Biometrics

A principled approach to the analysis of eye movements for behavioural biometrics is laid down. The approach grounds in foraging theory, which provides a sound basis to capture the uniqueness of individual eye movement behaviour. We propose a composite Ornstein-Uhlenbeck process for quantifying the exploration/exploitation signature characterising the foraging eye behaviour. The relevant parameters of the composite model, inferred from eye-tracking data via Bayesian analysis, are shown to yield a suitable feature set for biometric identification; the latter is eventually accomplished via a classical classification technique. A proof of concept of the method is provided by measuring its identification performance on a publicly available dataset. Data and code for reproducing the analyses are made available. Overall, we argue that the approach offers a fresh view on either the analyses of eye-tracking data and prospective applications in this field.

Visuospatial information foraging describes search behavior in learning latent environmental features

In the real world, making sequences of decisions to achieve goals often depends upon the ability to learn aspects of the environment that are not directly perceptible. Learning these so-called latent features requires seeking information about them. Prior efforts to study latent feature learning often used single decisions, used few features, and failed to distinguish between reward-seeking and information-seeking. To overcome this, we designed a task in which humans and monkeys made a series of choices to search for shapes hidden on a grid. On our task, the effects of reward and information outcomes from uncovering parts of shapes could be disentangled. Members of both species adeptly learned the shapes and preferred to select tiles expected to be informative earlier in trials than previously rewarding ones, searching a part of the grid until their outcomes dropped below the average information outcome-a pattern consistent with foraging behavior. In addition, how quickly humans learned the shapes was predicted by how well their choice sequences matched the foraging pattern, revealing an unexpected connection between foraging and learning. This adaptive search for information may underlie the ability in humans and monkeys to learn latent features to support goal-directed behavior in the long run.

A guide to area-restricted search: a foundational foraging behaviour

Area-restricted search is the capacity to change search effort adaptively in response to resource encounters or expectations, from directional exploration (global, extensive search) to focused exploitation (local, intensive search). This search pattern is used by numerous organisms, from worms and insects to humans, to find various targets, such as food, mates, nests, and other resources. Area-restricted search has been studied for at least 80 years by ecologists, and more recently in the neurological and psychological literature. In general, the conditions promoting this search pattern are: (1) clustered resources; (2) active search (e.g. not a sit-and-wait predator); (3) searcher memory for recent target encounters or expectations; and (4) searcher ignorance about the exact location of targets. Because area-restricted search adapts to resource encounters, the search can be performed at multiple spatial scales. Models and experiments have demonstrated that area-restricted search is superior to alternative search patterns that do not involve a memory of the exact location of the target, such as correlated random walks or Lévy walks/flights. Area-restricted search is triggered by sensory cues whereas concentrated search in the absence of sensory cues is associated with other forms of foraging. Some neural underpinnings of area-restricted search are probably shared across metazoans, suggesting a shared ancestry and a shared solution to a common ecological problem of finding clustered resources. Area-restricted search is also apparent in other domains, such as memory and visual search in humans, which may indicate an exaptation from spatial search to other forms of search. Here, we review these various aspects of area-restricted search, as well as how to identify it, and point to open questions.

Normal blindness: when we Look But Fail To See

Humans routinely miss important information that is 'right in front of our eyes', from overlooking typos in a paper to failing to see a cyclist in an intersection. Recent studies on these 'Looked But Failed To See' (LBFTS) errors point to a common mechanism underlying these failures, whether the missed item was an unexpected gorilla, the clearly defined target of a visual search, or that simple typo. We argue that normal blindness is the by-product of the limited-capacity prediction engine that is our visual system. The processes that evolved to allow us to move through the world with ease are virtually guaranteed to cause us to miss some significant stimuli, especially in important tasks like driving and medical image perception.

Developmental Dyslexia: Disorder or Specialization in Exploration?

We raise the new possibility that people diagnosed with developmental dyslexia (DD) are specialized in explorative cognitive search, and rather than having a neurocognitive disorder, play an essential role in human adaptation. Most DD research has studied educational difficulties, with theories framing differences in neurocognitive processes as deficits. However, people with DD are also often proposed to have certain strengths - particularly in realms like discovery, invention, and creativity - that deficit-centered theories cannot explain. We investigate whether these strengths reflect an underlying explorative specialization. We re-examine experimental studies in psychology and neuroscience using the framework of cognitive search, whereby many psychological processes involve a trade-off between exploration and exploitation. We report evidence of an explorative bias in DD-associated cognitive strategies. High DD prevalence and an attendant explorative bias across multiple areas of cognition suggest the existence of explorative specialization. An evolutionary perspective explains the combination of findings and challenges the view that individuals with DD have a disorder. In cooperating groups, individual specialization is favored when features that confer fitness benefits are functionally incompatible. Evidence for search specialization suggests that, as with some other social organisms, humans mediate the exploration-exploitation trade-off by specializing in complementary strategies. The existence of a system of collective cognitive search that emerges through collaboration would help to explain our species' exceptional adaptiveness. It also aligns with evidence for substantial variability during our evolutionary history and the notion that humans are adapted not to a particular habitat but to variability itself. Specialization creates interdependence and necessitates balancing complementary strategies. Reframing DD therefore underscores the urgency of changing certain cultural practices to ensure we do not inhibit adaptation. Key improvements would remove cultural barriers to exploration and nurture explorative learning in education, academia, and the workplace, as well as emphasize collaboration over competition. Specialization in complementary search abilities represents a meta-adaptation; through collaboration, this likely enables human groups (as a species and as cultural systems) to successfully adapt. Cultural change to support this system of collaborative search may therefore be essential in confronting the challenges humanity now faces.

