Στην παρούσα Μεταπτυχιακή Διπλωματική Εργασία υλοποιήθηκε ένα προγραμματιστικό περιβάλλον σε Matlab το οποίο μας επιτρέπει να μελετήσουμε τη συσχέτιση της δυναμικής βιολογικών νευρωνικών δικτύων με χρήση ομοιοματικών τεχνικών και μαθηματικών μοντέλων. Για το λόγο αυτό αναπτύχθηκαν προγράμματα που υλοποιούν μαθηματικά μοντέλα της δυναμικής νευρωνικών πληθυσμών και αντίστοιχα ομοιοματικές μέθοδοι. Το περιβάλλον δίνει τη δυνατότητα διερεύνησης της δυναμικής με τους δύο αυτούς τρόπους και παρέχει τρόπους σύγκρισης μεταξύ τους, ώστε να διερευνηθεί αν από τους δύο αυτούς τρόπους προσέγγισης, υπό τις ίδιες αρχικές συνθήκες, προκύπτουν αποτελέσματα συγκρίσιμα μεταξύ τους. Αρχικά, εξομοιώθηκε ένα βιολογικό νευρωνικό δίκτυο στην προσπάθεια προσέγγισης της λειτουργίας του ανθρώπινου εγκεφάλου από έναν υπολογιστή. Εξομοιώσαμε ένα νευρωνικό δίκτυο χρησιμοποιώντας μια σχέση η οποία δεδομένων των παραμέτρων του δικτύου και της κατάστασης διεγερσιμότητας του δικτύου αn κάποια χρονική στιγμή n υπολογίζει την κατάσταση διεγερσιμότητας του δικτύου αn+1 την επόμενη χρονική στιγμή n+1. Στη συνέχεια, περιγράφονται και αναλύονται μαθηματικά μοντέλα που χρησιμοποιήθηκαν για τη μακροσκοπική (στατιστική) συμπεριφορά των μεμονωμένων – δηλαδή χωρίς εξωτερικές συνδέσεις – νευρωνικών δικτύων (ομάδων αλληλοσυνδεδεμένων νευρώνων) του Κεντρικού Νευρικού Συστήματος. Μελετώντας κάποιες ξεχωριστές περιπτώσεις των νευρωνικών δικτύων και κάνοντας συγκεκριμένες θεωρήσεις για την κάθε μια, καταλήγουμε σε μαθηματικές εξισώσεις που αφορούν την περιγραφή της δυναμικής των δικτύων. Θα παρουσιαστεί, δηλαδή ένα πακέτο προγραμμάτων υλοποιημένο στο περιβάλλον Matlab που θα δέχεται ως είσοδο παραμέτρους του νευρωνικού πληθυσμού (δικτύου), θα υλοποιεί τις δύο μεθόδους μελέτης της δυναμικής του και θα εμφανίζει και θα συγκρίνει τα λαμβανόμενα αποτελέσματα. Ο σκοπός της εν λόγω διπλωματικής είναι η σύγκριση των αποτελεσμάτων που προκύπτουν για τη δυναμική νευρωνικών πληθυσμών με χρήση μαθηματικών μοντέλων σε σχέση με τα αντίστοιχα αποτελέσματα που προκύπτουν με χρήση μεθόδων εξομοίωσης. / -

The study of semantics in the brain explores how the brain represents, processes, and learns the meaning of language. In this thesis we show both that semantic representations can be decoded from electroencephalography data, and that we can detect the emergence of semantic representations as participants learn an artificial language mapping. We collected electroencephalography data while participants performed a reinforcement learning task that simulates learning an artificial language, and then developed a machine learning semantic representation model to predict semantics as a word-to-symbol mapping was learned. Our results show that 1) we can detect a reward positivity when participants correctly identify a symbol's meaning; 2) the reward positivity diminishes for subsequent correct trials; 3) we can detect neural correlates of the semantic mapping as it is formed; and 4) the localization of the neural representations is heavily distributed. Our work shows that language learning can be monitored using EEG, and that the semantics of even newly-learned word mappings can be detected using EEG. / Graduate

