Project description:Curiosity-driven exploration involves actively engaging with the environment to learn from it. Here, we hypothesize that the cognitive mechanisms underlying exploratory behavior may differ across individuals depending on personal characteristics such as autistic traits. In turn, this variability might influence successful exploration. To investigate this, we collected self- and other-reports of autistic traits from university students, and tested them in an exploration task in which participants could learn the hiding patterns of multiple characters. Participants' prediction errors and learning progress (i.e., the decrease in prediction error) on the task were tracked with a hierarchical delta-rule model. Crucially, participants could freely decide when to disengage from a character and what to explore next. We examined whether autistic traits modulated the relation of prediction errors and learning progress with exploration. We found that participants with lower scores on other-reports of insistence-on-sameness and general autistic traits were less persistent, primarily relying on learning progress during the initial stages of exploration. Conversely, participants with higher scores were more persistent and relied on learning progress in later phases of exploration, resulting in better performance in the task. This research advances our understanding of the interplay between autistic traits and exploration drives, emphasizing the importance of individual traits in learning processes and highlighting the need for personalized learning approaches.
Project description:Curiosity-driven learning is foundational to human cognition. By enabling humans to autonomously decide when and what to learn, curiosity has been argued to be crucial for self-organizing temporally extended learning curricula. However, the mechanisms driving people to set intrinsic goals, when they are free to explore multiple learning activities, are still poorly understood. Computational theories propose different heuristics, including competence measures (e.g., percent correct) and learning progress, that could be used as intrinsic utility functions to efficiently organize exploration. Such intrinsic utilities constitute computationally cheap but smart heuristics to prevent people from laboring in vain on unlearnable activities, while still motivating them to self-challenge on difficult learnable activities. Here, we provide empirical evidence for these ideas by means of a free-choice experimental paradigm and computational modeling. We show that while humans rely on competence information to avoid easy tasks, models that include a learning-progress component provide the best fit to task selection data. These results bridge the research in artificial and biological curiosity, reveal strategies that are used by humans but have not been considered in computational research, and introduce tools for probing how humans become intrinsically motivated to learn and acquire interests and skills on extended time scales.
Project description:It is necessary to understand the morphology of the vagus nerve (VN) to design and deliver effective and selective vagus nerve stimulation (VNS) because nerve morphology influences fiber responses to electrical stimulation. Specifically, nerve diameter (and thus, electrode-fiber distance), fascicle diameter, fascicular organization, and perineurium thickness all significantly affect the responses of nerve fibers to electrical signals delivered through a cuff electrode. We quantified the morphology of cervical and subdiaphragmatic VNs in humans, pigs, and rats: effective nerve diameter, number of fascicles, effective fascicle diameters, proportions of endoneurial, perineurial, and epineurial tissues, and perineurium thickness. The human and pig VNs were comparable sizes (∼2 mm cervically; ∼1.6 mm subdiaphragmatically), while the rat nerves were ten times smaller. The pig nerves had ten times more fascicles-and the fascicles were smaller-than in human nerves (47 vs. 7 fascicles cervically; 38 vs. 5 fascicles subdiaphragmatically). Comparing the cervical to the subdiaphragmatic VNs, the nerves and fascicles were larger at the cervical level for all species and there were more fascicles for pigs. Human morphology generally exhibited greater variability across samples than pigs and rats. A prior study of human somatic nerves indicated that the ratio of perineurium thickness to fascicle diameter was approximately constant across fascicle diameters. However, our data found thicker human and pig VN perineurium than those prior data: the VNs had thicker perineurium for larger fascicles and thicker perineurium normalized by fascicle diameter for smaller fascicles. Understanding these differences in VN morphology between preclinical models and the clinical target, as well as the variability across individuals of a species, is essential for designing suitable cuff electrodes and stimulation parameters and for informing translation of preclinical results to clinical application to advance the therapeutic efficacy of VNS.
Project description:Successful behaviour depends on the right balance between maximising reward and soliciting information about the world. Here, we show how different types of information-gain emerge when casting behaviour as surprise minimisation. We present two distinct mechanisms for goal-directed exploration that express separable profiles of active sampling to reduce uncertainty. 'Hidden state' exploration motivates agents to sample unambiguous observations to accurately infer the (hidden) state of the world. Conversely, 'model parameter' exploration, compels agents to sample outcomes associated with high uncertainty, if they are informative for their representation of the task structure. We illustrate the emergence of these types of information-gain, termed active inference and active learning, and show how these forms of exploration induce distinct patterns of 'Bayes-optimal' behaviour. Our findings provide a computational framework for understanding how distinct levels of uncertainty systematically affect the exploration-exploitation trade-off in decision-making.
Project description:Cognitive maps are thought to arise, at least in part, from our intrinsic curiosity to explore unknown places. However, it remains untested how curiosity shapes aspects of spatial exploration in humans. Combining a virtual reality task with indices of exploration complexity, we found that pre-exploration curiosity states predicted how much individuals spatially explored environments, whereas markers of visual exploration determined post-exploration feelings of interest. Moreover, individual differences in curiosity traits, particularly Stress Tolerance, modulated the relationship between curiosity and spatial exploration, suggesting the capacity to cope with uncertainty enhances the curiosity-exploration link. Furthermore, both curiosity and spatial exploration predicted how precisely participants could recall spatial-relational details of the environment, as measured by a sketch map task. These results provide new evidence for a link between curiosity and exploratory behaviour, and how curiosity might shape cognitive map formation.