Search Foraging Strategies of Migratory Raptors Under Different Environmental Conditions

Several studies have shown in different organisms how their movements can be fitted to different patterns to optimize search of food resources. According to abundance and availability of resources, different strategies will be optimal, such as Lévy and Brownian random search. We analyze the movement patterns of four species of migratory raptors with different degrees of ecological specialization in diet during the breeding and wintering periods to evaluate the differences according to species and season: the Egyptian Vulture, the Short-toed Snake Eagle, the Booted Eagle, and the Red Kite. From GPS locations, we obtained a set of segments and lengths that were analyzed to verify their fitting to the functions of Lévy and Brownian strategies. Egyptian Vulture’s trajectories fitted to both patterns during the breeding period, whereas during the wintering period most trajectories fitted a Brownian pattern. In the case of the Short-toed Eagle, fit was greater to a Lévy strategy throughout the year, while Booted Eagles and Red Kites exhibited a combination of search patterns. These differences could be accounted for different feeding strategies and environmental context over the annual cycle. In species with a specialized diet (i.e., Short-toed Eagle) the Lévy pattern would maximize the encounters with scarce and unpredictable resources, whereas for species with a broad trophic niche (i.e., Booted Eagle and Red Kite), movements could be adapted to exploit different resources according to their abundance. Scavengers like the Egyptian Vulture shift also between search strategies according to the distribution of carrion. Therefore, the analysis of food search patterns can be used as an indirect indicator to track changes in food availability across a broad range of environmental conditions. This is particularly important under the current context of global change which is largely expected to affect migratory species that spend their vital cycle in distant areas.

Strength of Belief Guides Information Foraging

Theories of how people value and search for information share the assumption that beliefs give rise to the perceived value of information. However, few studies have directly addressed the pre-search processes that influence information-foraging behavior. This experiment examined the influence of pre-search belief updating on the perceived value of information sources. A sample of college students completed a hypothesis-testing, medical-diagnosis task. The experiment used medical tests with equal objective informative value before unveiling a presenting symptom intended to alter the strength of belief in different disease hypotheses. The observed patterns of test selection suggest that changes in beliefs about disease hypotheses result in systematic and predictable changes in test preference-a notion we refer to as the principle of hypothesis-guided search. We also present a simulation of how pre-search processes (e.g., hypothesis generation and working memory capacity) and task variables (e.g., time pressure) influence subsequent information search.

Evolution of behavioural control from chordates to primates

This article outlines a hypothetical sequence of evolutionary innovations, along the lineage that produced humans, which extended behavioural control from simple feedback loops to sophisticated control of diverse species-typical actions. I begin with basic feedback mechanisms of ancient mobile animals and follow the major niche transitions from aquatic to terrestrial life, the retreat into nocturnality in early mammals, the transition to arboreal life and the return to diurnality. Along the way, I propose a sequence of elaboration and diversification of the behavioural repertoire and associated neuroanatomical substrates. This includes midbrain control of approach versus escape actions, telencephalic control of local versus long-range foraging, detection of affordances by the dorsal pallium, diversified control of nocturnal foraging in the mammalian neocortex and expansion of primate frontal, temporal and parietal cortex to support a wide variety of primate-specific behavioural strategies. The result is a proposed functional architecture consisting of parallel control systems, each dedicated to specifying the affordances for guiding particular species-typical actions, which compete against each other through a hierarchy of selection mechanisms. This article is part of the theme issue 'Systems neuroscience through the lens of evolutionary theory'.

Is the Mind a Network? Maps, Vehicles, and Skyhooks in Cognitive Network Science

Cognitive researchers often carve cognition up into structures and processes. Cognitive processes operate on structures, like vehicles driving over a map. Language alongside semantic and episodic memory are proposed to have structure, as are perceptual systems. Over these structures, processes operate to construct memory and solve problems by retrieving and manipulating information. Network science offers an approach to representing cognitive structures and has made tremendous inroads into understanding the nature of cognitive structure and process. But is the mind a network? If so, what kind? In this article, we briefly review the main metaphors, assumptions, and pitfalls prevalent in cognitive network science (maps and vehicles; one network/process to rule them all), highlight the need for new metaphors that elaborate on the map-and-vehicle framework (wormholes, skyhooks, and generators), and present open questions in studying the mind as a network (the challenge of capturing network change, what should the edges of cognitive networks be made of, and aggregated vs. individual-based networks). One critical lesson of this exercise is that the richness of the mind as network approach makes it a powerful tool in its own right; it has helped to make our assumptions more visible, generating new and fascinating questions, and enriching the prospects for future research. A second lesson is that the mind as a network-though useful-is incomplete. The mind is not a network, but it may contain them.

