Biases in selective information-processing or attention biases are features of most psychiatric disorders. Attention biases can be measured by monitoring visual scanning behaviour (VSB) which is directly linked to attention allocation processes. This thesis presents a general framework for studies of VSB when multiple images are presented simultaneously to the viewer. Within this general framework, a novel set of VSB parameters that characterize the different stages of the visual scanning process was developed. Using this set of parameters, biases towards thin and fat body shape images were detected in Anorexia Nervosa patients. A log-likelihood ratio detector utilizing VSB parameters had both high sensitivity (92%) and high specificity (90%). Preliminary results in VSB studies also show biases in adults with Major Depressive Disorder and elderly apathetic Alzheimer’s patients. The development of sensitive physiological markers in individuals with mental illness is crucial to the advance of research, diagnosis, and treatment in psychiatry.

Biases in selective information-processing or attention biases are features of most psychiatric disorders. Attention biases can be measured by monitoring visual scanning behaviour (VSB) which is directly linked to attention allocation processes. This thesis presents a general framework for studies of VSB when multiple images are presented simultaneously to the viewer. Within this general framework, a novel set of VSB parameters that characterize the different stages of the visual scanning process was developed. Using this set of parameters, biases towards thin and fat body shape images were detected in Anorexia Nervosa patients. A log-likelihood ratio detector utilizing VSB parameters had both high sensitivity (92%) and high specificity (90%). Preliminary results in VSB studies also show biases in adults with Major Depressive Disorder and elderly apathetic Alzheimer’s patients. The development of sensitive physiological markers in individuals with mental illness is crucial to the advance of research, diagnosis, and treatment in psychiatry.

Bodies provide important social information, and adults benefit from this information by recognizing and responding appropriately to bodies. Body recognition is enabled by the fact that human bodies are defined by parts, such as the limbs, torso, and head, arranged in a particular configuration. To understand the development of social cognition, it is important to analyze and document how infants come to recognize bodies. Infants are sensitive to distortions to the global configurations of bodies by 3.5 months of age, suggesting an early onset of body knowledge. It was unclear, however, whether such sensitivity indicates knowledge of the location of specific body parts or solely reflects sensitivity to the overall gestalt or outline of bodies. The current study addressed this by examining whether infants attend to specific locations in which parts of the body have been reorganized. Results of Experiments 1 and 2 show that 5-month-olds, but not 3.5-month-olds, are sensitive to the location of specific body parts, as demonstrated by a difference in allocation of attention to the body joint areas that were normal (e.g., where the arm connects to the shoulder) versus ones that were reorganized. Furthermore, to examine whether this kind of processing is driven by information from the face/head, in Experiment 3 I tested infants on images in which the face/head was removed. Infants no longer exhibited differential scanning of normal versus reorganized bodies. To further assess whether infants were responding to critical information provided by the face/head or whether their processing was disrupted solely because the headless images were incomplete bodies, Experiment 4 examined infants’ performance on body images missing limbs. Once again, infants failed to exhibit differential scanning of typical versus reorganized bodies. Together, these results suggest that 5-month-olds are sensitive to the location of body parts. However, the presence of the face/head (Experiment 3) and limbs (Experiment 4) are necessary for 5-month-olds to exhibit differential scanning of reorganized versus intact body images. Overall, by 5 months of age, infants are sensitive to precise locations of body parts, and thus demonstrate a rather sophisticated level of knowledge about the structure of the human body. The role that the face/head and limbs play in body structure knowledge development is still unclear, and future studies need to address this question.

This thesis demonstrates how a model-based observer can be applied to estimate the reference pilot expectation that can be achieved with any instrument scanning behavior and established models of vestibular inputs. The MBO, developed by the Georgia Tech Cognitive Engineering Center, is applied here in both simple maneuvers examining spatial disorientation and full Air Traffic Control concepts of operations examining loss of energy state awareness. The computational experiments presented in this thesis examine how different effects (i.e., instrument scan pattern, accuracy of pilot perception of flight display information, and awareness of control surface deflections) can prevent or mitigate the susceptibility to spatial disorientation and loss of energy state awareness, thus setting requirements for intervention and countermeasure designs in terms of the scanning behavior they must foster.

Quality of care is important in health care systems, and reducing medication errors is an effective approach to improve health care quality because medication errors are not rare and can cause adverse patient outcomes. Current researchers have adopted contextual, macro level methods to study the medication administration process, but the association between cognitive factors and nurses’ abilities to identify medication errors during this process remains unclear. In this research, I tested whether methods for analyzing visual scanning patterns are applicable to the study of health care processes, specifically how nurses complete the medication administration process. The data used in this study was collected during three experiments wherein nurse participants wore an eye tracking device to record their eye movements while they performed a medication administration process, with some trials containing an embedded patient identification error. The three experiments included: Nurses administering medications in a simulated setting Nurses using barcoding technology to administer medication in a simulated setting Nurses using barcoding technology to administer medication in a real clinical setting I focused on four types of visual scanning patterns when analyzing the eye tracking data: 1) nurses’ eye fixation distributions, 2) nurses’ maximum consecutive eye fixations, 3) nurses’ eye gaze transition ratios, and 4) nurses’ two gaze scanpaths. By using the aforementioned methods, I was able to distinguish visual scanning patterns between groups of nurses who identified and did not identify a patient identity error, assessed how barcode technology influenced nurses’ visual scanning patterns, and assessed how nurses’ visual scanning patterns differed in simulated and real clinical environments. These findings may have implications for the design of medication administration protocols, nurse training, and technology design.

