Dissecting (un)crowding.

In crowding, perception of a target deteriorates in the presence of nearby flankers. Surprisingly, perception can be rescued from crowding if additional flankers are added (uncrowding). Uncrowding is a major challenge for all classic models of crowding and vision in general, because the global configuration of the entire stimulus is crucial. However, it is unclear which characteristics of the configuration impact (un)crowding. Here, we systematically dissected flanker configurations and showed that (un)crowding cannot be easily explained by the effects of the sub-parts or low-level features of the stimulus configuration. Our modeling results suggest that (un)crowding requires global processing. These results are well in line with previous studies showing the importance of global aspects in crowding.

Global and high-level effects in crowding cannot be predicted by either high-dimensional pooling or target cueing.

In visual crowding, the perception of a target deteriorates in the presence of nearby flankers. Traditionally, target-flanker interactions have been considered as local, mostly deleterious, low-level, and feature specific, occurring when information is pooled along the visual processing hierarchy. Recently, a vast literature of high-level effects in crowding (grouping effects and face-holistic crowding in particular) led to a different understanding of crowding, as a global, complex, and multilevel phenomenon that cannot be captured or explained by simple pooling models. It was recently argued that these high-level effects may still be captured by more sophisticated pooling models, such as the Texture Tiling model (TTM). Unlike simple pooling models, the high-dimensional pooling stage of the TTM preserves rich information about a crowded stimulus and, in principle, this information may be sufficient to drive high-level and global aspects of crowding. In addition, it was proposed that grouping effects in crowding may be explained by post-perceptual target cueing. Here, we extensively tested the predictions of the TTM on the results of six different studies that highlighted high-level effects in crowding. Our results show that the TTM cannot explain any of these high-level effects, and that the behavior of the model is equivalent to a simple pooling model. In addition, we show that grouping effects in crowding cannot be predicted by post-perceptual factors, such as target cueing. Taken together, these results reinforce once more the idea that complex target-flanker interactions determine crowding and that crowding occurs at multiple levels of the visual hierarchy.

How do visual skills relate to action video game performance?

It has been claimed that video gamers possess increased perceptual and cognitive skills compared to non-video gamers. Here, we examined to which extent gaming performance in CS:GO (Counter-Strike: Global Offensive) correlates with visual performance. We tested 94 players ranging from beginners to experts with a battery of visual paradigms, such as visual acuity and contrast detection. In addition, we assessed performance in specific gaming skills, such as shooting and tracking, and administered personality traits. All measures together explained about 70% of the variance of the players' rank. In particular, regression models showed that a few visual abilities, such as visual acuity in the periphery and the susceptibility to the Honeycomb illusion, were strongly associated with the players' rank. Although the causality of the effect remains unknown, our results show that high-rank players perform better in certain visual skills compared to low-rank players.

Reference-frames in vision: Contributions of attentional tracking to nonretinotopic perception in the Ternus-Pikler display.

Perception depends on reference frames. For example, the "true" cycloidal motion trajectory of a reflector on a bike's wheel is invisible because we perceive the reflector motion relative to the bike's motion trajectory, which serves as a reference frame. To understand such an object-based motion perception, we suggested a "two-stage" model in which first reference frames are computed based on perceptual grouping (bike) and then features are attributed (reflector motion) based on group membership. The overarching goal of this study was to investigate how multiple features (i.e., motion, shape, and color) interact with attention to determine retinotopic or nonretinotopic reference frames. We found that, whereas tracking by focal attention can generate nonretinotopic reference-frames, the effect is rather small compared with motion-based grouping. Combined, our results support the two-stage model and clarify how various features and cues can work in conjunction or in competition to determine prevailing groups. These groups in turn establish reference frames according to which features are processed and bound together.

Unconscious retinotopic motion processing affects non-retinotopic motion perception.

Unconscious visual stimuli can affect conscious perception: For example, an invisible prime can affect responses to a subsequent target. The invisible interpretation of an ambiguous figure can have similar effects. Invisibility in these situations is typically explained by stimulus-suppression in early, retinotopic brain areas. We have previously argued that invisibility is closely linked to Gestalt ("object") organization principles. For example, motion is typically perceived in non-retinotopic, object-centered, and not in retinotopic coordinates. Such is the case for a bicycle-reflector that is perceived as circling, although its retinotopic trajectory is cycloidal. Here, we used a modified Ternus-Pikler display in which, just as in everyday vision, the retinotopic motion is invisible and the non-retinotopic motion is perceived. Nevertheless, the invisible retinotopic motion, can strongly degrade the conscious non-retinotopic motion percept. This effect cannot be explained by inhibition at a retinotopic processing stage.

Extracting medicinal chemistry intuition via preference machine learning.

