Making sense of real-world scenes

To interact with the world, we have to make sense of the continuous sensory input conveying information about our environment. A recent surge of studies has investigated the processes enabling scene understanding, using increasingly complex stimuli and sophisticated analyses to highlight the visual features and brain regions involved. However, there are two major challenges to producing a comprehensive framework for scene understanding. First, scene perception is highly dynamic, subserving multiple behavioral goals. Second, a multitude of different visual properties co-occur across scenes and may be correlated or independent. We synthesize the recent literature and argue that for a complete view of scene understanding, it is necessary to account for both differing observer goals and the contribution of diverse scene properties

Direct comparison of contralateral bias and face/scene selectivity in human occipitotemporal cortex

Human visual cortex is organised broadly according to two major principles: retinotopy (the spatial mapping of the retina in cortex) and category-selectivity (preferential responses to specific categories of stimuli). Historically, these principles were considered anatomically separate, with retinotopy restricted to the occipital cortex and category-selectivity emerging in the lateral-occipital and ventral-temporal cortex. However, recent studies show that category-selective regions exhibit systematic retinotopic biases, for example exhibiting stronger activation for stimuli presented in the contra- compared to the ipsilateral visual field. It is unclear, however, whether responses within category-selective regions are more strongly driven by retinotopic location or by category preference, and if there are systematic differences between category-selective regions in the relative strengths of these preferences. Here, we directly compare contralateral and category preferences by measuring fMRI responses to scene and face stimuli presented in the left or right visual field and computing two bias indices: a contralateral bias (response to the contralateral minus ipsilateral visual field) and a face/scene bias (preferred response to scenes compared to faces, or vice versa). We compare these biases within and between scene- and face-selective regions and across the lateral and ventral surfaces of the visual cortex more broadly. We find an interaction between surface and bias: lateral surface regions show a stronger contralateral than face/scene bias, whilst ventral surface regions show the opposite. These effects are robust across and within subjects, and appear to reflect large-scale, smoothly varying gradients. Together, these findings support distinct functional roles for the lateral and ventral visual cortex in terms of the relative importance of the spatial location of stimuli during visual information processing. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00429-021-02411-8

Two-dimensional superconductivity at the (111)LaAlO3_3/SrTiO3_3 interface

We report on the discovery and transport study of the superconducting ground state present at the (111)LaAlO$_3$/SrTiO$_3$ interface. The superconducting transition is consistent with a Berezinskii-Kosterlitz-Thouless transition and its 2D nature is further corroborated by the anisotropy of the critical magnetic field, as calculated by Tinkham. The estimated superconducting layer thickness and coherence length are 10 nm and 60 nm, respectively. The results of this work provide a new platform to clarify the microscopic details of superconductivity at LaAlO$_3$/SrTiO$_3$ interfaces, in particular in what concerns the link with orbital symmetry.Comment: 4 pages, 4 figure

Scene complexity modulates degree of feedback activity during object detection in natural scenes

Selective brain responses to objects arise within a few hundreds of milliseconds of neural processing, suggesting that visual object recognition is mediated by rapid feed-forward activations. Yet disruption of neural responses in early visual cortex beyond feed-forward processing stages affects object recognition performance. Here, we unite these discrepant findings by reporting that object recognition involves enhanced feedback activity (recurrent processing within early visual cortex) when target objects are embedded in natural scenes that are characterized by high complexity. Human participants performed an animal target detection task on natural scenes with low, medium or high complexity as determined by a computational model of low-level contrast statistics. Three converging lines of evidence indicate that feedback was selectively enhanced for high complexity scenes. First, functional magnetic resonance imaging (fMRI) activity in early visual cortex (V1) was enhanced for target objects in scenes with high, but not low or medium complexity. Second, event-related potentials (ERPs) evoked by target objects were selectively enhanced at feedback stages of visual processing (from ~220 ms onwards) for high complexity scenes only. Third, behavioral performance for high complexity scenes deteriorated when participants were pressed for time and thus less able to incorporate the feedback activity. Modeling of the reaction time distributions using drift diffusion revealed that object information accumulated more slowly for high complexity scenes, with evidence accumulation being coupled to trial-to-trial variation in the EEG feedback response. Together, these results suggest that while feed-forward activity may suffice to recognize isolated objects, the brain employs recurrent processing more adaptively in naturalistic settings, using minimal feedback for simple scenes and increasing feedback for complex scenes

Extremely small fabrication tolerant InP-based power-splitting and combining structures by deep etching

Design and realization of extremely small InP-based coupling structures with high performance and good compatibility with other components is reported: 3 dB coupler (90 mu m long, 0.7 dB loss), 1*16 coupler (141*32 mu m), Mach-Zehnder interferometer (0.6 dB loss, -28 dB crosstalk

Thin endometrial lining:is it more prevalent in patients utilizing preimplantation genetic testing for monogenic disease (PGT-M) and related to prior hormonal contraceptive use?

