This dissertation aims to develop a formal foundation to design an adaptive output feedback predictor for a class of unknown systems where parameters and order are unknown or high-dimensional. We present a reduced-order adaptive output-predictor scheme based on modal reduction and Lyapunov's method. Moreover, the credibility of the proposed reduced-order adaptive output-predictor scheme is validated by mathematical proof, and numerical and experimental studies, such as single pendulum, double pendulum, six-link pendulum, rope as a high-dimensional rope, and EEG data. Then the dissertation goal is to experimentally validate the proposed reduced-order model parameterization technique for tracking uncertain linear time-invariant (LTI) single-input, single-output (SISO) systems. The proposed theory focuses on parameterizing a high-dimensional, uncertain model and introduces a reduced-order adaptive output predictor capable of forecasting the system's output. This predictor utilizes auto-regressive filtered vectors, incorporating the input and output history. The adaptive output predictor is a simplified and known model, making it suitable for controlling high-dimensional, uncertain SISO systems without access to full-state measurements. Specifically, this work establishes the foundation for parameterizing uncertain models, creating a virtual structure that emulates the actual system, and offering a more manageable model for control when the objective is solely to regulate the system's output. The primary focus of this research is to assess the effectiveness and output-tracking capabilities of the proposed approach. These capabilities are extensively examined across diverse platforms and hardware configurations, relying solely on input and output data from the models without incorporating any additional information on the system dynamics. In the first experiment, the predictor's ability to track the angle of a single pendulum, including additional dynamics, is evaluated using only input-output data. The second experiment targets tracking the endpoint of a rope connected to a single pendulum, where the rope emulates a high-dimensional model. A vision system is designed and employed to acquire the rope endpoint position data. Before the rope experiment, a set of experiments is conducted on single pendulum hardware to ensure the accuracy of the vision system's data collection. Comparative analysis between data from object tracking via vision and data acquired through an encoder demonstrates negligible error. Finally, the input and the endpoint output data from the rope experiment are fed into the predictor to assess its capability to track the rope endpoint position without utilizing specific knowledge of the experimental hardware. Achieving negligible error in tracking implies that the predictor provides a simple and accurate representation of the rope dynamics. Consequently, designing a controller for this known model is equivalent to designing a controller for the actual rope system dynamics. The predictor, by closely emulating the behavior of the rope, becomes a reliable surrogate model for control design, simplifying the task of controller design for the complex and uncertain high-dimensional system. Finally, this study introduces a novel approach to enhance controller design for complex brain dynamics by employing a reduced-order adaptive output predictor proposed in [1], fine-tuned with chirp binaural beats. The proposed technique is promising for developing closed-loop controllers in non-invasive brain stimulation therapies, such as binaural beats stimulation, to improve working memory. The study focuses on parameterizing uncertain models and creates a predictor that utilizes auto-regressive filtered vectors to forecast mean phase lock values generated by binaural beats stimulation. The simplified and known model of the predictor proves effective in tracking brain responses, as demonstrated in experiments evaluating its ability to track mean phase locking values. The results indicate negligible tracking error, suggesting the predictor's reliability in representing brain dynamics and simplifying the task of controller design for the complex and uncertain high-dimensional system. / Doctor of Philosophy / This dissertation explores the development of a reduced-order adaptive output predictor for unknown systems with unknown or high-dimensional parameters and order. A reduced-order adaptive output predictor scheme is introduced, validated through mathematical proof, and tested in diverse scenarios, including pendulum systems and EEG data. The focus is on parameterizing uncertain models and creating a simplified adaptive output predictor capable of forecasting system output, specifically for SISO systems. Experimental validation involves tracking the angle of a single pendulum and the endpoint of a high-dimensional rope, demonstrating the predictor's accuracy without detailed knowledge of system dynamics. The study extends its application to complex brain dynamics, using the predictor fine-tuned with chirp binaural beats. Results show promise for developing closed-loop controllers in non-invasive brain stimulation therapies, offering a novel approach to improve working memory via helping to design closed-loop controllers.