Simple Threshold Rules Solve Explore/Exploit Trade-offs in a Resource Accumulation Search Task

How, and how well, do people switch between exploration and exploitation to search for and accumulate resources? We study the decision processes underlying such exploration/exploitation trade-offs using a novel card selection task that captures the common situation of searching among multiple resources (e.g., jobs) that can be exploited without depleting. With experience, participants learn to switch appropriately between exploration and exploitation and approach optimal performance. We model participants' behavior on this task with random, threshold, and sampling strategies, and find that a linear decreasing threshold rule best fits participants' results. Further evidence that participants use decreasing threshold-based strategies comes from reaction time differences between exploration and exploitation; however, participants themselves report non-decreasing thresholds. Decreasing threshold strategies that "front-load" exploration and switch quickly to exploitation are particularly effective in resource accumulation tasks, in contrast to optimal stopping problems like the Secretary Problem requiring longer exploration.

Priming exploration across domains: does search in a spatial environment influence search in a cognitive environment?

Is there a general tendency to explore that connects search behaviour across different domains? Although the experimental evidence collected so far suggests an affirmative answer, this fundamental question about human behaviour remains open. A feasible way to test the domain-generality hypothesis is that of testing the so-called priming hypothesis: priming explorative behaviour in one domain should subsequently influence explorative behaviour in another domain. However, only a limited number of studies have experimentally tested this priming hypothesis, and the evidence is mixed. We tested the priming hypothesis in a registered report. We manipulated explorative behaviour in a spatial search task by randomly allocating people to search environments with resources that were either clustered together or dispersedly distributed. We hypothesized that, in a subsequent anagram task, participants who searched in clustered spatial environments would search for words in a more clustered way than participants who searched in the dispersed spatial environments. The pre-registered hypothesis was not supported. An equivalence test showed that the difference between conditions was smaller than the smallest effect size of interest (d = 0.36). Out of several exploratory analyses, we found only one inferential result in favour of priming. We discuss implications of these findings for the theory and propose future tests of the hypothesis.

Uncertainty drives deviations in normative foraging decision strategies

Nearly all animals forage to acquire energy for survival through efficient search and resource harvesting. Patch exploitation is a canonical foraging behaviour, but there is a need for more tractable and understandable mathematical models describing how foragers deal with uncertainty. To provide such a treatment, we develop a normative theory of patch foraging decisions, proposing mechanisms by which foraging behaviours emerge in the face of uncertainty. Our model foragers statistically and sequentially infer patch resource yields using Bayesian updating based on their resource encounter history. A decision to leave a patch is triggered when the certainty of the patch type or the estimated yield of the patch falls below a threshold. The time scale over which uncertainty in resource availability persists strongly impacts behavioural variables like patch residence times and decision rules determining patch departures. When patch depletion is slow, as in habitat selection, departures are characterized by a reduction of uncertainty, suggesting that the forager resides in a low-yielding patch. Uncertainty leads patch-exploiting foragers to overharvest (underharvest) patches with initially low (high) resource yields in comparison with predictions of the marginal value theorem. These results extend optimal foraging theory and motivate a variety of behavioural experiments investigating patch foraging behaviour.

Semantic memory: A review of methods, models, and current challenges

Adult semantic memory has been traditionally conceptualized as a relatively static memory system that consists of knowledge about the world, concepts, and symbols. Considerable work in the past few decades has challenged this static view of semantic memory, and instead proposed a more fluid and flexible system that is sensitive to context, task demands, and perceptual and sensorimotor information from the environment. This paper (1) reviews traditional and modern computational models of semantic memory, within the umbrella of network (free association-based), feature (property generation norms-based), and distributional semantic (natural language corpora-based) models, (2) discusses the contribution of these models to important debates in the literature regarding knowledge representation (localist vs. distributed representations) and learning (error-free/Hebbian learning vs. error-driven/predictive learning), and (3) evaluates how modern computational models (neural network, retrieval-based, and topic models) are revisiting the traditional "static" conceptualization of semantic memory and tackling important challenges in semantic modeling such as addressing temporal, contextual, and attentional influences, as well as incorporating grounding and compositionality into semantic representations. The review also identifies new challenges regarding the abundance and availability of data, the generalization of semantic models to other languages, and the role of social interaction and collaboration in language learning and development. The concluding section advocates the need for integrating representational accounts of semantic memory with process-based accounts of cognitive behavior, as well as the need for explicit comparisons of computational models to human baselines in semantic tasks to adequately assess their psychological plausibility as models of human semantic memory.

