Melanopsin cells are the principal conduits for rod-cone input to non-image-forming vision

Rod and cone photoreceptors detect light and relay this information through a multisynaptic pathway to the brain by means of retinal ganglion cells (RGCs). These retinal outputs support not only pattern vision but also non-image-forming (NIF) functions, which include circadian photoentrainment and pupillary light reflex (PLR). In mammals, NIF functions are mediated by rods, cones and the melanopsin-containing intrinsically photosensitive retinal ganglion cells (ipRGCs). Rod-cone photoreceptors and ipRGCs are complementary in signalling light intensity for NIF functions. The ipRGCs, in addition to being directly photosensitive, also receive synaptic input from rod-cone networks. To determine how the ipRGCs relay rod-cone light information for both image-forming and non-image-forming functions, we genetically ablated ipRGCs in mice. Here we show that animals lacking ipRGCs retain pattern vision but have deficits in both PLR and circadian photoentrainment that are more extensive than those observed in melanopsin knockouts. The defects in PLR and photoentrainment resemble those observed in animals that lack phototransduction in all three photoreceptor classes. These results indicate that light signals for irradiance detection are dissociated from pattern vision at the retinal ganglion cell level, and animals that cannot detect light for NIF functions are still capable of image formation.     

Modeling and simulation of the vulnerability of interdependent power-water infrastructure networks to cascading failures

Critical infrastructures are becoming increasingly interdependent and vulnerable to cascading failures. Existing studies have analyzed the vulnerability of interdependent networks to cascading failures from the static perspective of network topology structure. This paper develops a more realistic cascading failures model that considers the dynamic redistribution of load in power network to explore the vulnerability of interdependent power-water networks. In this model, the critical tolerance threshold is originally proposed to indicate the vulnerability of network to cascading failures. In addition, some key parameters that are important to network vulnerability are identified and quantified through numerical simulation. Results show that cascading failures can be prevented when the values of tolerance parameter are above a critical tolerance threshold. Otherwise interdependent networks collapse after attacking a critical fraction of power nodes. Interdependent networks become more vulnerable with the increase in interdependence strength, which implies the importance of protecting those interconnected nodes to reduce the consequences of cascading failures. Interdependent networks are most vulnerable under high-load attack, which shows the significance of protecting high-load nodes.