Shyness is highly related to internalizing problems. However, not all shy children develop serious internalizing problems (IP). The aim of the current study was to identify the endogenous factors that might contribute to the resilience process from a self-regulation perspective. Participants included 73 children (33 boys; 40girls) who visited the lab at 6 and 9 years of age. Shyness, attentional control (AC), inhibitory control (IC), frontal electroencephalogram (EEG) asymmetry were measured at both 6 and 9 years using age appropriate questionnaires and tasks. Results indicated that age 6 shyness did not directly predict age 9 IP; instead it indirectly predicted IP through age 9 shyness. Neither AC, IC, frontal EEG asymmetry, nor the stability of frontal EEG asymmetry moderated the association between age 6 shyness and age 9 IP. However, there was a positive concurrent association between shyness and IP at 9 years. In addition, AC and IC moderated the shyness-IP association at age 9. Shyness was significantly associated with IP only when children had low AC or IC, but not when children had high AC or IC. / Master of Science / Shyness is highly related to internalizing problems. However, not all shy children develop serious internalizing problems (IP). The aim of the current study was to identify the within-individual factors that might protect children away from having IP from a self-regulation perspective. Participants included 73 children (33 boys; 40girls) who visited the lab at 6 and 9 years of age. Shyness, attentional control (AC), inhibitory control (IC), frontal electroencephalogram (EEG) asymmetry were measured at both 6 and 9 years using age appropriate questionnaires and tasks. Results indicated that children who are shy at 6 years old may not have IP at 9 years old. Instead children who are shy at 6 years old tend to be shy at 9 years old. And those who are shy at 9 years old are more likely to have IP at the same period of time. Neither AC, IC, frontal EEG asymmetry, nor the stability of frontal EEG asymmetry affect the direction or degree of the association between age 6 shyness and age 9 IP. In addition, AC and IC affect the concurrent shyness-IP association at age 9. Shyness was significantly associated with IP only when children had low AC or IC, but not when children had high AC or IC.

<p dir="ltr">Abstract: Atypical frontal alpha asymmetry is the difference in EEG-measured alpha-band power between right and left hemispheres, and patterns of lateralization are thought to reflect motivational direction (approach/withdrawal) and affective processing. Increased rightward frontal alpha asymmetry is associated with tendency toward approach-related behavior often displayed in attention-deficit/hyperactivity disorder (ADHD), though findings have been inconsistent. While differences in results may be partially accounted for by within-diagnosis heterogeneity, growing evidence suggests individual response tendency and emotional salience of a situation may influence one another. Investigating the potential interactions between trait and state measured variables may therefore clarify lateralization patterns in ADHD. The current study measured frontal alpha asymmetry in a well-characterized sample of school-aged children with and without ADHD. EEG during standard resting-state and emotional passive-viewing tasks were recorded from 220 children (nADHD = 97). A semi-structured clinical interview and standardized rating scales were collected to assign DSM-5 diagnoses and temperament group belonging. Parent measures included the behaviorally-rated Temperament in Middle Childhood Questionnaire (TMCQ). Latent profile analysis within the ADHD group revealed two temperament subgroups: emotionally regulated and emotionally dysregulated (high anger and sadness). EEG assessment suggests children broadly produced a more rightward asymmetry while in resting state compared to a task-based condition, though show no notable differences between neutral and negative emotional task conditions. ADHD diagnostic status, temperament group, and sex assigned at birth did not impact patterns of asymmetry. Results emphasize measurement differences in frontal alpha asymmetry between lab-based tasks and further highlight the importance of state influences on alpha lateralization.</p>

