Thesis (Ph.D.)--Syracuse University, 2008. / "Publication number: AAT 3345023."

Thesis (Ph. D.)--Westfälische Wilhelms-Universität zu Münster, 1974. / Vita. Includes bibliographical references (p. 327-338).

<p> What causes variation in the turnout of an individual from election to election? Most individual level predictors of turnout can account for the propensity of an individual to vote but fail to account for changes in turnout behavior. Broad aggregate factors can account for variation in turnout trends from election to election but fail to account for changes in turnout at the individual level. In this dissertation I argue that civic duty can capture the variation that typical predictors of voter turnout cannot. Civic duty can account for variation in the turnout of high and low propensity voters, as well as distinguish why some groups turnout in one election and other groups turnout in another. The capacity of civic duty to capture such variation comes from the sensitivity of civic duty to the saliency of identities and the competing group concerns they generate. Civic duty motivates an individual to vote due to a sense of obligation that is generated by multiple group identities, with these identities either complementing each other and enhancing a sense of civic duty or conflicting with each other and diminishing such a sense. I apply and test such theory using the case of the 2017 British general election. With this case I find that civic duty can uniquely capture a sense of European identity, as well as the variation in salience of such identity that can account for the highly unexpected turnout of Millennials in 2017.</p><p>

<p> Research on reward-driven learning has produced and substantiated theories of model-free and model-based reinforcement learning (RL), which respectively explain how humans and animals learn reflexive habits and build prospective plans. A highly developed line of work has unearthed the role of striatal dopamine in model-free learning, while the prefrontal cortex (PFC) appears to critically subserve model-based learning. The recent theory of meta-reinforcement learning (meta-RL) explained a wide array of findings by positing that the model-free dopaminergic reward prediction error trains the recurrent prefrontal network to execute arbitrary RL algorithms&mdash;including model-based RL&mdash;in its activations. </p><p> In parallel, a nascent understanding of a third reinforcement learning system is emerging: a non-parametric system that stores memory traces of individual experiences rather than aggregate statistics. Research on such <i>episodic learning</i> has revealed its unmistakeable traces in human behavior, developed theory to articulate algorithms underlying that behavior, and pursued the contention that the hippocampus is centrally involved. These developments lead to a set of open questions about (1) how the neural mechanisms of episodic learning relate to those underlying incremental model-free and model-based learning and (2) how the brain arbitrates among the contributions of this abundance of valuation strategies. </p><p> This thesis extends meta-RL to provide an account for episodic learning, incremental learning, and the coordination between them. In this theory of episodic meta-RL (EMRL), episodic memory reinstates activations in the prefrontal network based on contextual similarity, after passing them through a learned gating mechanism (Chapters 1 and 2). In simulation, EMRL can solve episodic contextual water maze navigation problems and episodic contextual bandit problems, including those with Omniglot class contexts and others with compositional structure (Chapter 3). Further, EMRL reproduces episodic model-based RL and its coordination with incremental model-based RL on the episodic two-step task (Vikbladh et al., 2017; Chapter 4). Chapter 5 discusses more biologically detailed extensions to EMRL, and Chapter 6 analyzes EMRL with respect to a set of recent empirical findings. Chapter 7 discusses EMRL in the context of various topics in neuroscience.</p><p>