BACKGROUND: A number of epilepsy syndromes are characterized by sleep-activated epileptiform discharges, however drivers of this process are not well understood. Previous research has found that thalamic injury in early life may increase the odds of sleep-activated spikes. Benign childhood epilepsy with centrotemporal spikes (BECTS) is among the most common pediatric-onset epilepsy syndromes, characterized by sleep-potentiated spike activity, a focal sensorimotor seizure semiology, and deficits in language, attention, and behavioral functioning. Though ictal and interictal electro-clinical activity resolves during mid-adolescence, adverse psychosocial outcomes may persist. Previous findings from monozygotic twin and neuroimaging studies suggest a multifactorial pattern of disease and raise suspicion for structural changes in thalamocortical connectivity focal to the seizure onset zone, though this has not been explored. OBJECTIVE: This research aims to (1) assess white matter differences in focal thalamocortical connectivity between BECTS cases and healthy controls using validated probabilistic tractography methods, (2) assess the association between spike burden and white matter connectivity focal to the seizure onset zone, and (3) evaluate longitudinal changes in thalamocortical connectivity across four cases. METHODS: 42 subjects ages 6-15 years were recruited between November 2015 and February 2018, including 23 BECTS cases and 19 healthy controls. Subjects underwent 3 Tesla structural and diffusion-weighted magnetic resonance imaging (2mm x 2mm x 2mm) with 64 gradient directions (b-value=2000) and 72 electrode sleep-deprived electroencephalographic (EEG) recordings. Seed and target regions of interest (ROIs) were created within each hemisphere using the Desikan-Killiany atlas, with the thalamus set as a seed ROI, and SOZ cortex and non-SOZ (NSOZ) cortex as target ROIs. Probabilistic tractography was executed using PROBTRACKX2 with 500 streamlines per seed voxel, 0.5 millimeter steps, and a curvature threshold of 0.2. All streamlines reaching the target ROI were summed and normalized by seed voxel count. Results for BECTS and healthy controls were plotted by age. The slope of thalamocortical connectivity versus age was computed for each group and compared between groups using nonparametric bootstrap analysis. Additionally, the association between SOZ connectivity and spike burden was assessed in a subgroup analysis using a linear regression model, controlling for age. RESULTS: A significant difference in the developmental trajectory of thalamocortical connectivity to the SOZ in BECTS cases compared to healthy controls was found (p=0.014), where the increase in connectivity with age observed in healthy controls was not present in BECTS children. These results did not extend to NSOZ thalamocortical connections (p=0.192). Longitudinal results support these observations, where all BECTS cases who underwent repeat imaging (N=4) showed a decrease in thalamocortical connectivity to the SOZ over the follow-up period. No relationship was found between thalamocortical connectivity and spike burden (p=0.840). CONCLUSIONS: These findings suggest that children with BECTS show subtle alterations in thalamocortical white matter development focal to the seizure onset zone. Thalamocortical connectivity to the SOZ does not appear to directly mediate non-REM sleep spike potentiation in BECTS. Limitations of this study include the potential for selection bias and limited power to detect sample differences. Additional research is needed to further characterize thalamocortical network changes and electrographic and neuropsychological correlates.

Transcranial direct current stimulation (TDCS) allows for the noninvasive modulation of cortical activity. In this study, the effects of cathodal and anodal TDCS treatment on baseline activity in the motor cortex of rats were investigated via translaminar electroencephalogram (EEG) recording and power spectral density analysis. Treatment with low intensity anodal TDCS for five minutes was found to increase delta and theta frequency cortical activity during and for up to five minutes following treatment. This study also assessed the interaction of TDCS with the phenomenon of cortical spreading depression (CoSD), which has been implicated in numerous disease states, including migraine and stroke. TDCS treatment was given concurrently with induction of CoSD via administration of potassium chloride to the surface of the dura. The presence of the spreading depression event, a characteristic low frequency wave observed to travel outwards from the point of CoSD induction and downwards through the cortex, was used as a proxy measure for the occurrence of CoSD. It was observed that animals treated with cathodal TDCS exhibited fewer spreading depression events relative to those treated with anodal TDCS or those receiving sham treatment. In this study, animals were segregated into groups that exhibited stimulus artifact during TDCS treatment and those that did not. Stimulus artifact was defined as a characteristic alpha and/or beta frequency activity spike lasting throughout and not longer than the period of stimulation. Those animals receiving TDCS without exhibiting stimulus artifact were considered for the purposes of this study to not have received proper TDCS treatment, and acted as a sham treatment group. Because salient differences emerged between the stimulus artifact positive and stimulus artifact negative groups, this study suggests that the presence of stimulus artifact could be used as a proxy measure for successful TDCS dosage.

