One of the important topics in sleep medicine is sleep structure. Normal sleep consists of rapid eye movement (REM) sleep and nonrapid eye movement (NRME) sleep states. NREM sleep can be further classified into stage 1, 2 and slow wave sleep (SWS) according to the current sleep scoring standard. Among them, SWS has been considered to be very important due to its r restorative value. The goal of this research is to detect SWS by using a single channel EEG signal. Its applications can be divided into two phases. In the first phase, a personalized SWS detector is designed for each individuals By combining these personalized SWS detectors, the second phase develops a general SWS detection method that can be applied to general population with any personalized training process. By applying the proposed method to 62 persons, the experimental results show that the proposed method, in average, achieves 90.69% classification accuracy 90.09% sensitivity and 93.97% specificity. Our experimental results also demonstrate, when applied to persons with higher AHI (apnoea-hypopnea index) values, the proposed method can still provided satisfactory results.

This study aims at sleep stage classification problem via EOG signals. The classification problem consists of four steps. The first step is to distinguish slow wave sleep from the rest of the sleep periods. Wake periods are identified in the second step. The third step finds REM sleep and the last step classifies stage 2 and stage1 sleep. By using different EOG signal features in different steps of the classification process, this work uses back-propagation trained neural networks to perform classification. With the exception of stage 1 sleep, the sensitivity and positive predictive value ranges from 70% to 80%. The overall classification accuracy is 74.80%.

Sleep staging can be used to assess whether sleep structure is abnormal. According to the R&K rule, human sleep can be divided into four different stages: Awake, Light Sleep, Deep Sleep and Rapid-Eye-Movement (REM) Sleep. Conventionally, sleep staging are scored mainly by EEG signals and complementally by EOG and EMG signals. The goal of this study is to detect slow wave sleep (SWS) automatically by using different combinations of EEG, EOG, and EMG signals. In particular, a total of 16 combinations of channels have been studied. Based on high amplitude slow wave characteristics of SWS, this study develops many of feature variables to characterize SWS. A subset of these features are employed to design neural network classifier to detect SWS. This study has noted interpersonal-differences in physiological signals between people and proposes solutions to this problem to improve the performance of SWS detection. The number of tested subjects from two different sleep centers is 1318 and 947 subjects, respectively. These subjects were divided into five groups for training and testing data in order to test performance of our proposed approach. By applying the proposed approach to 1318 subjects, the experimental results show that the proposed method achieves kappa of 0.63 by using a single EEG channel, kappa of 0.6 by using two channels EOG and kappa of 0.66 by using the best combination of multi-channel singals. The size of dataset used in this work is significantly large than those of previous studies and thus provide more reliable experimental results. The experimental results show that the proposed approach can provide satisfactory performance in dealing with dataset with more than 1000 subjects.

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Our ability to recall information and events is astounding and dependent on the medial temporal lobe (MTL) memory system. The synaptic interconnections between the neocortex (nCTX), entorhinal cortex (EC), and hippocampus (HPC) are the anatomical basis of this memory system. The electrophysiological basis of memory formation in this system is largely unknown, but the activity patterns that occur during slow wave sleep (SWS) are thought to play an important role. One prominent activity pattern that occurs during SWS is the slow oscillation (SO). It is a large-amplitude rhythm of ~1Hz that was first described in the nCTX and only occurs during SWS and deep anaesthesia. Using the urethane-anaesthetised rat, I provide the first description of the SO in the HPC in Chapter 2. I found that the SO in the HPC was dynamically coordinated with that in the nCTX. Because the EC is the anatomical interface between the nCTX and HPC, I hypothesised that it could be responsible for this coordination. Chapter 3 characterises the SO in the EC and its coordination with both the nCTX and HPC. My results suggested that the synaptic interconnections between the nCTX and HPC via the EC were not solely responsible for SO coordination across these structures. Another possibility is that SO coordination across the nCTX, EC, and HPC occurs via the nucleus reuniens thalami (NReu). In Chapter 4, I delivered trains of electrical stimulation to the frontal cortex (fCTX) to enhance the SO in the nCTX and assess any effect in the HPC. In addition, I delivered the same stimulation trains directly to the medial prefrontal cortex (mpfCTX) and NReu. I found that repeated stimulation in each structure entrained the hippocampal SO. I also found that repeated stimulation of the fCTX and mpfCTX enhanced SO coordination across the nCTX and HPC, but repeated stimulation of the NReu did not. My results suggested that SO coordination across the nCTX and HPC occurs via both the EC and NReu. Understanding the coordination of SO activity across these structures will provide insight to the electrophysiological basis of the MTL memory system and the role of SWS in its function.

