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Visual perception is a field of knowledge belonging to Cognitive Psychology. It was realized that such knowledge could contribute to the indexing of photographs based on the understanding of human cognition processes to identify how the individual interprets and their visual perception of a photograph. This understanding helps to establish criteria for selecting keywords for indexing photographs. This research presents Bloomer's (1990) visual perception factors and reflects on the literature review of how such studies can contribute to indexing photographs. As a result, two points stand out: visual perception can contribute to organizing more efficient and intuitive online photography catalogues, providing users with a better experience and ease in retrieving visual content, and finally, it can help information professionals select terms relevant to users., La percepción visual es un campo de conocimiento perteneciente a la Psicología Cognitiva. Se comprendió que dicho conocimiento puede contribuir a la indización de fotografías basada en la comprensión de los procesos de cognición humana para identificar cómo el individuo interpreta y cuál es su percepción visual de una fotografía. Esta comprensión ayuda a establecer criterios para seleccionar palabras clave para indizar fotografías. Esta investigación presenta los factores de percepción visual de Bloomer (1990) y reflexiona sobre la revisión de la literatura sobre cómo dichos estudios pueden contribuir al proceso de indexación de fotografías. Como resultado, destacan dos puntos: que la percepción visual puede contribuir a organizar catálogos de fotografía online más eficientes e intuitivos, proporcionando a los usuarios una mejor experiencia y facilidad en el proceso de recuperación de contenidos visuales; Finalmente, puede ayudar a los profesionales de la información a seleccionar términos que sean relevantes para los usuarios., A percepção visual é um campo do conhecimento pertencente à Psicologia Cognitiva. Percebeu-se que tal conhecimento pode contribuir para a indexação de fotografías a partir  do entendimento dos processos de cognição humana para identificar como o indivíduo interpreta e  qual  a sua percepção visual de  uma fotografia . Esta compreensão  ajuda a, estabelecer critérios para a seleção de palavras-chave para a indexação de fotografias.  Esta  pesquisa apresenta os fatores da percepção visual de Bloomer (1990) e faz uma reflexão a partir da revisão de literatura de como tais estudos podem contribuir para o processo de indexação de fotografias. Como resultado destacam-se  dois pontos: que a percepção visual pode contribuir para organizar catálogos online de fotografias mais eficientes e intuitivos, proporcionando aos usuários uma melhor experiência e facilidade no processo de recuperação de conteúdo visual; por último pode contribuir para que os profissinais da informação selecionem termos relevantes para os usuários.

Background: Evidence from the science of learning suggests that playful learning pedagogical approaches exist along a spectrum and can support student learning. Leveraging active engagement, iterative, socially interactive, meaningful, and joyful interactions with content also supports student learning. Translating these concepts into guidance and support for teachers is lacking. Method: We introduce a tool designed to support teachers in implementing across the facilitation spectrum and leverage the characteristics that help children learn. Across three international contexts, we engaged with 1207 teachers and the tool was used 4911 times. Results: Student age, the intended learning goal, and context influenced teachers’ use of the tool, suggesting that contextualization is critical, even when basing programs on evidence-based, universal principles given by the science of learning. Conclusion: Science of learning research must be effectively translated but we must use evidence from teachers and real-life classrooms to inform those studying the science of learning.

Prediction plays a critical role in comprehending human language. Many theoretical and computational models have attempted to characterize how we use context to facilitate language processing in noisy environments either with or without relying on predictive processing. Despite these attempts, we do not yet have a complete understanding of the role of prediction in language processing. Predictive coding models have recently gained popularity as potential architectures for the role of prediction during language comprehension. These models suggest that predictions about bottom-up inputs are continuously generated from higher cortical levels to lower levels in a hierarchical manner – i.e., a particular level generates predictions about the next lower level. As bottom-up input is encounter by each level of processing, prediction error is computed by comparing the input with the top-down prediction. The goal of this dissertation was to assess whether predictive coding models can account for the time course of information retrieval during predictive language processing. Specifically, the studies described examine the time course of pre-activations of lexical and sub-lexical features in both monolinguals and bilinguals using a combination of decoding electroencephalogram (EEG) with machine-learning classifiers and mass univariate event-related potential analysis. Chapter 1 describes an experiment that compared three frequently used models for signal classification – support vector machines (SVM), linear discriminant analysis (LDA), and random forest (RF) to determine which is best-suited for analyzing word pair prediction paradigms. Results showed that SVM was the best performing classifier of the three within two data sets from separate visual word priming paradigms. Chapter 2 describes an experiment which used EEG decoding with SVM classifiers and mass univariate ERP analyses to identify the time course of information retrieval prior to the onset of accurately predicted

Machines curate our news narratives to weaponize our minds against us, making commonsense politics impossible because we no longer share a common baseline of facts. Many helplessly accept this alienating and accelerating reality as the new normal. However, technology guided by humanistic principles and cognitive science may restore our vitality. My dissertation integrates psychology experiments on individuals and networked-groups, computational cognitive modeling, large-scale analyses of social media, open-source software development, and citizen science principles to illustrate how online networks and generative artificial intelligence can promote healthier attitudes towards established evidence and each other. In Chapter 2, I analyze networked behavior and narrative agency across a series of online social network experiments (total N = 660, 13,200 interactions). Through a hashtag generation game I manipulated communication patterns within a group to encourage shared or polarized beliefs. Entropy dynamics of generated hashtags and language data revealed that belief and behavioral coherence vary according to neighborhood topology at both local and global levels. Rewards for aligning hashtags also shifted participants' causal language use when writing personal narratives about a disaster event. Given these findings, Chapter 3 introduces a computational framework rooted in Bayesian decision theory to disentangle how rewards (e.g., engagement metrics embedded in social media) ought to influence our beliefs about evidence, and describes how the framework can guide interventions on networked-groups. For better and worse, people's beliefs are sensitive to online interactions. Chapter 4 integrates large-scale analyses of internet discourse (100,000 interactions), belief-updating experiments (total N = 2,676), and interactive data visualizations to (1) identify features of persuasion in naturalistic online interactions, and (2) extend those features into a crowdsourced data

Curiosity motivates many of our everyday behaviors, including learning, hobbies, and goal pursuit. Theories of cognitive aging (e.g., Baltes & Baltes, 1990; Carstensen, 1999; Hess, 2014) suggest that knowledge-based goals may decline as we age in favor of social-emotional goals, and thus, maintaining curiosity to learn may not fit with our goals as we get older. However, curiosity in older age is associated with a variety of positive outcomes (Sakaki et al., 2018) and can improve learning and memory performance (Galli et al., 2018; Kang et al., 2009; McGillivray et al., 2015). The current dissertation examines how different forms of curiosity may shift across the adult lifespan (Chapter 2) as well as how curiosity works to influence learning, memory, and metacognition in both younger adults and older adults (Chapters 3 and 4). Though some work suggests that curiosity declines with age (e.g., Chu et al., 2020), this dissertation (Study 1) reports evidence that different types of curiosity may show differential relationships with age. Specifically, one’s general tendency to be curious may decrease with increasing age, but one’s curiosity in response to interesting material, like trivia questions, may increase as we age, suggesting we may be more selective about when and why we experience curiosity in older age. Additionally, curiosity continues to be a motivator of learning and memory throughout the lifespan. Chapter 3 explores how this intrinsic motivation may interact with extrinsic motivation (i.e., value). Results suggest that both forms of motivation may independently influence both younger and older adults’ memory, but show different patterns on more detailed associative memory (i.e., memory for the binding of two or more pieces of information). Finally, Chapter 4 examines whether curiosity can influence memory for true and false information. The evidence suggests that curiosity may also improve memory for whether information is true or false, but that these

