La prise de décision est un processus adaptatif essentiel dont l’efficacité dépend de processus exécutifs, motivationnels, émotionnels et donc de l’intégrité de différents circuits cérébraux. Au sein d’une population saine, il existe des variabilités individuelles décisionnelles influencées par des facteurs génétiques, épigénétiques et environnementaux. De plus, de nombreuses pathologies mentales, neurobiologiques et neurodégénératives provoquent des altérations des processus décisionnels. Ainsi, déterminer des traits comportementaux et des substrats neurobiochimiques impliqués dans ce dysfonctionnement représente un intérêt majeur.Nous avons développé, chez la souris, un test de prise de décision, basé sur le test classiquement utilisé chez l’homme (l’Iowa Gambling Task), qui reproduit une situation incertaine, complexe et conflictuelle de choix : le Mouse Gambling Task (MGT). Grâce à une approche différentielle du comportement, nous avons observé des différences spontanées de capacités décisionnelles : certaines souris ont un comportement rigide et évitent toute pénalité (souris safe), d’autres ont un comportement exploratoire quitte à prendre des risques (souris risky), et une majorité des souris a un comportement intermédiaire (souris average). Nous avons ensuite révélé que les souris safe ont un comportement plus anxieux, une activation préfrontale plus faible que les autres groupes à l’issu du MGT, et un taux de sérotonine à l’état basal plus faible au niveau du cortex préfrontal. Les souris risky ont un comportement plus risqué dans plusieurs tests comportementaux et sont moins sensibles à la récompense. De plus, elles présentent un faible taux de sérotonine au niveau du cortex orbitofrontal ainsi qu’un taux de dopamine, noradrénaline et sérotonine plus important au niveau hippocampique.Afin de tester l’effet d’une modification de l’environnement sur les profils décisionnels caractérisés précédemment, nous avons réalisé le MGT sur un groupe de souris soumises soit à une dette aiguë de sommeil (DAS) soit à une dette chronique de sommeil (DCS). Nous avons alors montré qu’une DCS n’a pas d’effet sur les profils décisionnels mais qu’une DAS accentue ces profils décisionnels: les animaux safe deviennent d’autant plus rigides et évitent encore d’avantage les pénalités alors que les animaux risky choisissent systématiquement les options plus risquées, en adoptant un comportement rigide. Ces observations comportementales peuvent s’expliquer par un métabolisme sérotoninergique diminué au niveau du cortex orbitofrontal et augmenté au niveau hippocampique, ainsi que par un taux élevé de dopamine au niveau du striatum dorsal, structure cérébrale clé des processus d’automatisation.Par conséquent, le MGT permet de révéler, chez des souris consanguines saines, les caractéristiques comportementales et neurobiologiques individuelles de stratégies décisionnelles inadaptées pouvant être amplifiées par un stress environnemental. Ce modèle permettra, notamment, de déterminer les facteurs de vulnérabilité au développement de certaines psychopathologies (l’addiction et la dépression, par exemple) dont le manque de sommeil pourrait être un déclencheur ou un amplificateur. / Affective abilities that rely on the integrity of several neural circuits. In healthy subjects, inter-individual variability during decision-making exists due to genetic, epigenetic and environmental factors. Moreover, many psychiatric and neurobiological disorders are characterized by poor decision-making processes. Therefore, determining behavioral traits and neurobiological substrates involved in these processes is of major interest to unravel markers that could predict the emergence of neuropathologies.Based on the Iowa Gambling Task in humans, we developed a decision-making task in mice that assesses their ability to choose between several conflicting options under uncertainty. Thanks to a differential approach of mice’s behavior, we show that decision-making skills differed between mice: some mice exhibit a rigid behavior and avoid penalty (safe mice); others maintained exploratory behavior even if they took risks (risky mice); a majority of mice exhibit an intermediate behavior (average mice). We found that a combination of behavioral characteristics related to different psychopathologies in humans were specifically associated with extreme behavior in mice: safe mice exhibited a more anxious behavior, a lower prefrontal activation after the MGT than others subgroups of performance together with a lower basal rate of serotonin in the prefrontal cortex. Risky mice displayed a riskier behavior in various behavioral tasks, were less sensitive to reward, and had a lower basal rate of serotonin in the orbitofrontal cortex as well as a higher basal rate of serotonin, dopamine and noradrenaline in the hippocampus.To investigate the consequences of environmental changes on decision-making individual profiles, we performed the MGT on groups of mice either under Acute Sleep Dept (ASD) or under chronic sleep debt (CSD). We show that CSD didn't play any apparent effect but that ASD emphasized decision-making profiles: safe mice became drastically more rigid and avoided penalty; and risky mice chose systematically riskier options and developed rigid and unefficient decisions. These behavioral data could be explained by a decreased serotonin metabolism in the orbitofrontal cortex, an increase in the hippocampus and a high level of dopamine in the caudate putamen, the key brain area of habits.Therefore, in healthy inbred mice the MGT reveals individual inadapted decision-making strategies which are characterized by behavioral and neurobiological substrates exacerbated by an environmental stress. This paradigm also allows the determination of mice vulnerability to develop psychopathologies (e.g. depression, addiction) for which sleep debt could a trigger or a magnifier.

