<p> The number of visual distraction-caused crashes highlights a need for non-visual information displays in vehicles. Auditory-supported air gesture controls could fill that need. This dissertation covers four experiments that aim to explore the design auditory-supported air gesture system and examine its real-world influence on driving performance. The first three experiments compared different prototype gesture control designs as participants used the systems in a driving simulator. The fourth experiment sought to answer more basic questions about how auditory displays influence performance in target acquisition tasks. Results from experiment 1 offered optimism for the potential of auditory-supported displays for navigating simple menus by showing a decrease in off-road glance time compared to visual-only displays. Experiment 1 also showed a need to keep menu items small in number but large in size. Results from experiment 2 showed auditory-supported air gesture controls can result in safer driving performance relative to touchscreens, but at the cost of slight decrements in menu task performance. Results from experiment 3 showed that drivers can navigate through simple menu structures totally eyes-free, with no visual displays, even with less effort compared to visual displays and visual plus auditory displays. Experiment 4 showed that auditory displays convey information and allow for accurate target selection, but result in slower selections and relatively less accurate selections compared to displays with visual information, especially for more difficult target selections. Overall, the experimental data highlight potential for auditory-supported air gesture controls for increasing eyes-on-road time relative to visual displays both in touchscreens and air gesture controls. However, this benefit came at a slight cost to target selection performance as participants generally took longer to process auditory information in simple target acquisition tasks. Experimental results are discussed in the context of multiple resource theory and Fitts&rsquo;s law. Design guidelines and future work are also discussed. </p><p>

<p> One conceptualization of emotional awareness is described as attention to one&rsquo;s emotions and clarity of one&rsquo;s emotions. Clarity has been further divided into source awareness (i.e., knowing the causes of emotions) and type awareness (identifying actual emotions). Emotional awareness has been examined in relation to suspiciousness, one of four cognitive-perceptual disturbances in schizotypy. Studies have not, however, examined all three facets of emotional awareness in the other three cognitive-perceptual disturbances and have not examined attributional styles in conjunction with emotional awareness and their relation to cognitive-perceptual disturbances in schizotypy. In addition, previous studies have not examined self-report measures of emotional awareness in conjunction with behavioral/qualitative measures. The current study examined these factors using a cross-sectional design. In this study, 178 undergraduates completed self-report measures of emotional awareness, cognitive-perceptual disturbances, emotional arousal, and attributional style, in addition to completing behavioral tasks assessing type awareness and attention to emotions and a qualitative interview assessing source awareness. Results showed that low type awareness significantly predicted ideas of reference (after controlling for emotional arousal, source awareness, and attention to emotions) and suspiciousness (after controlling for sex, emotional arousal, attention, and source awareness). In addition, low internality for negative events was significantly associated with suspiciousness and odd beliefs/magical thinking. These findings build upon previous work in this area and have implications for potential treatments for cognitive and perceptual disturbances associated with schizotypy. Future directions for additional research are also discussed. </p><p>

<p> The tendency for humans to give preferential attention to animate agents in their immediate surroundings has been well-documented and likely reflects an evolved specialization to a persistent adaptive problem. In uncertain or ambiguous cases, this tendency can result in an over-detection of animacy, as the potential costs of failing to detect an animate agent far outweigh those of mistaken identification. In line with this, it seems likely that humans have evolved a sensitivity to specific cues which are indicative of animacy such that the mere presence of these cues will lead to detection, regardless of the objective category membership of the entity in question. There exists a wealth of research speaking to this effect with regards to motion cues, specifically in terms of the capacity for self-propulsion and goal-directed action. Morphological cues have also been implicated - most especially the presence of facial features &ndash; as they specify a capacity for perceptual feedback from the environment, which is essential for goal-directed motion. However, it remains an open question as to whether the capacity for animacy detection is similarly sensitive to facial information in the absence of motion cues. </p><p> The experiments reported here attempted to address this question by implementing a novel task in which participants were asked to judge the animacy or inanimacy (or membership in animal or object categories) of different images: animals with and without visible facial features, and objects with and without visible facial features. Beyond replicating a general advantage for detecting animate agents over inanimate objects, the primary predictions for these experiments were that facial features would have a differential effect on performance, such that they would improve performance when visible in animals, and would hinder performance when visible in objects. Experiments 1a and 1b provided a preliminary confirmation of this pattern of responses using images of familiar and unfamiliar animals (e.g., dogs versus jellyfish), and unaltered images of objects with and without faces. Experiment 2 improved on the design of this task by more closely matching the sets of images (the same animals facing toward or away from the camera, and objects with faces which had been digitally altered to disrupt the facial features), and by changing the prompt of the task from yes/no judgments of animacy to categorization into animal or object groups. Experiment 3 examined the face inversion effect, or the failure to recognize familiar faces when their orientation is inverted, on animal-object categorization. Lastly, experiments 4 and 5 attempted to extend the findings from experiment 2 to preschool-aged children, by implementing a card sorting task (experiment 4) and a computerized animal detection task (experiment 5). The results of this series of experiments highlight the prominent role of facial features in detecting animate agents in one&rsquo;s surroundings.</p><p>

