Thesis (Ph. D.)--Drexel University, 2007. / Includes abstract and vita. Includes bibliographical references (leaves 130-141).

abstract: Learning and transfer were investigated for a categorical structure in which relevant stimulus information could be mapped without loss from one modality to another. The category space was composed of three non-overlapping, linearly-separable categories. Each stimulus was composed of a sequence of on-off events that varied in duration and number of sub-events (complexity). Categories were learned visually, haptically, or auditorily, and transferred to the same or an alternate modality. The transfer set contained old, new, and prototype stimuli, and subjects made both classification and recognition judgments. The results showed an early learning advantage in the visual modality, with transfer performance varying among the conditions in both classification and recognition. In general, classification accuracy was highest for the category prototype, with false recognition of the category prototype higher in the cross-modality conditions. The results are discussed in terms of current theories in modality transfer, and shed preliminary light on categorical transfer of temporal stimuli. / Dissertation/Thesis / M.S. Psychology 2011

<p> James Hillman (1972) declared, &ldquo;What the psyche has experienced during the past seventy years in analytical therapy should also be possible for it wherever it goes&rdquo; (p. 5). As a life coach&mdash;someone who starts from a place of curiosity&mdash;I became curious. Did this mean that the imaginal practices of depth psychology could be used within a life coaching container? Could imaginal practices such as Jung&rsquo;s active imagination and Hillman&rsquo;s personifying work in a life coaching partnership? What benefits might life coaching clients gain through creating a connection with psychic figures? What would a life coach&mdash;or a depth psychologist&mdash;need to merge these two ways of engaging with individuals, both in terms of training and resources? And, finally, what does each profession&mdash;life coaching and depth psychology&mdash;obtain from such a merger? Using the methodology of hermeneutic phenomenology, I entered into a six-session soul-centered coaching partnership with three participants. Each took part in six sessions designed to develop their psychological creativity while experiencing a coaching relationship. Factoring in my own observations, as well as the personal accounts of the participants, I found that imaginal practices positively impacted participants&rsquo; abilities to connect with and move through their life transitions. This merging of the two professions would require life coaches to undergo extensive learning in depth psychology, and depth psychologists to acquire professional coaching skills, but this study holds forth promise for a blending of the two fields. </p><p>