The lead optimization process in drug discovery campaigns is an arduous endeavour where the input of many medicinal chemists is weighed in order to reach a desired molecular property profile. Building the expertise to successfully drive such projects collaboratively is a very time-consuming process that typically spans many years within a chemist's career. In this work we aim to replicate this process by applying artificial intelligence learning-to-rank techniques on feedback that was obtained from 35 chemists at Novartis over the course of several months. We exemplify the usefulness of the learned proxies in routine tasks such as compound prioritization, motif rationalization, and biased de novo drug design. Annotated response data is provided, and developed models and code made available through a permissive open-source license.

Unlocking crowding by ensemble statistics.

In crowding,1,2,3,4,5,6,7 objects that can be easily recognized in isolation appear jumbled when surrounded by other elements.8 Traditionally, crowding is explained by local pooling mechanisms,3,6,9,10,11,12,13,14,15 but many findings have shown that the global configuration of the entire stimulus display, rather than local aspects, determines crowding.8,16,17,18,19,20,21,22,23,24,25,26,27,28 However, understanding global configurations is challenging because even slight changes can lead from crowding to uncrowding and vice versa.23,25,28,29 Unfortunately, the number of configurations to explore is virtually infinite. Here, we show that one does not need to know the specific configuration of flankers to determine crowding strength but only their ensemble statistics, which allow for the rapid computation of groups within the stimulus display.30,31,32,33,34,35,36,37 To investigate the role of ensemble statistics in (un)crowding, we used a classic vernier offset discrimination task in which the vernier was flanked by multiple squares. We manipulated the orientation statistics of the squares based on the following rationale: a central square with an orientation different from the mean orientation of the other squares stands out from the rest and groups with the vernier, causing strong crowding. If, on the other hand, all squares group together, the vernier is the only element that stands out, and crowding is weak. These effects should depend exclusively on the perceived ensemble statistics, i.e., on the mean orientation of the squares and not on their individual orientations. In two experiments, we confirmed these predictions.

Intact and deficient contextual processing in schizophrenia patients.

Schizophrenia patients are known to have deficits in contextual vision. However, results are often very mixed. In some paradigms, patients do not take the context into account and, hence, perform more veridically than healthy controls. In other paradigms, context deteriorates performance much more strongly in patients compared to healthy controls. These mixed results may be explained by differences in the paradigms as well as by small or biased samples, given the large heterogeneity of patients' deficits. Here, we show that mixed results may also come from idiosyncrasies of the stimuli used because in variants of the same visual paradigm, tested with the same participants, we found intact and deficient processing.

Exploring Feature Dimensions to Learn a New Policy in an Uninformed Reinforcement Learning Task.

When making a choice with limited information, we explore new features through trial-and-error to learn how they are related. However, few studies have investigated exploratory behaviour when information is limited. In this study, we address, at both the behavioural and neural level, how, when, and why humans explore new feature dimensions to learn a new policy for choosing a state-space. We designed a novel multi-dimensional reinforcement learning task to encourage participants to explore and learn new features, then used a reinforcement learning algorithm to model policy exploration and learning behaviour. Our results provide the first evidence that, when humans explore new feature dimensions, their values are transferred from the previous policy to the new online (active) policy, as opposed to being learned from scratch. We further demonstrated that exploration may be regulated by the level of cognitive ambiguity, and that this process might be controlled by the frontopolar cortex. This opens up new possibilities of further understanding how humans explore new features in an open-space with limited information.

Neural substrates of motor and non-motor symptoms in Parkinson's disease: a resting FMRI study.

BACKGROUND: Recently, non-motor symptoms of Parkinson's disease (PD) have been considered crucial factors in determining a patient's quality of life and have been proposed as the predominant features of the premotor phase. Researchers have investigated the relationship between non-motor symptoms and the motor laterality; however, this relationship remains disputed. This study investigated the neural connectivity correlates of non-motor and motor symptoms of PD with respect to motor laterality. METHODS: Eight-seven patients with PD were recruited and classified into left-more-affected PD (n = 44) and right-more affected PD (n = 37) based on their MDS-UPDRS (Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale) motor examination scores. The patients underwent MRI scanning, which included resting fMRI. Brain regions were labeled as ipsilateral and contralateral to the more-affected body side. Correlation analysis between the functional connectivity across brain regions and the scores of various symptoms was performed to identify the neural connectivity correlates of each symptom. RESULTS: The resting functional connectivity centered on the ipsilateral inferior orbito-frontal area was negatively correlated with the severity of non-motor symptoms, and the connectivity of the contralateral inferior parietal area was positively correlated with the severity of motor symptoms (p < 0.001, |r| > 0.3). CONCLUSIONS: These results suggest that the inferior orbito-frontal area may play a crucial role in non-motor dysfunctions, and that the connectivity information may be utilized as a neuroimaging biomarker for the early diagnosis of PD.