Exploration versus exploitation in space, mind, and society

Foraging with your eyes: a novel task to study cognitive strategies involved in (visual) foraging behaviour

In this study we introduce a new gaze-contingent visual foraging task in which participants searched through an environment by looking at trees displayed on a computer screen. If the looked-at tree contained a fruit item, the item became visible and was collected. In each trial, the participant's task was to forage for a defined number of fruit items. In two experiments, fruit items were either randomly distributed about the trees (dispersed condition) or organised in one large patch (patchy condition). In the second experiment, we addressed the role of memory for foraging by including a condition that did not require memorising which trees had already been visited by changing their appearance (tree fading). Foraging performance was superior in the patchy as compared to the dispersed condition and benefited from tree-fading. In addition, with further analyses on search behaviour, these results suggest (1) that participants were sensitive to the distribution of resources, (2) that they adapted their search/foraging strategy accordingly, and (3) that foraging behaviour is in line with predictions derived from foraging theories, specifically area-restricted search, developed for large scale spatial foraging. We therefore argue that the visual search task presented shares characteristics and cognitive mechanisms involved in successful large-scale search and foraging behaviour and can therefore be successfully employed to study these mechanisms.

Global to local influences on temporal expectation in marmosets and humans

Marmosets are emerging rapidly as experimental models for studying the neural bases of cognition and, importantly, for modeling disorders of human cognition, but many aspects of their mental attributes remain to be characterized. When judging elapsed time, humans implicitly use prior information to predict upcoming events and reduce perceptual and decision-making uncertainty. An influential model of temporal expectation is the hazard rate model, which posits the likelihood of an event occurring in the future, provided it has not occurred already. Here, we report that marmosets trained on a reaction time task acquire the hazard rate model of expectation, consistent with the global task structure. The model emerges progressively with learning but unexpectedly continues to be modified by local contingencies, as demonstrated by a serial effect of trial duration on responses. The combined effects of global and local task structure are well described by a multiple regression model and computationally by Bayesian updating of the hazard function. Parallel experiments in human subjects similarly demonstrate global followed by local influences on reaction times and temporal expectation. Thus, in both marmosets and humans, task history and local structure continuously update task-specific responses, surprisingly at the expense of optimal responses after the competent acquisition of an internal model.

Alternative models of funding curiosity-driven research

Funding of curiosity-driven science is the lifeblood of scientific and technological innovation. Various models of funding allocation became institutionalized in the 20th century, shaping the present landscape of research funding. There are numerous reasons for scientists to be dissatisfied with current funding schemes, including the imbalance between funding for curiosity-driven and mission-directed research, regional and country disparities, path-dependency of who gets funded, gender and race disparities, low inter-reviewer reliability, and the trade-off between the effort and time spent on writing or reviewing proposals and doing research. We discuss possible alternative models for dealing with these issues. These alternatives include incremental changes such as placing more weight on the proposals or on the investigators and representative composition of panel members, along with deeper reforms such as distributed or concentrated funding and partial lotteries in response to low inter-reviewer reliability. We also consider radical alternatives to current funding schemes: the removal of political governance and the introduction of international competitive applications to a World Research Council alongside national funding sources. There is likely no single best way to fund curiosity-driven research; we examine arguments for and against the possibility of systematically evaluating alternative models empirically.

When to stop social learning from a predecessor in an information-foraging task

Striking a balance between individual and social learning is one of the key capabilities that support adaptation under uncertainty. Although intergenerational transmission of information is ubiquitous, little is known about when and how newcomers switch from learning loyally from preceding models to exploring independently. Using a behavioural experiment, we investigated how social information available from a preceding demonstrator affects the timing of becoming independent and individual performance thereafter. Participants worked on a 30-armed bandit task for 100 trials. For the first 15 trials, participants simply observed the choices of a demonstrator who had accumulated more knowledge about the environment and passively received rewards from the demonstrator's choices. Thereafter, participants could switch to making independent choices at any time. We had three conditions differing in the social information available from the demonstrator: choice only, reward only or both. Results showed that both participants' strategies about when to stop observational learning and their behavioural patterns after independence depended on the available social information. Participants generally failed to make the best use of previously observed social information in their subsequent independent choices, suggesting the importance of direct communication beyond passive observation for better intergenerational transmission under uncertainty. Implications for cultural evolution are discussed.

Pace of Life Is Faster for a Bored Person: Exploring the Relationship Between Trait Boredom and Fast Life History Strategy

Life history theory suggests that in harsh, unpredictable environments, individuals may benefit from adopting a fast life history strategy. This may involve experiencing boredom more frequently and intensely as an adaptive mechanism to seek novel stimuli, potentially increasing the number of sexual partners and offspring. This study explored the relationship between trait boredom-a chronic characteristic of feeling bored-and fast life history strategies. Our findings confirmed a positive association between boredom proneness and fast life history strategies at both individual and country levels. In Study 1, fast life history strategy was positively correlated with boredom proneness and mediated the relationship between perceived childhood support/resources and boredom proneness. In Study 2, we conducted a multi-level analysis using secondary data from 15 countries. The results showed that countries with higher boredom proneness scores showed more indicators of faster life history strategies. These results suggest that trait boredom may be a functional characteristic of fast life history strategists. This study is the first empirical investigation of trait boredom within a life history framework, highlighting trait boredom's functional role from evolutionary and ecological perspectives.