<p> Bad decisions can have devastating consequences, and there is a vast body of literature suggesting that human judgment and decision-making are riddled with numerous systematic violations of the rules of logic, probability theory, and expected utility theory. The discovery of these <i>cognitive biases</i> in the 1970s challenged the concept of Homo sapiens as the rational animal and has profoundly shaken the foundations of economics and rational models in the cognitive, neural, and social sciences. Four decades later, these disciplines still lack a rigorous theoretical foundation that can account for people&rsquo;s cognitive biases. Furthermore, designing effective interventions to remedy cognitive biases and improve human judgment and decision-making is still an art rather than a science. I address these two fundamental problems in the first and the second part of my thesis respectively. </p><p> To develop a theoretical framework that can account for cognitive biases, I start from the assumption that human cognition is fundamentally constrained by limited time and the human brain&rsquo;s finite computational resources. Based on this assumption, I redefine human rationality as reasoning and deciding according to cognitive strategies that make the best possible use of the mind&rsquo;s limited resources. I draw on the bounded optimality framework developed in the artificial intelligence literature to translate this definition into a mathematically precise theory of bounded rationality called <i>resource-rationality </i> and a new paradigm for cognitive modeling called <i>resource-rational analysis</i>. Applying this methodology allowed me to derive resource-rational models of judgment and decisionmaking that accurately capture a wide range of cognitive biases, including the anchoring bias and the numerous availability biases in memory recall, judgment, and decision-making. By showing that these phenomena and the heuristics that generate them are consistent with the rational use of limited resources, my analysis provides a rational reinterpretation of cognitive biases that were once interpreted as hallmarks of human irrationality. This suggests that it is time to revisit the debate about human rationality with the more realistic normative standard of resource-rationality. To enable a systematic assessment of the extent to which human cognition is resource- rational, I present an automatic method for deriving resource-rational heuristics from a mathematical specification of their function and the mind&rsquo;s computational constraints. Applying this method to multi-alternative risky-choice led to the discovery of a previously unknown heuristic that people appear to use very frequently. Evaluating human decision-making against resource-rational heuristics suggested that, on average, human decision-making is at most 88% as resource-rational as it could be. </p><p> Since people are equipped with multiple heuristics, a complete normative theory of bounded rationality also has to answer the question of when each of these heuristics should be used. I address this question with a rational theory of strategy selection. According to this theory, people gradually learn to select the heuristic with the best possible speed-accuracy trade-off by building a predictive model of its performance. Experiments testing this model confirmed that people gradually learn to make increasingly more rational use of their finite time and bounded cognitive resources through a metacognitive reinforcement learning mechanism. </p><p> Overall, these findings suggest that&mdash;contrary to the bleak picture painted by previous research on heuristics and biases&mdash;human cognition is not fundamentally irrational, and can be understood as making rational use of bounded cognitive resources. By reconciling rationality with cognitive biases and bounded resources, this line of research addresses fundamental problems of previous rational modeling frameworks, such as expected utility theory, logic, and probability theory. Resource-rationality might thus come to replace classical notions of rationality as a theoretical foundation for modeling human judgment and decision-making in economics, psychology, neuroscience, and other cognitive and social sciences. </p><p> In the second part of my dissertation, I apply the principle of resource-rationality to develop tools and interventions for improving the human mind. Early interventions educated people about cognitive biases and taught them the normative principles of logic, probability theory, and expected utility theory. The practical benefits of such interventions are limited because the computational demands of applying them to the complex problems people face in everyday life far exceed individuals&rsquo; cognitive capacities. Instead, the principle of resource-rationality suggests that people should rely on simple, computationally efficient heuristics that are well adapted to the structure of their environments. Building on this idea, I leverage the automatic strategy discovery method and insights into metacognitive learning from the first part of my dissertation to develop intelligent systems that teach people resource-rational cognitive strategies. I illustrate this approach by developing and evaluating a cognitive tutor that trains people to plan resource-rationally. My results show that practicing with the cognitive tutor improves people&rsquo;s planning strategies significantly more than does practicing without feedback. (Abstract shortened by ProQuest.)</p><p>

<p> The use of language is one of the defining features of human cognition. Focusing here on two key features of language, <i>productivity</i> and <i>robustness</i>, I examine how basic questions regarding linguistic representation can be approached with the help of probabilistic generative language models, or PGLMs. These statistical models, which capture aspects of linguistic structure in terms of distributions over events, can serve as both the product of language learning and as prior knowledge in real-time language processing. In the first two chapters, I show how PGLMs can be used to make inferences about the nature of people's linguistic representations. In Chapter 1, I look at the representations of language learners, tracing the earliest evidence for a noun category in large developmental corpora. In Chapter 2, I evaluate broad-coverage language models reflecting contrasting assumptions about the information sources and abstractions used for in-context spoken word recognition in their ability to capture people's behavior in a large online game of &ldquo;Telephone.&rdquo; In Chapter 3, I show how these models can be used to examine the properties of lexicons. I use a measure derived from a probabilistic generative model of word structure to provide a novel interpretation of a longstanding linguistic universal, motivating it in terms of cognitive pressures that arise from communication. I conclude by considering the prospects for a unified, expectations-oriented account of language processing and first language learning.</p><p>

