Browsing by Author "Herzog, M. H."
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Item Open Access About individual differences in vision(Pergamon Press, 2017) Grzeczkowski, L.; Clarke, A. M.; Francis, G.; Mast, F. W.; Herzog, M. H.In cognition, audition, and somatosensation, performance strongly correlates between different para-digms, which suggests the existence of common factors. In contrast, visual performance in seeminglyvery similar tasks, such as visual and bisection acuity, are hardly related, i.e., pairwise correlationsbetween performance levels are low even though test-retest reliability is high. Here we show similarresults for visual illusions. Consistent with previous findings, we found significant correlations betweenthe illusion magnitude of the Ebbinghaus and Ponzo illusions, but this relationship was the only signif-icant correlation out of 15 further comparisons. Similarly, we found a significant link for the Ponzo illu-sion with both mental imagery and cognitive disorganization. However, most other correlations betweenillusions and personality were not significant. The findings suggest that vision is highly specific, i.e., thereis no common factor. While this proposal does not exclude strong and stable associations between certainillusions and between certain illusions and personality traits, these associations seem to be the exceptionrather than the rule.Item Open Access Beyond Bouma's window: how to explain global aspects of crowding?(Public Library of Science, 2019-05) Doerig, A.; Bornet, A.; Rosenholtz, R.; Francis, G.; Clarke, Aaron M.; Herzog, M. H.In crowding, perception of an object deteriorates in the presence of nearby elements. Although crowding is a ubiquitous phenomenon, since elements are rarely seen in isolation, to date there exists no consensus on how to model it. Previous experiments showed that the global configuration of the entire stimulus must be taken into account. These findings rule out simple pooling or substitution models and favor models sensitive to global spatial aspects. In order to investigate how to incorporate global aspects into models, we tested a large number of models with a database of forty stimuli tailored for the global aspects of crowding. Our results show that incorporating grouping like components strongly improves model performance. Author summary Visual crowding highlights interactions between elements in the visual field. For example, an object is more difficult to recognize if it is presented in clutter. Crowding is one of the most fundamental aspects of vision, playing crucial roles in object recognition, reading and visual perception in general, and is therefore an essential tool to understand how the visual system encodes information based on its retinal input. Hence, classic models of crowding have focused only on local interactions between neighboring visual elements. However, abundant experimental evidence argues against local processing, suggesting that the global configuration of visual elements strongly modulates crowding. Here, we tested all available models of crowding that are able to capture global processing across the entire visual field. We tested 12 models including the Texture Tiling Model, a Deep Convolutional Neural Network and the LAMINART neural network with large scale computer simulations. We found that models incorporating a grouping component are best suited to explain the data. Our results suggest that in order to understand vision in general, mid-level, contextual processing is inevitable.Item Open Access Motion-based nearest vector metric for reference frame selection in the perception of motion(Association for Research in Vision and Ophthalmology Inc., 2016) Agaoglu, M. N.; Clarke, Aaron M.; Herzog, M. H.; Öğmen, H.We investigated how the visual system selects a reference frame for the perception of motion. Two concentric arcs underwent circular motion around the center of the display, where observers fixated. The outer (target) arc's angular velocity profile was modulated by a sine wave midflight whereas the inner (reference) arc moved at a constant angular speed. The task was to report whether the target reversed its direction of motion at any point during its motion. We investigated the effects of spatial and figural factors by systematically varying the radial and angular distances between the arcs, and their relative sizes. We found that the effectiveness of the reference frame decreases with increasing radial- and angular-distance measures. Drastic changes in the relative sizes of the arcs did not influence motion reversal thresholds, suggesting no influence of stimulus form on perceived motion.We also investigated the effect of common velocity by introducing velocity fluctuations to the reference arc as well. We found no effect of whether or not a reference frame has a constant motion. We examined several form- and motion-based metrics, which could potentially unify our findings. We found that a motion-based nearest vector metric can fully account for all the data reported here. These findings suggest that the selection of reference frames for motion processing does not result from a winner-take-all process, but instead, can be explained by a field whose strength decreases with the distance between the nearest motion vectors regardless of the form of the moving objects.Item Open Access No evidence for a common factor underlying visual abilities in healthy older people(American Psychological Association, 2019) Shaqiri, A.; Pilz, K. S.; Cretenoud, A. F.; Neumann, K.; Clarke, Aaron; Kunchulia, M.; Herzog, M. H.The world’s population is aging at an increasing rate. Even in the absence of neurodegenerative disorders, healthy aging affects perception and cognition. In the context of cognition, common factors are well established. Much less is known about common factors for vision. Here, we tested 92 healthy older and 104 healthy younger participants in 19 visual tests (including visual search and contrast sensitivity) and three cognitive tests (including verbal fluency and digit span). Unsurprisingly, younger participants performed better than older participants in almost all tests. Surprisingly, however, the performance of older participants was mostly uncorrelated between visual tests, and we found no evidence for a common factor.Item Open Access What crowding can tell us about object representations(Association for Research in Vision and Ophthalmology Inc., 2016) Manassi, M.; Lonchampt, S.; Clarke, Aaron; Herzog, M. H.In crowding, perception of a target usually deteriorates when flanking elements are presented next to the target. Surprisingly, adding further flankers can lead to a release from crowding. In previous work we showed that, for example, vernier offset discrimination at 9� of eccentricity deteriorated when a vernier was embedded in a square. Adding further squares improved performance. The more squares presented, the better the performance, extending across 20� of the visual field. Here, we show that very similar results hold true for shapes other than squares, including unfamiliar, irregular shapes. Hence, uncrowding is not restricted to simple and familiar shapes. Our results provoke the question of whether any type of shape is represented at any location in the visual field. Moreover, small changes in the orientation of the flanking shapes led to strong increases in crowding strength. Hence, highly specific shape-specific interactions across large parts of the visual field determine vernier acuity.Item Open Access What to choose next? a paradigm for testing human sequential decision making(Frontiers Research Foundation, 2017) Tartaglia, E. M.; Clarke, Aaron; Herzog, M. H.Many of the decisions we make in our everyday lives are sequential and entail sparse rewards. While sequential decision-making has been extensively investigated in theory (e.g., by reinforcement learning models) there is no systematic experimental paradigm to test it. Here, we developed such a paradigm and investigated key components of reinforcement learning models: the eligibility trace (i.e., the memory trace of previous decision steps), the external reward, and the ability to exploit the statistics of the environment's structure (model-free vs. model-based mechanisms). We show that the eligibility trace decays not with sheer time, but rather with the number of discrete decision steps made by the participants. We further show that, unexpectedly, neither monetary rewards nor the environment's spatial regularity significantly modulate behavioral performance. Finally, we found that model-free learning algorithms describe human performance better than model-based algorithms.