Over the last decades, imaging methods in animal models underwent revolutionary developments. Yet the potential of novel and accurate techniques for the imaging of neural substrates realizes fully only through interaction with human research and its system-level understanding of brain function. For instance, cross-species investigation is fundamental for auditory neuroscience, in particular in the study of sound source localization processing. The translation of auditory spatial cues into their neural representation has been addressed in multiple studies across species, allowing the development of theoretical and functional models of auditory space. However, auditory localization within the vertical plane remains less explored, with few animal studies addressing the neuroscience of elevation perception in the cortex. The study presented here aims to set the basis to bridge this knowledge gap, leveraging the interaction of human and animal neuroscience. Recent human studies identified an inverse linear relationship between sound source elevation and cortical activity and revealed remarkable plasticity in auditory cortical tuning for elevation. Building on these results, our laboratory conducted an Electroencephalography (EEG) experiment with human subjects. That study confirmed that sound source elevation is represented in a systematic manner in the human auditory cortex, but did not elucidate how the cortical substrate supports this representation. In fact, EEG lacks the spatial resolution to fully investigate the generators of the signals it measures, the circuital components of the auditory cortex. To bypass this challenge, we can assess if the same experimental protocol can yield similar results in a mouse model, the substrates of which can then be interrogated with molecular imaging tools. The results of such circuital dissection do not necessarily translate back to human research but can inform and guide its explorations provided solid theoretical basis and supporting computational models. Thus, in this dissertation we develop a comprehensive experimental platform for mouse EEG, aiming to translate protocols from human cognitive neuroscience to animal models. This translation, and its validation, lays the groundwork for further interrogation of the neural substrates of auditory perception and is the purpose of two experiments we present at the end of this thesis. We dedicate Chapter 1 to highlighting the necessity of integrating human and animal models to comprehend cortical functions and their implications for complex behavior. To further demonstrate the potential of this approach, in Chapter 2 we highlight the importance of omission responses, corollary discharge, and mismatch negativity (MMN) research from an interactionist standpoint, further showcasing how animal models can elucidate circuit-level substrates and contribute to multisensory integration theories. This investigation requires a deep understanding of spatial audition, and to this end in Chapter 3, we provide such detailed exploration, focusing on the auditory system's ability to localize sound within a three-dimensional space. In Chapter 4 we detail the modular setup for mouse EEG and imaging that we developed from scratch as part of this doctoral work. This setup is designed to facilitate the precise delivery of auditory stimuli and the accurate recording of EEG and optical imaging data under controlled conditions. The modular design philosophy centers on the integration of a robotic surgery station, anesthesia system, stimulus delivery system, optical imaging, and EEG systems in an integrated station, ensuring seamless transfer between different stations depending on the experiment requirements. We overview these components in the hardware section, which also describes the auditory stimulation system with its speaker arch that can be employed in a horizontal or vertical position. We also describe the surgical station, highlighting the modified stereotaxic apparatus and the surgical robot that allows for automated skull drilling and electrode array placement with micrometer-level precision. In the EEG systems section, we delineate the two types of EEG apparatus used in the experiments: subcutaneous needle electrodes (SNE) and multielectrode array (MEA). We discuss the advantages and drawbacks of SNE, the electrode positioning, and the importance of the reference and ground electrodes. We also describe the MEA system, emphasizing its high-density recordings and reduced movement artifacts. Finally, in the workflow section, we outline the sequence of operations for the experiments, from electrode implantation to processor initialization and stimulus presentation. We detail the electrode implantation procedures for both SNE and MEA, the initialization of processors and software for managing the EEG and stimulation systems, and the Python experimental platform that integrates all these components into a cohesive experimental protocol. We first employed this setup for the experiment detailed in Chapter 5 to explore the processing of sound source elevation in mice employing an adapter-probe paradigm. The aim was to assess whether it would yield comparable results to its application in humans. This paradigm is designed to induce short-term auditory adaptation, which leads to a decrease in neural responses to stimuli. By utilizing an adapter stimulus without local cues, we prevent suppression of location-specific processing, while