Collaboration with other agents requires people to reflect on several aspects of their collaborator's capabilities: How good are they at a task? Do they have access to the same information as I do? How useful is their advice? This dissertation takes a closer look at how people answer these questions while interacting with other humans and more importantly, with AI agents. First, we discuss the role of mental models in facilitating people's interactions with other agents. In Chapter 2, we present a computational framework to understand how people assess the ability of other humans and AI agents. Our research reveals a discrepancy in people's assessments: individuals accurately gauge another human's ability on a task, but consistently overestimate an AI agent's performance on the same task. In Chapter 3, we examine how people navigate advice when a human or an AI advisor has access to different information than they do. We find that while people take into account this difference in information, they consistently underestimate the value of advice. Finally, in Chapter 4, using two case studies we demonstrate the utility of cognitive modeling in inferring people's latent reliance on AI. The first case study models people's decision to accept advice, and the second case study models people's decision to intervene in the AI's course of action. We conclude by discussing avenues for future work. Altogether, this dissertation uses a cognitive science lens to improve our understanding of human-AI interaction, highlighting the role of mental models and drawing valuable lessons from human-human interaction.

Children’s ability to use higher-order thinking and learn complex, higher-order concepts is crucial for academic and later employment success. One form of higher-order thinking is transfer, which occurs when learning in one context affects learning in another. Many science concepts require higher-order thinking and relational reasoning so understanding transfer in this domain is particularly valuable in understanding how children learn these concepts. The present studies consider how children’s science, technology, engineering, and mathematics (STEM) podcasts, digital audio programs that aim to engage children with STEM topics, and parent-child conversation while listening to podcasts support children’s learning and transfer. Children’s podcasts are a unique unimodal modality because they include features like conversation, description, and sound effects to encourage audio engagement. However, not much is known about how children learn from podcasts and the factors that could facilitate children’s transfer of science concepts presented in podcasts. Study 1 examined whether children learn from podcasts, and if supporting visual information affected their learning. Participants were 69 children between 7- and 8-years-old who listened (or listened and viewed related images) to an 11-minute science podcast about the water cycle and answered recall and transfer questions. Results from this study revealed no effect of modality on children’s learning, and children in both audio and audiovisual conditions performed above chance on transfer questions. Using a semantic textual similarity analysis, we showed that children in the audiovisual condition did not incorporate visual information in their description of concepts. These results highlight the value of podcasts as a unimodal context that could benefit higher-order concept learning. Study 2 investigated the effect of parent-child conversation while listening to a podcast on children’s learning and transfer. Participants w

Understanding abstract relations is a crucial aspect of human cognition. This thesis explores how children learn to reason about semantic relations, such as antonyms and synonyms, and the factors that enhance their ability to use these relations for analogical reasoning (e.g., understanding that big:small hold the same relation as clean:dirty). Chapter I investigates the early stages of how young children generate antonyms, identifies patterns in their responses across different parts of speech, and compares their abilities to those of relational and natural language models. Chapters II and III focus on how both children and models utilize antonyms to solve verbal analogies, and how relational language cues and semantic distance affect this skill. This thesis provides a comprehensive examination of the development of antonymy understanding and identifies key factors that can enhance the ability of both children and models to solve verbal analogies.

The modern world is densely populated by physical structures that were designed and made by people, from transient arrangements like stacks of books and sandwiches, to enduring constructions like bridges and skyscrapers. Physical assembly– the construction of a new object from existing parts– accounts for some of the most complex acts of human cognition. What are the core cognitive processes that underlie this ability? The study of physical assembly presents unique opportunities and challenges because it relies on interactions between multiple cognitive processes, including perception, working memory, planning, and action selection. This dissertation introduces new experimental methods to investigate these processes, by characterizing the impact of physical assembly experience on our ability to build. Moreover, it explores far-reaching consequences of assembly experience on cognition, including the ability to remember objects, as well as the language we use to communicate about them. Over three chapters, I investigate three consequences of assembly experience. In Chapter 1, I investigate how practice assembling objects changes the procedures we use to construct them, finding that people learn to build more quickly and accurately, and use increasingly consistent procedures to do so. In Chapter 2, I explore how assembling objects impacts our memory of those objects, finding that how well we remember an object depends crucially on the way we encode it during assembly. In Chapter 3, I go beyond the consequences of assembly for individuals to ask how shared assembly experience impacts how collaborators communicate about objects, and find that people coordinate on linguistic conventions for referring to increasingly abstract procedures over time. These results comprise a set of ways that people– individually and collectively– leverage prior assembly experience to improve their ability to build, elucidating one of the most pervasive and complex human behaviors. By clarifyi

Searching and exploring online is a part of our everyday lives – shaping how we learn, work and innovate. However, today, people are drowning in information, with few mechanisms for managing or synthesizing large volumes of disparate information. It is a struggle to find the right information or identify relevant unknown unknowns for those who lack knowledge of a particular domain or well-defined goals. Even experts juggle dozens of disparate information silos spread out across different apps, websites, and work sessions. This is cognitively overwhelming and time-consuming, preventing people from developing a comprehensive understanding, gaining deep insights, and achieving their creative potential. This is especially true in complex creative information work like scientific research, founding a startup or innovating to protect the public during a pandemic.As the Web paradigm evolves to include Generative AI models and beyond, we are experiencing a shift in how we search, learn, work and create. With this transformation in human-AI interaction, it is important to investigate how we might present the user with the right information in the right context, the right representation, and at the right time. This thesis explores this in the context of cognitively complex information work (such as knowledge discovery, synthesis, and creativity). It presents two types of contributions: (1) Empirical studies that further our understanding of how people explore, make sense of, and create using information on the Web. The studies follow a mixed-methods approach, combining large-scale and longitudinal quantitative data analysis with in-depth qualitative inquiry. (2) Computational and interaction techniques that augment these cognitive processes by seamlessly integrating knowledge from the Web into the user’s work context.Each study observes user behavior, challenges, and strategies at different stages of information exploration, sensemaking, and creative processes. Each system in

This Dissertation investigated the interplay between executive function, creative thinking, and examples. Over 200 participants completed this experiment consisting of a battery of five creative thinking tasks and a battery of seven executive function tasks. All participants completed two different versions of each of the creative thinking tasks, one version with the help of examples to get them started on idea generation and one version without the help of examples. Data were analyzed both as latent and observed variables. Key results indicated that: (1) participants generated ideas that were rated as more creative when they had the help of examples than when they did not have examples; (2) executive function (particularly inhibition) was positively related to creativity in both conditions; (3) the role of executive function was not observed to depend on whether examples were involved in the idea generation process; and (4) conformity to examples was not observed to mediate the relation between executive function and creativity.