Value construction through sequential sampling explains serial dependencies in decision making

Deciding between a pair of familiar items is thought to rely on a comparison of their subjective values. When the values are similar, decisions take longer, and the choice may be inconsistent with stated value. These regularities are thought to be explained by the same mechanism of noisy evidence accumulation that leads to perceptual errors under conditions of low signal to noise. However, unlike perceptual decisions, subjective values may vary with internal states (e.g. desires, priorities) that change over time. This raises the possibility that the apparent stochasticity of choice reflects changes in value rather than mere noise. We hypothesized that these changes would manifest in serial dependencies across decision sequences. We analyzed data from a task in which participants chose between snack items. We developed an algorithm, Reval, that revealed significant fluctuations of the subjective values of items within an experimental session. The dynamic values predicted choices and response times more accurately than stated values. The dynamic values also furnished a superior account of the BOLD signal in ventromedial prefrontal cortex. A novel bounded-evidence accumulation model with temporally correlated evidence samples supports the idea that revaluation reflects the dynamic construction of subjective value during deliberation, which in turn influences subsequent decisions.

The influence of anxiety on exploration: A review of computational modeling studies

Exploratory behaviors can serve an adaptive role within novel or changing environments. Namely, they facilitate information gain, allowing an organism to maintain accurate beliefs about the environment and select actions that better maximize reward. However, finding the optimal balance between exploration and reward-seeking behavior - the so-called explore-exploit dilemma - can be challenging, as it requires sensitivity to one's own uncertainty and to the predictability of one's surroundings. Given the close relationship between uncertainty and anxiety, a body of work has now also emerged identifying associated effects on exploration. In particular, the field of computational psychiatry has begun to use cognitive computational models to characterize how anxiety may modulate underlying information processing mechanisms, such as estimation of uncertainty and the value of information, and how this might contribute to psychopathology. Here, we review computational modeling studies investigating how exploration is influenced by anxiety. While some apparent inconsistencies remain to be resolved, studies using reinforcement learning tasks suggest that directed (but not random) forms of exploration may be elevated by trait and/or cognitive anxiety, but reduced by state and/or somatic anxiety. Anxiety is also consistently associated with less exploration in foraging tasks. Some differences in exploration may further stem from how anxiety modulates changes in uncertainty over time (learning rates). Jointly, these results highlight important directions for future work in refining choice of tasks and anxiety measures and maintaining consistent methodology across studies.

Midlife dynamics of white matter architecture in lexical production

We aimed to examine the white matter changes associated with lexical production difficulties, beginning in midlife with increased naming latencies. To delay lexical production decline, middle-aged adults may rely on domain-general and language-specific compensatory mechanisms proposed by the LARA model (Lexical Access and Retrieval in Aging). However, the white matter changes supporting these mechanisms remains largely unknown. Using data from the CAMCAN cohort, we employed an unsupervised and data-driven methodology to examine the relationships between diffusion-weighted imaging and lexical production. Our findings indicate that midlife is marked by alterations in brain structure within distributed dorsal, ventral, and anterior cortico-subcortical networks, marking the onset of lexical production decline around ages 53-54. Middle-aged adults may initially adopt a "semantic strategy" to compensate for lexical production challenges, but this strategy seems compromised later (ages 55-60) as semantic control declines. These insights underscore the interplay between domain-general and language-specific processes in the trajectory of lexical production performance in healthy aging and hint at potential biomarkers for language-related neurodegenerative pathologies.

Consistent long-distance foraging flights across years and seasons at colony level in a neotropical bat

All foraging animals face a trade-off: how much time should they invest in exploitation of known resources versus exploration to discover new resources? For group-living central place foragers, this balance is challenging. Due to the nature of their movement patterns, exploration and exploitation are often mutually exclusive, while the availability of social information may discourage individuals from exploring. To examine these trade-offs, we GPS-tracked groups of greater spear-nosed bats (Phyllostomus hastatus) from three colonies on Isla Colón, Panamá. During the dry season, when these omnivores forage on the nectar of unpredictable balsa flowers, bats consistently travelled long distances to remote, colony-specific foraging areas, bypassing flowering trees closer to their roosts. They continued using these areas in the wet season, when feeding on a diverse, presumably ubiquitous diet, but also visited other, similarly distant foraging areas. Foraging areas were shared within but not always between colonies. Our longitudinal dataset suggests that bats from each colony invest in long-distance commutes to socially learned shared foraging areas, bypassing other available food patches. Rather than exploring nearby resources, these bats exploit colony-specific foraging locations that appear to be culturally transmitted. These results give insight into how social animals might diverge from optimal foraging.

The effect of target scarcity on visual foraging

Previous studies have investigated the effect of target prevalence in combination with the effect of explicit target value on human visual foraging strategies, though the conclusions have been mixed. Some find that individuals have a bias towards high-value targets even when these targets are scarcer, while other studies find that this bias disappears when those targets are scarcer. In this study, we tested for a bias for scarce targets using standard feature versus conjunction visual foraging tasks, without an explicit value being given. Based on the idea of commodity theory and implicit value, we hypothesized that participants would show a scarcity bias. The bias was investigated using a Bayesian statistical model which has been developed for predicting target-by-target foraging behaviours. However, we found no evidence of a scarcity bias in our experiment, suggesting that participants did not inherently find rarer targets more rewarding.

Predecisional information search adaptively reduces three types of uncertainty

How do people search for information when they are given the opportunity to freely explore their options? Previous research has suggested that people focus on reducing uncertainty before making a decision, but it remains unclear how exactly they do so and whether they do so consistently. We present an analysis of over 1,000,000 information-search decisions made by over 2,500 individuals in a decisions-from-experience setting that cleanly separates information search from choice. Using a data-driven approach supported by a formal measurement framework, we examine how people allocate samples to options and how they decide to terminate search. Three major insights emerge. First, predecisional information search has at least three drivers that can be interpreted as reducing three types of uncertainty: structural, estimation, and computational. Second, the selection of these drivers of information search is adaptive, sequential, and guided by environmental knowledge that integrates prior expectations, task instructions, and personal experiences. Third, predecisional information search exhibits substantial interindividual heterogeneity, with individuals recruiting different drivers of information search. Together, these insights suggest that human information search is complex in ways that cannot be fully explained by monolithic accounts of information search, including proposals focused on estimation uncertainty or cost-benefit analysis. We conclude that broader theories of human information-search behavior are necessary.