Thesis (Ph.D.)--University of Alberta, 2009. / A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Doctor of Philosphy, Centre for Neuroscience. Title from pdf file main screen (viewed on November 6, 2009). Includes bibliographical references.

This study provides the baseline and initial assessment of the napping habits of the United States Military Academy Class of 2007. This portion of a four-year longitudinal study examines data collected on 62 Cadets over 32 days from 4 October 2004 to 4 November 2004 using actigraphy data and sleep logs. Data were stratified and cleaned in accordance with nap infrastructure. A total of 607 naps were reported for a total of 73.3 hours of additional sleep. Naps ranged from 15 minutes to six hours and occurred most frequently on weekdays. This finding contrasts with research of other samples of adolescent college students. Weekend naps were shorter in duration than weekday naps. This finding was also a departure from current scientific nap research findings. Consistent with other research, most naps were between 30 minutes to one and one half hours in length. Frequency and duration of naps were greatest on Wednesdays. The primary type of nap taken was restorative, as opposed to appetitive or prophylactic in nature. Afternoon naps were more prevalent than morning naps, possibly reflecting Cadet class schedule rather than sleep need. Suggestions for additional research are proposed.

The method targeted memory reactivation (TMR) uses specific stimulation when subjects are completing tasks and during sleep. The TMR process is known to influence the consolidation of declarative memories. The aim of this thesis is to conduct a systematic review on the effects of TMR on declarative memory consolidation during slow-wave sleep (SWS). The research question is to answer what effect TMR during SWS has on the consolidation of declarative memory in healthy humans when presented with associated cues of the targeted learning experiences. Eighteen studies were included in this review. Four studies found a significant effect of TMR on declarative memory consolidation, and 10 found a non-significant effect. In four studies the effect of TMR depended on different inclusions, analyses, and factors, for example between slow oscillation up-and down-states and between participants that vary in pre-sleep performance in the examined task. In contrast to previous findings, this review does not provide evidence for the effect of TMR on declarative memories during SWS. More research analysing different factors, such as different cues, age of participants, duration of SWS, and specific experimental tasks, needs to be done in the fields of TMR and auditory cues.

Chez les mammifères, l’alternance des états de vigilance nécessite la mise en jeu de mécanismes spéci ques qui facilitent les transitions entre l’éveil, le sommeil lent (SL) et le sommeil paradoxal (SP). L’objectif de cette thèse s’inscrit dans l’optique de disséquer chez la souris les processus neuronaux contrôlant l’alternance physiologique entre ces trois états de vigilance. Au cours de cette thèse, nous avons tout d’abord démontré par des approches complémentaires ex vivo et in vivo que le glucose peut favoriser l’endormissement par son action excitatrice directe sur les neurones promoteurs du SL localisés dans l’aire préoptique ventrolatérale (VLPO). Nous avons ensuite, par deux approches méthodologiques di érentes et complémentaires, contribué à préciser le rôle physiologique des neurones exprimant l’hormone de mélano-concentration (MCH) dans la régulation du cycle veille-sommeil, démontrant ainsi qu’en plus de faciliter le déclenchement et le maintien du SP lorsqu’ils sont activés, ils contrôlent certains aspects du SL en favorisant, au cours SL, un SL plus profond ainsi que la terminaison des épisodes de SL. Forts de ces nouveaux résultats supportant une contribution des neurones MCH à la régulation du SL, nous avons déterminé une voie potentielle pouvant sous-tendre cette fonction physiologique à travers leurs projections efférentes sur le VLPO. Nos résultats préliminaires indiquent que la stimulation optogénétique des axones des neurones MCH dans le VLPO favorise le déclenchement d’un état de transition entre SL et SP sans pour autant conduire au SP / In mammals, alternating between vigilance states requires some speci c processes that facilitate transitions between wake, Slow-Wave Sleep (SWS), and Paradoxical Sleep (PS). The objective of this thesis was to decipher, in mice, the neuronal mechanisms that control the alternation between these three vigilance states. During thus thesis, we first demonstrated using complementary ex vivo and in vivo approaches that glucose can facilitate sleep induction by directly exciting sleep- promoting neurons located within the ventrolateral preoptic nucleus (VLPO). Then, by developing two different and complementary approaches, we contributed to clarify the physiological role of melanin-concentrating hormone (MCH)-expressing neurons in sleep-wake regulation. Indeed, in addition to their PS-promoting effect when activated, we found that MCH neurons also contribute to the regulation of some aspects of SWS regulation by favouring the appearance of a deeper SWS and facilitating SWS episodes termination. These new results supporting a role of MCH neurons to SWS regulation led us to investigate a putative pathway underlying such an effect through efferent projections from MCH neurons to the VLPO. Preliminary results suggest that the optogenetic stimulation of axons from MCH neurons within the VLPO could facilitate the appearance of a transition state between SWS and PS without triggering PS onset