<p> Working memory is a collection of cognitive resources that allow for the temporary maintenance and manipulation of information. This information can then be used to accomplish task goals in a variety of different contexts. To do this, the working memory system is able to process many different kinds of information using resources dedicated to the processing of those specific types of information. This processing is modulated by a control component which is responsible for guiding actions in the face of interference. Recently, the way in which working memory handles the processing of this information has been the subject of debate. Specifically, current models of working memory differ in their conceptualization of its functional architecture and the interaction between domain-specific storage structures and domain-general control processes. Here, domain-specific processing is when certain components of a model are dedicated to processing certain kinds of information, be it spatial or verbal. Domain-general processing is a when a component of a model can process multiple kinds of information. One approach conceptualizes working memory as consisting of various discrete components that are dedicated to processing specific kinds of information. These multiple component models attempt to explain how domain-specific storage structures are coordinated by a domain-general control mechanism. They also predict that capacity variations in those domain-specific storage structures can directly affect the performance of the domain-general control mechanism. Another approach focuses primarily on the contributions of a domain-general control mechanism to behavior. These controlled attention approaches collapse working memory and attention and propose that a domain-general control mechanism is the primary source of individual differences. This means that variations in domain-specific storage structures are not predicted to affect the functioning of the domain-general control mechanism. This dissertation will make the argument that conceptualizing working memory as either domain-specific or domain-general creates a false dichotomy. To do this, different ways of measuring working memory capacity will first be discussed. That discussion will serve as a basis for understanding the differences, and similarities between both models. A more detailed exposition of both the multiple component model and controlled attention account will follow. Behavioral and physiological evidence will accompany the descriptions of both models. The emphasis of the evidence presented here will be on load effects: observed changes in task performance when information is maintained in working memory. Load effects can be specific to the type of information being maintained (domain-specific), or occur regardless of information type (domain-general). This dissertation will demonstrate how the two models fail to address evidence for both domain-specific and domain-general load effects. Given these inadequacies, a new set of experiments will be proposed that will seek to demonstrate both domain-specific and domain-general effects within the same paradigm. Being able to demonstrate both these effects will go some way towards accounting for the differing evidence presented in the literature. A brief conceptualization of a possible account to explain these effects will then be discussed. Finally, future directions for research will be described.</p><p>

<p> It was not known if and to what extent there was a relationship exists between an affirmative presence of insomnia and less need for sleep to cognitive impairments in bipolar disorder type 1 patient population. Lacanian topology and memory consolidation theory provides a comprehensive theoretical foundation for this quantitative correlational study design to determine whether a correlation exists between impaired sleep and cognitive impairments in BP-1 patients. This study included a convenience sample of 286 BP-1 patients collected from the Genetics of Bipolar Disorder in Latino population study. The Schedule for Affective Disorders and Schizophrenia Change in Symptomology was used to measure presence of insomnia and decrease need for sleep, and the South Texas Assessment of Neurocognition was used to measure cognitive functioning related to verbal memory, spatial memory, attention, executive function, speed of processing and inhibition. Spearman&rsquo;s rank order correlation analysis was conducted to answer the first and second research questions, and multiple regression to answer the third research question. The results of the study showed significant inverse correlations between insomnia, speed of processing (<i>rs</i> = -.129; <i>p</i> = .029), executive functioning (<i>r_s</i> = -.116; <i>p</i> = .05), decreased need for sleep and speed of processing (<i>r_s</i> = -.118; <i>p</i> = .046). Moreover, it revealed that insomnia and decreased need for sleep as a set were significant predictors for the speed of processing, <i>F</i> (2, 283) = 3.08, <i> p</i> = .048. The findings of this study added to the literature on how sleep disturbances effects cognitive functioning in BP-1 patients and resulted in several implications for clinicians and researchers.</p><p>

The visual processing of a stimulus is facilitated by attention when it is at an attended location compared to an unattended location. However, whether attentional selection operates on the basis of visual features (e.g., color) independently of spatial locations is less clear. Six experiments were designed to examine how color information as well as location information affected attentional selection. In Experiment 1, the color of the targets and the spatial distance between them were both manipulated. Stimuli were found to be grouped based on color similarity. Additionally, the evidence suggested direct selection on the basis of color groups, rather than selection that was mediated by location. By varying the probabilities of target location and color, Experiments 2, 3 and 4 demonstrated that the use of color in perceptual grouping and in biasing the priority of selection is not automatic, but is modulated by task demands. Experiments 5 and 6 further investigated the relationship between using color and using location as the selection basis under exogenous and endogenous orienting. The results suggest that the precise nature of the interaction between color and location varies according to the mode of attentional control. Collectively, these experiments contribute to an understanding of how different types of information are used in selection and suggest a greater degree of flexibility of attentional control than previously expected. The flexibility is likely to be determined by a number of factors, including task demands and the nature of attentional control.