The exploration-exploitation trade-off in a foraging task is affected by mood-related arousal and valence

The exploration-exploitation trade-off shows conceptual, functional, and neural analogies with the persistence-flexibility trade-off. We investigated whether mood, which is known to modulate the persistence-flexibility balance, would similarly affect the exploration-exploitation trade-off in a foraging task. More specifically, we tested whether interindividual differences in foraging behavior can be predicted by mood-related arousal and valence. In 119 participants, we assessed mood-related interindividual differences in exploration-exploitation using a foraging task that included minimal task constraints to reduce paradigm-induced biases of individual control tendencies. We adopted the marginal value theorem as a model-based analysis approach, which approximates optimal foraging behavior by tackling the patch-leaving problem. To assess influences of mood on foraging, participants underwent either a positive or negative mood induction. Throughout the experiment, we assessed arousal and valence levels as predictors for explorative/exploitative behavior. Our mood manipulation affected participants' arousal and valence ratings as expected. Moreover, mood-related arousal was found to predict exploration while valence predicted exploitation, which only partly matched our expectations and thereby the proposed conceptual overlap with flexibility and persistence, respectively. The current study provides a first insight into how processes related to arousal and valence differentially modulate foraging behavior. Our results imply that the relationship between exploration-exploitation and flexibility-persistence is more complicated than the semantic overlap between these terms might suggest, thereby calling for further research on the functional, neural, and neurochemical underpinnings of both trade-offs.

Two variations and one similarity in memory functions deployed by mice and humans to support foraging

Assessing variations in cognitive function between humans and animals is vital for understanding the idiosyncrasies of human cognition and for refining animal models of human brain function and disease. We determined memory functions deployed by mice and humans to support foraging with a search task acting as a test battery. Mice searched for food from the top of poles within an open arena. Poles were divided into groups based on visual cues and baited according to different schedules. White and black poles were baited in alternate trials. Striped poles were never baited. The requirement of the task was to find all baits in each trial. Mice's foraging efficiency, defined as the number of poles visited before all baits were retrieved, improved with practice. Mice learnt to avoid visiting unbaited poles across trials (long-term memory) and revisits to poles within each trial (working memory). Humans tested with a virtual reality version of the task outperformed mice in foraging efficiency, working memory, and exploitation of the temporal pattern of rewards across trials. Moreover, humans, but not mice, reduced the number of possible movement sequences used to search the set of poles. For these measures, interspecies differences were maintained throughout the 3 weeks of testing. By contrast, long-term memory for never-rewarded poles was similar in mice and humans after the first week of testing. These results indicate that human cognitive functions relying on archaic brain structures may be adequately modelled in mice. Conversely, modelling in mice fluid skills likely to have developed specifically in primates requires caution.

Gazing at Social Interactions Between Foraging and Decision Theory

Finding the underlying principles of social attention in humans seems to be essential for the design of the interaction between natural and artificial agents. Here, we focus on the computational modeling of gaze dynamics as exhibited by humans when perceiving socially relevant multimodal information. The audio-visual landscape of social interactions is distilled into a number of multimodal patches that convey different social value, and we work under the general frame of foraging as a tradeoff between local patch exploitation and landscape exploration. We show that the spatio-temporal dynamics of gaze shifts can be parsimoniously described by Langevin-type stochastic differential equations triggering a decision equation over time. In particular, value-based patch choice and handling is reduced to a simple multi-alternative perceptual decision making that relies on a race-to-threshold between independent continuous-time perceptual evidence integrators, each integrator being associated with a patch.

Foraging behavior in visual search: A review of theoretical and mathematical models in humans and animals

Visual search (VS) is a fundamental task in daily life widely studied for over half a century. A variant of the classic paradigm-searching one target among distractors-requires the observer to look for several (undetermined) instances of a target (so-called foraging) or several targets that may appear an undefined number of times (recently named as hybrid foraging). In these searches, besides looking for targets, the observer must decide how much time is needed to exploit the area, and when to quit the search to eventually explore new search options. In fact, visual foraging is a very common search task in the real world, probably involving additional cognitive functions than typical VS. It has been widely studied in natural animal environments, for which several mathematical models have been proposed, and just recently applied to humans: Lévy processes, composite and area-restricted search models, marginal value theorem, and Bayesian learning (among others). We conducted a systematic search in the literature to understand those mathematical models and study its applicability in human visual foraging. The review suggests that these models might be the first step, but they seem to be limited to fully comprehend foraging in visual search. There are essential variables involving human visual foraging still to be established and understood. Indeed, a jointly theoretical interpretation based on the different models reviewed could better account for its understanding. In addition, some other relevant variables, such as certain individual differences or time perception might be crucial to understanding visual foraging in humans.

Efficient Lévy walks in virtual human foraging

Efficient foraging depends on decisions that account for the costs and benefits of various activities like movement, perception, and planning. We conducted a virtual foraging experiment set in the foothills of the Himalayas to examine how time and energy are expended to forage efficiently, and how foraging changes when constrained to a home range. Two hundred players foraged the human-scale landscape with simulated energy expenditure in search of naturally distributed resources. Results showed that efficient foragers produced periods of locomotion interleaved with perception and planning that approached theoretical expectations for Lévy walks, regardless of the home-range constraint. Despite this constancy, efficient home-range foraging trajectories were less diffusive by virtue of restricting locomotive search and spending more time instead scanning the environment to plan movement and detect far-away resources. Altogether, results demonstrate that humans can forage efficiently by arranging and adjusting Lévy-distributed search activities in response to environmental and task constraints.