silencing other sound-responsive neurons. We then present probe stimuli from different elevations, the responses to which should be dependent on the elevation modulation rather than the auditory processing suppressed by the adapter. This strategy allows us to record elevation-specific EEG activity with a better signal-to-noise ratio than would be otherwise possible. With this approach, we measured ERP components that align with those documented in humans, with a typical latency shift. Among these components, we identified a novel ERP correlate of sound source elevation processing in mice. This neural signature consists of a slow-rising mid-latency ERP component, which parallels the one elicited by the same protocol in humans. However, the effect of elevation was small, and limited to a contrast between the response to central stimuli and those above and below the animal. Our results reinforce the notion that mice ERPs can be used to investigate sound source elevation, highlighting similarities between human and mouse auditory processing. However, these conclusions hinge on an additional exploration into whether the auditory system of anesthetized mice can reliably produce responses specific to sound elevation. We address this critical aspect in the experiment presented in Chapter 6. In this second experiment, we employed a mismatch paradigm to discern whether anesthetized mice could differentiate between high and low sound sources. This involved alternating each sound source elevation as a deviant within a regular sequence of stimuli at the same elevation. We hypothesized that if the mice's auditory system could distinguish these elevations, we would observe an MMN effect, indicated by more negative responses to deviant stimuli compared to standard ones. This effect would be more pronounced for deviant stimuli from elevations further from the standard than for those closer. To enhance our experimental setup, we utilized a proprietary MEA for improved standardization and spatial resolution. With this setup we observed a biphasic MMN, with two distinct negative deflections, confirming the auditory system's capability to process stimuli from different elevations. This finding was intriguing, also considering the importance of head movements in auditory spatial perception, as discussed earlier. The biphasic nature of MMN might reflect different stages of cortical processing, with the late MMN suggesting complex spectral comparison as a possible analog of the human late discriminative negativity. We also found that deviant stimuli at -30 and 90° elevation did not elicit mismatch responses when presented in experimental blocks where the standard was at a 60° distance, but did when the standard was at a 120° distance. This finding confirmed our initial hypothesis However, our results also highlighted the unique status of the 30° elevation stimulus. In contrast to other elevations, the 30° stimulus showed a more pronounced early adaptation, and elicited a strong MMN as a deviant in the 60° proximity scenario. This suggests a possible bias in auditory processing towards this elevation range, potentially influenced by top-down modulation. The distinct adaptation behavior of the 30° stimulus could be a consequence of such modulation, aligning with behavioral studies and electrophysiological findings in other species. Further, we proposed a model where MMN elicitation in mice depends on the proximity of the deviant to a preferred elevation angle, near 30°, and the distance of the standard from the deviant. Such model could capture the dynamics of elevation representation mismatch. To explore these effects, further experiments with additional conditions are needed, potentially leading to a quantitative model of elevation deviance. Finally, in Chapter 7 we further explore possible research directions that could follow the work presented here, beyond what was already introduced in the experimental chapters

This dissertation examines the emerging practice of consumer neuroscience and neuromarketing, combined called CNNM. CNNM utilizes tools and technologies to measure brain activity and human behavior coupled with scientific theories for explaining behavior and cognition. Consumer neuroscience is one of the newest areas of application of neuroscience and related techniques, and is of significant social consequence for its possible deployment in the market place to both study and shape consumer behavior. Concerns arise in terms of consumer influence and manipulation, but there are also concerns regarding the actual efficacy and utility of the technologies and the application of behavioral theories. The dissertation's three essays each examine a facet of CNNM. Using historical sources, conference participation, and ethical analyses, the dissertation forms a multi-prong effort at a better understanding of CNNM through the use of science and technology