The job-related fatality rate in the construction industry is high as a result of multiple factors associated with the safety of workers. However, mental fatigue, a prominent factor affecting one’s hazard perception, from engagement in construction tasks and its effects on fall hazard has not been adequately studied. This thesis proposes a two-trajectory framework to assess mental fatigue using Electroencephalography (EEG). Primarily, Wavelet Packet Decomposition (WPD) was used to obtain energy in each brain wave, and seven mental fatigue indices including θ, α, β, α/β, θ/α, θ/β, and (θ + α)/β were calculated. Secondarily, sample entropy (SampleEn) values were calculated for groups under comparison to examine the results from the WPD. Results from the adopted method suggest that typical construction activities and height exposure can cause mental fatigue and reduce vigilance level in workers. It is essential to have a quantitative approach for continuous cognitive monitoring to enhance construction safety.

This thesis set out to investigate the electrophysiological correlates of maths anxiety (MA). Research has shown that those with high MA (HMA) tend to have poorer accuracy and increased reaction time on maths based tasks and that high maths anxious individuals avoid situations where they might have to use maths. This can impact on their future by restricting their degree or job prospects. Previous research has identified the behavioural cognitive and psychological effects of MA and recently studies have begun to examine the associated underlying mechanisms in the brain. Chapter one outlines the background MA behavioural and measurement research before evaluating the neurophysiological methods used in cognitive neuroscience and the use of electroencephalography (EEG) in chapter two. Chapter three continues by outlining previous research concerning the neurophysiological processing of maths and number before evaluating relevant neurophysiological research concerning MA. Four experimental studies are conducted, exploring the neurophysiological underpinnings of MA research using EEG. Each of these recruits 30 participants and measures of electro-cortical (Event Related Potentials (ERPs), Global Field Power, Frequency etc.) and questionnaire measures are implemented. The first study aimed to identify whether the behavioural effects of MA (poorer accuracy and increased reaction time) are consistent with ERP differences (component amplitude and latency differences) in the brain and to understand why these effects are experienced. This revealed no significant comparisons between ERP components and behavioural responses involving low and high maths anxious individuals, but this may have been due to the lack of an anxious response by using a verification task, rather than requiring calculation. Study two introduces the measurement of gamma activity as a neurophysiological measure of anxiety and threat processing and brings three core areas of anxiety research together: Previous studies outline high anxiety in connection with gamma modulation, also showing gamma band activity is associated with the amygdala and finally, that the amygdala is responsible for the processing of threat perception and anxiety. This research has not been brought together when studying MA. Results produced similar ERP findings to the previous study but the introduction of gamma activity into the research provided the first differences between high and low MA (LMA) groups, showing significantly greater gamma activity levels in HMA individuals. However, this study only used numerically-based tasks, thus the third study implemented a non-numerical condition to act as a control. Study three replicates the findings showing a reduced level of gamma activity in high MA individuals for the non-numerical based task, however, this was also reduced for the simple maths task. It was theorised that it is more likely to be the initial threat perception that represents the anxious response and gamma activity increases. To test this and remove any working memory demands, the fourth study implements the presentation of single digit observation (using single digit numbers and letters). Even though there was no demand on working memory, high maths anxious participants displayed similar levels of gamma activity as low maths anxious individuals during letter observation. However, they had significantly greater levels during the observation of number. Findings suggest that HMA individuals may not only struggle with the processing of maths stimuli, but may have a threat-related response to the simple observation of numerical stimuli. This implies that HMA individuals consistently apply an avoidance technique due to a threat response associated with increased levels of gamma activity. The findings of the each study are finally discussed in terms of their contribution to the neurophysiological underpinnings of MA, the first exploration of this using gamma activity, future research and the extent that number anxiety may act as a precursor or sine qua non to MA.

Humans tend to preferentially process information relevant to themselves. For instance, in experiments where participants learn to manipulate stimuli referenced to themselves or someone else, participants exhibit larger reward processing signals for themselves. Additionally, attention and perception are biased not only towards one’s self but those related to them. However, the aspect of processing information related to known-others has not been addressed in reward learning. Here, I sought to address this issue. Specifically, I recorded electroencephalographic (EEG) data from 15 undergraduate student participants who played a simple two-choice “bandit” gambling game where a photo presented before each gamble indicated whether it benefited either the participant, an individual they knew, or a stranger. EEG data from 64 electrodes on a standard 10-20 layout were analyzed for event-related potentials (ERPs) elicited by target photos and gambling outcomes. Post experiment, I examined the relationship between relatedness and the amplitude reward learning ERPs, namely the reward positivity and the P300, with one-way repeated measures analyses of variance. My results demonstrate that the amplitudes of reward learning ERPs are sensitive to the target of a gamble. A secondary goal of this research was to determine if these differences could be explained by attentional and perceptual responses to cues of who a given gamble was for. Indeed, stepwise linear regression analyses identified the P2, N2, and P3 indexed relevance to self as predictors of resultant reward signals. My findings provide further evidence that a reward learning system within the medial-frontal cortex is sensitive to others with varying self-relevance, which may be a function of biases in attention and perception. / Graduate