Systems Neuroscience of Natural Behaviors in Rodents

Animals evolved in complex environments, producing a wide range of behaviors, including navigation, foraging, prey capture, and conspecific interactions, which vary over timescales ranging from milliseconds to days. Historically, these behaviors have been the focus of study for ecology and ethology, while systems neuroscience has largely focused on short timescale behaviors that can be repeated thousands of times and occur in highly artificial environments. Thanks to recent advances in machine learning, miniaturization, and computation, it is newly possible to study freely moving animals in more natural conditions while applying systems techniques: performing temporally specific perturbations, modeling behavioral strategies, and recording from large numbers of neurons while animals are freely moving. The authors of this review are a group of scientists with deep appreciation for the common aims of systems neuroscience, ecology, and ethology. We believe it is an extremely exciting time to be a neuroscientist, as we have an opportunity to grow as a field, to embrace interdisciplinary, open, collaborative research to provide new insights and allow researchers to link knowledge across disciplines, species, and scales. Here we discuss the origins of ethology, ecology, and systems neuroscience in the context of our own work and highlight how combining approaches across these fields has provided fresh insights into our research. We hope this review facilitates some of these interactions and alliances and helps us all do even better science, together.

Dopamine as a Multifunctional Neurotransmitter in Gastropod Molluscs: An Evolutionary Hypothesis

AbstractThe catecholamine 3,4-dihydroxyphenethylamine, or dopamine, acts as a neurotransmitter across a broad phylogenetic spectrum. Functions attributed to dopamine in the mammalian brain include regulation of motor circuits, valuation of sensory stimuli, and mediation of reward or reinforcement signals. Considerable evidence also supports a neurotransmitter role for dopamine in gastropod molluscs, and there is growing appreciation for its potential common functions across phylogeny. This article reviews evidence for dopamine's transmitter role in the nervous systems of gastropods. The functional properties of identified dopaminergic neurons in well-characterized neural circuits suggest a hypothetical incremental sequence by which dopamine accumulated its diverse roles. The successive acquisition of dopamine functions is proposed in the context of gastropod feeding behavior: (1) sensation of potential nutrients, (2) activation of motor circuits, (3) selection of motor patterns from multifunctional circuits, (4) valuation of sensory stimuli with reference to internal state, (5) association of motor programs with their outcomes, and (6) coincidence detection between sensory stimuli and their consequences. At each stage of this sequence, it is proposed that existing functions of dopaminergic neurons favored their recruitment to fulfill additional information processing demands. Common functions of dopamine in other intensively studied groups, ranging from mammals and insects to nematodes, suggest an ancient origin for this progression.

Hunters, busybodies and the knowledge network building associated with deprivation curiosity

The open-ended and internally driven nature of curiosity makes characterizing the information seeking that accompanies it a daunting endeavour. We use a historico-philosophical taxonomy of information seeking coupled with a knowledge network building framework to capture styles of information-seeking in 149 participants as they explore Wikipedia for over 5 hours spanning 21 days. We create knowledge networks in which nodes represent distinct concepts and edges represent the similarity between concepts. We quantify the tightness of knowledge networks using graph theoretical indices and use a generative model of network growth to explore mechanisms underlying information-seeking. Deprivation curiosity (the tendency to seek information that eliminates knowledge gaps) is associated with the creation of relatively tight networks and a relatively greater tendency to return to previously visited concepts. With this framework in hand, future research can readily quantify the information seeking associated with curiosity.

Foraging with Anne Treisman: Features versus conjunctions, patch leaving and memory for foraged locations

Foraging tasks are increasingly used to investigate human visual attention as they may provide a more dynamic and multifaceted picture of attentional orienting than more traditionally used visual search tasks. A common way of assessing foraging performance involves measuring when foragers decide to move to a new "patch" with a higher yield. We assessed this using Anne Treisman's famous feature versus conjunction manipulation in an iPad foraging task. We measured how well patch leaving accorded with the predictions of the marginal value theorem that describes how foragers may optimize their foraging by leaving a patch once the average yield within a patch drops below the average yield in the whole environment. Human foraging in our paradigm deviated from the predictions of such optimal foraging conceptions, and our participants kept on foraging within the same patch for longer than expected. Patch leaving and intertarget times differed surprisingly little between feature and conjunction foraging, especially in light of the dramatic differences typically seen between performance on feature and conjunction visual search tasks. Other aspects of foraging performance (run number and switch costs) differed strongly between feature and conjunction foraging, however. We conclude that human foraging is probably influenced by too many factors to be captured with a relatively simple mathematical model.