The existence of emotional and behavioural problems in young children has been extensively documented. Such problems have a substantial impact on children themselves, their families, their schools, and society more generally. A basic tenet of social cognitive psychology is that the way people think in their daily lives about themselves and their social world is linked with the way they behave. Based on this assumption, the main aim of this thesis was to explore whether and how children who show emotional and behavioural problems in the first year of primary school, differ from their nonproblem peers in the way they think about themselves and their relationships with their mothers, teachers and peers. Three studies were carried out. The first two dealt with the development of a standardised procedure for identifying emotional and behavioural problems in children in the first year of primary school. The third study endeavoured to explore social cognitions of the selected children. In the first study, 61 reception class teachers in London (England) evaluated three existing behaviour rating scales by providing assessments for children in their classes. One of these scales was further evaluated for use In India, In a normative study of 488 children. Using this measure, 210 children attending the first year In 26 primary schools were selected. Of these, 115 formed the target group- showing emotional and behavioural problems and the rest were their comparison children- free from reported problems but matched on gender within the same class. The children's social cognitions were examined in individual interviews. The measures used included the Harter Scale, Cassidy's Incomplete Stories With Doll Families and the Puppet Interview. The children in the target group scored significantly lower than the comparison group on all the measures except the Puppet Interview, depicting a less positive view of themselves and their relationships with their mothers, teachers and peers. Follow up analyses indicated that the differences in the two groups were largely due to those children who showed internalising or multiple problems. Children showing predominantly externalising problems did not differ significantly from their comparisons. The findings add to the literature by showing that a meaningful link exists.

<p>RL has been transformative for neuroscience by providing a normative anchor for interpreting neural and behavioral data. End-to-end RL methods have scored impressive victories with minimal compromises in autonomy, hand-engineering, and generality. The cost of this minimalism in practice is that model-free RL methods are slow to learn and generalize poorly. Humans and animals exhibit substantially improved flexibility and generalize learned information rapidly to new environment by learning invariants of the environment and features of the environment that support fast learning rapid transfer in new environments. An important question for both neuroscience and machine learning is what kind of ``representational objectives'' encourage humans and other animals to encode structure about the world. This can be formalized as ``representation feature learning,'' in which the animal or agent learns to form representations with information potentially relevant to the downstream RL process. We will overview different representational objectives that have received attention in neuroscience and in machine learning. The focus of this overview will be to first highlight conditions under which these seemingly unrelated objectives are actually mathematically equivalent. We will use this to motivate a breakdown of properties of different learned representations that are meaningfully different and can be used to inform contrasting hypotheses for neuroscience. We then use this perspective to motivate our model of the hippocampus. A cognitive map has long been the dominant metaphor for hippocampal function, embracing the idea that place cells encode a geometric representation of space. However, evidence for predictive coding, reward sensitivity, and policy dependence in place cells suggests that the representation is not purely spatial. We approach the problem of understanding hippocampal representations from a reinforcement learning perspective, focusing on what kind of spatial representation is most useful for maximizing future reward. We show that the answer takes the form of a predictive representation. This representation captures many aspects of place cell responses that fall outside the traditional view of a cognitive map. We go on to argue that entorhinal grid cells encode a low-dimensional basis set for the predictive representation, useful for suppressing noise in predictions and extracting multiscale structure for hierarchical planning.

abstract: Properly deciding to engage in or to withhold an action is a critical ability for goal-oriented movement control. Such decision may be driven by expected value from the choice of action but associating physical effort may discount such value. A novel anticipatory stopping task was developed to investigate effort discounted decision process potentially present in proactive inhibitory control. Subjects performed or abstained from target reach if they believed it was a Go or Stop trial respectively. Reward was awarded to a reach, correctly timed to hit a target at the same time as the moving bar in Go trials. During the Stop trials, correctly judging to not engage in a reach from the color of the moving bar that linked to the bar’s probability of stopping before the target resulted in gaining a reward. Resistive force field incurred additional physical effort for choosing to reach. Introducing effort expectedly decreased the tendency to respond at trials with higher stop probability. Surprisingly, tendency to respond increased and corresponding reaction time decreased in the trials with lower stop probability. Such asymmetric effect suggests that the value of context ineffective response is discounted, and the value of context effective response is flexibly enhanced by its associated effort cost to drive decision-process in goal-oriented manner. Medial frontal event related potential (ERP) locked to the onset of moving bar appearance reflected such effort discounted decision process. Theta band observed in Stop trials accounted for evaluation of effort and context possibly reinforcing such decision-making. / Dissertation/Thesis / Masters Thesis Biomedical Engineering 2018