Humans must process fleeting auditory information in real time, such as speech and music. The amplitude modulation of the acoustic waveforms of speech and music is rhythmically organized in time, following, for example, the beats of music or the syllables of speech, and this property enables temporal prediction and proactive perceptual optimization. At the neural level, external rhythmic sensory input entrains internal neural oscillatory activities, including low-frequency (e.g., delta, 1-4 Hz) phase, high-frequency (e.g., beta, 15-25 Hz) power, and their phase-amplitude coupling. These neural entrainment activities represent internal temporal prediction and proactive perceptual optimization. The present thesis investigated two critical but previously unsolved questions. First, do these multiple entrainment mechanisms for tracking auditory rhythm have distinct but coordinated perceptual functions? Second, does regularity in the temporal (when) domain associate with prediction and perception in the orthogonal spectral (what) domain of audition? This thesis addressed these topics by combining electroencephalography (EEG), psychophysics, and statistical modeling approaches. Chapter II shows that beta power entrainment reflects both rhythmic temporal prediction (when events are expected) and violation of spectral information prediction (what events are expected). Chapter III further demonstrates that degree of beta power entrainment prior to a pitch change reflects how well an upcoming pitch change will be predicted. Chapter IV reveals that rhythmic organization of sensory input proactively facilitates pitch perception. Trial-by-trial behavioural-neural associations suggested that delta phase entrainment reflects temporal expectation, beta power entrainment reflects temporal attention, and their phase-amplitude coupling reflects the alignment of these two perceptual mechanisms and is associated with auditory-motor communication. Together, this thesis advanced our understanding of how neural entrainment mechanisms relate to perceptual functions for tracking auditory events in time, which are essential for perceiving speech and music. / Thesis / Doctor of Science (PhD) / Perceiving speech and musical sounds in real time is challenging, because they occur in rapid succession and each sound masks the previous one. Rhythmic timing regularities (e.g., musical beats, speech syllable onsets) may greatly aid in overcoming this challenge, because timing regularity enables the brain to make temporal predictions and, thereby, anticipatorily prepare for perceiving upcoming sounds. This thesis investigated the perceptual and neural mechanisms for tracking auditory rhythm and enhancing perception. Perceptually, rhythmic regularity in streams of tones facilitates pitch perception. Neurally, multiple neural oscillatory activities (high-frequency power, low-frequency phase, and their coupling) track auditory inputs, and they are associated with distinct perceptual mechanisms (enhancing sensitivity or decreasing reaction time), and these mechanisms are coordinated to proactively track rhythmic regularity and enhance audition. The findings start the discussion of answering how the human brain is able to process and understand the information in rapid speech and musical streams.

People with schizophrenia are known to have difficulties with episodic memory (EM). The purpose of this investigation was to examine the relationship between theta-power and: i) behavioural measures of EM performance, ii) event- related potential (ERP) indices of recollection and, iii) measures of schizophrenia symptomatology. In doing so, the aim was to gain a better understanding of the basic neural mechanisms that contribute to successful EM performance, and how these may differ for people with schizophrenia. The present investigation adopted an endophenotypic approach and collected measures of schizotypy from student participants to minimise patient factors that can confound interpretations. Fifty- four participants were asked to complete a reality-monitoring exclusion EM paradigm whilst electroencephalogram (EEG) data were collected. Measures of theta-power and ERPs were time-locked to words presented during the retrieval phase. There was a significant positive correlation between theta-power over Fz between 600-1000ms post-stimulus presentation and estimates of recollection in the imagine condition as well as a significant negative correlation between these measures of theta-power for perceive items and ERP indices of recollection for imagine items. There was also a significant positive correlation between measures of frontal theta-power in the imagine condition and negative schizotypy. The epoch employed means it is likely these measures of theta- power reflect processes contributing to the content-specific retrieval of imagined items, and post-retrieval processes acting in service of differentiating imagined items in EM. Results are discussed in terms of suggestions for interventions and directions for future research.