Neural Activation Patterns Associated with Maternal Mouthbrooding and Energetic State in an African Cichlid Fish

Parental care is widespread in the animal kingdom, but for many species, provisioning energetic resources must be balanced with trade-offs between self-promoting and offspring-promoting behaviors. However, little is known about the neural mechanisms underlying these motivational decisions. Mouthbrooding is an extreme form of parental care most common in fishes that provides an ideal opportunity to examine which brain regions are involved in parenting and energetics. The African cichlid fish Astatotilapia burtoni is a maternal mouthbrooder in which females hold developing young inside their mouths for 2 weeks. This brood care makes feeding impossible, so females undergo obligatory starvation. We used immunohistochemistry for the neural activation marker pS6 to examine which brain regions were involved in processing salient information in mouthbrooding, starved, and fed females. We identified brain regions more associated with maternal brood care (TPp, Dc-4/-5), and others reflective of energetic state (Dl-v, NLTi). Most nuclei examined, however, were involved in both maternal care and energetic status. Placement of each of the 16 examined nuclei into these functional categories was supported by node by node comparisons, co-activity networks, hierarchical clustering, and discriminant function analysis. These results reveal which brain regions are involved in parental care and food intake in a species where provisioning is skewed towards the offspring when parental feeding is not possible. This study provides support for both distinct and shared circuitry involved in regulation of maternal care, food intake, and energy balance, and helps put the extreme parental case of mouthbrooding into a comparative and evolutionary context.

Similarities and differences in spatial and non-spatial cognitive maps

Learning and generalization in spatial domains is often thought to rely on a "cognitive map", representing relationships between spatial locations. Recent research suggests that this same neural machinery is also recruited for reasoning about more abstract, conceptual forms of knowledge. Yet, to what extent do spatial and conceptual reasoning share common computational principles, and what are the implications for behavior? Using a within-subject design we studied how participants used spatial or conceptual distances to generalize and search for correlated rewards in successive multi-armed bandit tasks. Participant behavior indicated sensitivity to both spatial and conceptual distance, and was best captured using a Bayesian model of generalization that formalized distance-dependent generalization and uncertainty-guided exploration as a Gaussian Process regression with a radial basis function kernel. The same Gaussian Process model best captured human search decisions and judgments in both domains, and could simulate realistic learning curves, where we found equivalent levels of generalization in spatial and conceptual tasks. At the same time, we also find characteristic differences between domains. Relative to the spatial domain, participants showed reduced levels of uncertainty-directed exploration and increased levels of random exploration in the conceptual domain. Participants also displayed a one-directional transfer effect, where experience in the spatial task boosted performance in the conceptual task, but not vice versa. While confidence judgments indicated that participants were sensitive to the uncertainty of their knowledge in both tasks, they did not or could not leverage their estimates of uncertainty to guide exploration in the conceptual task. These results support the notion that value-guided learning and generalization recruit cognitive-map dependent computational mechanisms in spatial and conceptual domains. Yet both behavioral and model-based analyses suggest domain specific differences in how these representations map onto actions.

Semantic Search in Psychosis: Modeling Local Exploitation and Global Exploration

Impairments in category verbal fluency task (VFT) performance have been widely documented in psychosis. These deficits may be due to disturbed “cognitive foraging” in semantic space, in terms of altered salience of cues that influence individuals to search locally within a subcategory of semantically related responses (“clustering”) or globally between subcategories (“switching”). To test this, we conducted a study in which individuals with schizophrenia (n = 21), schizotypal personality traits (n = 25), and healthy controls (n = 40) performed VFT with “animals” as the category. Distributional semantic model Word2Vec computed cosine-based similarities between words according to their statistical usage in a large text corpus. We then applied a validated foraging-based search model to these similarity values to obtain salience indices of frequency-based global search cues and similarity-based local cues. Analyses examined whether diagnosis predicted VFT performance, search strategies, cue salience, and the time taken to switch between vs search within clusters. Compared to control and schizotypal groups, individuals with schizophrenia produced fewer words, switched less, and exhibited higher global cue salience, indicating a selection of more common words when switching to new clusters. Global cue salience negatively associated with vocabulary ability in controls and processing speed in schizophrenia. Lastly, individuals with schizophrenia took a similar amount of time to switch to new clusters compared to control and schizotypal groups but took longer to transition between words within clusters. Findings of altered local exploitation and global exploration through semantic memory provide preliminary evidence of aberrant cognitive foraging in schizophrenia.

Multiscale Computation and Dynamic Attention in Biological and Artificial Intelligence

Biological and artificial intelligence (AI) are often defined by their capacity to achieve a hierarchy of short-term and long-term goals that require incorporating information over time and space at both local and global scales. More advanced forms of this capacity involve the adaptive modulation of integration across scales, which resolve computational inefficiency and explore-exploit dilemmas at the same time. Research in neuroscience and AI have both made progress towards understanding architectures that achieve this. Insight into biological computations come from phenomena such as decision inertia, habit formation, information search, risky choices and foraging. Across these domains, the brain is equipped with mechanisms (such as the dorsal anterior cingulate and dorsolateral prefrontal cortex) that can represent and modulate across scales, both with top-down control processes and by local to global consolidation as information progresses from sensory to prefrontal areas. Paralleling these biological architectures, progress in AI is marked by innovations in dynamic multiscale modulation, moving from recurrent and convolutional neural networks-with fixed scalings-to attention, transformers, dynamic convolutions, and consciousness priors-which modulate scale to input and increase scale breadth. The use and development of these multiscale innovations in robotic agents, game AI, and natural language processing (NLP) are pushing the boundaries of AI achievements. By juxtaposing biological and artificial intelligence, the present work underscores the critical importance of multiscale processing to general intelligence, as well as highlighting innovations and differences between the future of biological and artificial intelligence.