studies (STS) methods. The first essay is an historical review of the usage of technologies to measure brain activity and behavior, parallel to the development of psychological theories created to account for human decisionmaking. This essay presents a new conception of "closure" and "momentum" as envisioned by social construction of technology and technological momentum theories, arriving at a new concept for inclusion called "convergence" which offers a multi-factor explanation for the acceptance and technical implementation of unsettled science. The second essay analyzes four discourses discovered during the review of approximately seventy presentations and interviews given by experts in the field of CNNM. Using and adapting actor-network theory, the essay seeks to describe the creation of expertise and group formation in the field of CNNM researchers. The third essay draws on a variety of ethical analyses to expand understanding of the ethical concerns regarding CNNM. It raises questions that go beyond the actual efficacy of CNNM by applying some of the theories of Michel Foucault relating to the accumulation of power via expertise. This essay also points in the direction for actionable steps at ameliorating some of the ethical concerns involving CNNM. CNNM is a useful technique for understanding consumer behavior and, by extension, human behavior and neuroscience more generally. At the same time, it has been routinely misunderstood and occasionally vilified (for concerns about both efficacy and non-efficacy). This dissertation develops some of the specific historical movements that created the field, surveys and analyzes some of the foremost experts and how they maneuvered in their social network to achieve that status, and identifies novel ethical issues and some solutions to those ethical issues. / Ph. D. / Consumer neuroscience, or neuromarketing, (CNNM) is a new and emerging field which uses different devices to measure brain activity and behavior. For many years, scientists and marketers have been seeking to understand and explain decisions and, more specifically, consumer decisions. It has only been in the most recent decades that technology and scientific theories have been working in a close fashion to help understand human decision and consumer behavior. In three essays, this dissertation uses tools from science and technology studies (STS) to better understand CNNM. In Essay One, I track the parallel history of the technologies to measure brain activity and behavior with scientific theories put forward to explain them. In Essay Two, I analyze the content of presentations given by experts in the field to understand how CNNM expertise is formed. In Essay Three, I explore the ethical concerns and propose some new ways of solving some of the ethical problems (such as power, influence, and expertise.) CNNM is an important social phenomenon because of its possibilities of helping marketers, but it is also important for its part in developing areas of technology and scientific theories. The dissertation represents some new approaches at helping to understand its complexities and consequences.

Response inhibition and the ability to navigate distracting information are both integral parts of cognitive control and are imperative to adaptive behavior in everyday life. Thus far, research has only inconclusively been able to draw inferences regarding the association between response stopping and the effects of interfering information. Using a novel combination of the Simon task and a stop signal task, the current study set out to investigate the behavioral as well as the neurophysiological underpinnings of the relationship between response stopping and interference processing. We tested n = 27 healthy individuals and combined temporal EEG signal decomposition with source localization methods to delineate the precise neurophysiological dynamics and functional neuroanatomical structures associated with conflict effects on response stopping. The results showed that stopping performance was compromised by conflicts. Importantly, these behavioral effects were reflected by specific aspects of information coded in the neurophysiological signal, indicating that conflict effects during response stopping are not mediated via purely perceptual processes. Rather, it is the processing of specific, stop-relevant stimulus features in the sensory regions during response selection, which underlies the emergence of conflict effects in response stopping. The findings connect research regarding response stopping with overarching theoretical frameworks of perception–action integration.