abstract: Approximately 1% of the world population suffers from epilepsy. Continuous long-term electroencephalographic (EEG) monitoring is the gold-standard for recording epileptic seizures and assisting in the diagnosis and treatment of patients with epilepsy. However, this process still requires that seizures are visually detected and marked by experienced and trained electroencephalographers. The motivation for the development of an automated seizure detection algorithm in this research was to assist physicians in such a laborious, time consuming and expensive task. Seizures in the EEG vary in duration (seconds to minutes), morphology and severity (clinical to subclinical, occurrence rate) within the same patient and across patients. The task of seizure detection is also made difficult due to the presence of movement and other recording artifacts. An early approach towards the development of automated seizure detection algorithms utilizing both EEG changes and clinical manifestations resulted to a sensitivity of 70-80% and 1 false detection per hour. Approaches based on artificial neural networks have improved the detection performance at the cost of algorithm's training. Measures of nonlinear dynamics, such as Lyapunov exponents, have been applied successfully to seizure prediction. Within the framework of this MS research, a seizure detection algorithm based on measures of linear and nonlinear dynamics, i.e., the adaptive short-term maximum Lyapunov exponent (ASTLmax) and the adaptive Teager energy (ATE) was developed and tested. The algorithm was tested on long-term (0.5-11.7 days) continuous EEG recordings from five patients (3 with intracranial and 2 with scalp EEG) and a total of 56 seizures, producing a mean sensitivity of 93% and mean specificity of 0.048 false positives per hour. The developed seizure detection algorithm is data-adaptive, training-free and patient-independent. It is expected that this algorithm will assist physicians in reducing the time spent on detecting seizures, lead to faster and more accurate diagnosis, better evaluation of treatment, and possibly to better treatments if it is incorporated on-line and real-time with advanced neuromodulation therapies for epilepsy. / Dissertation/Thesis / M.S. Electrical Engineering 2012

abstract: Development of post-traumatic epilepsy (PTE) after traumatic brain injury (TBI) is a major health concern (5% - 50% of TBI cases). A significant problem in TBI management is the inability to predict which patients will develop PTE. Such prediction, followed by timely treatment, could be highly beneficial to TBI patients. Six male Sprague-Dawley rats were subjected to a controlled cortical impact (CCI). A 6mm piston was pneumatically driven 3mm into the right parietal cortex with velocity of 5.5m/s. The rats were subsequently implanted with 6 intracranial electroencephalographic (EEG) electrodes. Long-term (14-week) continuous EEG recordings were conducted. Using linear (coherence) and non-linear (Lyapunov exponents) measures of EEG dynamics in conjunction with measures of network connectivity, we studied the evolution over time of the functional connectivity between brain sites in order to identify early precursors of development of epilepsy. Four of the six TBI rats developed PTE 6 to 10 weeks after the initial insult to the brain. Analysis of the continuous EEG from these rats showed a gradual increase of the connectivity between critical brain sites in terms of their EEG dynamics, starting at least 2 weeks prior to their first spontaneous seizure. In contrast, for the rats that did not develop epilepsy, connectivity levels did not change, or decreased during the whole course of the experiment across pairs of brain sites. Consistent behavior of functional connectivity changes between brain sites and the "focus" (site of impact) over time was demonstrated for coherence in three out of the four epileptic and in both non-epileptic rats, while for STLmax in all four epileptic and in both non-epileptic rats. This study provided us with the opportunity to quantitatively investigate several aspects of epileptogenesis following traumatic brain injury. Our results strongly support a network pathology that worsens with time. It is conceivable that the observed changes in spatiotemporal dynamics after an initial brain insult, and long before the development of epilepsy, could constitute a basis for predictors of epileptogenesis in TBI patients. / Dissertation/Thesis / M.S. Bioengineering 2012

Individuals with high working memory capacity (WMC) appear to be particularly good at focusing their attention (McCabe, Roediger, McDaniel, Balota, & Hambrick, 2010). Therefore, we studied the correlation between WMC and the ability to suppress neurological activity from a task-irrelevant stimulus. The research question tests the foundations of Lavie’s perceptual load theory; that early selection occurs, by testing if higher WMC enhances people’s ability to inhibit processing of task-irrelevant stimuli from low versus high load (i.e. the difference from low to high load should be smaller for high WMC than for low WMC). This was operationalised by measuring the correlation of WMC and auditory processing under low versus high visual load. Auditory processing was measured with auditory steady state responses (ASSR), and WMC was measured with an operation-letter span task. The results showed no significant correlation between WMC and ability to suppress task-irrelevant stimuli. Based on the data, it is not possible to conclude with certainty that effects of load on auditory processing are unaffected by WMC, because confidence intervals were large.

