Monitoring bio-electric events is a common procedure, which provides medical data required in clinical and research applications. Electrophysiological measurements are applied in diagnosis as well as evaluation of the performance of different body organs and systems, e. g. the heart, muscles and the nervous system. Furthermore, it is staple feature in operation rooms and extensive care units. The performance of the recording system is affected by the tools and instrumentation used and the bio-electrode is a key-player in electrophysiology, hence, the improvements in the electrode recording technique will be directly reflected in the system?s performance in terms of the signal quality, recording duration as well as patient comfort. In this thesis, a design methodology for micro-spike array dry bio-electrodes is introduced. <br /><br /> The purpose of this methodology is to meet the design specifications for portable long-term EEG recording and optimize the electrical performance of the electrodes by maximizing the electrode-skin contact surface area, while fulfilling design constraints including mechanical, physiological and economical limitations. This was followed by proposing a low cost fabrication technique to implement the electrodes. The proposed electrode design has a potential impact in enhancing the performance of the current recording systems, and also suits portable monitoring and long term recording devices. The design process was aided by using a software design and optimization tool, which was specifically created for this application. <br /><br /> The application conditions added challenges to the electrode design in order to meet the required performance requirements. On the other hand, the required design specifications are not fulfilled in the current electrode technologies which are designed and customized only for short term clinical recordings. <br /><br /> The electrode theory of application was verified using an experimental setup for an electrochemical cell, but the overall performance including measuring the electrode impedance is awaiting a clinical trial.

One of the important measures for sleep quailty is sleep structure. Normal sleep consists of awake, rapid eye movement (REM) sleep and nonrapid eye movement (NREM) sleep states. NREM sleep can be further classified into stage 1, stage 2 and slow wave sleep (SWS). These stages can be analyzed quantitatively from various electrical signals such as the electroencephalogram (EEG), electro-oculogram (EOG), and electromyogram (EMG). The goal of this research is to develop a simple four-stage process to classify sleep into wake, REM, stage 1, stage 2 and SWS by using a single EEG channel. By applying the proposed approach to 48727 distinct epochs which are acquired from 62 persons, the experimental results show that the proposed method is achieves 76.98% of accuracy. The sensitivity and PPV for wake are 85.96% and 68.35%. Furthermore, the sensitivity and PPV for REM are 82.13% and 74.11%, respectively. The sensitivity and PPV for the stage 1 are 9.02% and 39.00%. The sensitivity and PPV for the stage 2 are 84.19% and 79.36%. The sensitivity and PPV for SWS are 81.53% and 85.40%.

A Human-Machine Interface is a device that allows humans to inter- act with and use machines. One such device is a Brain-Computer Interface which allows the user to communicate to a computer system through thought patterns. A commonly used technique, electroencephalography, uses multiple sensors positioned on the subject’s cranium to extract electrical changes as a representation of thought patterns. This report investigates the use of a single EEG sensor as a user-friendly BCI implementation. The primary goal of this report is to determine if specific mental tasks can be reliably detected with such a system. / text

Meditation training has been shown to improve attention and emotion regulation. However, the mechanisms responsible for these effects are largely unknown. In order to make further progress, a rigorous interdisciplinary approach that combines both empirical and theoretical experiments is required. This dissertation uses such an approach to analyze electroencephalogram (EEG) data collected during two three-month long intensive meditation retreats in four steps. First, novel tools were developed for preprocessing the EEG data. These tools helped remove ocular artifacts, muscular artifacts, and interference from power lines in a semi-automatic fashion. Second, in order to identify the cortical correlates of meditation, longitudinal changes in the cortical activity were measured using spectral analysis. Three main longitudinal changes were observed in the retreat participants: (1) reduced individual alpha frequency after training, similar reduction has been consistently found in experienced meditators; (2) reduced alpha-band power in the midline frontal region, which correlated with improved vigilance performance; and (3) reduced beta-band power in the parietal-occipital regions, which correlated with daily time spent in meditation and enhanced self-reported psychological well-being. Third, a formal computational model was developed to provide a concrete and testable theory about the underlying mechanisms. Four theoretical experiments were run, which showed, (1) reduced intrathalamic gain after training, suggesting enhanced alertness; (2) increased cortico-thalamic delay, which strongly correlated with the reduction in individual alpha frequency (found during spectral analysis); (3) reduction in intrathalamic gain provided increased stability to the brain; and (4) anterior-posterior division in the modeled reticular nucleus of the thalamus (TRN) layer and increased connectivity in the posterior region of TRN after training. Fourth, correlation analysis was performed to ground the changes in cortical activity and model parameters into changes in behavior and self-reported psychological functions. Through these four steps, a concrete theory of the mechanisms underlying focused-attention meditation was constructed. This theory provides both mechanistic and teleological reasoning behind the changes observed during meditation training. The theory further leads to several predictions, including the possibility that customized meditation techniques can be used to treat patients suffering from neurodevelopmental disorders and epilepsy. Lastly, the dissertation attempts to link the theory to the long-held views that meditation improves awareness, attention, stability, and psychological well-being. / text