In this dissertation, two exemplar-based models of categorization, the General Context Model (GCM) and the Exemplar Based Random Walk model (EBRW), were used to describe between-group categorization differences in artificial and natural language categories. Prior research has shown that political Conservatives in avoidance mode are more exclusive categorizers of natural language category members than Conservatives in approach mode, but this effect was absent for Liberals (Rock & Janoff-Bulman, 2010). In Experiment 1, experimenter-generated stimuli were used to show that the EBRW could account for between-group differences in categorization decisions. In Experiment 2, the data collected by Rock and Janoff-Bulman were used to develop techniques allowing the GCM to account for between-group differences in natural language categorization decisions. Experiment 3 extends these methods to allow the EBRW to account for between-group differences in natural language categorization decisions. Across these experiments, the models identify between-group differences in determining similarity, bias to give an "in-the-category" decision, and the amount of information required to make a categorization decision. Techniques for modeling natural language categorization decisions are discussed.

Existing research suggests that there is a relation between academic and cognitive ability and externalizing behavior in young children, but the direction of this relation is unclear. The present study tested competing models of the relation between academic and cognitive functioning and behavior problems during early childhood. Participants were 223 children (120 boys, 103 girls) who participated in a longitudinal study from age 3 to 6. A reciprocal model was supported in which early academic and cognitive problems and externalizing behavior predict one another over time, controlling for mothers' education and family stress. When hyperactivity, inattention, and aggression were examined separately with controls, there was evidence that the reciprocal relation was driven primarily by inattention and hyperactivity. No significant gender differences were found. These results suggest that the reciprocal relation between academic and cognitive ability and inattention/hyperactivity is evident early in development, highlighting the need for early assessment and intervention.

The literature on age-related cognitive changes suggests that some older adults may begin to experience cognitive declines resulting in difficulty engaging in adaptive behavior necessary for functional independent living. Understanding the relationship between these cognitive and functional changes will be important for guiding researchers and clinicians in addressing this issue. Many theories regarding the underlying causes of cognitive aging have been proposed. Most causes appear to be related to changes in the efficiency and accuracy with which information is processed. Two current, competing hypotheses of cognitive aging include the processing speed theory of aging and the frontal lobe theory of aging; however, these theories propose two different mechanisms of cognitive change. Processing speed theory suggests that cognitive aging is a bottom-up process in which diffuse declines in a foundational cognitive process impact higher order cognitive functions. In contrast, frontal lobe theory suggests a top down process in that frontal lobe functions decline first and influence other processes in the brain. The current project examined data collected from a large multi-site sample during the Staying Keen in Later Life (SKILL) study. Specifically, the current study investigated both processing speed and frontal lobe theories of aging in an effort to determine which hypothesis best fit the data. It was observed that each model fit the data equally well, thus suggesting that both processes play a critical role in daily functioning. Additionally, the constructs overlapped substantially suggesting that the cognitive constructs may not be as separable as traditionally thought. Finally, the model was invariant across age groups and no differences were observed between young-old, middle-old, and old-old groups.

<p> Choosing specific implementational details is one of the most important aspects of creating and evaluating a model. In order to properly model cognitive processes, choices for these details must be made based on empirical research. Unfortunately, modelers are often forced to make decisions in the absence of relevant data. My work investigates the effects of these decisions. Looking at infant speech segmentation, I incorporate empirical research into model choices regarding model input, inference, and evaluation. First, I use experimental results to argue for syllables as a basic unit for early segmentation and show that the segmentation task is less difficult than previously thought. I then explore the role of various inference algorithms, each of which produces testable predictions. Lastly, I argue that standard methods of model evaluation make unrealistic assumptions about the goal of learning. Evaluating models in terms of their ability to support additional learning tasks shows that gold standard performance alone is an insufficient metric for measuring segmentation quality. In each of these three instances, I treat model design decisions as free parameters whose impact must be evaluated. By following this approach, future researchers can better gauge the success or failure of cognitive models. </p>