Our visual perception is shaped by both external and internal factors, which continuously compete for limited neural resources. Salient external (exogenous) events capture our attention automatically, whereas internal (endogenous) attention can be directed towards sensory events according to our current behavioural goals. Advances in neuroimaging and brain stimulation have allowed us to begin to map the underlying functional neural architecture mediating both exogenously driven and endogenously controlled visual attention, including electrophysiological techniques such as electroencephalography and magnetoencephalography (EEG/MEG). However, while the neural EEG/MEG correlates of endogenously controlled attention have been investigated in much detail, the neural EEG/MEG correlates of exogenously driven attention are substantially less well understood. One reason for this is that exogenously driven effects are difficult to isolate from the influence of endogenous control processes. In a series of three experiments, I sought to: 1) Study how the perceptual outcomes of both endogenously and exogenously driven attention can be effectively dissociated and investigated. 2) Provide a better understanding of the functional architecture of attention control in regards to its underlying neural substrates and oscillatory signatures, particularly when exogenously driven. To this end, I employed a visuospatial attention paradigm which, by design, behaviourally dissociates exogenous from endogenously driven effects (experiment 1). Furthermore, by utilizing the same behavioural paradigm in combination with neuronavigated MRI-based transcranial magnetic stimulation (TMS) over two key attentional network nodes (i.e., the right intraprarietal sulcus and right temporo-parietal junction), I probed the extent to which the neural substrates of endogenous vs. exogenous orienting are overlapping or can be dissociated (experiment 2). Lastly, I used electroencephalography (EEG) to investigate the oscillatory signatures underlying attention in a task which is typically employed to study exogenous orienting and which putatively triggers exogenous attention in isolation (experiment 3). The results revealed that while exogenous attentional processes can be behaviourally dissociated from endogenous attention (experiment 1), the neural substrates of exogenous attention appear to cover a wide network of attention areas. This includes nodes in both the right ventral attention network (i.e., right temporo-parietal junction) but also the right dorsal network (i.e., the right intraparietal sulcus), which has predominantly been associated with endogenous attention control (experiment 2). Interestingly, even in tasks that have been utilized to test exogenous attentional effects in isolation, endogenous control processes, as indexed by increased mid-frontal theta-band activity, can heavily influence the behavioural outcome (experiment 3). Based on these results, I conclude that there appears to be strong interplay between endogenous control and exogenously driven attention processes. These findings highlight that in order to better understand the functional architecture of (purely) exogenously driven effects, we need to effectively account for the potential influence of endogenous control. One approach to achieve this is by manipulating both types of attention simultaneously instead of in separation, as illustrated in the present work.

<p> The digital landscape that we inhabit offers new ways of cultivating relationships. Humans are programmed to seek social acceptance and avoid social rejection. Facebook taps into this core motivation by offering variable social rewards. Habits are eventually formed that keep users coming back for more rewards. What impact does habituated Facebook use have on relationships and other criteria defined by well-being theories?</p><p> The sample for this study was 36 students who were recruited to participate in one or two phases of a sequential mixed methods study. The quantitative phase involved two surveys: the first, a validated instrument; the second, a 38-question survey created for the study to inquire about research participants&rsquo; experience using Facebook. For the qualitative phase, four students from the first phase were interviewed to further explore their experience with Facebook and well-being.</p><p> A central accomplishment of this study was the creation of a new Facebook well-being survey (FWBS). The design of this survey guided the data analysis which uncovered the key findings of this study. Results were divided into four categories of time that participants spent using Facebook per day. Half of the categories, including the largest, showed a positive correlation between well-being and the amount of time spent creating content.</p><p> Overall, participants reported that they spend significantly more time consuming (65%) than creating (35%) Facebook content. The FWBS asked participants to rank their favorite Facebook features from most to least used. Private and public messages were the most popular with Likes ranking high for the creation of content. Participants with very high well-being scores mostly used messaging features while those with very low well-being scores spent their time using other Facebook features in addition to messaging.</p><p> Emotions and relationships were the well-being components most impacted by Facebook. Sixty-five percent of participants reported they have unhealthy Facebook habits. Facebook can help with loneliness but is also a distraction, time-killer, and social-crutch. Unless Facebook is used wisely and sparingly it reduces well-being. To be a socially engaged in the Millennial Generation a Facebook account is not optional.</p>

Thesis (Ph. D.)--University of California, San Diego, 1997. / Vita. Includes bibliographical references (leaves 299-311).

<p> Speech perception requires that the listener identify <i>where</i> the meaningful units are (e.g., syllables) before they can identify <i> what</i> those units might be. This segmentation is difficult because there exist no clear, systematic silences between words, syllables or phonemes. One potentially useful cue is the acoustic envelope: slow (&lt; 10 Hz) fluctuations in sound amplitude over time. Sharp increases in the envelope are loosely related to the onsets of syllables. In addition to this cue, the brain may also make use of the temporal regularity of syllables which last ~200 ms on average across languages. This quasi-rhythmicity enables prediction as a means to identify the onsets of syllables. The work presented here supports neural synchrony to the envelope at the syllabic rate as a critical mechanism to segment the sound stream. Chapter 1 and 2 show synchrony to both speech and music and demonstrate a relationship between synchrony and successful behavior. Chapter 3, following up on this work, compares the data from Chapter 2 with two competing computational models&mdash;oscillator vs evoked&mdash;and shows that the data are consistent with an oscillatory mechanism. These chapters support the oscillator as an effective means of read-in and segmentation of rhythmic input.</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>

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