Orientadora: Profa. Dra. Paula Ayako Tiba / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Neurociência e Cognição, 2016. / Memórias de extinção são um produto das variações nas condições de condicionamento e na quantidade de tempo e sessões de extinção. Aumentos de sono paradoxal após a exposição a sessões de extinção foram descritas anteriormente, contudo trabalhos anteriores não testaram mais de um dia de extinção e tão pouco testaram se a modificação do sono após a extinção dependeria do intervalo de tempo entre condicionamento e extinção. Nós exploramos modificações da arquitetura do sono em diferentes condições de aprendizagem a extinção do medo condicionado. Em primeiro lugar, usamos uma tarefa de condicionamento de medo ao contexto (CMC) a fim de explorar o efeito de um evento aversivo (o choque elétrico) e um possível efeito do intervalo de tempo entre a sessão condicionamento e a sessão de extinção no sono e comportamento. O primeiro grupo, chamado Extinção Múltipla recebeu um treino de CMC com uma apresentação de choque único seguido por cinco sessões de extinção. O segundo grupo, chamado extinção única, foi treinado no CMC e expostos à extinção sete dias após este treino. O terceiro grupo - chamado choque imediato - recebeu uma sessão de treinamento com um único choque aplicado imediatamente depois de entrar na caixa de condicionamento e seguiu o mesmo protocolo de extinção que o grupo de extinção múltipla. A resposta de congelamento foi o parâmetro comportamental analisado. Informações sobre sono-vigília foram registradas através da coleta de dados de ECOG e EMG e classificado entre três fases: vigília, sono de ondas lentas e sono paradoxal. Os resultados mostraram aumento do sono de ondas lentas após CMC e aumento do sono paradoxal depois de CMC e extinção entre os grupos T-múltipla e T-única. Nossas descobertas apoiam achados anteriores sobre a relação entre sono paradoxal e aprendizagem da extinção e sugerem que modificações de sono de ondas lentas para extinção antecipada sejam dependentes do tempo. / Extinction memory is a product of variations in fear conditioning and fear extinction procedure and the amount of time and sessions of extinction. Increases in paradoxical sleep (PS) after exposure to extinction sessions was previously described; however, previous works did not test more than one day of extinction and did not test whether sleep modifications after extinction are dependent upon the time interval between conditioning and extinction. We explored sleep architecture modifications on different conditions of conditioned fear extinction learning. We first adapted a contextual fear-conditioning task in order to explore the effect of an aversive event (the electric shock) and a possible effect of time interval between conditioning and extinction session on sleep and behaviour. The first group, named Multiple Extinction (T-10 Multiple) received a contextual fear conditioning (CFC) training with a single shock presentation followed by five sessions of extinction. The second group, named single extinction (T-Single), was trained in the same CFC procedure and exposed to one single extinction session, seven days after training. The third group ¿ named immediate shock ¿ received a training 1session with a single shock applied immediately after entering the conditioning box following the same protocol of extinction as the T-Multiple group. The freezing response was the behavioural parameter analysed. Sleep-wake information was recorded by collecting electrocorticogram (ECOG) and electromyogram (EMG) data and scored as one between three phases: awake, slow wave sleep (SWS) and PS. Results showed that SWS increased after CFC, and it also showed that PS increased after CFC and extinction for either T-Multiple and T- Single group. Our findings support previous findings on PS relation with extinction learning and suggest some time-dependent SWS modification for early extinction re-exposure. The discovery of the participation of PS in contextual fear extinction and SWS role on nuances of extinction procedure expands the understanding of behaviour and sleep relations and, at the same time, offer a behavioural model to study sleep dependent stressful memory related to PTSD or HPA axis without the unconditioned behavioural and physiological effects of ES.