Searching through a series of environments is a pervasive everyday experience and although visual search and sequence learning are long researched fields, little is known about people’s ability to learn a visual search sequence. Environments that require more visual search may disrupt sequence learning, for a multitude of reasons. They require more effort, time, and, if people were learning a sequence of eye movements, they would increase the noise to signal ratio. However, some visual search environments may permit sequence learning. In particular, when people search a familiar context of distractors, they can more quickly find the target than when searching a novel context. This dissertation investigated the impact of visual search demands (i.e. popout vs non-popout targets) and distractor environment (i.e. static vs consistently changing contexts vs random distractors) on sequence learning. The results show that sequence learning occurred in all conditions, suggesting that random noise in the environment and the need to perform visual search does not interfere with sequence learning. This finding has implications for understanding the mechanisms of sequence learning as well as implications for the everyday world. When people interact with user interfaces, they often engage in the same sequence of actions. These findings show that sequence learning occurs in a variety of cases and suggest that when user interface updates and items are no longer where and when users expect them, people will likely struggle to complete their tasks.

Information has always been contagious. Rumors, gossip, advice, knowledge, and wisdom have reliably spread between people via mediums such as radio waves, the written word, and in-person conversations among others. However, the scale of information contagion has expanded to a global scale with the proliferation of wireless communication technologies. While increased accessibility to information can produce mass societal benefits, these technologies can also facilitate the spread of conspiracies and misinformation, which has been an ongoing issue on social media platforms over the past decade. Previous work has adapted epidemiological approaches for modeling information contagion, where information is conceptualized as a biological pathogen. Despite the utility of the disease metaphor, information contagion differs in that the successful transmission of a message relies on cognitive processes of the receiver. These processes can involve a person’s capability and willingness to evaluate a post, emotional reaction to the topic content, and perceived credibility of the message sender. The current work will examine mechanisms for information contagion by assessing how factors related to cognitive effort, emotional affect, and social conformity influence social media engagement on the level of users (i.e., dispositional traits) and posts (i.e., textual features). Chapter 1 tests how dispositional traits of users such as tendency for reflective thinking, narcissism, and political orientation influence the likelihood to propagate health-related information in a newsfeed simulation exercise. Chapter 2 explores how properties of social media posts, specifically textual characteristics reflecting linguistic complexity, emotional affect, and use of social references influence contagion effects on the platforms Reddit and X (formerly ‘Twitter’). Chapter 3 adapts graph theory to construct semantic networks of message content to characterize differences in associations between top

Perceptual Learning (PL) refers to experience-based changes enhancing the ability to extract sensory information from the environment leading to alterations in perceptual processing. A pivotal inquiry in this field investigates the potential for adult perceptual systems to undergo modifications through experience. While historically, research in the field has primarily delved into isolating and understanding individual visual processes, recent years have witnessed a growing interest in harnessing PL for therapeutic interventions in visual impairments. However, the translational potential of such interventions is impeded by methodological constraints, including small sample sizes, homogeneity within participant populations, and challenges in replications. The core objective of my dissertation is to advance our understanding of visual PL by designing innovative methodologies and tools to explore its potential for translational applications. Each chapter of my dissertation contributes distinctively to this overarching aim: Chapter 1 provides a comprehensive review of extant PL literature, pinpointing prevailing limitations and gaps in the field; Chapter 2 introduces and validates PLFest, a cross platform open-source tool for PL research, fostering collaboration and data sharing within the scientific community; Chapter 3 introduces a gaze contingent display framework for PL research, utilizing simulated central vision loss as a model to assess specificity and generalizability of learning; and Chapter 4 examines the implications of a gamified visual rehabilitation strategy for promoting learning and designing targeted interventions for patients with schizophrenia. Through these multifaceted investigations, my thesis aims to deepen our understanding of visual PL dynamics and lay foundations for its broader application in clinical contexts.

Face recognition errors occur frequently, with consequences that range from personal embarrassment to eyewitness misidentification. Established interventions have taken a variety of approaches in attempts to improve face recognition, yet they have lacked in their capacity for practical use. With this in mind, I created an application-oriented training program in an effort to improve face recognition in real-world contexts. Specifically, I designed the training to teach individuals how to process faces holistically, or in terms of how facial features spatially relate to one another. After developing the training, I conducted three experiments to assess the general efficacy of the training, examine its capacity to improve recognition over time, and compare its impact against two established other-race face recognition interventions. Experiment samples consisted of 196 to 320 participants, whom I recruited through the UC Riverside Psychology subject pool and CloudResearch Connect. In all experiments, participants completed a baseline recognition memory task, followed by the training or an alternate condition (matched control in Experiments 1 and 2, individuation or cross-race effect awareness in Experiment 3), then completed another recognition memory task. In Experiment 2, participants completed two additional recognition memory tasks 24 hours and 1 week after the manipulation. Memory strength, operationalized as accuracy on the recognition memory task, was compared before versus after the manipulation to determine whether the training produced an improvement in recognition memory ability. Across the experiments, multilevel modeling revealed that the training did not lead to improved face recognition ability. Instead, training participants generally displayed poorer recognition memory ability after the manipulation compared to their average recognition ability at baseline. Slight fluctuations in recognition ability had returned to baseline levels after one week (Exper

This dissertation addresses how contextualized expertise and task design can improve wisdom of the crowd estimates. The first two chapters apply the wisdom of the crowd to two related tasks that require spatial knowledge. The third chapter applies the wisdom of the crowd to a subset ranking task. In Chapter 1, I investigate how framing effects impact the wisdom of the crowd. Participants selected tiles that either represented US states or African countries in two frames, present and absent. I constructed three wisdom of the crowd estimates: an unweighted average, a confidence-weighted average, and a wisdom of the crowd within estimate that combines an individual's responses across frames. I found that combining the estimates from the two frames resulted in an improved wisdom of the crowd estimate.In Chapter 2, I build on the wisdom of the crowd application for a task that again requires spatial knowledge. Participants supplied a point estimate and a radius centered at that point estimate for where various US cities were located. Unweighted and radius-weighted wisdom of the crowd estimates were more accurate than most individuals, but the cognitive model-based wisdom of the crowd estimates tended to be even more accurate. I describe how using cognitive modeling that contextualizes expertise led to improved wisdom of the crowd estimates.In Chapter 3, I present a new extension for the Thurstone model to partial ranking data. Ranking tasks have usually had participants rank all items, but I present two different types of partial ranking tasks where either an experimenter or a participant selects the items to be ranked. I demonstrate how the Thurstone model can be used to generate wisdom of the crowd estimates, and speculate how other partial ranking tasks can be developed to better elicit diverse estimates from the crowd.In all, these chapters detail specific applications of the wisdom of the crowd effect that better contextualize expertise, elicit multiple meaningful e

Humans often fail to accord with the predictions of optimal decision making models. How can we be such poor decision makers in simple task environments and yet also be deft navigators of the real world? This dissertation presents work suggesting that these two observations are likely related: Our decision making strategies have been shaped by the complexity and uncertainty of real-world decision problems, and we apply these strategies even in much simpler decision contexts. In each of the dissertation’s chapters, we consider a presumed suboptimal behavior and demonstrate how it can emerge from rational responses to uncertainty. In chapters 2 and 3, we focus on the case of patch foraging. We show that both adults’ over-exploitation and children’s over-exploration can stem from rational inference of the environment’s underlying structure. Our results reveal that these two opposing behaviors emerge from different structural priors. Finally, in chapter 4, we focus on the reward learning deficits that characterize anhedonia. Using a reinforcement learning model, we show that simulated agents who have rationally adapted to an unpredictable early life environment produce anhedonia-like behavior when later placed in a predictable environment. Collectively, this work demonstrates how multi-scale learning processes work to mitigate the many forms of uncertainty present in real-world decisions. By taking these learning processes into account, we are able to rationalize multiple “suboptimal” behaviors.

