Στην παρούσα διπλωματική εργασία γίνεται μελέτη της μεθόδου ανάλυσης ανεξάρτητων συνιστωσών στο ηλεκτροοεγκεφαλογράφημα. Αφού εξετάσουμε το κομμάτι της φυσιολογίας του εγκεφάλου θα δοθεί ένα μαθηματικό υπόβαθρο της ανάλυσης ανεξάρτητων συνιστωσών. Στη συνέχεια θα γίνει μια βιβλιογραφική έρευνα στη σύγκριση αλγορίθμων της ανάλυσης ανεξάρτητων συνιστωσών όταν εφαρμόζονται σε ηλεκτροεγκεφαλογραφήματα με στόχο την βέλτιστη εξαγωγή παρασίτων. Στο τέλος θα γίνει εφαρμογή της μεθόδου της ανάλυσης ανεξάρτητων συνιστωσών σε πραγματικά δεδομένα ηλεκτροεγκεφαλογραφήματος 64 καναλιών μέσω του περιβάλλοντος του Matlab. Στόχος της εφαρμογής αυτής είναι ο διαχωρισμός των ανεξάρτητων συνιστωσών μη-εγκεφαλικής προέλευσης και η αφαίρεση τους από τα αρχικά δεδομένα. / This thesis is a study of the independent componenet analysis in electroencephalogram. After looking at the piece of brain physiology we will give a mathematical framework of independent component analysis. Then it will become a literature search in the comparison algorithms of Independent Component Analysis in EEGs when applied with a view to optimal extraction of artifacts. At the end will be the method of independent component analysis to real EEG data 64 channels through the environment of Matlab. The aim of this application is the separation of independent components of non brain activity and removing them from the original data.

Το θέμα της παρούσας διατριβής αφορά στην μοντελοποίηση ενός εξελιγμένου ιατρι- κού συστήματος κατάλληλου για τη διαχείριση ζωτικών σημάτων με κύριο άξονα εφαρμογής τις διάφορες κατηγορίες ηλεκτροεγκεφαλογραφημάτων (EEG). Με τον όρο εξελιγμένο ιατρικό σύστημα αναφερόμαστε στη συγκεκριμένη διατριβή σε ένα ανεξάρτητο ανοικτό πληροφοριακό σύστημα που καλύπτει έναν πολύ συγκεκριμένο ιατρικό τομέα. Ως ζωτικά σήματα ή βιοσήματα για τη διατριβή νοούνται ψηφιακές καταγρα- φές ιατρικών οργάνων που μπορούν να αποθηκευτούν σε ψηφιακά αρχεία προτυποποιημένου μορφότυπου (format). Η διαχείριση περιλαμβάνει ανοικτές αρχιτεκτονικές λογισμικού με τις οποίες αρχειο- θετούνται και γίνονται αντικείμενο διαδραστικής επεξεργασίας ετερογενείς καταγραφές ια- τρικής πληροφορίας. Ο συγκεκριμένος ιατρικός τομέας ανάπτυξης του θέματος της διατριβής οριοθετείται στον ευρύτερο τομέα της επιληψίας και εστιάζεται στη χειρουργική της επιληψίας. Η βασική πρωτοτυπία της διατριβής έγκειται στη μοντελοποίηση και υλοποίηση ενός εξελιγμένου ιατρικού συστήματος για τη διαχείριση ηλεκτροεγκεφαλογραφημάτων (EEG), άλλων ζωτικών σημάτων καθώς και όλο το σύνολο των απεικονιστικών ιατρικών εξετάσεων που απαιτούνται και την υποστήριξη λήψης απόφασης στη χειρουργική της επιληψίας. Η αρχιτεκτονική πάνω στην οποία αναπτύχθηκε η πλατφόρμα αυτή αναφέρεται ως DESSA και αποτελεί έναν ολοκληρωμένο ηλεκτρονικό χώρο εργασίας κατάλληλο για όλες τις ειδικότητες ιατρών που ασχολούνται με το συγκεκριμένο θέμα. Η DESSA είναι προϊόν στενής συνεργασίας μεταξύ ιατρών, μηχανικών και αναλυτών αγοράς. / -