Fixation durations on familiar items are longer due to attenuation of exploration

Previous studies have shown that fixations on familiar stimuli tend to be longer than on unfamiliar stimuli, theorized to be a result of retrieval of information from memory. We hypothesize that extended fixations are due to a lesser need to explore an already familiar stimulus. Participant's gaze was tracked as they tried to encode or retrieve a familiar face displayed either alone or alongside other unfamiliar faces. Regardless of the memory task (encoding\retrieval), longer fixation durations were observed when a single familiar face was presented alone, and not when presented among unfamiliar ones. Thus, fixations were not prolonged when it was possible to explore other, unfamiliar stimuli. We conclude that prolonged fixations on familiar stimuli reflect a lesser need to explore an already familiar percept. The results underscore how memory representations influence active sensing, yielding fresh insights into efficient deployment of attention resources. We conclude that fixation durations could be used in applied memory detection tests, preferably together with other measures and when the familiar stimulus is presented alone.

Beyond risk preferences in sequential decision-making: How probability representation, sequential structure and choice perseverance bias optimal search

Sequential decision-making, where choices are made one after the other, is an important aspect of our daily lives. For example, when searching for a job, an apartment, or deciding when to buy or sell a stock, people often have to make decisions without knowing what future opportunities might arise. These situations, which are known as optimal stopping problems, involve a risk associated with the decision to either stop or continue searching. However, previous research has not consistently found a clear connection between individuals' search behavior in these tasks and their risk preferences as measured in controlled experimental settings. In this paper, we explore how particular characteristics of optimal stopping tasks affect people's choices, extending beyond their stable risk preferences. We find that (1) the way the underlying sampling distribution is presented (whether it is based on experience or description), (2) the sequential presentation of options, and (3) the unequal frequencies of choices to reject versus to accept significantly bias people choices. These results shed light on the complex nature of decisions that unfold sequentially and emphasize the importance of incorporating context factors when studying human decision behavior.

A normative framework dissociates need and motivation in hypothalamic neurons

Physiological needs evoke motivational drives that produce natural behaviors for survival. In previous studies, the temporally intertwined dynamics of need and motivation have made it challenging to differentiate these two components. On the basis of classic homeostatic theories, we established a normative framework to derive computational models for need-encoding and motivation-encoding neurons. By combining the model-based predictions and naturalistic experimental paradigms, we demonstrated that agouti-related peptide (AgRP) and lateral hypothalamic leptin receptor (LHLepR) neuronal activities encode need and motivation, respectively. Our model further explains the difference in the dynamics of appetitive behaviors induced by optogenetic stimulation of AgRP or LHLepR neurons. Our study provides a normative modeling framework that explains how hypothalamic neurons separately encode need and motivation in the mammalian brain.

A short natural history of mental time travels: a journey still travelled?

Tulving's introduction of episodic memory and the metaphor of mental time travel has immensely enriched our understanding of human cognition. However, his focus on human psychology, with limited consideration of evolutionary perspectives, led to the entrenched notion that mental time travel is uniquely human. We contend that adopting a phylogenetic perspective offers a deeper insight into cognition, revealing it as a continuous evolutionary process. Adherence to the uniqueness of pre-defined psychological concepts obstructs a more complete understanding. We offer a concise natural history to elucidate how events that occurred hundreds of millions of years ago have been pivotal for our ability to mentally time travel. We discuss how the human brain, utilizing parts with ancient origins in a networked manner, enables mental time travel. This underscores that episodic memories and mental time travel are not isolated mental constructs but integral to our perception and representation of the world. We conclude by examining recent evidence of neuroanatomical correlates found only in great apes, which show great variability, indicating the ongoing evolution of mental time travel in humans.This article is part of the theme issue 'Elements of episodic memory: lessons from 40 years of research'.

Balancing exploration and exploitation? The impact of cost and inhibitory control on information gathering in early childhood

The information-seeking behaviour of adults focuses on optimizing the gathering and utilizing information to minimize search costs. In contrast, children tend to engage in information search during decision-making with less consideration for costs. This difference in behaviour is believed to be linked to the development of executive functions. Therefore, the present study aimed to investigate the relationship between executive function and cost-related information-gathering behaviour. We assessed 56 children aged 4-6 years, involving three tasks: an information-gathering task, an inhibitory control and a working memory task. In the information-gathering task, children participated in both non-cost and cost conditions, where they were given the opportunity to freely gather information or incur a cost to acquire information. The findings revealed that children with higher inhibitory control tended to gather less information when a cost was involved. This highlights the important role of inhibitory control in shaping information-seeking behaviour in early childhood.

An Active-Inference Approach to Second-Person Neuroscience

Social neuroscience has often been criticized for approaching the investigation of the neural processes that enable social interaction and cognition from a passive, detached, third-person perspective, without involving any real-time social interaction. With the emergence of second-person neuroscience, investigators have uncovered the unique complexity of neural-activation patterns in actual, real-time interaction. Social cognition that occurs during social interaction is fundamentally different from that unfolding during social observation. However, it remains unclear how the neural correlates of social interaction are to be interpreted. Here, we leverage the active-inference framework to shed light on the mechanisms at play during social interaction in second-person neuroscience studies. Specifically, we show how counterfactually rich mutual predictions, real-time bodily adaptation, and policy selection explain activation in components of the default mode, salience, and frontoparietal networks of the brain, as well as in the basal ganglia. We further argue that these processes constitute the crucial neural processes that underwrite bona fide social interaction. By placing the experimental approach of second-person neuroscience on the theoretical foundation of the active-inference framework, we inform the field of social neuroscience about the mechanisms of real-life interactions. We thereby contribute to the theoretical foundations of empirical second-person neuroscience.