Simple Aesthetic Sense and Addiction Emerge in Neural Relations of Cost-Benefit Decision in Foraging

A rudimentary aesthetic sense is found in the stimulus valuations and cost-benefit decisions made by primitive generalist foragers. These are based on factors governing personal economic decisions: incentive, appetite, and learning. We find that the addictive process is an extreme expression of aesthetic dynamics. An interactive, agent-based model, ASIMOV, reproduces a simple aesthetic sense from known neural relations of cost-benefit decision in foraging. In the presence of very high reward, an addiction-like process emerges. A drug-like prey provides extreme reward with no nutritive value, initiating high selectivity and prolonged cravings for drug through reward learning. Varying reward experience, caused by homeostatic changes in the neural circuitry of reward, further establishes the course of addiction, consisting of desensitization, withdrawal, resensitization, and associated changes in nutritional choice and pain sensitivity. These observations are consistent with the early evolution of addiction mechanisms in simple generalist foragers as an aesthetic sense for evaluating prey. ASIMOV is accessible to inspection, modification, and experiment, is adaptable as an educational tool, and provides insight on the possible coevolutionary origins of aesthetics and the addiction process.

Dopamine neurons do not constitute an obligatory stage in the final common path for the evaluation and pursuit of brain stimulation reward

The neurobiological study of reward was launched by the discovery of intracranial self-stimulation (ICSS). Subsequent investigation of this phenomenon provided the initial link between reward-seeking behavior and dopaminergic neurotransmission. We re-evaluated this relationship by psychophysical, pharmacological, optogenetic, and computational means. In rats working for direct, optical activation of midbrain dopamine neurons, we varied the strength and opportunity cost of the stimulation and measured time allocation, the proportion of trial time devoted to reward pursuit. We found that the dependence of time allocation on the strength and cost of stimulation was similar formally to that observed when electrical stimulation of the medial forebrain bundle served as the reward. When the stimulation is strong and cheap, the rats devote almost all their time to reward pursuit; time allocation falls off as stimulation strength is decreased and/or its opportunity cost is increased. A 3D plot of time allocation versus stimulation strength and cost produces a surface resembling the corner of a plateau (the “reward mountain”). We show that dopamine-transporter blockade shifts the mountain along both the strength and cost axes in rats working for optical activation of midbrain dopamine neurons. In contrast, the same drug shifted the mountain uniquely along the opportunity-cost axis when rats worked for electrical MFB stimulation in a prior study. Dopamine neurons are an obligatory stage in the dominant model of ICSS, which positions them at a key nexus in the final common path for reward seeking. This model fails to provide a cogent account for the differential effect of dopamine transporter blockade on the reward mountain. Instead, we propose that midbrain dopamine neurons and neurons with non-dopaminergic, MFB axons constitute parallel limbs of brain-reward circuitry that ultimately converge on the final-common path for the evaluation and pursuit of rewards.

Foraging in Mind

People and other animals can search for information inside their heads. Where does this ability come from, and what does it enable cognitive systems to do? In this article, we address the behavioral and cognitive similarities between search in external environments and internal environments (e.g., memory). These require both maplike representations and the means to navigate them, and the latter involves modulation between exploitation and exploration analogous to a foraging process called area-restricted search. These findings have implications for understanding a number of cognitive abilities commonly considered to be hallmarks of the human species, such as well-developed executive control and goal-directed cognition, autonoetic consciousness (i.e., self-awareness), deliberation, and free will. Moreover, this research extends our conception of what organisms may share these abilities and how they evolved.

The Ecology of Individual Differences Empirically Applied to Space-Use and Movement Tactics

Movement provides a link between individual behavioral ecology and the spatial and temporal variation in an individual's landscape. Individual variation in movement traits is an important axis of animal personality, particularly in the context of foraging ecology. We tested whether individual caribou (Rangifer tarandus) displayed plasticity in movement and space-use behavior across a gradient of resource aggregation. We quantified first-passage time and range-use ratio as proxies for movement-related foraging behavior and examined how these traits varied at the individual level across a foraging resource gradient. Our results suggest that individuals adjusted first-passage time but not range-use ratio to maximize access to high-quality foraging resources. First-passage time was repeatable, and intercepts for first-passage time and range-use ratio were negatively correlated. Individuals matched first-passage time but not range-use ratio to the expectations of our patch-use model that maximized access to foraging resources, a result that suggests that individuals acclimated their movement patterns to accommodate both intra- and interannual variation in foraging resources on the landscape. Collectively, we highlight repeatable movement and space-use tactics and provide insight into how individual plasticity in movement interacts with landscape processes to affect the distribution of behavioral phenotypes and potentially fitness and population dynamics.

