Charting developmental EEG gamma changes in the auditory modality /

The oscillation of neuronal circuits reflected in the EEG gamma frequency may be fundamental to the perceptual process referred to as binding (the integration of various thoughts and perceptions into a coherent picture). The aim of our study was to expand our knowledge of the developmental course ofEEG gamma in the auditory modality. 2 We investigated EEG 40 Hz gamma band responses (35.2 to 43.0 Hz) using an auditory novelty oddball paradigm alone and with a visual-number-series distracter task in 208 participants as a function of age (7 years to adult) at 9 sites across the sagital and lateral axes (F3, Fz, F4, C3, Cz, C4, P3, Pz, P4). Gamma responses were operationally defined as change in power or a change in phase synchrony level from baseline within two time windows. The evoked gamma response was defined as a significant change from baseline occurring between 0 to 150 ms after stimulus onset; the induced gamma response was measured from 250 to 750 ms after stimulus onset. A significant evoked gamma band response was found when measuring changes in both power and phase synchrony. The increase in both measures was maximal at frontal regions. Decreases in both measures were found when participants were distracted by a secondary task. For neither measure were developmental effects noted. However, evoked gamma power was significantly enhanced with the presentation of a novel stimulus, especially at the right frontal site (F4); frontal evoked gamma phase synchrony also showed enhancement for novel stimuli but only for our two oldest age groups (16-18 year olds and adults). Induced gamma band responses also varied with task-dependent cognitive stimulus properties. In the induced gamma power response in all age groups, target stimuli generated the highest power values at the parietal region, while the novel stimuli were always below baseline. Target stimuli increased induced synchrony in all regions for all participants, but the novel stimulus selectively affected participants dependent on their age and gender. Adult participants, for example, exhibited a reduction in gamma power, but an increase in synchrony to the novel stimulus within the same region. Induced gamma synchrony was more sensitive to the gender of the participant than was induced gamma power. While induced gamma power produced little effects of age, gamma synchrony did have age effects. These results confirm that the perceptual process which regulates gamma power is distinct from that which governs the synchronization for neuronal firing, and both gamma power and synchrony are important factors to be considered for the "binding" hypothesis. However, there is surprisingly little effect of age on the absolute levels of or distribution of EEG gamma in the age range investigated.

A Multi-Objective Genetic Algorithm with Side Effect Machines for Motif Discovery

Understanding the machinery of gene regulation to control gene expression has been one of the main focuses of bioinformaticians for years. We use a multi-objective genetic algorithm to evolve a specialized version of side effect machines for degenerate motif discovery. We compare some suggested objectives for the motifs they find, test different multi-objective scoring schemes and probabilistic models for the background sequence models and report our results on a synthetic dataset and some biological benchmarking suites. We conclude with a comparison of our algorithm with some widely used motif discovery algorithms in the literature and suggest future directions for research in this area.

Investigation of the Relationship between Sexual Orientation and Objective Height, along with Predictors of Height Distortion

Studies that have used mostly self-reported height have found that men with a same-sex orientation and women with an other-sex orientation are shorter, on average, than men with an other-sex orientation and women with a same-sex orientation, respectively. This thesis examined whether an objective height difference exists or whether a psychosocial account (e.g., distortion of self-reports) may explain these putative height differences. Also, this thesis examined whether certain individual differences (e.g, gender roles and socially desirable responding) predict height distortion. Eight hundred and thirteen participants, recruited at Brock University, the Niagara Community and through surrounding LGBT events, completed self-reported height, measures of gender roles and socially desirable responding, and had their height measured. Using hierarchical linear regressions, it was found that Same-Sex/Both-Sex Oriented men were shorter, on average, than predominantly Other-Sex Oriented men; however, there was no difference in objective height between Same-Sex/Both-Sex Oriented women and predominantly Other-Sex Oriented women. These findings contribute to existing biological theories of men's sexual orientation development and do not contribute to biological theories of women's sexual orientation development. Height distortion was not related to sexual orientation and only marginally related to sex. Predictors of height distortion were Impression Management, in both men and women, and Unmitigated Agency, in men. These findings highlight the complexity of sexual orientation development in men and women. These findings also highlight the role of certain psychosocial factors in how people perceive their bodies and/or how they want their bodies to be perceived by others.

Multi-Objective Genetic Algorithms for the Single Allocation Hub Location Problem

Hub Location Problems play vital economic roles in transportation and telecommunication networks where goods or people must be efficiently transferred from an origin to a destination point whilst direct origin-destination links are impractical. This work investigates the single allocation hub location problem, and proposes a genetic algorithm (GA) approach for it. The effectiveness of using a single-objective criterion measure for the problem is first explored. Next, a multi-objective GA employing various fitness evaluation strategies such as Pareto ranking, sum of ranks, and weighted sum strategies is presented. The effectiveness of the multi-objective GA is shown by comparison with an Integer Programming strategy, the only other multi-objective approach found in the literature for this problem. Lastly, two new crossover operators are proposed and an empirical study is done using small to large problem instances of the Civil Aeronautics Board (CAB) and Australian Post (AP) data sets.

The effects of consistency and inconsistency between attentional focus and task objective in learning a golf putting task

Converging evidence has demonstrated learning advantages when an individual is instructed to focus their attention externally. However, many of the motor tasks utilized in past research had clear external objectives (i.e., putting accuracy), creating a compatible relationship between an external focus of attention (i.e., outcome) and an external task objective (i.e., putting accuracy). The present study examined whether or not the consistency of instructions and task objective would differentially impact the acquisition of a golf putting task. Participants performed a putting task in a control condition or in one of four experimental conditions resulting from the factorial interaction of task instructions (internal or external) and task objective (internal or external). The retention and transfer data revealed that participants who received an external task objective demonstrated superior outcome scores. Participants who received technique information paired with outcome information demonstrated superior technique scores.

A Scalability Study and New Algorithms for Large-Scale Many-Objective Optimization

Many real-world optimization problems contain multiple (often conflicting) goals to be optimized concurrently, commonly referred to as multi-objective problems (MOPs). Over the past few decades, a plethora of multi-objective algorithms have been proposed, often tested on MOPs possessing two or three objectives. Unfortunately, when tasked with solving MOPs with four or more objectives, referred to as many-objective problems (MaOPs), a large majority of optimizers experience significant performance degradation. The downfall of these optimizers is that simultaneously maintaining a well-spread set of solutions along with appropriate selection pressure to converge becomes difficult as the number of objectives increase. This difficulty is further compounded for large-scale MaOPs, i.e., MaOPs possessing large amounts of decision variables. In this thesis, we explore the challenges of many-objective optimization and propose three new promising algorithms designed to efficiently solve MaOPs. Experimental results demonstrate the proposed optimizers to perform very well, often outperforming state-of-the-art many-objective algorithms.