Thought for food: the endothermic brain hypothesis

The evolution of whole-body endothermy occurred independently in dinosaurs and mammals and was associated with some of the most significant neurocognitive shifts in life's history. These included a 20-fold increase in neurons and the evolution of new brain structures, supporting similar functions in both lineages. We propose the endothermic brain hypothesis, which holds that elaborations in endotherm brains were geared towards increasing caloric intake through efficient foraging. The hypothesis is grounded in the intrinsic coupling of cognition and organismic self-maintenance. We argue that coevolution of increased metabolism and new forms of cognition should be jointly investigated in comparative studies of behaviors and brain anatomy, along with studies of fossil species. We suggest avenues for such research and highlight critical open questions.

Value construction through sequential sampling explains serial dependencies in decision making

Many decisions are expressed as a preference for one item over another. When these items are familiar, it is often assumed that the decision maker assigns a value to each of the items and chooses the item with the highest value. These values may be imperfectly recalled, but are assumed to be stable over the course of an interview or psychological experiment. Choices that are inconsistent with a stated valuation are thought to occur because of unspecified noise that corrupts the neural representation of value. Assuming that the noise is uncorrelated over time, the pattern of choices and response times in value-based decisions are modeled within the framework of Bounded Evidence Accumulation (BEA), similar to that used in perceptual decision-making. In BEA, noisy evidence samples accumulate over time until the accumulated evidence for one of the options reaches a threshold. Here, we argue that the assumption of temporally uncorrelated noise, while reasonable for perceptual decisions, is not reasonable for value-based decisions. Subjective values depend on the internal state of the decision maker, including their desires, needs, priorities, attentional state, and goals. These internal states may change over time, or undergo revaluation, as will the subjective values. We reasoned that these hypothetical value changes should be detectable in the pattern of choices made over a sequence of decisions. We reanalyzed data from a well-studied task in which participants were presented with pairs of snacks and asked to choose the one they preferred. Using a novel algorithm (Reval), we show that the subjective value of the items changes significantly during a short experimental session (about 1 hour). Values derived with Reval explain choice and response time better than explicitly stated values. They also better explain the BOLD signal in the ventromedial prefrontal cortex, known to represent the value of decision alternatives. Revaluation is also observed in a BEA model in which successive evidence samples are not assumed to be independent. We argue that revaluation is a consequence of the process by which values are constructed during deliberation to resolve preference choices.

Knowing what to know: Implications of the choice of prior distribution on the behavior of adaptive design optimization

Adaptive design optimization (ADO) is a state-of-the-art technique for experimental design (Cavagnaro et al., 2010). ADO dynamically identifies stimuli that, in expectation, yield the most information about a hypothetical construct of interest (e.g., parameters of a cognitive model). To calculate this expectation, ADO leverages the modeler's existing knowledge, specified in the form of a prior distribution. Informative priors align with the distribution of the focal construct in the participant population. This alignment is assumed by ADO's internal assessment of expected information gain. If the prior is instead misinformative, i.e., does not align with the participant population, ADO's estimates of expected information gain could be inaccurate. In many cases, the true distribution that characterizes the participant population is unknown, and experimenters rely on heuristics in their choice of prior and without an understanding of how this choice affects ADO's behavior. Our work introduces a mathematical framework that facilitates investigation of the consequences of the choice of prior distribution on the efficiency of experiments designed using ADO. Through theoretical and empirical results, we show that, in the context of prior misinformation, measures of expected information gain are distinct from the correctness of the corresponding inference. Through a series of simulation experiments, we show that, in the case of parameter estimation, ADO nevertheless outperforms other design methods. Conversely, in the case of model selection, misinformative priors can lead inference to favor the wrong model, and rather than mitigating this pitfall, ADO exacerbates it.

Exploration-Exploitation and Suicidal Behavior in Borderline Personality Disorder and Depression

Importance

Clinical theory and behavioral studies suggest that people experiencing suicidal crisis are often unable to find constructive solutions or incorporate useful information into their decisions, resulting in premature convergence on suicide and neglect of better alternatives. However, prior studies of suicidal behavior have not formally examined how individuals resolve the tradeoffs between exploiting familiar options and exploring potentially superior alternatives.

Objective

To investigate exploration and exploitation in suicidal behavior from the formal perspective of reinforcement learning.

Design, Setting, and Participants

Two case-control behavioral studies of exploration-exploitation of a large 1-dimensional continuous space and a 21-day prospective ambulatory study of suicidal ideation were conducted between April 2016 and March 2022. Participants were recruited from inpatient psychiatric units, outpatient clinics, and the community in Pittsburgh, Pennsylvania, and underwent laboratory and ambulatory assessments. Adults diagnosed with borderline personality disorder (BPD) and midlife and late-life major depressive disorder (MDD) were included, with each sample including demographically equated groups with a history of high-lethality suicide attempts, low-lethality suicide attempts, individuals with BPD or MDD but no suicide attempts, and control individuals without psychiatric disorders. The MDD sample also included a subgroup with serious suicidal ideation.

Main Outcomes and Measures

Behavioral (model-free and model-derived) indices of exploration and exploitation, suicide attempt lethality (Beck Lethality Scale), and prospectively assessed suicidal ideation.

Results

The BPD group included 171 adults (mean [SD] age, 30.55 [9.13] years; 135 [79%] female). The MDD group included 143 adults (mean [SD] age, 62.03 [6.82] years; 81 [57%] female). Across the BPD (χ23 = 50.68; P < .001) and MDD (χ24 = 36.34; P < .001) samples, individuals with high-lethality suicide attempts discovered fewer options than other groups as they were unable to shift away from unrewarded options. In contrast, those with low-lethality attempts were prone to excessive behavioral shifts after rewarded and unrewarded actions. No differences were seen in strategic early exploration or in exploitation. Among 84 participants with BPD in the ambulatory study, 56 reported suicidal ideation. Underexploration also predicted incident suicidal ideation (χ21 = 30.16; P < .001), validating the case-control results prospectively. The findings were robust to confounds, including medication exposure, affective state, and behavioral heterogeneity.