When an organism experiences a salient event, such as when a reward or punishment is received, it is crucial that the information pertaining to that stimulus is encoded and consolidated into memory. The memory of the salient event then allows the organism to continue seeking or avoiding that stimulus. However, it is essential that the organism is also able to recognize the events leading up to encountering the salient stimuli. Theoretically, this requires retroactive enhancement of memory. Retroactive enhancement of memory occurs when previously seemingly irrelevant memories are enhanced at a later time point due to a salient event. While there is theoretical support for the possibility of retroactive enhancement of memories, the empirical evidence in human participants has largely been mixed primarily due to methodological differences and conflation of learning paradigms. Furthermore, as prior studies that have attempted to elicit retroactive enhancement of memory using rewards have only used monetary rewards, it is unclear if social rewards could elicit the effect as well. The effect of retroactive enhancement of memory using rewards on false memories is also unclear. To address the inconsistencies and ambiguities in the literature, this dissertation examined the effects of monetary and social rewards on retroactive enhancement of memory and false memories using an operant conditioning paradigm in Study 1 and a classical conditioning paradigm in Study 2. First, while the data in Study 1 provided evidence of retroactive enhancement of memory for both monetary and social rewards, the data in Study 2 did not support retroactive enhancement of memory. Second, using a two-step conditioning process, results from Study 1 suggest that monetary and social rewards can exert comparable influence on memory in an operant conditioning paradigm. However, results from Study 2 demonstrated that recall in the conditioning phase of the social reward condition was significantly highe

In order to organize the information that people encounter in their environments they have to develop the ability to organize their experience into categories. Category learning has been studied using both stable environments in which the underlying categories do not change, and in dynamic environments in which the underlying category structure changes independent of people’s behavior. In many natural environments, however, category structures can change as a consequence of people’s behavior. In order to study how people learn categories that are dynamically coupled to their behavior, we conduct two experiments in which the underlying category structure changed as people became more accurate. Results from these experiments show that people can quickly adapt to changes in an underlying category structure, and that complicated learning dynamics occur as they transition from one structure to another.We argue that existing models of category learning are not well suited to capturing people’s behavior in these tasks, and introduce a new framework to measure the dynamics of categorization. This approach is based on Coupled Hidden Markov Models (CHMMs), and allows us to directly model the effect of stimulus similarity in the categorical associations of stimuli across trials in a task. Using data from a previously published category learning study, we show that the CHMM can adequately describe people’s categorization behavior, and serves as an interpretable and useful measurement model for understanding how people learn to associate stimuli with categories over time.We further test the CHMM as a predictive model with out-of-sample generalization tests, using data from two previous experiments. One experiment involves people learning to categorize faces in terms of different category structures including gender, hair color, and trustworthiness. We show that the CHMM performs progressively better for more abstract categories, and often outperforms the well-established General

When babies are born into the world, they have no concept of how much there is to learn and know about the world. As they age and grow, infants make and retain memories with rapid improvements in recollection for the unique spatio-temporal circumstance. Three studies investigate episodic memory in toddlers, emphasizing the role of the hippocampus in encoding and retrieving spatio-temporal and context-specific memories. Through innovative research methods including behavioral experiments, neuroimaging during natural sleep, and eye-tracking techniques, it was found that hippocampal activation correlates with the ability to retain episodic details and distinguish between similar events. Key findings across the chapters highlight that while spatial associative memory capacities are more robust earlier in development, the abilities to process temporal sequences and perform context discrimination are also evident in the second and third year of life and are linked to hippocampal function. These insights contribute to our understanding of the foundational aspects of memory development and its implications for cognitive development in early life.

Perceptual decisions are accompanied by a level of confidence that tends to track our decisional accuracy. However, this correspondence can be dissociated in noisy and atypical environments or in some clinical populations. This raises an important question: what are the neural computations of perceptual metacognition if their output can diverge from perceptual decisions themselves? In a recent paper, it was argued that tuned inhibition — i.e., the degree to which a neuron is inhibited by neighboring neurons with opposing tuning preferences, which varies from neuron to neuron — is a crucial part of the underlying mechanism. In this dissertation, we aimed to investigate the neural mechanisms underlying perceptual metacognition by seeking evidence of tuned inhibition via functional magnetic resonance imaging (fMRI). We first explored how we might validate the tuned inhibition model using fMRI data, by simulating the activity of ‘voxels’ of different compositions in the presence of evidence for and against a perceptual decision in a decision and confidence task. We showed that it is possible to quantify how a voxel’s level of tuned inhibition dictates its predictive power for confidence judgments, thus providing support for use of these stimuli and analyses in fMRI data to validate the model. The observed relationships from our model simulations were then applied to human fMRI data. We identified evidence of the model within decision-making and density-sensitive regions of the brain using fMRI. Finally, we provided further evidence supporting tuned inhibition as a model of confidence by decoding high- versus low-confidence responses on a trial-by-trial basis from voxels within higher order regions, such as the dorsal prefrontal cortex.

Studies have demonstrated alcohol-related deficits in LTP associated with histaminergic and glutamatergic impairments. The histaminergic H3R inverse agonist ABT-239 has shown promise in reversing these deficits. The present study focuses on another H3R inverse agonist, SAR-152594, and its impact on LTP deficits following moderate PAE. The findings reveal that systemic administration of 1 mg/kg of SAR-152594 reverses deficits in potentiation fEPSPs in adult male rats exposed to moderate PAE. Time-frequency analyses of evoked responses indicate PAE-related reductions in power during the fEPSP and increased power during later components of evoked responses, both reversed by SAR-152594. These results provide further evidence that H3R inverse agonism is a potential therapeutic strategy to address deficits in synaptic plasticity associated with PAE. This study also investigated extracellular glutamate levels with a glutamate biosensor in vivo. Following HFS stimulation, the results show differences in fractional change in amplitude of the evoked responses in PAE animals when compared with controls. These results support the alcohol-related deficits in LTP and support the hypothesis that there is a disruption in glutamate release from the presynaptic terminal.

From a young age, children incorporate gender and gender stereotypes into their understanding of the world. From around 8.5 years old, children report that some musical instruments are “for boys” and others “for girls” (Abeles & Porter, 1978). Previous studies suggest that these judgments are largely influenced by past exposure to particular gender-instrument pairings (e.g., “My brother plays the trumpet, so trumpet is for boys”). In the present study, we investigated whether physical (size) and musical (pitch, volume) attributes affected children’s gendered judgments of musical instruments. To avoid potential influence from children’s past experiences, we used fictional instruments. Participants were 60 children (31 girls, 29 boys), aged 8.5 to 11 years old (M = 9.36, SD = 0.73) from across the United States and Canada. On each trial, children saw (large or small) and heard (high or low, loud or soft) a fictional instrument onscreen. Their task was to select which of two characters (girl or boy) should play the instrument. Main effects were found for instrument volume (p = .026) and pitch (p = .002), with children being more likely to select boys for louder instruments and lower-pitched instruments. In contrast, no effect of size was observed (p = .919). Results suggest that specific attributes of instruments impact children’s gender stereotyping and that beliefs about which gender should play which instruments do not come solely from past exposure to specific gender-instrument pairings.

