No description available.

Emotion Regulation refers to the process of controlling our emotions. However, the brain regions which are involved in emotional processes, such as the prefrontal cortices, are the last regions to be developed throughout the human brain. Those who are most affected by this slow development are adolescents especially since they undergo hormonal and neural changes. Previous research has shown mindfulness meditation improves emotional stability and inhibitory control. Since our brain is not fully developed until the age of 25, it is particularly interesting to get knowledge of the effect of mindfulness on emotion regulation in adolescents, which is the aim of this thesis. A total of three studies met the inclusion criteria and were included in this systematic review. The results showed a larger reaction in the amplitude of P2, N2, and late positive potentials on both negative and positive stimuli but not neutral stimuli. Differences were observed in the high vs low mindfulness adolescents in frontal EEG asymmetry during emotion regulation tasks. These findings suggest that even brief mindfulness can have a positive effect on emotion regulation processes by enhancing prefrontal cortices. These findings contribute to the understanding of whether mindfulness affects emotional regulation in a developing brain. However, future research is needed to clarify the effects of mindfulness on emotion regulation in adolescents.

In this thesis, the perturbation-based decomposition technique developed by Szlavik [1] was used in an attempt to solve the inverse problem in EEG source localization. A set of dipole locations were forward modeled using a 4-layer sphere model of the head at uniformly distributed lead locations to form the vector basis necessary for the method. Both a two-dimensional and a pseudo-three-dimensional versions of the model were assessed with the two-dimensional model yielding decompositions with minimal error and the pseudo-three-dimensional version having unacceptable levels of error. The utility of interpolation as a method to reduce the number of data points to become overdefined was assessed as well. The approach was effective as long as the number of component functions did not exceed the number of data points and stayed relatively small (less than 77 component functions). This application of the method to a spatially variate system indicates its potential for other systems and with some tweaking to the least squares algorithm used, could be applied to multivariate systems.

Depression has increased among adolescents and adults over the last decade. Effective treatments and techniques to improve personal well being and disorders like depression are much needed. Mindfulness is a psychological technique that involves actively paying attention to one's awareness of the present moment with nonjudgmental acceptance (Kabat-Zinn, 1990). While the effectiveness of mindfulness interventions has been widely studied, relatively little research has been done on the effects of mindfulness interventions on depression using neuroimaging techniques such as functional magnetic resonance imaging (fMRI) or electroencephalography (EEG). This systematic review includes four studies that investigates the effectiveness of mindfulness interventions on depression measured by fMRI or EEG and different rating scales measuring depression. The results from this systematic review shows that mindfulness interventions may have an effect on depression. Two of the studies (Ferri et al., (2017); Yang et al., (2016), found significant differences in the rating scales for depression. The studies also suggest that mindfulness interventions can impact the brain regions involved in negative emotional processing in individuals with depression, such as the default mode network (DMN) and the dorsal anterior cingulate cortex (dACC).

Many of the skills that are considered noteworthy in our societies are either acquired through training and dedication or granted to those lucky enough to have the right genetics and environment. But one skill that is often overlooked is the ability to keep rhythm. This skill is both remarkable in temporal accuracy and common. And although rhythm-keeping is a common cognitive skill, not much is known about the neural correlates of rhythm-keeping. The aim of the current exploratory study was to investigate the electrophysiological correlates of rhythm-keeping. In this study, participants were asked to perform a task where they were introduced to a rhythm with both auditory and visual cues to correct themselves after. They were then supposed to keep the rhythm for approximately thirty seconds, even though all stimuli indicating the rhythm were removed after six seconds of performing the task. During the task, electrophysiological data were collected using electroencephalography (EEG). The electrophysiological data and task performance were then analysed using mass univariate analysis, but no significant relationship was found between the electrophysiological data and rhythm-keeping performance. Potential issues underlying these non-significant findings, as well as solutions to address these, will be addressed.