Conclusions and Relevance

The findings suggest that narrow exploration and inability to abandon inferior options are associated with serious suicidal behavior and chronic suicidal thoughts. By contrast, individuals in this study who engaged in low-lethality suicidal behavior displayed a low threshold for taking potentially disadvantageous actions.

Openness to experience predicts eye movement behavior during scene viewing

Individuals' abilities to perform goal-directed spatial deployments of attention are distinguishable from their broader preferences for how they use spatial attention when circumstances do not compel a specific deployment strategy. Although these preferences are likely to play a major role in how we interact with the visual world during daily life, they remain relatively understudied. This exploratory study investigated two key questions about these preferences: firstly, are individuals consistent in their preferences for how they deploy their spatial attention when making shifts of attention versus adopting an attentional breadth? Secondly, which other factors are associated with these preferences? Across two experiments, we measured how participants preferred to deploy both attentional breadth (using an adapted Navon task) and eye movements (using a free-viewing task). We also measured participants' working memory capacities (Experiment 1), and their personalities and world beliefs (Experiment 2). In both experiments, there were consistent individual differences in preference for attentional breadth and eye movement characteristics, but these two kinds of preference were unrelated to each other. Working memory capacity was not linked to these preferences. Conversely, the personality trait of Openness to Experience robustly predicted two aspects of eye movement behavior preference, such that higher levels of Openness predicted smaller saccades and shorter scan paths. This suggests that personality dimensions may predict preferences for more absorbed engagement with visual information. However, it appears that individuals' preferences for shifts of attention during scene viewing do not necessarily relate to the breadth of attention they choose to adopt.

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 .

Free will: An Example of the Dopaminergic System

Neuroscience has convinced people that much of their behavior is determined by causes unknown to them and beyond their control. However, are advances in neuroscience truly a prerequisite for such beliefs? Robert Kane's theory of ultimate responsibility is libertarian theory. Its innovative nature makes it possible to discuss the neurophysiological basis of its postulates. Using the functions of the midbrain dopaminergic system as an example, this article provides an overview of this neurophysiological basis. According to Kane, if we are to be ultimately responsible for our wills as well as for our actions, some actions in our lives must lack sufficient motives and causes. These are self-forming actions. Dopamine is hypothesized to mediate self-forming action execution. Dopamine not only mediates action but also ensures synaptic plasticity in the brain, that is, learning from action; hence, dopamine changes the acting individual and provides the formation of our own wills. The basal ganglia, which are the main target of dopamine in the brain, act through parallel pathways and are involved in decision-making processes. Dopamine is also involved in the regulation of the neurodynamical properties of prefrontal cortex networks with random spiking noise. It can be assumed that the activity of the dopaminergic system is closely related to the physiological basis of free will.

Temporal Patterns of Angular Displacement of Endosomes: Insights into Motor Protein Exchange Dynamics

The material transport system, facilitated by motor proteins, plays a vital role in maintaining a non-equilibrium cellular state. However, understanding the temporal coordination of motor protein activity requires an advanced imaging technique capable of measuring 3D angular displacement in real-time. In this study, a Fourier transform-based plasmonic dark-field microscope has been developed using anisotropic nanoparticles, enabling the prolonged and simultaneous observation of endosomal lateral and rotational motion. A sequence of discontinuous 3D angular displacements has been observed during the pause and run phases of transport. Notably, a serially correlated temporal pattern in the intermittent rotational events has been demonstrated during the tug-of-war mechanism, indicating Markovian switching between the exploitational and explorational modes of motor protein exchange prior to resuming movement. Alterations in transition frequency and the exploitation-to-exploration ratio upon dynein inhibitor treatment highlight the relationship between disrupted motor coordination and reduced endosomal transport efficiency. Collectively, these results suggest the importance of orchestrated temporal motor protein patterns for efficient cellular transport.

Familiarity and social relationships in degus (Octodon degus)

Degus (Octodon degus) are a highly gregarious species of caviomorph rodent native to South America. Kinship does not appear to play a role in degu social structure, and alloparenting is often observed between unrelated females. We hypothesize that female degus readily establish new, cooperative peer relationships. Here we examined changes in dyadic behavior as individuals became more familiar, testing the prediction that interactions between female strangers would quickly resemble those of cagemates. Adult degus underwent a several week series of 20 minute "reunion" social exposures, interleaving reunions with initial strangers and, as a control, familiar cagemates. Males showed initially higher levels of interaction with strangers that converged with cagemate levels over experience. Females could be split into two groups: those that consistently interacted more with strangers (SC-HIGH) and those that did not (SC-LOW); however, unlike males, the higher interaction levels observed between strangers did not change with familiarity. Following 10 reunion sessions female strangers were housed together to create "new cagemates". Even after co-housing, SC-HIGH (but not SC-LOW) females continued to interact more with the relatively unfamiliar peer than their prior cagemate, particularly in face-to-face and rear-sniffing interactions. A final set of reunions with new strangers found that individual differences in female responses to social novelty were preserved. These results reveal sex differences in the rules relating familiarization to social relationships in degus, and that female predispositions toward cooperation may be due to inherent responses to new individuals more than to how they negotiate relationships over time.

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.