Στην εργασία αυτή θα γίνει μελέτη και εφαρμογή της μεθόδου Ανάλυσης Ανεξάρτητων Συνιστωσών πάνω σε σήματα ηλεκτροεγκεφαλογραφημάτων. Το πρώτο κεφάλαιο αποτελείται από μια εισαγωγή στις ιδιότητες και την προέλευση των ηλεκτροεγκεφαλικών σημάτων, καθώς και στη μεθοδολογία, τον σκοπό και τη χρησιμότητα των ΗΕΓ. Στη συνέχεια παρουσιάζονται τα προβλήματα που αντιμετωπίζει η ανάλυση σημάτων όταν εφαρμόζεται στα ΗΕΓ, καθώς και οι μέχρι στιγμής χρησιμοποιούμενες λύσεις. Στο δεύτερο κεφάλαιο της εργασίας παρουσιάζονται τα αποτελέσματα της βιβλιογραφικής έρευνας πάνω στην ανάλυση ανεξάρτητων συνιστωσών. Επίσης θα δοθεί το μαθηματικό υπόβαθρο και η αιτιολόγηση της επιλογής ενός συγκεκριμένου αλγορίθμου, του FastICA. Στο τρίτο κεφάλαιο γίνεται η εφαρμογή της μεθόδου ΑΑΣ πάνω σε καταγεγραμμένα σήματα ηλεκτροεγκεφαλογραφημάτων, μέσω του περιβάλλοντος Matlab. Πραγματοποιείται η ανάλυση σε συνιστώσες, αναγνωρίζονται και αφαιρούνται τα σήματα μη εγκεφαλικής προέλευσης και τελικά χρησιμοποιείται μέθοδος απεικόνισης των πηγών εγκεφαλικής δραστηριότητας ως ισοδύναμα ηλεκτρικά δίπολα. Το τέταρτο και τελευταίο κεφάλαιο συνοψίζει τα αποτελέσματα και τα συμπεράσματα που εξήχθησαν κατά τη διάρκεια της εκπόνησης αυτής της διπλωματικής. / -

Real-world decision making is challenging due, in part, to changes in the underlying reward structure: the best option last week may be less rewarding today. Determining the best response is even more challenging when feedback validity is low. Presented here are the results of two experiments designed to determine the degree to which midbrain reward processing is responsible for detecting reward contingency changes when feedback validity is low. These results suggest that while midbrain reward systems may be involved in detecting unexpected uncertainty in non-stationary environments, other systems are likely involved when feedback validity is low – namely, the locus-coeruleus-norepinephrine system. Finally, a computational model that combines these systems is described and tested. Taken together, these results downplay the role of the midbrain reward system when feedback validity is low, and highlight the importance of the locus-coeruleus-norepinephrine system in detecting reward contingency changes.

No description available.

abstract: The recent spotlight on concussion has illuminated deficits in the current standard of care with regard to addressing acute and persistent cognitive signs and symptoms of mild brain injury. This stems, in part, from the diffuse nature of the injury, which tends not to produce focal cognitive or behavioral deficits that are easily identified or tracked. Indeed it has been shown that patients with enduring symptoms have difficulty describing their problems; therefore, there is an urgent need for a sensitive measure of brain activity that corresponds with higher order cognitive processing. The development of a neurophysiological metric that maps to clinical resolution would inform decisions about diagnosis and prognosis, including the need for clinical intervention to address cognitive deficits. The literature suggests the need for assessment of concussion under cognitively demanding tasks. Here, a joint behavioral- high-density electroencephalography (EEG) paradigm was employed. This allows for the examination of cortical activity patterns during speech comprehension at various levels of degradation in a sentence verification task, imposing the need for higher-order cognitive processes. Eight participants with concussion listened to true-false sentences produced with either moderately to highly intelligible noise-vocoders. Behavioral data were simultaneously collected. The analysis of cortical activation patterns included 1) the examination of event-related potentials, including latency and source localization, and 2) measures of frequency spectra and associated power. Individual performance patterns were assessed during acute injury and a return visit several months following injury. Results demonstrate a combination of task-related electrophysiology measures correspond to changes in task performance during the course of recovery. Further, a discriminant function analysis suggests EEG measures are more sensitive than behavioral measures in distinguishing between individuals with concussion and healthy controls at both injury and recovery, suggesting the robustness of neurophysiological measures during a cognitively demanding task to both injury and persisting pathophysiology. / Dissertation/Thesis / Ph.D. Speech and Hearing Science 2014

In recent years, emotion classification using electroencephalography (EEG) has attracted much attention with the rapid development of machine learning techniques and various applications of brain-computer interfacing. In this study, a general model for emotion recognition was created using a large dataset of 116 participants' EEG responses to happy and fearful videos. We compared discrete and dimensional emotion models, assessed various popular feature extraction methods, evaluated the efficacy of feature selection algorithms, and examined the performance of 2 classification algorithms. An average test accuracy of 76% was obtained using higher-order spectral features with a support vector machine for discrete emotion classification. An accuracy of up 79% was achieved on the subset of classifiable participants. Finally, the stability of EEG patterns in emotion recognition was examined over time by evaluating consistency across sessions. / Thesis / Master of Science (MSc)