L’activité de conduite automobile prend place dans un environnement dynamique en constante évolution. Le conducteur doit progresser sur la route au moyen de son véhicule, tout en interagissant adéquatement avec l'environnement et les autres usagers. Pour réaliser cette tâche, le conducteur doit percevoir son environnement, interpréter les événements pour se représenter correctement la situation de conduite, anticiper ces changements, et prendre des décisions afin d'engager des actions sur le véhicule lui permettant d'atteindre les buts qu'il se fixe à court et long terme. A cet égard, la complexité et la diversité des processus perceptifs, cognitifs et sensori-moteurs requis pour la conduite automobile font de cette activité un objet d'étude particulièrement riche pour les sciences de la cognition.Pour étudier l'activité du conducteur automobile afin de la comprendre, l'expliquer et peut-être la prédire, les sciences cognitives se dirigent vers la modélisation de la cognition humaine. Cette démarche permet une représentation et une description plus ou moins fine du système cognitif du conducteur automobile. Cependant, un modèle de la cognition ne permet qu'une description théorique. Grâce à son implémentation informatique, il devient possible de simuler les théories utilisées et déployer numériquement celles mises en jeu dans la modélisation cognitive.Ce travail de thèse s'articule autour de la modélisation cognitive du conducteur automobile, de son implémentation informatique sur une plateforme de développement virtuel et de sa simulation au sein de cette plateforme. Le modèle théorique que nous avons implémenté est COSMODRIVE, en développement au laboratoire du LESCOT à l'IFSTTAR, et la plateforme de développement accueillant le modèle est SIVIC, développée au LIVIC. C'est dans ce contexte que nous nous sommes engagés dans le développement computationnel et informatique du modèle COSMODRIVE, afin de pouvoir simuler l'activité perceptive et cognitive du conducteur automobile. Pour cela, nous nous sommes limités à certains processus cognitifs primordiaux, comme les fonctions stratégiques (planification d'itinéraires et réalisation de plans stratégiques), ou les fonctions perceptives (exploration et intégration de l'information visuelle), les fonctions cognitives tactiques (construction de représentations mentales, intégration perceptivo-cognitive de l'information, structuration des connaissances de conduite, etc), ou encore les fonctions d'exécution d'actions (régulation courte par zones enveloppes ou par points de poursuite).Par l'implémentation informatique du modèle COSMODRIVE sur SIVIC, il devient possible "d'incarner numériquement" des théories cognitives et de les "opérationnaliser" pour formuler des hypothèses de recherche sous la forme de prédictions de performances que l'on pourra évaluer empiriquement auprès de conducteurs humains. Ces hypothèses formulées, nous avons conduit des expérimentations sur un simulateur de conduite que nous avons construit. Afin d'éprouver notre modèle théorique et informatique du conducteur, nous avons comparé les performances des conducteurs humains avec les prédictions issues de la simulation. Les résultats obtenus ont permis de valider cette approche et de confirmer l'intérêt de la simulation cognitive pour appréhender les activités mentales du conducteur automobile. / Driving activity takes place in a dynamic and constantly changing environment. The driver has to make his car evolving on the road while ensuring adequate interactions with its close environment and other road users. In order to perform this task, the driver has to perceive the environment he is evolving in, to interpret events in order to correctly understand the current driving situation, to be able to anticipate its evolution and take decisions regarding vehicle control in order to reach his short and long term goals safely. As a result, both complexity and variety of perceptual, cognitive and sensorimotor processes involved in the driving activity make it very rich context for cognitive sciences.The modeling of human cognition, a specific method which belongs to cognitive sciences field, has been chosen to study driver's activity aiming at understanding, explaining or even predicting it. This approach allows a representation and a description of the driver's cognitive system with different levels of granularity. Thus, such a model offers only a theoretical description. When implemented on a computer, it opens the way to the simulation allowing the digital deployment of the theories involved in the cognitive model design.This thesis is focused on cognitive modeling of car driver, its implementation and its simulation using a virtual platform. The theoretical model that we implemented is COSMODRIVE, developed at IFSTTAR - LESCOT laboratory and the implementation platform we used for this, named SIVIC, is developed at IFSTTAR - LIVIC.This is the context where we started the computational development of the COSMODRIVE model in order to simulate the perceptual and cognitive activity of car driver. Indeed, we chose to limit our implementation to some crucial cognitive processes such as strategic functions (route planning and strategic plans execution), perceptual functions (exploration and integration of visual information), cognitive tactical functions (construction of mental representations, perceptual and cognitive integration of information, structuring of driving knowledge, etc.), or executive functions of actions (short control loop by ''envelopes zones'' or pursuit points).Through computer simulation, we used the numerical model as an innovative tool for scientific investigation in the field of cognitive sciences: The numerical simulation of cognitive functions identified and modeled by COSMODRIVE allowed us to define experimental hypotheses which leed us to conduct experiments in a driving simulator that we have built. To test the theoretical model and computer of the car driver, we compared the performance of human drivers on one hand and the predictions issued from the simulation on the other hand. It opens innovative opportunities for the development and the use of cognitive modeling and simulation of car driver.