The ability to remember spatial locations is critical to human functioning, both in an evolutionary and an everyday sense. And yet, spatial memories and judgments often show systematic errors. Explanations for such errors have ranged from assumptions that memories are nonmetric, to the use of imperfect inferences, to the optimal combination of multiple sources of information. More recently, bias has been explained through the Category Adjustment Model - a Bayesian model in which fine-grained and categorical information are optimally combined (Huttenlocher, Hedges, & Duncan, 1991). However, experiments testing this model have largely used locations contained in simple geometric shapes. Use of this paradigm raises the issue of whether the results generalize to location memory in the complex natural world, as it should if it is to provide an over-arching framework for thinking about spatial memory. Here, this issue is addressed using a novel extension of the location memory paradigm that allows for testing of location memory in an everyday, 3D environment. The results support two predictions of the Category Adjustment Model - that memory for locations is biased toward central values, and that the magnitude of error increases with the retention interval. Future directions for testing the model in an increasingly ecologically valid manner are discussed. / Psychology

Yes / Depictions of vision with AMD in public information material typically show a central region of absolute vision loss. Patients with early and moderate disease frequently do not report this. We aimed to measure how a group of people with AMD perceive everyday scenes in order to produce accurate depictions. We report on six people aged 65-82 years with monocular AMD (visual acuity +0.04 to +1.64 logMAR) and normal vision in the fellow eye. Participants viewed 4 images monocularly, alternating between eyes. The image was digitally altered to approximate participants’ descriptions of their perception with the affected eye. The altered image was viewed with the unaffected eye, and compared with the original image viewed with the affected eye. This was repeated iteratively until a perceptual match was achieved between the modified image/unaffected eye and the original image/affected eye. For five AMD participants with visual acuity +0.04 to +0.50 logMAR the modified images did not resemble those in current public information material. Image modifications required to achieve perceptual similarity with the affected eyes included localised distortion, contrast reduction and blur. Widespread colour desaturation was also required in some cases. One participant with advanced geographic atrophy reported an absolute positive scotoma, similar to existing depictions. Vision in people with AMD may not conform to the common depiction of a central region of absolute vision loss. The accurate representations of AMD patients’ vision produced in this study will enable better understanding of the visual consequences of AMD. / College of Optometrists Postdoctoral Award; National Institute for Health Research Postdoctoral Fellowship

Autonomous driving is the concept of a vehicle that operates in traffic without instructions from a driver. A major challenge for such a system is to provide a comprehensive, accurate and compact scene model based on information from sensors. For such a model to be comprehensive it must provide 3D position and semantics on relevant surroundings to enable a safe traffic behavior. Such a model creates a foundation for autonomous driving to make substantiated driving decisions. The model must be compact to enable efficient processing, allowing driving decisions to be made in real time. In this thesis rectangular objects (The Stixelworld) are used to represent the surroundings of a vehicle and provide a scene model. LIDAR and semantic segmentation are fused in the computation of these rectangles. This method indicates that a dense and compact scene model can be provided also from sparse LIDAR data by use of semantic segmentation. / Fullt självkörande fordon behöver inte förare. Ett sådant fordon behöver en precis, detaljerad och kompakt modell av omgivningen baserad på sensordata. Med detaljerad avses att modellen innefattar all information nödvändig för ett trafiksäkert beteende. Med kompakt avses att en snabb bearbetning kan göras av modellen så att fordonet i realtid kan fatta beslut och manövrera i trafiken. I denna uppsats tillämpas en metod där man med rektangulära objekt skapar en modell av omgivningen. Dessa beräknas från LIDAR och semantisk segmentering. Arbetet indikerar att med hjälp av semantisk segmentering kan en tät, detaljerad och kompakt modell göras även från glesa LIDAR-data.

In this thesis, the restorative effects of exposure to nature are examined through the lens of existing restoration theories. Limitations of existing theories, such as Attention Restoration Theory and Psycho-evolutionary Restoration Theory, are highlighted. To address the limitations of existing theories, an expanded theoretical framework is proposed: The expanded framework introduces a newly proposed neural mechanism and theory of restoration that build on existing theories by proposing a link to recently discovered reward systems in the ventral visual pathway. Results from six experiments provide consistent evidence to suggest that positive and negative responses to visual scenes are related to the low-level visuospatial properties of the scenes. Specifically, a discovery is made to suggest that the power of a limited visual spatial frequency range can consistently predict responses to natural, urban, and abstract scenes on measures of restoration (blink-rates, number of fixations, self-reported stress and pleasantness). This provides the first evidence to suggest that low-level visual properties of scenes may play an important role in affective and physiological responses to scenes. Furthermore, this newly discovered relationship provides a new way to objectively predict the relative restorative value of any given scene.

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Recently, two attentional modes have been associated with specifi c eye movement patterns during scene processing. Ambient mode, characterized by short fi xations and long saccades during early scene inspection, is associated with localization of objects. Focal mode, characterized by longer fi xations, is associated with more detailed object feature processing during later inspection phase. The aim of the present study was to investigate the development of these attentional modes. More specifi cally, we examined whether indications of ambient and focal attention modes are similar in infants and adults. Therefore, we measured eye movements in 3- to 12-months-old infants while exploring visual scenes. Our results show that both adults and 12-month-olds had shorter fi xation durations within the fi rst 1.5 s of scene viewing compared with later time phases (>2.5 s); indicating that there was a transition from ambient to focal processing during image inspection. In younger infants, fi xation durations between two viewing phases did not differ. Our results suggest that at the end of the fi rst year of life, infants have developed an adult-like scene viewing behavior. The evidence for the existence of distinct attentional processing mechanisms during early infancy furthermore underlines the importance of the concept of the two modes.