Premenstrual dysphoric disorder (PMDD) is a severe dysphoric form of premenstrual syndrome (PMS) that is included as a diagnosis for further study in the DSM-IV (APA, 2000). A primary aim of the present study was to characterize the co-occurrence of PMDD and major depression, in a sample that spans the entire range of depressive severity. The range included non-depressed controls, women meeting criteria for dysthymia, and women meeting criteria for current Major Depressive Disorder (MDD). Co-occurrence of MDD and PMDD were only statistically significant when considering Lifetime MDD. Resting frontal electroencephalographic (EEG) asymmetry has been hypothesized to tap a diathesis toward depression or other emotion-related psychopathology. Another primary aim was to assess Frontal EEG asymmetry in college women who meet criteria for Pre-Menstrual Dysphoric Disorder (n = 25) and 25 matched controls. Participants were assessed four times in a two week period. Women reporting low premenstrual dysphoric symptomatology exhibited greater relative left frontal activity at rest than did women high in premenstrual dysphoric symptomatology. These results are consistent with a diathesis-stress model for premenstrual dysphoric symptomatology. A secondary aim was to assess whether individuals with PMDD or menstrual related mood variability, but no current diagnosis of depression, have an increased family history of depression. Promising evidence of a relationship between family history of MDD and a likelihood of PMDD was discovered. A trend was found for Spectrum PMDD women: a higher rate of Family History of MDD (36%) than non PMDD women (19.6%). Ideally, resting frontal electroencephalographic (EEG) asymmetry could help us learn more about the etiology of depression and hormonal-related depression specifically, and test whether they may share etiological factors.

This dissertation examines the processing of sentences involving long-distance linguistic dependencies, or sentences containing elements that must be linked across intervening words and phrases. Specifically, both behavioral (self-paced reading and eye tracking) and neurophysiological (electroencephalography) methods were used (a) to evaluate the relative importance of backward- and forward-looking dependency satisfaction processes in the comprehension of sentences involving wh-dependencies and (b) to determine the extent to which common neurocognitive mechanisms are involved the processing of wh- and anaphoric dependencies. With respect to the first issue, both behavioral andneurophysiological results indicated a core role for forward-looking, expectancy-based processes in the comprehension of wh-dependency sentences. Regarding the latter issue, despite considerable overlap in the reading patterns associated with wh-dependencies and (at least some types of) anaphora, the neurophysiological responses related to these dependency types indicated that their processing draws on distinct neurocognitive mechanisms.

La electroencefalografía (EEG) es una técnica no invasiva que sirve para caracterizar la actividad eléctrica del cerebro. En la actualidad existe un creciente interés en el desarrollo de técnicas digitales de procesamiento para interpretar dichas señales, estas técnicas consisten en transformar la información contenida en las señales de EEG en datos numéricos y/o gráficos que faciliten su análisis y sistematización. El objetivo de la presente tesis es el estudio y la aplicación de diferentes técnicas de procesamiento de EEG a casos típicos como la detección no supervisada de ritmos cerebrales, de potenciales relacionados a la ejecución de movimientos y crisis epilépticas. Para el procesamiento de las señales de EEG se utilizaron las técnicas de Transformada de Fourier, procesamientos tiempo-frecuencia como la Transformada de Gabor y la Transformada Wavelet, y diferentes mediciones de la entropía de la señal, como la entropía dependiente del tiempo, la entropía espectral y la entropía multirresolución.

Tyrimo metu Sukeltųjų potencialų metodu buvo ištirti 8 šizofrenija sergantys asmenys bei 8 sveiki kontroliniai asmenys. Dažnio ir trukmės nesutapimo negatyvumo (MMN) potencialai pacientams buvo registruoti prieš, 2 savaitės po, ir 4 savaitės po Kvetiapino vartojimo. Rezultatai neparodė statistiškai reikšmingo MMN skirtumo nei MMN amplitudėje nei latensijoje. Taip pat, neaptikta statistiškai reikšmingų koreliacijų tarp PANSS skalės rezultatų pokyčių bei MMN pokyčių. Vidutinėse MMN amplitudziu vertėse, bei individualiuose bandymuose, galima įžvelgti tendenciją: MMN amplitudės deficitas dar labiau padidėja po 2 savaičių Kvetiapino vartojimo, ir pradeda kilti bei viršija baseline, po 4 savaičių. Tai gali būti adaptacinio periodo indikatorius. Šio tyrimo rezultatai sutampa su anksesniais tyrimais, kurie teigia jog atipiniai antipsichotikai neveikia MMN parametrų. Tačiau, turint omenyje stebimas tendencijas, būtų tikslinga tyrimą pakartoti su didesniu stebėjimo periodu bei tiriamųjų apimtimi. / 8 Shizophrenic patients and 8 healthy controls patients were inspected by evoked potential method in order to evaluate Quetiapine effects to MMN potential. Patients were examined before, 2 weeks and 4 weeks after Quetiapine treatment. MMN frequency and duration potentials were registered and analised. The results shows no significant MMN difference neither in MMN amplitude nor in latency. Foremore, no significant corellations between PANSS scale results and MMN differences were found. One could observe tendency of MMN amplitude's deficit to increase after two weeks of treatments, and reduce after 4 weeks, in most electrodes surpassing baseline values. This tendency occures at grand averange MMN's as well as at single trials. The decrease in amplitude after 2 weeks could be the indication of antipsychotic treatment adaptation period, after this period amplitude starts to increase. In conclusion, reseach results goes inline with previously observed atypic antipsychotic effects on MMN. Concidering the tendencties observed, it is reccomended to repeat the experiment with longer period of Quetiapine treatment.