A Comparison of Rapid Rule-Learning Strategies in Humans and Monkeys

Interspecies comparisons are key to deriving an understanding of the behavioral and neural correlates of human cognition from animal models. We perform a detailed comparison of the strategies of female macaque monkeys to male and female humans on a variant of the Wisconsin Card Sorting Test (WCST), a widely studied and applied task that provides a multiattribute measure of cognitive function and depends on the frontal lobe. WCST performance requires the inference of a rule change given ambiguous feedback. We found that well-trained monkeys infer new rules three times more slowly than minimally instructed humans. Input-dependent hidden Markov model-generalized linear models were fit to their choices, revealing hidden states akin to feature-based attention in both species. Decision processes resembled a win-stay, lose-shift strategy with interspecies similarities as well as key differences. Monkeys and humans both test multiple rule hypotheses over a series of rule-search trials and perform inference-like computations to exclude candidate choice options. We quantitatively show that perseveration, random exploration, and poor sensitivity to negative feedback account for the slower task-switching performance in monkeys.

Exploration, exploitation, and development: Developmental shifts in decision-making

Decision-making requires balancing exploration with exploitation, yet children are highly exploratory, with exploration decreasing with development. Less is known about what drives these changes. We examined the development of decision-making in 188 three- to eight-year-old children (M = 64 months; 98 girls) and 26 adults (M = 19 years; 13 women). Children were recruited from ethnically diverse suburban middle-class neighborhoods of Columbus, Ohio, USA. Results indicate that mature reward-based choices emerge relatively late in development, with children tending to over-explore. Computational modeling suggests that this exploration is systematic rather than random, as children tend to avoid repeating choices made on the previous trial. This pattern of exploration (reminiscent of novelty preference) decreased with development, whereas the tendency to exploit increased.

Simple autonomous agents can enhance creative semantic discovery by human groups

Innovation is challenging, and theory and experiments indicate that groups may be better able to identify and preserve innovations than individuals. But innovation within groups faces its own challenges, including groupthink and truncated diffusion. We performed experiments involving a game in which people search for ideas in various conditions: alone, in networked social groups, or in networked groups featuring autonomous agents (bots). The objective was to search a semantic space of 20,000 nouns with defined similarities for an arbitrary noun with the highest point value. Participants (N = 1875) were embedded in networks (n = 125) of 15 nodes to which we sometimes added 2 bots. The bots had 3 possible strategies: they shared a random noun generated by their immediate neighbors, or a noun most similar from among those identified, or a noun least similar. We first confirm that groups are better able to explore a semantic space than isolated individuals. Then we show that when bots that share the most similar noun operate in groups facing a semantic space that is relatively easy to navigate, group performance is superior. Simple autonomous agents with interpretable behavior can affect the capacity for creative discovery of human groups.

Motor Strategies: The Role of Active Behavior in Spatial Hearing Research

When completing a task, the ability to implement behavioral strategies to solve it in an effective and cognitively less-demanding way is extremely adaptive for humans. This behavior makes it possible to accumulate evidence and test one's own predictions about the external world. In this work, starting from examples in the field of spatial hearing research, I analyze the importance of considering motor strategies in perceptual tasks, and I stress the urgent need to create ecological experimental settings, which are essential in allowing the implementation of such behaviors and in measuring them. In particular, I will consider head movements as an example of strategic behavior implemented to solve acoustic space-perception tasks.

Neural mechanisms of information seeking

We ubiquitously seek information to make better decisions. Particularly in the modern age, when more information is available at our fingertips than ever, the information we choose to collect determines the quality of our decisions. Decision neuroscience has long adopted empirical approaches where the information available to decision-makers is fully controlled by the researchers, leaving neural mechanisms of information seeking less understood. Although information seeking has long been studied in the context of the exploration-exploitation trade-off, recent studies have widened the scope to investigate more overt information seeking in a way distinct from other decision processes. Insights gained from these studies, accumulated over the last few years, raise the possibility that information seeking is driven by the reward system signaling the subjective value of information. In this piece, we review findings from the recent studies, highlighting the conceptual and empirical relationships between distinct literatures, and discuss future research directions necessary to establish a more comprehensive understanding of how individuals seek information as a part of value-based decision-making.

Performance errors during rodent learning reflect a dynamic choice strategy

Humans, even as infants, use cognitive strategies, such as exploration and hypothesis testing, to learn about causal interactions in the environment. In animal learning studies, however, it is challenging to disentangle higher-order behavioral strategies from errors arising from imperfect task knowledge or inherent biases. Here, we trained head-fixed mice on a wheel-based auditory two-choice task and exploited the intra- and inter-animal variability to understand the drivers of errors during learning. During learning, performance errors are dominated by a choice bias, which, despite appearing maladaptive, reflects a dynamic strategy. Early in learning, mice develop an internal model of the task contingencies such that violating their expectation of reward on correct trials (by using short blocks of non-rewarded "probe" trials) leads to an abrupt shift in strategy. During the probe block, mice behave more accurately with less bias, thereby using their learned stimulus-action knowledge to test whether the outcome contingencies have changed. Despite having this knowledge, mice continued to exhibit a strong choice bias during reinforced trials. This choice bias operates on a timescale of tens to hundreds of trials with a dynamic structure, shifting between left, right, and unbiased epochs. Biased epochs also coincided with faster motor kinematics. Although bias decreased across learning, expert mice continued to exhibit short bouts of biased choices interspersed with longer bouts of unbiased choices and higher performance. These findings collectively suggest that during learning, rodents actively probe their environment in a structured manner to refine their decision-making and maintain long-term flexibility.

Dynamic diversity is the answer to proxy failure

We argue that a diverse and dynamic pool of agents mitigates proxy failure. Proxy modularity plays a key role in the ongoing production of diversity. We review examples from a range of scales.