Recent advances in neuroimaging and electromagnetic measurement technology have permitted the exploration of structural and functional brain alterations associated with chronic pain. A number of cortical and subcortical brain regions have been found to be involved in the experience of chronic pain (Baliki et al., 2008; Jensen et al., 2010). Evidence suggests that living with chronic pain shapes the brain from both an architectural and a functional perspective, and that individuals living with chronic pain display altered brainwave activity even at rest. Quantitative EEG (qEEG) is a method of spectral analysis that utilizes a fast Fourier transform algorithm to convert analog EEG signals into digital signals, allowing for precise quantification and analysis of signals both at single electrode locations and across the scalp as a whole. An important advance that has been permitted by qEEG analysis is the development of lifespan normative databases against which individual qEEGs can be compared (Kaiser, 2006; Thatcher et al, 2000). Pilot data utilizing qEEG to examine brainwave patterns of individuals with chronic pain have revealed altered EEG activity at rest compared to age- and gender-matched healthy individuals (Burroughs, 2011). The current investigation extended the findings of the pilot study by utilizing qEEG to examine a larger sample of individuals with chronic pain. Individuals with chronic pain displayed significantly reduced slow wave activity in frontal, central, and temporal regions. Findings will be presented in terms of specific patterns of altered EEG activity seen in individuals with chronic pain.

The aging population and increase of ambulatory surgeries have greatly increased strain on surgical and post-surgical staff that decreases the safety of care. Our overall goal is to find ways to decrease the time of anesthetic recovery to allow for more efficient post-surgical treatment. The specific aims of this study were to assess the correlations between neurocognitive recovery measures of attention and vigilance to brain dynamics. We analyzed reaction time via auditory psychomotor vigilance testing (aPVT) testing and the Richmond agitation-sedation scale (RASS) scores in 145 patients prior to and preceding surgery. Intraoperative electroencephalogram was also recorded for 115 of those patients. Data was analyzed to associate aPVT performance to recovery time and intraoperative brain dynamics. We found an association coefficient between reaction time and RASS recovery of 0.022 (p-value = 0.0001) showing a significant association. Further, we found age to be a significant confounding variable (p=0.04421) and included this in our association model. Lastly, there was no significant association found between intraoperative burst suppression and reaction time values (p=0.497). Overall, aPVT was found to be a robust test to assess recovery timeline in peri-operative anesthesia care unit patients. These results highlighted the potential use of an objective metric to track neurocognitive recovery after anesthesia, especially in elderly patients undergoing surgery.

No description available.

No description available.

Timing, and ergo rhythm, are intrinsic features of language that help facilitate real-time speech comprehension. However, work exploring how variable timing is processed in speech is limited. This dissertation addresses this gap in literature by exploring the tenets of how temporal variability is cognitively processed, particularly in the context of real-time stimulus processing. This research is one of the first works to examine temporal variations in linguistic and other acoustically complex contexts. Using electroencephalography (EEG) and behavioural methods, participants were tested on their perception of temporal variations within a continuous stream of either simple tones, complex waves, or syllables. Two timing deviants were presented that occurred early or late compared to other stimuli in the sequence. Event-related potentials (ERPs) were recorded for each stimulus type across three experiments. A fourth experiment tested participant recognition memory for syllable order. Results showed differential processing between the two timing deviants. Unexpectedly earlier tokens elicited larger pre-attentive responses compared to late, suggesting a saliency for the earlier tokens that was not present for the delayed ones. This pattern was observed across all three levels of acoustic and linguistic complexity. Compared to sequences with no timing deviants or an early timing deviant, unexpectedly late tokens were more detrimental to memory, suggesting a negative impact of delays on verbal recognition. Thus, not only were early and late timing variations processed differently, but delays in continuous sequences were also more cognitively taxing for working memory. The results reported in this dissertation contribute to existing knowledge by enriching our understanding of the fundamentals of how aspects of prosodic timing may affect attention and memory. Additionally, it provides new insights into how speech synthesis can be used in neurolinguistic research by tracking how neurophysiological responses change with increasing acoustic complexity and linguistic familiarity. / Dissertation / Doctor of Philosophy (PhD) / This thesis examines how unexpectedly shorter or longer pauses in speech may affect speech comprehension. Specifically, the research reported here examined how stimuli that are presented unexpectedly early or unexpectedly late in a steady-rate sequence impact a listener’s attention and memory. Although the speed at which we speak has been studied previously, work on unexpected changes in its timing has been limited. This research begins to explore this aspect of speech processing. It contributes to our understanding of how speech timing is processed in two important ways. First, we found that unexpected delays in both non-linguistic sounds and syllables were less noticeable than unexpectedly early presentations, when participants were not required to pay attention to them. Second, we found that unexpected delays made recognition memory for stimulus order worse. Overall, the results of these studies indicate that unexpected delays in the rhythm of speech make it more difficult to understand.