Although numerous studies have closely examined the processes by which working memory (WM) updates and maintains information, there has been a paucity of research examining the switching mechanism between these two WM functions. O’Reilly & Frank (2006) proposed that the switching process is governed by a WM 'gate' that opens the gate to switch WM function from maintenance to updating and closes the gate to reverse the process. It is noteworthy that subsequent studies have consistently observed an asymmetry between opening and closing the WM gate. This asymmetry is manifested as a higher time cost but a lower error rate when closing the WM gate than when opening the gate. Until now, this asymmetry and the WM gating process have not been well understood. The objective of my dissertation was to elucidate the essential components of WM gating processes that determine the asymmetry between opening and closing. In particular, the roles of inhibitory control (on the state of the WM gate switches from) and intentional control (on the state the gate switches to) were investigated. A total of four studies were conducted in stages. The first study extracted the neurophysiological constituents of WM gating processes. The second study investigated the difference in effort investment between WM gate opening and closing. Another two studies further explored the causality of the asymmetry via brain stimulation methods. All studies replicated the behavioral asymmetry between gate opening and closing (lower error rate and higher time cost for gate closing). A common neurophysiological pathway of the WM gating cascade from the ventral stream to the frontal cortex was revealed, suggesting that WM gate opening and closing follow common steps of inhibition of the previous gate state and reactivation of the required gate state. Nevertheless, the ventral stream distinguished residual preceding gate activation, whereby a stronger preceding gate state (open) remained highly activated before closing than gate-close state before opening and subsequently affected inhibitory control over it. Additionally, distinct frontal activities were observed between opening and closing, indicating a switch of attention to different sources. Strong intentional control was involved to direct the attention to sensory information during gate opening. These findings suggest that the opening of the WM gate is more effortful than the closing of the WM gate, which is perceived as more natural and effortless. It is likely that the human brain tends to maintain the WM in a closed state, and this default tendency to close the WM gate may be the origin of the asymmetry in gating performance. This knowledge sheds the light on the mechanism of WM controls and suggests a potential for predicting the developmental patterns of WM and WM deficiencies in psychiatric disorders.:PREFACE III ACKNOLEDGEMENTS V LIST OF FIGURES XI LIST OF TABLES XIII INDEX OF ABBREVATIONS XV ABSTRACT XVII CHAPTER 1 INTRODUCTION 1 1.1 A general introduction 3 1.2 What is the gating of WM? 4 1.3 Cognitive processes associated with WM gating 6 1.3.1 Switching-inspired view of WM gating mechanism 6 1.3.2 Inhibitory control and its potential association with gating cost in time 7 1.3.3 Intentional control and its potential association with gating accuracy 9 1.3.4 My hypothesized model of WM gating 9 1.4 Neurophysiological and anatomical associations with the WM gating process 11 1.4.1 The role of alpha band activities in the inhibition of the preceding gate 12 1.4.2 The role of theta band activities in the reconfiguration of the new WM gate 13 1.4.3 The prefrontal cortex potentially executes the WM gating 14 1.4.4 Associations between the WM gating and the frontoposterior network 15 1.5 Neurobiological underpinnings of the WM Gating 16 1.5.1 The GABAergic system and its associations with inhibitory control 16 1.5.2 The norepinephrine system and its associations with intentional control 17 CHAPTER 2 HYPOTHESES AND METHODOLOGIES 19 2.1 General hypotheses and objectives 21 2.2 Research questions and study design 22 2.2.1 The paradigm: reference-back task 22 2.2.2 Study 1: whether and how are WM gating processes constituted? 24 2.2.3 Study 2: how do individuals engage in WM gating processes? 25 2.2.4 Study 3: how does effort affect WM gating? 26 2.2.5 Study 4: what drives the difference between WM gate opening and closing? 28 CHAPTER 3 STUDIES 31 3.1 Study 1: a ventral stream-prefrontal cortex processing cascade enables WM gating dynamics 33 3.1.1 Abstract 33 3.1.2 Introduction 33 3.1.3 Results and Discussion 37 3.1.4 Methods 47 3.1.5 Competing interests 55 3.1.6 Data availability 55 3.1.7 Code availability 55 3.1.8 Acknowledgements 55 3.2 Study 2: time-on-task effects on WM gating processes—a role of theta synchronization and the norepinephrine system 55 3.2.1 Abstract 55 3.2.2 Introduction 56 3.2.3 Materials and Methods 60 3.2.4 Results 66 3.2.5 Discussion 71 3.2.6 Acknowledgements 74 3.2.7 Funding 74 3.2.8 Conflicts of Interest 75 3.2.9 Availability of data and materials 75 3.3 Study 3: atVNS specifically enhances WM gate closing mechanism 75 3.3.1 Abstract 75 3.3.2 Significance