Approximate information for efficient exploration-exploitation strategies

This paper addresses the exploration-exploitation dilemma inherent in decision-making, focusing on multiarmed bandit problems. These involve an agent deciding whether to exploit current knowledge for immediate gains or explore new avenues for potential long-term rewards. We here introduce a class of algorithms, approximate information maximization (AIM), which employs a carefully chosen analytical approximation to the gradient of the entropy to choose which arm to pull at each point in time. AIM matches the performance of Thompson sampling, which is known to be asymptotically optimal, as well as that of Infomax from which it derives. AIM thus retains the advantages of Infomax while also offering enhanced computational speed, tractability, and ease of implementation. In particular, we demonstrate how to apply it to a 50-armed bandit game. Its expression is tunable, which allows for specific optimization in various settings, making it possible to surpass the performance of Thompson sampling at short and intermediary times.

The structure and development of explore-exploit decision making

A critical component of human learning reflects the balance people must achieve between focusing on the utility of what they know versus openness to what they have yet to experience. How individuals decide whether to explore new options versus exploit known options has garnered growing interest in recent years. Yet, the component processes underlying decisions to explore and whether these processes change across development remain poorly understood. By contrasting a variety of tasks that measure exploration in slightly different ways, we found that decisions about whether to explore reflect (a) random exploration that is not explicitly goal-directed and (b) directed exploration to purposefully reduce uncertainty. While these components similarly characterized the decision-making of both youth and adults, younger participants made decisions that were less strategic, but more exploratory and flexible, than those of adults. These findings are discussed in terms of how people adapt to and learn from changing environments over time.Data has been made available in the Open Science Foundation platform (osf.io).

The generative neural microdynamics of cognitive processing

The entorhinal cortex and hippocampus form a recurrent network that informs many cognitive processes, including memory, planning, navigation, and imagination. Neural recordings from these regions reveal spatially organized population codes corresponding to external environments and abstract spaces. Aligning the former cognitive functionalities with the latter neural phenomena is a central challenge in understanding the entorhinal-hippocampal circuit (EHC). Disparate experiments demonstrate a surprising level of complexity and apparent disorder in the intricate spatiotemporal dynamics of sequential non-local hippocampal reactivations, which occur particularly, though not exclusively, during immobile pauses and rest. We review these phenomena with a particular focus on their apparent lack of physical simulative realism. These observations are then integrated within a theoretical framework and proposed neural circuit mechanisms that normatively characterize this neural complexity by conceiving different regimes of hippocampal microdynamics as neuromarkers of diverse cognitive computations.

Addressing the data bottleneck in medical deep learning models using a human-in-the-loop machine learning approach

Any machine learning (ML) model is highly dependent on the data it uses for learning, and this is even more important in the case of deep learning models. The problem is a data bottleneck, i.e. the difficulty in obtaining an adequate number of cases and quality data. Another issue is improving the learning process, which can be done by actively introducing experts into the learning loop, in what is known as human-in-the-loop (HITL) ML. We describe an ML model based on a neural network in which HITL techniques were used to resolve the data bottleneck problem for the treatment of pancreatic cancer. We first augmented the dataset using synthetic cases created by a generative adversarial network. We then launched an active learning (AL) process involving human experts as oracles to label both new cases and cases by the network found to be suspect. This AL process was carried out simultaneously with an interactive ML process in which feedback was obtained from humans in order to develop better synthetic cases for each iteration of training. We discuss the challenges involved in including humans in the learning process, especially in relation to human–computer interaction, which is acquiring great importance in building ML models and can condition the success of a HITL approach. This paper also discusses the methodological approach adopted to address these challenges.

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.

Information foraging with an oracle

During ecological decisions, such as when foraging for food or selecting a weekend activity, we often have to balance the costs and benefits of exploiting known options versus exploring novel ones. Here, we ask how individuals address such cost-benefit tradeoffs during tasks in which we can either explore by ourselves or seek external advice from an oracle (e.g., a domain expert or recommendation system). To answer this question, we designed two studies in which participants chose between inquiring (at a cost) for expert advice from an oracle, or to search for options without guidance, under manipulations affecting the optimal choice. We found that participants showed a greater propensity to seek expert advice when it was instrumental to increase payoff (study A), and when it reduced choice uncertainty, above and beyond payoff maximization (study B). This latter result was especially apparent in participants with greater trait-level intolerance of uncertainty. Taken together, these results suggest that we seek expert advice for both economic goals (i.e., payoff maximization) and epistemic goals (i.e., uncertainty minimization) and that our decisions to ask or not ask for advice are sensitive to cost-benefit tradeoffs.

Evidence for optimal semantic search throughout adulthood

As people age, they learn and store new knowledge in their semantic memory. Despite learning a tremendous amount of information, people can still recall information relevant to the current situation with ease. To accomplish this, the mind must efficiently organize and search a vast store of information. It also must continue to retrieve information effectively despite changes in cognitive mechanisms due to healthy aging, including a general slowing in information processing and a decline in executive functioning. How effectively does the mind of an individual adjust its search to account for changes due to aging? We tested 746 people ages 25 through 69 on a semantic fluency task (free listing animals) and found that, on average, retrieval follows an optimal path through semantic memory. Participants tended to list a sequence of semantically related animals (e.g., lion, tiger, puma) before switching to a semantically unrelated animal (e.g., whale). We found that the timing of these transitions to semantically unrelated animals was remarkably consistent with an optimal strategy for maximizing the overall rate of retrieval (i.e., the number of animals listed per unit time). Age did not affect an individual's deviation from the optimal strategy given their general performance, suggesting that people adapt and continue to search memory optimally throughout their lives. We argue that this result is more likely due to compensating for a general slowing than a decline in executive functioning.

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.