STUDY QUESTION: Is a thin endometrial lining before ovulation triggering more prevalent in patients utilizing preimplantation genetic testing for monogenic disease (PGT-M) compared to the regular IVF/ICSI population and is this associated with prior hormonal contraceptive use? SUMMARY ANSWER: Thin (1 year prior to treatment). Endometrial thickness was routinely measured on the day of hCG triggering or 1 day prior. The prevalence of an endometrial lining or 8 mm (20.0% vs 1.7%, mean difference 18.3%, 95% CI: 2.3, 34.3%). A trend towards lower birth weight and gestation- and gender-adjusted birth weight (z-score) was also found in this group. No statistically significant differences were detected in pregnancy rate, live birth rate, or incidence of preterm delivery or SGA. Within the control group, no statistically significant differences were found in outcomes between patients with an endometrial lining 8 mm. LIMITATIONS, REASONS FOR CAUTION: The study is retrospective. Various types of hormonal contraceptives were reported which possibly exert different effects on the endometrial lining. In relation to pregnancy outcome measures, numbers were very limited; therefore, no firm conclusions should be drawn. WIDER IMPLICATIONS OF THE FINDINGS: This study provides further insight into the role of prior hormonal contraceptive use as a possible contributor to the occurrence of thin endometrial lining during ART treatment. Future studies should provide more information on its clinical relevance, to determine whether PGT-M patients can be reassured, or should be counselled to stop hormonal contraceptive use and change to an alternative contraceptive method prior to PGT treatment. STUDY FUNDING/COMPETING INTERESTS: No specific funding was used and no conflicts of interests are declared. TRIAL REGISTRATION NUMBER: N/A

Definition of animal breeding goals for sustainable production systems

What we do is determined by the way we "view" a complex issue and what sample of issues or events we choose to deal with. In this paper, a model based on a communal, cultural, or people-centered worldview, informed by a subjective epistemology and a holistic ontology, is considered. Definitions and interpretations of sustainable agriculture are reviewed. Common elements in published definitions of sustainable agriculture and animal production among those who seek long-term and equitable solutions for food production are resource efficiency, profitability, productivity, environmental soundness, biodiversity, social viability, and ethical aspects. Possible characteristics of future sustainable production systems and further development are presented. The impact of these characteristics on animal breeding goals is reviewed. The need for long-term biologically, ecologically, and sociologically sound breeding goals is emphasized, because animal breeding determined only by short-term market forces leads to unwanted side effects. Hence, a procedure for defining animal breeding goals with ethical priorities and weighing of market and non-market values is suggested. Implementation of non-market as well as market economic trait values in the aggregate genotype, as suggested, may allow for breeding programs that contribute to sustainable production systems. Examples of breeding goals in salmon, cattle, and pigs are given, and the resulting genetic responses are evaluated with respect to economic profit (or costs) and other criteria of sustainability. Important prerequisites for breeding programs for sustainable production are appropriate governmental policies, awareness of our way of thinking, and a more communal worldview informed by a subjective epistemology and a holistic ontology

Low-level contrast statistics are diagnostic of invariance of natural textures

Texture may provide important clues for real world object and scene perception. To be reliable, these clues should ideally be invariant to common viewing variations such as changes in illumination and orientation. In a large image database of natural materials, we found textures with low-level contrast statistics that varied substantially under viewing variations, as well as textures that remained relatively constant. This led us to ask whether textures with constant contrast statistics give rise to more invariant representations compared to other textures. To test this, we selected natural texture images with either high (HV) or low (LV) variance in contrast statistics and presented these to human observers. In two distinct behavioral categorization paradigms, participants more often judged HV textures as “different” compared to LV textures, showing that textures with constant contrast statistics are perceived as being more invariant. In a separate electroencephalogram (EEG) experiment, evoked responses to single texture images (single-image ERPs) were collected. The results show that differences in contrast statistics correlated with both early and late differences in occipital ERP amplitude between individual images. Importantly, ERP differences between images of HV textures were mainly driven by illumination angle, which was not the case for LV images: there, differences were completely driven by texture membership. These converging neural and behavioral results imply that some natural textures are surprisingly invariant to illumination changes and that low-level contrast statistics are diagnostic of the extent of this invariance