Cognitive effort has been identified as the basis of the contectual interference (Cl) effect (Lee, Swinnen, & Serrien, 1994). It has been argued that higher levels of cognitive activity related to either the evaluation of movement information (encoding) or the retrieval of movement plans are demanded by the conditions of random rather than blocked practice. Current theories of skill acquisition appear to more heavily emphasize evaluative/encoding than retrieval processes. Furthermore, a review of evidence from research on the knowledge of results (KR) and observational learning implicates the critical role of evaluative processes as well. A series of three experiments was designed to (a) test the isomorphism of evaluative processes and cognitive effort within the contextual interference paradigm, and (b) use the Cl phenomenon as a way to explore the more general role of evaluative processes in motor skill acquisition. The typical Cl effect was replicated in Experiment 1 using three spatial variations of a multi-segment arm movement task. However, this experiment featured the co-occurrence of differential demands for both encoding variability and retrieval practice. In Experiment 2, one of the variations from Experiment 1 was practiced within the context of two unrelated video games. The results showed that no acquisition or retention performance differences emerged between blocked and random practice groups. These results suggest that the role of retrieval practice as the basis of the Cl effect should be questioned. Experiment 3 A replicated Experiment 1 with pans of blocked and random groups. In Experiment 3B, using a second set of three spatial variations, an attempt was made to reduce differential encoding variability while keeping differential retrieval practice intact between one pair of blocked and random groups (verbalize groups). The blocked group was required to evaluate and associate the features of each pattern variation during the acquisition phase, and to verbalize their thoughts. A random group was also required to verbalize the cognitive strategies they used to learn the patterns. The co-occurrence of differential encoding variability and retrieval was maintained for the remaining pair of blocked and random groups (control groups). The results of Experiment 1 were replicated in Experiment 3A and by the control groups in Experiment 3B. In Experiment 3B, relative retention and retention performance improved to a greater extent for the blocked verbalize than the blocked control group. However, relative retention and retention performance were not similar between the blocked verbalize and random groups, indicating that the evaluation of pattern variations in isolation does not appear to be an effective intervention with which to reduce the demands for differential encoding variability between blocked and random groups. Analysis of qualitative data obtained in Experiment 3B indicated differences between blocked and random groups in the degree to which the features of the spatial patterns were compared, suggesting that information derived from single task evaluation may not be equivalent to the information derived from multiple task comparison. Results are discussed within Glenberg's (1979) component levels theory. Insight into the nature of the cognitive processes underlying the Cl effect may have implications for a general explanation of motor skill acquisition. The relationship between cognitive effort, the development of knowledge, and skill acquisition is outlined in a preliminary framework for a unified theory of skill acquisition. The ability of the proposed framework to incorporate a range of experimental data and theoretical views is discussed. / Graduate

<p> The field of management&rsquo;s growing interest in mindfulness appears to stem from the increasing need for new ways to deal with the complexities of ambiguous and uncertain environments. This dissertation examined the context of middle managers faced with the heavy burden of making an increasing number of decisions under difficult conditions and the intervention of mindfulness for improved decision outcomes. By means of a systematic review, with a realist synthesis approach, evidence-based research was carried out to address the research question: <i>How does mindfulness affect middle managers for improved decision making?</i> The findings identified the middle manager context as one characterized by a lack of knowledge, involvement, and understanding of the firm strategy. They are expected to act with strategic agency without awareness of strategic plans. This leads not only to frustration but a reliance on intuition rather than reasoning for decision making. The mindfulness findings showed increased cognitive [mindful] awareness and increased cognitive flexibility enabling a highbred <i>mindful rationality</i>, where increased strategic awareness and reduced negative affect improved decision making. The implications from this research suggest mindfulness may provide both the cognitive and emotional states necessary for middle managers to improve their decision making. </p><p>