Body appearance values modulate risk aversion in eating restriction

The understanding of eating disorders is hindered by the lack of integration between existing psychosocial and neurobiological approaches. We address this problem by developing a novel transdiagnostic and computational approach to eating restriction decisions. We first validated a novel paradigm which extends an established monetary risk task to involve body stimuli with psychosocial values. We used advanced behavioral data analysis of a large (total N = 539) sample of women from across the eating restraint spectrum, including those with anorexia nervosa (AN; n = 31), recovered from AN (n = 23), and subclinical women with varying levels of eating restraint (n = 485), obtained from an online experiment, public event, and laboratory-based study. We found that social and motivational values regarding body appearance have a significant effect on value-based, decision making in eating restriction. Subsequently, validated descriptive and predictive advanced computational modeling indicated that these behaviors are driven by an aversion to risk rather than loss, with desirable body outcomes being associated with less risk aversion, and undesirable body outcomes linked to greater risk aversion. These findings indicate that cognitive and social factors influence eating decisions by distinct mechanisms. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Efficiency traps beyond the climate crisis: exploration-exploitation trade-offs and rebound effects

Higher levels of economic activity are often accompanied by higher energy use and consumption of natural resources. As fossil fuels still account for 80% of the global energy mix, energy consumption remains closely linked to greenhouse gas (GHG) emissions and thus to climate change. Under the assumption of sufficiently elastic demand, this reality of global economic development based on permanent growth of economic activity, brings into play the Jevons Paradox, which hypothesises that increases in the efficiency of resource use leads to increases in resource consumption. Previous research on the rebound effects has limitations, including a lack of studies on the connection between reinforcement learning and environmental consequences. This paper develops a mathematical model and computer simulator to study the effects of micro-level exploration-exploitation strategies on efficiency, consumption and sustainability, considering different levels of direct and indirect rebound effects. Our model shows how optimal exploration-exploitation strategies for increasing efficiency can lead to unsustainable development patterns if they are not accompanied by demand reduction measures, which are essential for mitigating climate change. Moreover, our paper speaks to the broader issue of efficiency traps by highlighting how indirect rebound effects not only affect primary energy (PE) consumption and GHG emissions, but also resource consumption in other domains. By linking these issues together, our study sheds light on the complexities and interdependencies involved in achieving sustainable development goals. This article is part of the theme issue 'Climate change adaptation needs a science of culture'.

Cognitive Archeology and the Attentional System: An Evolutionary Mismatch for the Genus Homo

Brain evolution is a key topic in evolutionary anthropology. Unfortunately, in this sense the fossil record can usually support limited anatomical and behavioral inferences. Nonetheless, information from fossil species is, in any case, particularly valuable, because it represents the only direct proof of cerebral and behavioral changes throughout the human phylogeny. Recently, archeology and psychology have been integrated in the field of cognitive archeology, which aims to interpret current cognitive models according to the evidence we have on extinct human species. In this article, such evidence is reviewed in order to consider whether and to what extent the archeological record can supply information regarding changes of the attentional system in different taxa of the human genus. In particular, behavioral correlates associated with the fronto-parietal system and working memory are employed to consider recent changes in our species, Homo sapiens, and a mismatch between attentional and visuospatial ability is hypothesized. These two functional systems support present-moment awareness and mind-wandering, respectively, and their evolutionary unbalance can explain a structural sensitivity to psychological distress in our species.

Mnemicity: A Cognitive Gadget?

Episodic representations can be entertained either as "remembered" or "imagined"-as outcomes of experience or as simulations of such experience. Here, we argue that this feature is the product of a dedicated cognitive function: the metacognitive capacity to determine the mnemicity of mental event simulations. We argue that mnemicity attribution should be distinguished from other metacognitive operations (such as reality monitoring) and propose that this attribution is a "cognitive gadget"-a distinctively human ability made possible by cultural learning. Cultural learning is a type of social learning in which traits are inherited through social interaction. In the case of mnemicity, one culturally learns to discriminate metacognitive "feelings of remembering" from other perceptual, emotional, action-related, and metacognitive feelings; to interpret feelings of remembering as indicators of memory rather than imagination; and to broadcast the interpreted feelings in culture- and context-specific ways, such as "I was there" or "I witnessed it myself." We review evidence from the literature on memory development and scaffolding, metacognitive learning and teaching, as well as cross-cultural psychology in support of this view before pointing out various open questions about the nature and development of mnemicity highlighted by our account.

A shared novelty-seeking basis for creativity and curiosity

Curiosity and creativity are central pillars of human growth and invention. Although they have been studied extensively in isolation, the relationship between them has not yet been established. We propose that both curiosity and creativity emanate from the same mechanism of novelty seeking. We first present a synthesis showing that curiosity and creativity are affected similarly by a number of key cognitive faculties such as memory, cognitive control, attention, and reward. We then review empirical evidence from neuroscience research, indicating that the same brain regions are involved in both curiosity and creativity, focusing on the interplay between three major brain networks: the default mode network, the salience network, and the executive control network. After substantiating the link between curiosity and creativity, we propose a novelty-seeking model (NSM) that underlies them and suggests that the manifestation of the NSM is governed by one's state of mind.

Dynamic pathogen detection and social feedback shape collective hygiene in ants

Cooperative disease defense emerges as group-level collective behavior, yet how group members make the underlying individual decisions is poorly understood. Using garden ants and fungal pathogens as an experimental model, we derive the rules governing individual ant grooming choices and show how they produce colony-level hygiene. Time-resolved behavioral analysis, pathogen quantification, and probabilistic modeling reveal that ants increase grooming and preferentially target highly-infectious individuals when perceiving high pathogen load, but transiently suppress grooming after having been groomed by nestmates. Ants thus react to both, the infectivity of others and the social feedback they receive on their own contagiousness. While inferred solely from momentary ant decisions, these behavioral rules quantitatively predict hour-long experimental dynamics, and synergistically combine into efficient colony-wide pathogen removal. Our analyses show that noisy individual decisions based on only local, incomplete, yet dynamically-updated information on pathogen threat and social feedback can lead to potent collective disease defense.