Project description:People are willing to spend time and money to receive information and content they are curious about, such as answers to trivia questions, suggesting they find information rewarding. In neurotypical adults, states of high curiosity satisfaction are also known to enhance the learning and memory of information encountered in that state. Here, we investigated whether the relationship between curiosity, satisfaction, and learning was altered in a group with specific learning difficulty (dyslexia). Using a willingness-to-wait paradigm, we observed that adults with and without dyslexia are willing to spend time waiting for verbal and visual information. This indicates that the same "wanting" mechanisms are seen in individuals with dyslexia for information. We then examined whether information that was desirable was also associated with enhanced memory. Our findings indicate that information does function like a reward, with the gap between expected and received information driving memory. However, this memory effect was attenuated in individuals with dyslexia. These findings point to the need to understand how reward drives learning and why this relationship might differ in dyslexia.
Project description:Many nocturnally active fireflies use precisely timed bioluminescent patterns to identify mates, making them especially vulnerable to light pollution. As urbanization continues to brighten the night sky, firefly populations are under constant stress, and close to half of the species are now threatened. Ensuring the survival of firefly biodiversity depends on a large-scale conservation effort to monitor and protect thousands of populations. While species can be identified by their flash patterns, current methods require expert measurement and manual classification and are infeasible given the number and geographic distribution of fireflies. Here we present the application of a recurrent neural network (RNN) for accurate automated firefly flash pattern classification. Using recordings from commodity cameras, we can extract flash trajectories of individuals within a swarm and classify their species with an accuracy of approximately seventy percent. In addition to its potential in population monitoring, automated classification provides the means to study firefly behavior at the population level. We employ the classifier to measure and characterize the variability within and between swarms, unlocking a new dimension of their behavior. Our method is open source, and deployment in community science applications could revolutionize our ability to monitor and understand firefly populations.
Project description:Research has started to acknowledge the importance of emotions for complex learning and cognitive performance. However, research on epistemic emotions has only recently become more prominent. Research in educational psychology in particular has mostly focused on examining achievement emotions instead of epistemic emotions. Furthermore, only few studies have addressed functional mechanisms underlying multiple different epistemic emotions simultaneously, and only one study has systematically compared the origins and effects of epistemic emotions with other emotions relevant to knowledge generation (i.e., achievement emotions; Vogl et al., 2019). The present article aimed to replicate the findings from Vogl et al. (2019) exploring within-person interrelations, origins, and outcomes of the epistemic emotions surprise, curiosity, and confusion, and the achievement emotions pride and shame, as well as to analyze their robustness and generalizability across two different study settings (online; Study 1, n = 169 vs. lab; Study 2, n = 79). In addition, the previous findings by Vogl et al. (2019, Study 3) and the present two new studies were meta-analytically integrated to consolidate evidence on origins and outcomes of epistemic emotions. The results of the two new studies largely replicated the findings by Vogl et al. (2019). Combined with the meta-analytic results, the findings confirm distinct patterns of antecedents for epistemic vs. achievement emotions: Pride and shame were more strongly associated with the correctness of a person's answer (i.e., accuracy), whereas surprise, curiosity, and confusion were more strongly related to incorrect responses a person was confident in (i.e., high-confidence errors) producing cognitive incongruity. Furthermore, in contrast to achievement emotions, epistemic emotions had positive effects on the exploration of knowledge. Implications for research and practice are discussed.
Project description:This paper considers how an interdisciplinary approach to the "wicked problem" of plastics pollution offers unique and important collaborative possibilities. Specially, the paper considers the approach of the Synthetic Collective, a group comprising artists, humanities scholars, and scientists. Considering first how artists and scientists might respond differently to tracking, mapping, understanding, and representing plastics pollution, we then look for potential points of commonality across disciplinary difference. In respect to the urgent and multifaceted problem of marine plastics pollution in the Great Lakes region, we ask what are some of the successes and pitfalls of bringing together diverse approaches and interests? The paper concludes with a clear strategy: a set of instructions geared towards building successful interdisciplinary collaborations. Ultimately, we conclude that a strong relationship amongst scientists and artists is possible, fruitful, and indeed warranted when shared goals are the driving principle of the group.
Project description:The Mars Science Laboratory rover Curiosity engaged in a monthlong campaign investigating the Bagnold dune field in Gale crater. What represents the first in situ investigation of a dune field on another planet has resulted in a number of discoveries. Collectively, the Curiosity rover team has compiled the most comprehensive survey of any extraterrestrial aeolian system visited to date with results that yield important insights into a number of processes, including sediment transport, bed form morphology and structure, chemical and physical composition of aeolian sand, and wind regime characteristics. These findings and more are provided in detail by the JGR-Planets Special Issue Curiosity's Bagnold Dunes Campaign, Phase I.