Understanding the significance of nail adornments in shaping perceptions of attractiveness and mate value provides insights into human behavior and preferences. In the current investigation, participants rated human nail length and color on physical attractiveness and partner desirability measures. Results revealed significant effects of nail length and color across different demographic groups. Medium-length nails consistently received higher ratings for physical attractiveness, cuteness, and partner desirability compared to short and long nails. White-colored nails were generally rated most attractive, while blue and black nails received the lowest ratings. Additionally, participants reported a moderate association between having manicured nails and feelings of confidence and productivity. In sum, these findings indicate how individuals may exhibit nail preferences in a manner following the principles of evolutionary psychology.

In this dissertation, I argue that researchers interested in examining the development, maintenance, transmission, and co-occurrence of epistemically unwarranted beliefs would benefit by incorporating, in diverse ways, an important dimension that might prove useful in providing explanatory power in understanding how seemingly unrelated unwarranted claims tend to co-occur. That dimension is social prejudice.To make this argument, I start with a philosophical argument concerning the demarcation problem of separating science from nonscience. Specifically, I argue about separating science from pseudoscience based on the behavior of practitioners rather than the features of ideas or claims. Conceiving of pseudoscience as that which emerges from pseudoscientific behavior has consequences for the treatment of scientific fraud and misconduct in the demarcation literature. This serves as the main focal point of the argument. However, the argument also serves as setting the stage for acknowledging that several major pseudoscientific ideas, including some that are prejudicial in nature, have emerged from within the scientific community and were or even still are considered mainstream scientific theories. Subsequently, I describe both original and replication research examining several factors associated with the contents of peoples’ beliefs. I begin with an experiment examining how people treat positive and negative evidence for a secular and a religious/supernatural claim. This research revealed how people set different evidentiary standards when considering the nature of the claim, the nature of the evidence, and how these considerations intersect with individuals’ own identity. Following this, I describe research investigating socio-cognitive profiles associated with a willingness to share various forms of misinformation concerning the then-novel COVID-19 pandemic, finding primarily that the construct of social dominance orientation is positively associated with willingness to share conspiratorial misinformation. In the final two chapters, I describe a multi-stage project exploring (a) the degree to which explicitly prejudicial and nonprejudicial epistemically unwarranted beliefs covary, (b) underlying socio-cognitive profiles associated with the endorsement or rejection of prejudicial and non-prejudicial epistemically unwarranted beliefs, and (c) peoples’ explicit reasoning behind their beliefs concerning a subset of epistemically unwarranted claims, including prejudicial claims. Findings from this research show robust association between prejudicial and non-prejudicial unwarranted beliefs, that these associations share underlying socio-cognitive profiles associated with belief endorsement. Finally, peoples’ explicit reasoning patterns do not systematically differ when justifying their positions about beliefs that are overtly prejudicial in nature compared to beliefs that are not overtly prejudicial in nature. I conclude with lessons that this research can tell us about how to improve efforts to combat the endorsement and spread of epistemically unwarranted beliefs.

Software development can be seen as a process in which the knowledge and decisions of a wide variety of people are integrated to produce a machine-readable specification. The majority of today's specification and programming languages are based on computer-oriented and mathematical concepts. Those languages are difficult for people that are not a software professional. Domain models and domain-specific languages are a way to capture knowledge from people who have no software expertise, while also resulting in specifications that can be used as software. This thesis reports on the creation of a domain-oriented method to systematically transform knowledge and decisions of all people involved in a development process, into unambiguous specifications. A systematic literature review revealed that existing domain-oriented techniques have a low engineering maturity, are barely connected to human communication and thinking, and lack methodical support for applying domain models and domain-specific languages to create system specifications. This thesis describes how these three problems are addressed by a method called MuDForM. 25 years of modeling and specification experience was captured in a method definition and gradually improved, driven by the outcome of case studies and shortcomings of existing methods. A reflection on the method from the perspective of cognitive science and linguistics concludes this thesis, demonstrating the feasibility of cognition-based specifications. The result is a method with a uniform metamodel with precise modeling concepts, a process that guides the path from knowledge elicitation to engineered model, and a set of principles that enable implementation and improvement of the method. The method can be seen as a step in transforming a computer-centered and mathematics-oriented discipline, into one that facilitates knowledge and decision specification for all people involved in software development.

Motor skill learning, or learning a sequence of movements, is a fundamental process that occurs throughout one’s life, from learning how to pick up your coffee cup to learning to play Für Elise. The primary perspective of when motor skill learning occurs is that it occurs during rest periods, offline, rather than concurrently with practice, online. However, those interpretations have conflated learning with performance. In this dissertation, I will propose an account that assumes learning occurs online, concurrently with practice, and that reactive inhibition, the worsening of performance as task performance continues, are sufficient to explain motor skill learning. Chapter 1 provides evidence that this alternate online account is sufficient to explain the ordinal results of performance improvements following a rest period. However, this experiment was unable to rule out the offline learning account. Chapter 2 implements the underlying assumptions of both the online, offline, and hybrid accounts into 10 different computational models. Overall, a hybrid model was able to best fit the data suggesting that both online and offline learning occur. Further, we demonstrated the necessity of assuming reactive inhibition in any interpretation of performance data. These models also indicated that there may be learning differences resulting from training schedules. Chapter 3 examined if learning rates were dependent on training schedules. Contrary to prior work, we found no evidence that training schedule influenced learning rates in a motor skill task where few errors are made. Taken together, my dissertation provides compelling evidence that learning occurs online, concurrently with the task, and challenges the predominant view that motor skill learning only occurs offline.

The medial Prefrontal Cortex (mPFC) can be thought of as the pre-motor cortex decision-making area in the brain (Fine & Hayden, 2021), where the activity then dictates “action plans” in a hierarchy of goals. Within the mPFC, the dorsal Anterior Cingulate Cortex (dACC) has specifically displayed activity leading to behavioral change such as exploration and changes in social stimuli interactions; however, the specifics for the stimuli whether it be a novel animal or a specific action outcome that determines the neuronal firing patterns in the dACC are unknown. For this reason, 12 tetrodes recording electrophysiological data during social and object investigation were implanted into the dACC of the Octodon Degu, a rodent model starting to be used in social cognitive studies. The subjects were implanted and then once healed, placed in a chamber and exposed to a battery of social interactions with random conspecifics or novel objects, counterbalancing the order and chamber location to ensure minimize experimental confounds. In the current report, evidence presenting support of neuronal encoding for social situations is provided by a significant difference between firing rates of social/non-social behaviors within neurons using Rank Sum tests, displaying the potential that the dACC encodes social contextual behaviors on the reflexive self.