Age-related declines in hearing abilities are common and can be attributed to changes in the peripheral and central levels of the auditory system. Although central auditory processing is enhanced in younger musicians, the influence of lifelong musicianship on age-related decline in central auditory processing has not yet been investigated. Therefore, the purpose of this dissertation was to investigate whether lifelong musicianship can mitigate age-related decline in central auditory processing. In the first experiment, age-related declines on four hearing assessments were compared between musicians and non-musicians. Speech-in-noise and gap-detection thresholds were found to decline at a slower rate in musicians, providing an increasing advantage with age. Furthermore, musicians had a lifelong advantage in detecting a mistuned harmonic, although the rate of age-related decline was similar for both musicians and non-musicians. Importantly, there was no significant effect of musicianship on pure-tone thresholds, suggesting that lifelong musicianship can mitigate age-related decline in central but not peripheral auditory processing. To test this hypothesis, a second experiment compared auditory evoked responses (AERs) between groups of older and younger musicians and non-musicians. Results indicated that exogenous neural activity was enhanced in musicians, but that age-related changes were similar between musicians and nonmusicians. Furthermore, endogenous, attention-dependent neural activity was enhanced in older adults, suggesting a compensatory cognitive strategy. Importantly, endogenous activity was preferentially enhanced in older musicians, suggesting that lifelong musicianship enhanced cognitive processes related to auditory perception. In the final experiment, the ability to segregate simultaneous sounds was tested in older and younger musicians and non-musicians by using a mistuned harmonic paradigm, where AERs to harmonic complexes were compared to AERs when one of the harmonics was mistuned. Results indicated that musical training in older adults has little effect on early automatic registration of the mistuned harmonic. In contrast, late attention-dependent activity, associated with the perception of the mistuned harmonic as a separate sound, was influenced by musical training in older adults, suggesting that lifelong musicianship preserves or enhances cognitive components of concurrent sound segregation. In summary, musical training was found to reduce age-related decline in hearing abilities due to enhanced central processing of auditory information.

The goal of the study was to use electrical signals from primary motor cortex to generate accurate predictions of the movement onset time of performed movements, for potential use in asynchronous brain-machine interface (BMI) systems. Four subjects, two with electroencephalogram and two with electrocorticogram electrodes, performed various movements while activity from their primary motor cortices was recorded. An analysis program used several criteria (change point, fractal dimension, spectral entropy, sum of differences, bandpower, bandpower integral, phase, and variance), derived from the neural recordings, to generate predictions of movement onset time, which it compared to electromyogram activity onset time, determining prediction accuracy by receiver operating characteristic curve areas. All criteria, excepting phase and change-point analysis, generated accurate predictions in some cases.

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

In our daily lives, we often make decisions that require the use of self-control, weighing trade-offs between various attributes: for example, selecting a food based on its health rather than its taste. Previous research suggests that re-weighting attributes may rely on selective attention, associated with decreased neural oscillations over posterior brain regions in the alpha (8-12 Hz) frequency range. Here, we utilized the high temporal resolution and whole-brain coverage of electroencephalography (EEG) to test this hypothesis in data collected from hungry human subjects exercising dietary self-control. Prior analysis of this data has found time-locked neural activity associated with each food’s perceived taste and health properties from approximately 400 to 650 ms after stimulus onset (Harris et al., 2013). We conducted time-frequency analyses to examine the role of alpha-band oscillations in this attribute weighting. Specifically, we predicted that there would be decreased alpha power in posterior electrodes beginning approximately 400 ms after stimulus onset for the presentation of healthy food relative to unhealthy food, reflecting shifts in selective attention. Consistent with this hypothesis, we found a significant decrease in alpha power for presentations of healthy relative to unhealthy foods. As predicted, this effect was most pronounced at posterior occipital and parietal electrodes and was significant from approximately 450 to 700 ms post-stimulus onset. Additionally, we found significant alpha-band decreases in right temporal electrodes during these times. These results extend previous attention research to multi-attribute choice, suggesting that the re-weighting of attributes can be measured neuro-computationally.