Auditiv mismatch negativity (MMN) är en neurologisk hjärnrespons som visar hur känslig hjärnan är för auditiva förändringar. Perceptuell load teorin argumenterar att krävande visuella sökuppgifter eliminerar auditiva distraktorer från att bearbetas i arbetsminnet. Syftet är att observera event-related potential (ERP) händelser för att se om avvikande ljud exkluderas under hög visuell belastning. Ett korsmodalt uppmärksamhetstest utfördes där deltagarna (N = 26) fick utföra en visuell sökuppgift med två svårighetsgrader samtidigt som de skulle ignorera tonfrekvenser som spelades upp i bakgrunden. Resultatet visade auditiv MMN-respons under både låg och hög visuell belastning. Det fanns ingen tydlig skillnad på MMN mellan låg och hög belastning. Hörselcortex registrerade en avvikande ton i oddball och att samma ton fanns i kontroll-upplägget. Argument för att distraktorer bearbetas under kontrollerad uppmärksamhet. Ytterligare studier med större stickprov och olika ljudfrekvenser, naturliga och icke naturliga, krävs för att se hur ljuden påverkar bearbetningsprocessen.

Esta tese apresenta uma revisão relativa às questões cognitivas de processamento de informações envolvidas na aprendizagem motora, para consolidar pesquisa empírica a esse respeito. Baseado em fontes bibliográficas, apresenta-se o contexto histórico da cultura educacional brasileira da pesquisa em movimento humano. Propõe-se metodologia de observação e quantificação de sinais bioelétricos-fisiológicos para identificação de aspectos relacionados a diferentes etapas da aprendizagem humana no âmbito da cognição e da motricidade. Descreve-se experimento dados originais para a área das Ciências do Movimento Humano, em que se monitora – com EEG e EMG – quantifica e interpreta a alteração de sinais de base em relação a modificações ocorridas durante vários momentos da aquisição da memória motora - aprendizagem - relativa à prática deliberada de partitura musical por violonista. Os dados reforçaram as hipóteses já comprovadas na literatura quanto ao maior esforço do sistema nervoso relacionada à exposição do violonista a uma tarefa específica e sua prática deliberada pelo sistema musculoesquelético, não servindo para generalizações, apenas como validação do desenho experimental e das análises estatísticas realizadas. O objetivo de monitorar, quantificar e descrever a dinâmica neural de freqüência eletrofisiológica durante o desenvolvimento de padrões musculoesqueléticos de coordenação e controle, foi alcançado. / This article presents a revision related to the cognitive questions of information processing involved in motor learning, to consolidate empirical research on the subject. The historical Brazilian educational background to culture of the human movement research is presented, based on bibliographical sources. Methodology of observation and quantification of bioelectrical physiological signals is proposed, which serves to identify the modifications occurred during the task-acquisition process. A experiment is described, along with data relevant for the Human Movement Sciences, in which the alteration of base signals in relation to various movements of the task are monitored, quantified and interpreted. The task consists of learning and performing a short musical excerpt by guitarists.

x, 133 p. ; ill. (some col.) A print copy of this title is available through the UO Libraries under the call number: SCIENCE QP405 .J67 2007 / Meditation has been defined as a "group of practices that self-regulate the body and mind, thereby affecting mental events by engaging a specific attentional set" (Cahn & Polich, 2006). We conducted a randomized, longitudinal trial to examine the effects of concentrative meditation training (40 min/day, 5 days/week for 8 weeks) on top-down, voluntary control of attention with a progressive muscle relaxation training group as a control. To determine if training produced changes in attentional network efficiency we compared, pre- and post-training, mean validity effect scores (difference between invalid cue and center cue reaction time) in the contingent capture paradigm (Folk et al., 1992). The meditation group showed a trend towards improvement of top-down attention while the relaxation group did not. Using EEG we assessed the changes in amplitudes of wavelets during periods of mind-wandering and meditation. Periods in which subjects were on- vs. off-focus during the meditation task were identified by asking subjects to make button presses whenever the mind wandered and also at probe tones, if they were off-focus. After training, the episodes of mind-wandering were significantly lower in the meditation group as compared to the relaxation group. Increased amplitudes of alpha and theta EEG frequencies in the occipital and right parietal areas were seen during the meditation task for the meditation but not the relaxation group as an effect of training. A baseline EEG trait effect of reduced mental activity was seen (meditation training: occipital and right parietal areas; relaxation training: only occipital areas). Within a given meditation session, prior to training, alpha and theta activity was lower in on-focus conditions (occurring immediately after subjects discovered they were off-focus and returned to active focus on the breath/syllable) compared to meditative focus segments. After training, we found higher alpha amplitude in periods of meditative focus as compared to periods of mind wandering for both groups. However, the meditation group showed significantly higher theta amplitude than the relaxation group during the meditative state segments. / Adviser: Marjorie Woollacott