A narrative review and analysis of the most relevant research in cognitive psychology on the use of illustrative examples for the learning of declarative concepts (that is, abstract concepts denoted by key terms and short definitions that can be applied to a wide variety of scenarios) is presented. ). Different studies are analyzed, namely: incorporation of questions in the text, contrast between studying definitions and examples or only definitions, contrast between studying provided examples Vs. examples created by the student, homogeneous examples Vs examples with thematic diversity. The conclusions highlight that the examples function as primary learning objectives. The importance of thematic diversity is emphasized., Se presenta una revisión narrativa y análisis de las investigaciones más relevantes en psicología cognitiva sobre el uso de ejemplos ilustrativos para el aprendizaje de conceptos declarativos (esto es, conceptos abstractos denotados por términos clave y definiciones cortas que se pueden aplicar a una amplia variedad de escenarios). Se analizan diferentes estudios, a saber: incorporación de preguntas en el texto, contraste entre estudiar definiciones y ejemplos o sólo definiciones, contraste entre estudiar ejemplos provistos Vs. ejemplos creados por el estudiante, ejemplos homogéneos Vs ejemplos con diversidad temática. Las conclusiones destacan que los ejemplos funcionan como objetivos primarios del aprendizaje. Se enfatiza la importancia de la diversidad temática., Se presenta una revisión narrativa y análisis de las investigaciones más relevantes en psicología cognitiva sobre el uso de ejemplos ilustrativos para el aprendizaje de conceptos declarativos (esto es, conceptos abstractos denotados por términos clave y definiciones cortas que se pueden aplicar a una amplia variedad de escenarios). Se analizan diferentes estudios, a saber: incorporación de preguntas en el texto, contraste entre estudiar definiciones y ejemplos o sólo definiciones, contraste entre estudiar ejemplos provistos Vs. ejemplos creados por el estudiante, ejemplos homogéneos Vs ejemplos con diversidad temática. Las conclusiones destacan que los ejemplos funcionan como objetivos primarios del aprendizaje. Se enfatiza la importancia de la diversidad temática.

College students from socioeconomically challenging backgrounds are more likely to drop out of college before being awarded a bachelor’s degree. A challenging background predicts difficulties in emotion regulation, which may affect adjustment to college and, subsequently, persistence in college until a bachelor’s degree is awarded. Previous research has identified cognitive fusion, a state in which one unquestioningly believes the literal content of their thoughts, and inflexible usage of self and other-blame as predictors of negative social, psychological, and academic outcomes. The present study used self-report data collected from emerging adult college students at a small midwestern university to assess whether the presence of high cognitive fusion would increase the effects of self and other-blame usage on college adjustment outcomes. While none of the moderation models tested were significant, higher cognitive fusion was significantly associated with lower reports of psychological and social adjustment to college. The exploratory analyses conducted suggest that both childhood socioeconomic status and cognitive fusion influence college adjustment for emerging adults. Thus, interventions seeking to improve college persistence for students from challenging backgrounds may benefit from incorporating therapies that reduce cognitive fusion.

This thesis investigates the question ‘What is knowledge?’ In intuition-based epistemology the question is often considered to concern how ‘knowledge’ is used linguistically or conceptually rather than what knowledge is. In addition, since intuitions are used as evidence despite empirical experiments indicating that people’s intuitions vary a great deal and that little conclusive systematicity can be found, it is argued that approaches with such a focus cannot provide a solid foundation to answer the initial question.By instead looking at naturalistic approaches, a pluralistic cognitive epistemological approach which accepts ontological naturalism, methodological cooperative naturalism, and evolutionary epistemology can be identified. Given this approach – close to that of Hilary Kornblith – it is possible to look at how various relevant sciences see the natural phenomenon of knowledge. This provides a complement to Kornblith’s sole focus on cognitive ethology. By also including the perspectives of cognitive psychology and evolutionary systems theory a new view of knowledge is made possible.The emerging picture indicates that the natural phenomenon of knowledge plausibly can be seen as consisting in dynamic internal survival-beneficial structures.For higher organisms, such structures importantly involve reflexive and reflective memory processes that (satisficingly) reliably produce (satisficingly) true beliefs.

The introduction of virtual reality (VR) to flying training has recently gained much attention, with numerous VR companies, such as Loft Dynamics and VRpilot, looking to enhance the training process. Such a considerable change to how pilots are trained is a subject that warrants careful consideration. Examining the effect that VR has on learning in other areas gives us an idea of how VR can be suitably applied to flying training. Some of the benefits offered by VR include increased safety, decreased costs, and increased environmental sustainability. Nevertheless, some challenges ahead for developers to consider are negative transfer of learning, cybersickness, and failure for users to adopt the technology. In addition to this discussion, existing technologies are presented and compared across a number of areas. Future directions for research and development in VR flying training are considered, highlighting the importance of thorough testing procedures and shifting research focus to the considerate integration of VR into flying training procedures.

Source memory is the ability to remember the origin of information stored in memory. Source memory has been of growing interest to memory researchers because influential models of episodic memory make opposing predictions about its properties. Particularly contentious is whether source memory retrieval is thresholded (i.e., fails discretely), or continuous (i.e., graded precision). Recent work has shifted away from tasks with discretely coded sources towards ones where both source presentation and responses are continuous. Distributions of source error in continuous-outcome tasks were observed to be highly leptokurtic with heavy tails, interpretable as a mixture of high-precision memory, and uniformly distributed guesses due to retrieval failure. This thesis critically evaluates this interpretation along two main lines of inquiry, the first related to the role of decision-making and the second related to intrusion errors. First, Study 1 applies a formal model of decision-making in the Smith (2016) circular diffusion model to distinguish between properties of decision-making and memory in the continuous-outcome task. Without a model of decision-making, response variability in decision-making can be erroneously attributed to memory processes. Models with decision-making variability and guessing in isolation and in combination were fit to joint distributions of response outcomes and times. Comparison of model fits revealed that guessing was necessary for good fit, suggesting that heavy tails in the distribution of response error is due to memory, rather than decision-making. Study 1 also conditioned participants’ source responding on their confidence in an old/new recognition task, addressing a potential confound by ruling out the possibility that participant guessing was only due to a lack of source memory for unrecognised items. Second, Studies 2 and 3 both concern the role of intrusion errors. Intrusions are responses driven by information retrieved about items othe

Este trabajo, que aborda un análisis cualitativo de los marcos mentales en el periodismo, tiene su principal referencia en las ideas bien establecidas y desarrolladas por Lakoff, el distinguido profesor de Ciencia Cognitiva y Lingüística de la Universidad de California en Berkeley. Según las propias ideas de Lakoff: "La prensa es un pilar de una sociedad libre y la democracia cae sin ella" El encuadre en las noticias puede mostrar diferentes versiones de la realidad. Están relacionados con los pensamientos de la gente y, más específicamente, con la psicología cognitiva. En definitiva, son estructuras mentales que alimentan las creencias sociales. La famosa expresión: "Economía, estúpidos", utilizada en la campaña de 1992 en la que se enfrentaron Bill Clinton y George H. W. Bush, está en nuestras mentes. Por esta razón considero de gran interés el tratamiento que la prensa española (en un arco ideológico representado por el centro político de izquierda, el centro político de derecha, y los posicionamientos que superan los referentes anteriores en ambos espectros) da al papel de los empresarios y por lo tanto a las empresas y sus objetivos económicos en nuestro país., This work, approaching a qualitative analysis of mental frames in journalism, has its main reference in the well stablished ideas developed by Lakoff, the Distinguished Professor of Cognitive Science and Linguistics at the University of California at Berkeley. According to Lakoff´s own ideas: “The press is a pillar of a free society and democracy falls without it.” Framing in the news can show different versions of reality. The are related to people´s thoughts and, more specifically, to cognitive psychology. In short, they are mental structures that feed social believes. The famous expression: “Economy, stupid” used in the campaign of 1992 in which Bill Clinton and George H. W. Bush faced, is set up in our minds. For this reason, I considered of great interest the treatment that Spanish press (in an ideological arc represented by the political left center, the political right center and the positions that exceed the previous references in both spectrum) gives to the role of entrepreneurs and therefore to companies and their economic goals in our country.