Η συνδετικότητα εγκεφάλου αφορά σε πρότυπα δικτύων τόσο ανατομικών, όσο στατιστικά ή και αιτιακά συσχετισμένων συνδέσεων διακριτών μονάδων του νευρικού συστήματος του εγκεφάλου. Στην εργασία αυτή μελετάται τόσο η απόδοση όσο και η φυσιολογική ερμηνεία μετρικών υπολογισμού της στατιστικής καθώς και αιτιακής συνάφειας χρονοσειρών. Οι χρονοσειρές αφορούν σε καταγραφές περιοχών/ηλεκτροδίων του ηλεκτροεγκεφαλογραφήματος ύπνου φυσιολογικών ανθρώπων. Πιο συγκεκριμένα, οι μέθοδοι υπολογισμού της συνδετικότητας εφαρμόζονται μεταξύ περιοχών του εγκεφάλου και σε χρονικές στιγμές όπου λαμβάνουν χώρα μικρογεγονότα του ύπνου, όπως υπνικές άτρακτοι (sleep spindles) και K-συμπλέγματα (K-complexes), με απώτερο σκοπό την κατανόηση του ρόλου αυτών των γεγονότων στον ύπνο. / During Non-Rapid Eye Movement (NREM) sleep brain is considered to be relatively disconnected from the environment. Also connectedness between brain areas has been found decreased, although we do not know the role played in this by specific elements of sleep microstructure. We developed a method with millisecond time resolution appropriate for assessing brain connectivity during NREM sleep spindles, the φ-coherence. It is based on the observation by Nolte (2008) that when the phase between two signals is zero, the coherence value can be attributed to volume conduction rather than functional neuronal connection. So φ-coherence excludes this value. The new method counts among the effective connectivity measures as advantageous in (a) its superb time resolution (b) ability to study events clustered from different time periods or subjects (c) simultaneous study of any choice from all possible combinations of EEG electrodes and display their φ-coherence in time-frequency topological maps and (d) parameterization of all the plots included in the maps regarding frequency, time and φ-coherence threshold. Preliminary results from 360 fast spindles recorded in whole night sleep of two healthy volunteers the use of φ-coherence indicated a prevailing connectivity pattern of causal interactions mostly from centroparietal regions (C3, Cz, C4, Pz, P3, P4) to right frontotemporal regions (F8, T4). The study aims to help our understanding of the role played by spindles not only in sleep maintenance but also in memory consolidation and in several neuropsychiatric disorders.

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. / -

The visual system receives a series of fluctuating light patterns on the retina, yet visual perception is strikingly different from this unorganized and ambiguous input. Thus visual processes must organize the input into coherent units, or objects, and segregate them from others. These processes, collectively called perceptual organization, are fundamental to our ability to perceive and interact with objects in the world. Nevertheless, they are not yet understood, perhaps because serial, hierarchical assumptions that were long held impeded progress. In a series of experiments, this dissertation investigated the mechanisms that contribute to perceptual organization and ultimately to our ability to perceive objects. A new hypothesis is that during the course of object assignment potential objects on either side of a border are accessed on a fast pass of processing and engage in inhibitory competition for object status; the winner is perceived as the object and the loser is suppressed, leading that region to be seen as part of the shapeless background. Previous research suggested that at least shape level representations are accessed on the fast pass of processing before object assignment. In the first series of experiments (Chapter 1), we found that meaning (semantics) is also accessed on the fast pass of processing for regions that are ultimately perceived as shapeless grounds. This finding contradicts traditional feed-forward theories of perception that assumed that meaning is accessed only for figures after object assignment. The experiments in Chapter 2 examine activity in the alpha band of the EEG, which has been used as an index of inhibition. More alpha activity was observed when participants viewed stimuli designed such that there was more competition for figural status from the region ultimately perceived as the ground. The results support the proposal that inhibitory competition occurs during the course of object perception, and these results are the first online measure of competition during figure assignment. The final series of experiments (Chapter 3) investigated how quickly saccadic behaviors that required perceptual organization can be initiated. The experiments show that participants can initiate saccades that are based on perceptual organization approximately 200 ms after stimulus onset, much faster than was assumed on feed-forward models of perception. Collectively, these experiment support models of object perception that involve the mutual interaction and competition of objects properties via feedforward and iterative feedback processing, and the eventual suppression of the losing ground regions before object assignment.

Nonrestorative sleep refers to the experience of sleep as insufficiently refreshing, often despite the appearance of normal sleep according to objective parameters. As a result, a valid and reliable measure of the subjective experience of NRS is required in order to allow for standardization and comparability in its assessment. This thesis reports the results of a study involving the development and validation of a scale to assess NRS, the Nonrestorative Sleep Scale (NRSS). The psychometric properties of the NRSS were assessed in a group of 256 participants recruited from a sleep clinic population. Principal component analysis revealed four domains. The scale demonstrated good internal and test-retest reliability and reasonable validity compared to other measures. Overnight polysomnographic variables were also compared to scores on the scale and a few were found to be weakly correlated with scale scores. These included alpha EEG, sleep efficiency, and REM latency.

Nonrestorative sleep refers to the experience of sleep as insufficiently refreshing, often despite the appearance of normal sleep according to objective parameters. As a result, a valid and reliable measure of the subjective experience of NRS is required in order to allow for standardization and comparability in its assessment. This thesis reports the results of a study involving the development and validation of a scale to assess NRS, the Nonrestorative Sleep Scale (NRSS). The psychometric properties of the NRSS were assessed in a group of 256 participants recruited from a sleep clinic population. Principal component analysis revealed four domains. The scale demonstrated good internal and test-retest reliability and reasonable validity compared to other measures. Overnight polysomnographic variables were also compared to scores on the scale and a few were found to be weakly correlated with scale scores. These included alpha EEG, sleep efficiency, and REM latency.

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.