Biology Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2749
Browse
3 results
Search Results
Item Using a high-dimensional model of semantic space to predict neural activity(2014) Jackson, Alice Freeman; Bolger, Donald J; Neuroscience and Cognitive Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation research developed the GOLD model (Graph Of Language Distribution), a graph-structured semantic space model constructed based on co-occurrence in a large corpus of natural language, with the intent that it may be used to explore what information may be present about relationships between words in such a model and the degree to which this information may be used to predict brain responses and behavior in language tasks. The present study employed GOLD to examine genera relatedness as well as two specific types of relationship between words: semantic similarity, which refers to the degree of overlap in meaning between words, and associative relatedness, which refers to the degree to which two words occur in the same schematic context. It was hypothesized that this graph-structured model of language constructed based on co-occurrence should easily capture associative relatedness, because this type of relationship is thought to be present directly in lexical co-occurrence. Additionally, it was hypothesized that semantic similarity may be extracted from the intersection of the set of first-order connections, because two words that are semantically similar may occupy similar thematic or syntactic roles across contexts and thus would co-occur lexically with the same set of nodes. Based on these hypotheses, a set of relationship metrics were extracted from the GOLD model, and machine learning techniques were used to explore predictive properties of these metrics. GOLD successfully predicted behavioral data as well as neural activity in response to words with varying relationships, and its predictions outperformed those of certain competing models. These results suggest that a single-mechanism account of learning word meaning from context may suffice to account for a variety of relationships between words. Further benefits of graph models of language are discussed, including their transparent record of language experience, easy interpretability, and increased psychologically plausibility over models that perform complex transformations of meaning representation.Item The effect of mental stress on brain dynamics and performance related to attention control during a vigilance task: An electroencephalographic investigation(2013) Russell, Bartlett Anne Healy; Hatfield, Bradley D; Neuroscience and Cognitive Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Anxiety can increase distractibility and undermine the quality of psychomotor performance. Models of attention processing postulate that anxiety consumes limited executive resources necessary for maintaining goal-oriented, "top-down" attention control and suppressing stimulus-driven "bottom-up" distraction. Attention Control Theory (ACT) predicts that anxiety adversely affects the efficiency, and particularly inhibitory components of executive, frontally mediated top-down attention control. We used two approaches for examining this model. First, though attention affects synchrony among neural structures, information regarding how human oscillatory patterns (measured with electroencephalography, EEG) change as state anxiety increases is limited. Second, while anxiety affects the balance between top-down and bottom-up mechanisms, to our knowledge no one has yet measured anxiety's effect on attention using a neural measure of top-down control in conjunction with more traditional bottom-up measures of attention capture (e.g., the P3 event related potential, or ERP). Purpose: Study 1 examines the oscillatory patterns (spectral dynamics) of the cortex in order to investigate whether frontal regions exhibit patterns of reduced efficiency and altered networking with posterior regions during threat of shock. In order to assess the relationship between top-down and bottom-up attention dynamics, Study 2 uses the same threat protocol to measure attention-directed top-down modulation of sensory signaling (steady-state visual evoked potential, or ssVEP modulation) and of bottom-up attention capture by discrete targets and distractors (Event Related Potentials, ERPs). Results: The spectral analyses in Study 1 suggest decreased processing efficiency and decreased frontal networking (coherence) with more posterior regions as anxiety increased. Reduced coherence, however, could indicate either increased or decreased top-down focus; Study 2 provides more insight. Neural responses to task-relevant targets (ERPs) diminished as threat increased, while responses to task-irrelevant distractors remained unchanged. Contrary to what ACT would predict, we observed an increase in attention modulation of an ssVEP frequency associated with amplifying the task-relevant signal and no change in an ssVEP associated with inhibiting task-irrelevant stimuli. These findings suggest top-down attention control increased under threat, but was not enough to prevent degraded processing of task-relevant targets coincident with reduced efficiency on task performance. Implications and suggestions for refining ACT are discussed.Item A PROGRAMMATIC RESEARCH APPROACH TO UNDERSTANDING THE IMPACT OF TEAM ENVIRONMENT ON CEREBRAL CORTICAL DYNAMICS AND ATTENTION(2012) Miller, Matthew Walker; Hatfield, Bradley D; Neuroscience and Cognitive Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation describes a programmatic research approach to understanding how team environments alter individuals' brain dynamics so as to produce variations in individuals' cognitive-motor performances. This research is of fundamental interest as humans frequently perform in team environments. Specifically, the central purpose of this research was to determine if adaptive team environments are conducive to efficient brain dynamics such that tasks are accomplished with minimal neural costs. The dissertation is comprised of four studies (papers), each of which makes a unique contribution to the dissertation's central objective. The first paper reports a positive directional relationship between cerebral cortical activation as well as networking and task load. The second paper describes a new neurophysiological method for indexing attentional reserve, which is positively related to the efficiency of cerebral cortical activation and networking. The third paper describes the development of a paradigm employed to investigate the impact of team environment on neurocognitive functioning. This study used non-physiological techniques to index neurocognitive functioning while participants performed a cognitive-motor task in various team environments. Results suggest that, relative to neutral environments, maintaining performance in maladaptive team environments comes at a neurocognitive cost, while adaptive team environments enhance performance without such a cost. The final study applied the neurophysiological methods described in the first two studies to the team environment paradigm employed in the third study to provide neurobiological evidence in support of the conclusions reached in the third paper. Additionally, the final paper provides insight into the neurobiological changes underlying the alterations in neurocognitive functioning and task performance reported in the third paper. Specifically, the final paper reports that, relative to neutral environments, maintaining performance in maladaptive team environments comes at the expense of the efficiency of cerebral cortical activation and attentional reserve, while adaptive team environments enhance performance without such costs. Additionally, the final paper suggests that adaptive team environments may generate more optimal states of arousal, leading to performance enhancement. By comprehending the impact of team environments on brain dynamics, humans performing as members of teams in a variety of settings may be better equipped to maximize their performances.