As people age, they can expect some of their memory to fail or to become slower while doing mental calculations. However, it is an oversimplification to describe cognitive aging as only cognitive deterioration. This dissertation explores various ways that adult learners can adapt to cognitive changes brought by aging. In chapter 1, we find that older adults are worse than younger adults at a planning task because they use suboptimal planning strategies. Once we teach older adults the optimal strategy, there are no longer differences in performance between the two age groups. In chapter 2, we show how extra practice can help older adults increase their ability to match or exceed the performance of a younger adult on various cognitive tasks. In chapters 3 and 4, we investigate how older adults allocate their effort towards learning new technologies depending on ease of use and the amount of time needed to learn. We found that older adults can learn a complex virtual machine as well as younger adults and that older adults are as willing as younger adults to expend effort towards learning difficult machines. However, we also found that older adults will conserve their effort and choose easier machines when we manipulated the amount of time they have to learn. Altogether, these results support the notion of older adults as adaptive learners and help provide a more nuanced view of cognitive aging, one where older adults are sometimes capable of excelling on cognitive tasks.

The performance of intense exercise in a tropical climate is associated with limited exercise capacity due to thermal strain. This limitation is exacerbated in sports requiring full protective equipment. Research evidence suggests disturbances in cognitive function due to thermal discomfort and/or protective equipment (e.g., helmets), and thus sports that require skills in decision-making, fast reaction times, precision, and/or inhibition can be greatly affected. The objective of this study was to investigate the effects of countermeasures on the psychological and physiological responses in young international fencers wearing full protective equipment during an ecological fencing task. Nine young international fencers performed an aiming task in tropical conditions (1) without cooling interventions and (2) with cumulative cooling interventions (i.e., pre+percooling and head+torso). Participants completed a battery of cognitive (i.e., simple and choice reaction times, Stroop test), affective (i.e., PANAS), and perception (i.e., thermal environment, Feeling Scale, rating of perceived exertion) tests in each session, and their heart rate, skin temperature, and fencing performances (i.e., execution time and total score) were checked at several time points. Although the results revealed no differences in the perception of the thermal environment or the cognitive and affective scores, the cooling interventions seemed to improve movement precision during the fencing task and limit the decrease in pleasurable feelings related to the physical task. This study suggests that attentional resources are more available with cumulative cooling interventions, which leads to better performance during an ecological fencing task in tropical conditions.

We constrained the binding problem by creating maps of different attributes. We compared the performance of different models with different maps in our current study. Our preliminary results showed that the performance of the model is the highest when location maps were used. These results suggest that the optimal way to constrain the binding problem is to create location maps of different attributes.

It is proposed that performance degradation from exposure to non-lethal technology is mediated by impulsive and reflective approachavoidance motivation. An approach-avoidance motivational framework was used to specify a four-stage information processing model that predicts performance degradation. The first stage is Evaluation: it processes physiological, sensory, perceptual, and cognitive information. The second stage is Comparison: it processes the content of the Evaluation into avoidance and approach motivational indices. The third stage is Probability: it processes information from previous stages into a probability of choosing to continue or abandon goal-directed behavior. Finally, the fourth stage is Performance: it processes performance accuracy on a given task and occurs only when people continue their goal after dissuasive technology exposure. Depending on previous stages, performance can be degraded on tasks relevant to goal completion. An experiment was used to validate the model. Results supported the hypothesis that information is processed using the approach-avoidance motivational framework.

Success in extreme environments comes with a cost of subtle performance decrements that if not mitigated properly can lead to lifethreatening consequences. Identification and prediction of performance decline could alleviate deleterious consequences and enhance success in challenging and high-risk operations. The Rim-to-Rim Wearables at the Canyon for Health (R2R WATCH) project was designed to examine the cognitive, physiological, and biological markers of performance decline in the extreme environment of the Grand Canyon Rim-to-Rim (R2R) hike. The study utilized commercial off-the-shelf cognitive and physiological monitoring techniques, along with subjective self-assessments and hematologic measurements to determine subject performance and changes across the hike. The multiyear effort collected these multiple data streams in parallel on a large sample of participants hiking the R2R, leading to a rich and complex data set. This article describes the methodology and its evolution as devices and measurements were assessed after each data collection event. It also highlights a subset of the patterns of results found across the data streams. Subsequent work will draw on this data set to focus on building more sophisticated, predictive statistical models and dive deeper into specific analyses (such as the physiological and biological profiles of hikers who were left behind by their hiking partners).

Within the last ten years research on art therapy and its positive impact on oncology patients’ stress and anxiety during treatment has been minimal. Oncology patients whether they are children or adults when diagnosed experience similar reactions due to their diagnosis, treatment, and in some cases end of life care. The current question is whether or not art therapy does have a positive impact on decreasing the stress and anxiety with oncology patients while undergoing treatment. Deane, Fitch & Carmen (2000), discussed art therapy as a healing art that is “intended to integrate physical, emotional, and spiritual care by facilitating creative ways for patients to respond to their cancer experience” (Deane, 2000, p. 147). Additionally, overall improvement of the patient’s quality of life (QOL) were explored by Rossana (2021). This literature review intends to present the relevant research on how art therapy has had a positive impact on an oncology patients’ stress and anxiety during treatment as well as a positive impact on their QOL.

Many animals and humans process the visual field with varying spatial resolution (foveated vision) and use peripheral processing to make intelligent eye movements and point the fovea to acquire high-resolution information about objects of interest. A foveated architecture results in computationally efficient rapid scene exploration and can result in energy savings for computer vision. A foveated model can also serve as a proxy to identify circumstances in which humans might make an error and as a tool to understand human vision. Foveated architectures have been implemented into previous computer vision models. However, they have not been explored with the latest computer vision architecture transformer networks, which result in better robustness against adversarial attacks and better representation of spatial relationships across the entire image. We propose foveated computational module for object classification (FoveaTer) and object detection (FST) integrated into the vision transformer architecture. We evaluate FoveaTer’s computational savings and gains in robustness to adversarial attacks relative to a full-resolution model. We used the self-attention weights to optimize the guidance of the model eye movements. We have also investigated using FoveaTer to predict the various behavioral effects of humans. We performed a psychophysics experiment for the scene categorization task and predicted the human categorization performance using the FoveaTer model. Using two additional psychophysics experiments, a forced-fixation mouse recognition experiment to detect mouse in the visual periphery and a visual search experiment to detect mouse using a limited number of fixations, We have also evaluated how the FST model uses contextual information to guide eye movements like humans. In addition, we trained anthropomorphic CNN models to detect simulated tumors in simulated 3D Digital Breast Tomosynthesis phantoms and compare their performance and errors against that of radiolo

Success in extreme environments comes with a cost of subtle performance decrements that if not mitigated properly can lead to lifethreatening consequences. Identification and prediction of performance decline could alleviate deleterious consequences and enhance success in challenging and high-risk operations. The Rim-to-Rim Wearables at the Canyon for Health (R2R WATCH) project was designed to examine the cognitive, physiological, and biological markers of performance decline in the extreme environment of the Grand Canyon Rim-to-Rim (R2R) hike. The study utilized commercial off-the-shelf cognitive and physiological monitoring techniques, along with subjective self-assessments and hematologic measurements to determine subject performance and changes across the hike. The multiyear effort collected these multiple data streams in parallel on a large sample of participants hiking the R2R, leading to a rich and complex data set. This article describes the methodology and its evolution as devices and measurements were assessed after each data collection event. It also highlights a subset of the patterns of results found across the data streams. Subsequent work will draw on this data set to focus on building more sophisticated, predictive statistical models and dive deeper into specific analyses (such as the physiological and biological profiles of hikers who were left behind by their hiking partners).

