Segregation of object and background motion in the retina

An important task in vision is to detect objects moving within a stationary scene. During normal viewing this is complicated by the presence of eye movements that continually scan the image across the retina, even during fixation. To detect moving objects, the brain must distinguish local motion within the scene from the global retinal image drift due to fixational eye movements. We have found that this process begins in the retina: a subset of retinal ganglion cells responds to motion in the receptive field centre, but only if the wider surround moves with a different trajectory. This selectivity for differential motion is independent of direction, and can be explained by a model of retinal circuitry that invokes pooling over nonlinear interneurons. The suppression by global image motion is probably mediated by polyaxonal, wide-field amacrine cells with transient responses. We show how a population of ganglion cells selective for differential motion can rapidly flag moving objects, and even segregate multiple moving objects

Reconnecting with nature for sustainability

Calls for humanity to ‘reconnect to nature’ have grown increasingly louder from both scholars and civil society. Yet, there is relatively little coherence about what reconnecting to nature means, why it should happen and how it can be achieved. We present a conceptual framework to organise existing literature and direct future research on human–nature connections. Five types of connections to nature are identified: material, experiential, cognitive, emotional, and philosophical. These various types have been presented as causes, consequences, or treatments of social and environmental problems. From this conceptual base, we discuss how reconnecting people with nature can function as a treatment for the global environmental crisis. Adopting a social–ecological systems perspective, we draw upon the emerging concept of ‘leverage points’—places in complex systems to intervene to generate change—and explore examples of how actions to reconnect people with nature can help transform society towards sustainability

Sleep and immune function

Sleep and the circadian system exert a strong regulatory influence on immune functions. Investigations of the normal sleep–wake cycle showed that immune parameters like numbers of undifferentiated naïve T cells and the production of pro-inflammatory cytokines exhibit peaks during early nocturnal sleep whereas circulating numbers of immune cells with immediate effector functions, like cytotoxic natural killer cells, as well as anti-inflammatory cytokine activity peak during daytime wakefulness. Although it is difficult to entirely dissect the influence of sleep from that of the circadian rhythm, comparisons of the effects of nocturnal sleep with those of 24-h periods of wakefulness suggest that sleep facilitates the extravasation of T cells and their possible redistribution to lymph nodes. Moreover, such studies revealed a selectively enhancing influence of sleep on cytokines promoting the interaction between antigen presenting cells and T helper cells, like interleukin-12. Sleep on the night after experimental vaccinations against hepatitis A produced a strong and persistent increase in the number of antigen-specific Th cells and antibody titres. Together these findings indicate a specific role of sleep in the formation of immunological memory. This role appears to be associated in particular with the stage of slow wave sleep and the accompanying pro-inflammatory endocrine milieu that is hallmarked by high growth hormone and prolactin levels and low cortisol and catecholamine concentrations

Pt and CoB trilayer Josephson π junctions with perpendicular magnetic anisotropy

We report on the electrical transport properties of Nb based Josephson junctions with Pt/Co68B32/Pt ferromagnetic barriers. The barriers exhibit perpendicular magnetic anisotropy, which has the main advantage for potential applications over magnetisation in-plane systems of not affecting the Fraunhofer response of the junction. In addition, we report that there is no magnetic dead layer at the Pt/Co68B32 interfaces, allowing us to study barriers with ultra-thin Co68B32. In the junctions, we observe that the magnitude of the critical current oscillates with increasing thickness of the Co68B32 strong ferromagnetic alloy layer. The oscillations are attributed to the ground state phase difference across the junctions being modified from zero to π. The multiple oscillations in the thickness range 0.2 ⩽ dCoB ⩽ 1.4 nm suggests that we have access to the first zero-π and π-zero phase transitions. Our results fuel the development of low-temperature memory devices based on ferromagnetic Josephson junctions

Recurrent network dynamics reconciles visual motion segmentation and integration

In sensory systems, a range of computational rules are presumed to be implemented by neuronal subpopulations with different tuning functions. For instance, in primate cortical area MT, different classes of direction-selective cells have been identified and related either to motion integration, segmentation or transparency. Still, how such different tuning properties are constructed is unclear. The dominant theoretical viewpoint based on a linear-nonlinear feed-forward cascade does not account for their complex temporal dynamics and their versatility when facing different input statistics. Here, we demonstrate that a recurrent network model of visual motion processing can reconcile these different properties. Using a ring network, we show how excitatory and inhibitory interactions can implement different computational rules such as vector averaging, winner-take-all or superposition. The model also captures ordered temporal transitions between these behaviors. In particular, depending on the inhibition regime the network can switch from motion integration to segmentation, thus being able to compute either a single pattern motion or to superpose multiple inputs as in motion transparency. We thus demonstrate that recurrent architectures can adaptively give rise to different cortical computational regimes depending upon the input statistics, from sensory flow integration to segmentation