UMD Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/3
New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.
More information is available at Theses and Dissertations at University of Maryland Libraries.
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Item The Role of Cognitive Control in Bilingual Code-Switch Comprehension(2021) Salig, Lauren; Novick, Jared; Neuroscience and Cognitive Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Bilinguals experience a conflict when comprehending a sentence that code-switches from one language to another. However, why bilinguals experience conflict during code-switch comprehension is unclear. This study asks: Does being in a cognitive state conducive to resolving conflict help bilinguals read code-switches faster? If so, it would indicate that comprehending a code-switch involves conflict at an early lexical/syntactic level because faster resolution of the conflict would facilitate faster code-switch reading. 101 Spanish-English bilinguals completed Flanker-arrow trials to manipulate their engagement of cognitive control—which regulates conflict detection and resolution. Immediately after this cognitive-control manipulation, bilinguals read code-switched or unilingual sentences. Having cognitive control engaged prior to encountering a code-switch did not result in faster reading of code-switches. This finding provides preliminary evidence that reading a code-switch may not involve conflict at a lexical/syntactic level. Future work should further investigate the type of conflict that bilinguals encounter during code-switch comprehension.Item COGNITIVE CONTROL, EVOLUTIONARY GAMES, AND LIE ALGEBRAS(2019) Raju, Vidya; P. S., Krishnaprasad; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In recent years, pursuit-based feedback control laws have helped realize complex spatio-temporal behaviors of robot collectives by utilizing relative information (e.g. optic flow) of the target with respect to the pursuer. For instance, these algorithms can enable a team of Unmanned Aerial Vehicles (UAVs) perform search, rescue and surveillance. However, such platforms are far from being completely autonomous and frequently require human intervention to reset the goals for the mission midstream, to be accomplished by choosing one from a pool of control laws. While this can ensure achievement of very specific goals over a short duration, such as reaching a search location and performing motions to cover an annular region around it, there is a need to autonomously generate high level goals especially in the face of adverse or unexpected events. This requires using sensory information gathered from the environment in which the agents operate to decide the next course of action. The broad aim of this thesis is to establish a mathematical framework to enable a collective of robotic agents, each with a finite set of actions to choose from, arrive at a cognitive decision that is justified by aggregated evidence. We motivate the use of models from evolutionary game theory, particularly the replicator dynamics, to model the evolution of the probabilities associated with choosing each action. We take inspiration from neuroscience for realizing context-dependent decision making by means of a three-layer cognitive hierarchy operating at multiple timescales. We show how evolutionary game theory offers a natural framework to model this hierarchy. In particular, replicator dynamics associated to fitness maps capture the evolution of a finite number of population fractions or probabilities that grow depending on the fitness or reward obtained for each population type. In the present setting, we interpret the types as synonymous with strategies implemented by feedback laws and the decision of an autonomous agent as represented by probabilities over its strategies. This formulation can be used to realize a combination of available control laws that will enable the agent to achieve its goal. In the bottom layer are the dynamics of an agent which responds to external stimuli from the physical environment at a fast timescale by a combination of its feedback laws. In the intermediate layer is the replicator dynamics evolving in a comparatively slower timescale, in which the decision making that goes behind choosing the feedback law in the lower layer is updated using knowledge of the fitness of each strategy. In the top layer evolving at the slowest timescale, we consider replicator control systems specified by control laws that seek to realize context dependence (cognition) at the higher level. The contributions of this thesis are in all three layers of the cognitive hierarchy, explained through a top-down approach. We first consider the top layer by extending the replicator dynamics to a replicator control system whose controls vary the fitness of strategies in a time-dependent manner. We show a Lie algebraic structure in the space of fitness maps. We exploit this mathematical structure in the dynamics to modulate the fitness so that an arbitrary final set of probabilities can be attained from an initial state. In the process, we determine the associated controllability conditions. In the intermediate layer, we highlight an optimizing property of the replicator dynamics by showing that it satisfies first order necessary conditions for optimality for an appropriate cost function. In the bottom layer, we consider the interpretations of mixed strategies in the agent's physical world. An instance of dyadic pursuit in which the pursuer aims to capture a target using the motion camouflage pursuit strategy while trading off the accuracy of sensory information for the speed of response to the stimuli is explored. In the final part of this thesis, we consider a cognitive description of starling flocks by treating each flock as a single decision-making entity. We use observations made from several flocking events and formulate a data smoothing problem using the game-theoretic formulation in this thesis to understand the temporal evolution of fractions of the relative kinetic energy allocated to the different behavioral modes. We propose a function, the optimal cost arising out of the solution to an underlying optimal control problem, as a measure of cognitive effort involved in producing these behaviors. Lastly, we conclude with a discussion on ongoing work, some challenges and future research directions.Item The Malleability of Cognitive Control and its Effects on Language Skills(2013) Hussey, Erika; Dougherty, Michael R; Neuroscience and Cognitive Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Cognitive control, or executive function (EF), refers to the mental ability to regulate and adjust behavior across domains in the face of interference, conflict, or new rules. Evidence from psycholinguistics suggests a role for cognitive control in a range of language processing tasks including syntactic ambiguity resolution and verbal fluency. Separate work demonstrates that EF abilities are malleable with extensive practice, such that training improvements transfer across domains to novel tasks that rely on the same underlying EF mechanisms (an effect dubbed 'process-specificity'). In uniting these two growing literatures, this dissertation investigated the (causal) role of cognitive control for language processing through two longitudinal training interventions. In one study, I demonstrated that practicing a battery of cognitive tasks conferred selective benefits on untrained reading tasks requiring syntactic ambiguity resolution. Compared to controls, individuals who responded most to an EF training task exhibited (1) higher accuracy to comprehension questions indexing offline reinterpretation, and (2) faster real-time recovery efforts to resolve among conflicting interpretations. A second experiment extended these findings by addressing the degree to which training on a single EF task was necessary and sufficient to confer transfer to untrained, related language measures. Participants were assigned to practice a single training task that was minimally different from other training groups' tasks in terms of EF demands. By and large, participants who practiced a high-EF training task were exclusive in demonstrating a cross-assessment improvement profile consistent with a process-specific account: Pre/post benefits across a range of ostensibly different linguistic (verbal fluency, syntactic ambiguity resolution) and non-linguistic (Stroop, recognition memory) tasks were observed selectively for conditions with high-EF demands; no benefits were seen for cases when the need for cognitive control was minimized. Together, these findings provide support for the malleability of EF skills and suggest a critical (and perhaps causal) role for domain-general cognitive control in language processing. Further, the present studies indicate that within the right framework, and having appropriate linking hypotheses, cognitive training may be a viable way to improve language use.