Assigning Rated Items to Locations in Non-List Display Layouts

One of the most common ways in which results are displayed by an information retrieval system is in the form of a list, in which the most relevant results appear in the first positions. Today's large screens, however, allow one to create more complex displays of results, especially in cases such as image retrieval, in which each unit returned is fairly compact. For these layouts the simple list model is no longer valid, since the relations between the slots in which the results are placed do not form a sequence, that is, the relation among them is no longer that of a total order. In this paper we model these layouts as partial orders and show that a "stalwart display" property (a layout in which items' relevance is unambiguously conveyed by their display position) can be obtained only in the case of lists. For the other layouts, we define two classes of representation functions: "safe" functions (which display results without adding spurious structure) and "rich" functions (which do not drop any structure from the result set), as well as an algorithm to optimally display fully ordered result sets in arbitrary display layouts.

Resynthesizing behavior through phylogenetic refinement

This article proposes that biologically plausible theories of behavior can be constructed by following a method of "phylogenetic refinement," whereby they are progressively elaborated from simple to complex according to phylogenetic data on the sequence of changes that occurred over the course of evolution. It is argued that sufficient data exist to make this approach possible, and that the result can more effectively delineate the true biological categories of neurophysiological mechanisms than do approaches based on definitions of putative functions inherited from psychological traditions. As an example, the approach is used to sketch a theoretical framework of how basic feedback control of interaction with the world was elaborated during vertebrate evolution, to give rise to the functional architecture of the mammalian brain. The results provide a conceptual taxonomy of mechanisms that naturally map to neurophysiological and neuroanatomical data and that offer a context for defining putative functions that, it is argued, are better grounded in biology than are some of the traditional concepts of cognitive science.

Neurocognitive free will

Free will is an apparent paradox because it requires a historical identity to escape its history in a self-guided fashion. Philosophers have itemized design features necessary for this escape, scaling from action to agency and vice versa. These can be organized into a coherent framework that neurocognitive capacities provide and that form a basis for neurocognitive free will. These capacities include (1) adaptive access to unpredictability, (2) tuning of this unpredictability in the service of hierarchical goal structures, (3) goal-directed deliberation via search over internal cognitive representations, and (4) a role for conscious construction of the self in the generation and choice of alternatives. This frames free will as a process of generative self-construction, by which an iterative search process samples from experience in an adaptively exploratory fashion, allowing the agent to explore itself in the construction of alternative futures. This provides an explanation of how effortful conscious control modulates adaptive access to unpredictability and resolves one of free will's key conceptual problems: how randomness is used in the service of the will. The implications provide a contemporary neurocognitive grounding to compatibilist and libertarian positions on free will, and demonstrate how neurocognitive understanding can contribute to this debate by presenting free will as an interaction between our freedom and our will.

Lower Attentional Skills predict increased exploratory foraging patterns

When engaged in a search task, one needs to arbitrate between exploring and exploiting the environment to optimize the outcome. Many intrinsic, task and environmental factors are known to influence the exploration/exploitation balance. Here, in a non clinical population, we show that the level of inattention (assessed as a trait) is one such factor: children with higher scores on an ADHD (Attention Deficit/Hyperactivity Disorder) questionnaire exhibited longer transitions between consecutively retrieved items, in both a visual and a semantic search task. These more frequent exploration behaviours were associated with differential performance patterns: children with higher levels of ADHD traits performed better in semantic search, while their performance was unaffected in visual search. Our results contribute to the growing literature suggesting that ADHD should not be simply conceived as a pure deficit of attention, but also as a specific cognitive strategy that may prove beneficial in some contexts.

Environmental harshness and unpredictability, life history, and social and academic behavior of adolescents in nine countries

Safety is essential for life. To survive, humans and other animals have developed sets of psychological and physiological adaptations known as life history (LH) tradeoff strategies in response to various safety constraints. Evolutionarily selected LH strategies in turn regulate development and behavior to optimize survival under prevailing safety conditions. The present study tested LH hypotheses concerning safety based on a 6-year longitudinal sample of 1,245 adolescents and their parents from 9 countries. The results revealed that, invariant across countries, environmental harshness, and unpredictability (lack of safety) was negatively associated with slow LH behavioral profile, measured 2 years later, and slow LH behavioral profile was negatively and positively associated with externalizing behavior and academic performance, respectively, as measured an additional 2 years later. These results support the evolutionary conception that human development responds to environmental safety cues through LH regulation of social and learning behaviors. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Evolutionary-developmental modeling of neurodiversity and psychopathology

Modeling the extremes of mental/emotional conditions requires explicit account of evolutionary-developmental sources of human neurodiversity, not merely psychopathology. The target article's approach could be improved by incorporation of a hierarchical scheme wherein mental/emotional infrastructure interacts across differentiated layers of function. The notion "symptom networks" thus calls for differentiation into hierarchically interacting components of mental/emotional evolution and development.