The performance of intense exercise in a tropical climate is associated with limited exercise capacity due to thermal strain. This limitation is exacerbated in sports requiring full protective equipment. Research evidence suggests disturbances in cognitive function due to thermal discomfort and/or protective equipment (e.g., helmets), and thus sports that require skills in decision-making, fast reaction times, precision, and/or inhibition can be greatly affected. The objective of this study was to investigate the effects of countermeasures on the psychological and physiological responses in young international fencers wearing full protective equipment during an ecological fencing task. Nine young international fencers performed an aiming task in tropical conditions (1) without cooling interventions and (2) with cumulative cooling interventions (i.e., pre+percooling and head+torso). Participants completed a battery of cognitive (i.e., simple and choice reaction times, Stroop test), affective (i.e., PANAS), and perception (i.e., thermal environment, Feeling Scale, rating of perceived exertion) tests in each session, and their heart rate, skin temperature, and fencing performances (i.e., execution time and total score) were checked at several time points. Although the results revealed no differences in the perception of the thermal environment or the cognitive and affective scores, the cooling interventions seemed to improve movement precision during the fencing task and limit the decrease in pleasurable feelings related to the physical task. This study suggests that attentional resources are more available with cumulative cooling interventions, which leads to better performance during an ecological fencing task in tropical conditions.

El siguiente trabajo describe puntos de convergencia que pueden surgir en el concepto de inconsciente en la teoría psicoanalítica y en la teoría cognitiva, demostrando que estas uniones entre conceptos de distintas disciplinas permiten dar paso a mayores posibilidades de exploración para el continuo descubrimiento y conocimiento del ser humano. Su importancia radica, por tanto, en la propuesta de una mirada ampliada y de un cruce de perspectivas, que permiten tomar distancia del conflicto paradigmático que, en ocasiones, ha representado un estancamiento en los abordajes de la psicología. En este sentido, se exploran diversos conceptos asociados al inconsciente en los paradigmas objeto de estudio. Desde el psicoanálisis se incluye el inconsciente que desarrolla Freud en tres sentidos (descriptivo, dinámico, sistémico) y su evolución para explicar la psique y la mente inconsciente, teniendo en cuenta términos relacionados, como la represión, el ello, el yo, el superyó, la resistencia, el preconsciente, la repetición y los procesos primario y secundario. Por su lado, el inconsciente cognitivo se asocia a términos como procesamiento inconsciente primario y secundario, representaciones mentales, memoria y esquemas cognitivos., The following work describes points of convergence that can arise in the concept of unconscious in psychoanalytic theory and in the cognitive theory, demonstrating that these unions between concepts from different disciplines allow for greater exploration possibilities for continuous discovery and knowledge. of the human being. Its importance lies, therefore, in the proposal of an expanded view and a crossing of perspectives, which allow distance from the paradigmatic conflict that, on certain occasions, have represented a stagnation for the approaches of psychology. In the same way, various concepts associated with the unconscious are explored in the paradigms under study. Psychoanalysis includes the unconscious developed by Freud in three senses (descriptive, dynamic, systemic) and its evolution to explain the psyche and the unconscious mind, taking into account related terms, such as repression, the id, the ego, resistance, the preconscious, the repetition and the primary and secondary process. By the other hand, the cognitive unconscious is associated with terms such as primary and secondary unconscious processing, mental representations, memory and cognitive schemas.

Social context alters cognitive performance, but the mechanisms for this remain unclear. One possibility is that stressors associated with social contexts mediate changes in cognitive performance by influencing attention. We conducted two experiments to investigate how social context affects performance on an attention task in capuchin monkeys (Cebus [Sapajus] apella). We additionally validated and measured physiological stress through salivary cortisol. In experiment one, capuchins were exposed to three conditions where they were either isolated or paired with an affiliative or agonistic social partner separated by a barrier. In experiment two, subjects received affiliative and agonistic conditions without barriers to allow for physical contact. Following a period of social interaction or isolation, subjects were tested on an attention task. Saliva samples were collected and analyzed for cortisol levels. We analyzed the relationship between social condition, attention performance, and salivary cortisol levels. In experiment one and two, neither attention performance nor cortisol differed significantly across the social conditions. However, there was a significant interaction between condition and cortisol on attention performance in both experiments. In experiment one, this interaction was driven by a significant negative correlation between cortisol and attention performance in the isolation condition; this relationship was not present in either social condition. In experiment two, the interaction was driven by a non-significant positive relationship between cortisol and attention performance in the affiliative condition only. These results imply a potential role of cortisol in attention performance that is context specific, and highlight the importance of including social contexts in cognitive studies.

Transmission and processing of information takes time. In the case of motion perception, the brain could theoretically compensate for these delays by using information about a moving object's past trajectory to predict where the object is located at the present moment. This thesis aimed to explore the neural delays that accumulate during visual processing in humans, and whether these can be compensated during perception of objects moving with a predictable trajectory. In Study 1, we used forward encoding modelling of EEG data to show that, after onset of a simple, static stimulus, the spatial specificity of the neural representation of the stimulus fluctuated over time. This indicates that stimulus processing unfolds in a series of feedforward and feedback sweeps of neural activity through regions of the visual cortex consisting of neurons with varying receptive field sizes. Following this, in Study 2, we again used multivariate analysis of EEG data to investigate the neural response to moving stimuli, to discover whether the brain extrapolates the position of moving objects to compensate for neural delays. We found that objects moving into a position on the screen were represented in that location much earlier than if they were flashed in the same position. This predictive encoding of position served to fully compensate for the delays that accumulate during early stimulus processing. Finally, in Study 3, we investigated the consequences of compensation for delays on perception. In the High-Phi illusion, uncorrelated noise textures are interpreted as motion due to a rotating inducing texture; we show that perception of illusory motion can be explained by extrapolation of the preceding motion. Furthermore, the perceived position of a flashed static object was biased by these predictive signals, and the magnitude of illusory motion jumps and position shifts scaled with the speed of the inducing motion. Overall, these results show that processing even simple visual inf

Innovation is vital in various fields, and analogical thinking is a powerful tool for gen- erating creative solutions to complex problems. However, recognizing analogies can be time- consuming, and successful recognition doesn’t guarantee their adoption in innovation. In this thesis, A novel computational support system for analogical innovation is proposed that employs the cognitive mechanisms for chunking and recombination as mediums of interaction. Chunking involves identifying and extracting meaningful chunks or segments from a design problem into interactive tiles called magnets while recombination involves combining these magnets to gener- ate insightful questions that elicit divergent thinking. In this way, the proposed system aims to streamline the process of recognizing and selecting analogical inspirations for innovation while avoiding premature rejection and design fixation.To evaluate the effectiveness of the system, a within-subjects study involving 23 participants was conducted, comparing the proposed interface with a baseline. The study found that using chunking and recombination as interactive mechanisms helped prevent premature rejection of useful analogical leads, resulting in 4 times fewer ignored analogical leads. Participants were also found to make 12 times fewer changes to their decisions, given a minor increment in processing time in the order of 1.5 minutes. Overall, these results suggest that our proposed intervention is an effective tool for facilitating the selection of beneficial analogies, fostering analogical innovation through computational support.