statement 76 3.3.3 Introduction 76 3.3.4 Materials and Methods 78 3.3.5 Results 92 3.3.6 Discussion 103 3.3.7 Data and code availability statement 107 3.3.8 Conflict of interest statement 107 3.3.9 Acknowledgements 107 3.4 Study 4: inhibitory control in WM gate opening: insights from alpha desynchronization and norepinephrine activity under atDCS stimulation 108 3.4.1 Abstract 108 3.4.2 Introduction 108 3.4.3 Materials and Methods 112 3.4.4 Results 121 3.4.5 Discussion 126 3.4.6 Acknowledgements 131 3.4.7 Conflicts of interest 131 3.4.8 Ethics Statement 131 3.4.9 Data and Code Availability Statement 131 CHAPTER 4 DISCUSSION 133 4.1 Summary of findings 135 4.2 The ventral stream-frontal cortex pathway of the WM gating 137 4.2.1 The ventral stream distinguishes the residual preceding gate activation 137 4.2.2 A possible hub of suppressing the preceding gate state in the parietal lobe 139 4.2.3 A cascade towards frontal cortices for reconfiguring new gate state 141 4.2.4 Distinct neural networks between opening and closing 142 4.2.5 WM gating as a switch toward external and internal information 144 4.3 Neural modulations of the WM gating process 145 4.3.1 Cognitive demands of the WM gating and NE’s modulation 145 4.3.2 The modulatory role of GABA and accompanied ABA in WM gating 148 4.4 Implications for future studies 149 4.4.1 What is the difference between WM gating and task switching? 149 4.4.2 What is the key to opening or closing the WM gate? 150 4.4.3 Is the gate-close the real default mode of the WM gate? 151 4.5 Limitations and Conclusion 153 4.5.1 Limitations 153 4.5.2 Conclusion 155 CHATPTER 5 REFERENCE 157 CHAPTER 6 APPENDEX 191 6.1 Supplementary materials for Study 1 193 6.2 Supplementary figures for Study 2 196 DECLARATION 199

In this dissertation, I have addressed the question of how resting-state EEG markers primarily in the alpha frequency range are linked to general cognitive performance and age. In the three studies presented in the work, I show that alpha power, frequency, and temporal dynamics, have distinct contributions to cognitive control functions in different age groups. Moreover, individual alpha peak frequency as well as the slope of 1/f decay of the PSD shows consistent age-related alterations, while alpha power is linked to structural alterations in the white matter. Our research extends further existing literature by specifying relevant neural networks as well as important methodological considerations that should be taken into account when analysing properties of oscillations.

Epileptic seizure presents a formidable threat to the life of its sufferers, leaving them unconscious within seconds of its onset. Having a mortality rate that is at least twice that of the general population, it is a true cause for concern which has gained ample attention from various research communities. About 800 million people in the world will have at least one seizure experience in their lifespan. Injuries sustained during a seizure crisis are one of the leading causes of death in epilepsy. These can be prevented by an early detection of seizure accompanied by a timely intervention mechanism. The research presented in this dissertation explores Kriging methods to exploit spatial correlations of electroencephalogram (EEG) Signals from the brain, for fast and accurate seizure detection in the Internet of Medical Things (IoMT) using edge computing paradigms, by modeling the brain as a three-dimensional spatial object, similar to a geographical panorama. This dissertation proposes basic, hierarchical and distributed Kriging models, with a deep neural network (DNN) wrapper in some instances. Experimental results from the models are highly promising for real-time seizure detection, with excellent performance in seizure detection latency and training time, as well as accuracy, sensitivity and specificity which compare well with other notable seizure detection research projects.

The Emotiv Insight is a commercially available, low-cost, mobile EEG device that is commonly overshadowed by its costlier counterpart, the Emotiv EPOC. The purpose of this report is to investigate if the Emotiv Insight is a suitable headset to be used as a controlling factor in conjunction with an Arduino microcontroller and various electrical components that are used towards the development of an open-sourced, affordable electric wheelchair with the primary goal of providing those who either do not have the financial resources or the physical capability to operate a traditional wheelchair due to their disability a viable option to improve their quality of life. All of the C++ code, STL files used to fabricate the 3d-printed components are uploaded to a GitHub repository as open sourced files to allow individuals with access to a 3d-printer to either build the open sourced wheelchair for their personal use, or refine the design to suit their needs.