Approved for public release, distribution is unlimited / The Benefield Anechoic Facility (BAF), Edwards Air Force Base, California, is the largest anechoic military test facility in the world for testing developmental and operational electromagnetic equipment. Supervisors must often extend employees' work hours considerably in order to meet mission (i.e., test) timelines. Supervisors at the BAF currently have no accurate means of identifying when an employee's work performance is at risk of decreasing due to sleep deprivation, unbalanced circadian rhythms, and/or fatigue. Therefore, the focus of this research was to create a method for supervisors to effectively gauge the work performance levels of employees placed at risk for sleep deprivation. Thus, individual sleep data were collected for one week on eight volunteers at the BAF using assigned sleep monitoring devices known as Actigraphs. Extensive questionnaires were developed to determine volunteers' sleep pattern, demographics, and sleep history. For analysis purposes, the Fast Avoidance Scheduling Tool (FAST), based on the Sleep, Activity, Fatigue, and Task Effectiveness (SAFTE) model was used to determine how the performance level of each volunteer differed based on the amount of sleep acquired. The results demonstrated that as the week progressed and the volunteers' sleep decreased, the effectiveness of their work performance correspondingly decreased to a level where the safety of the test and the volunteers were both at risk. / Civilian, United States Air Force

Sleep is a basic need as important as physical fitness and good nutrition. Without enough sleep, we will create a sleep debt and experience sleepiness. Sleepiness can be defined as the inability to stay awake, a condition that has become a health problem in our 24-hour-7-day-a-week society. Estimates suggest that up to one-third of the population suffers from excessive sleepiness. Among other interactions, sleepiness affects our performance, increasing the risk of being involved in accidents. A considerable portion of work related accidents and injuries are related to sleepiness resulting in large costs for the individuals and society. Professional drivers are one example of workers who are at risk of sleepiness related accidents. Up to 40% of heavy truck accidents could be related to sleepiness. A better knowledge about reliable indicators and predictors of sleepiness is important in preventing sleepiness related accidents. This thesis investigates both objective and subjective indicators of sleepiness, how these relate to each other, and how their pattern changes over time. The indicators investigated were electroencephalography, heart rate variability, simple reaction time, head movement, and subjective ratings of sleepiness (Study I-IV). In Study V, a questionnaire study was conducted with professional drivers in northern Sweden. This study mainly deals with predictors of sleepiness. When subjects were sleep deprived both objective and subjective ratings indicated a rapid increase in sleepiness during the first hour of the test followed by a levelling off. This change in pattern was evident for all the indicators except heart rate and heart rate variability. On the other hand, HRV was correlated with the increase of EEG parameters during the post-test sleep period. The changes in pattern of the indicators included in the thesis are analysed in the perspective of temporal patterns and relationships. Of the tested indicators, a subjective rating of sleepiness with CR-10 was considered to be the most reliable indicator of sleepiness. Of the investigated predictors of sleepiness, prior sleep habits were found to be strongly associated to sleepiness and the sleepiness related symptoms while driving. The influences of driving conditions and individual characteristics on sleepiness while driving were lower. A multidisciplinary approach when investigating and implementing indicators and predictors of sleepiness is important. In addition to their actual relations to the development of sleepiness, factors such as technical and practical limitations, work, and individual and situational needs must be taken into account.