We see over an enormous range of mean light levels, greater than the range of output signals retinal neurons can produce. Even highlights and shadows within a single visual scene can differ approximately 10,000-fold in intensity-exceeding the range of distinct neural signals by a factor of approximately 100. The effectiveness of daylight vision under these conditions relies on at least two retinal mechanisms that adjust sensitivity in the approximately 200 ms intervals between saccades. One mechanism is in the cone photoreceptors (receptor adaptation) and the other is at a previously unknown location within the retinal circuitry that benefits from convergence of signals from multiple cones (post-receptor adaptation). Here we find that post-receptor adaptation occurs as signals are relayed from cone bipolar cells to ganglion cells. Furthermore, we find that the two adaptive mechanisms are essentially mutually exclusive: as light levels increase the main site of adaptation switches from the circuitry to the cones. These findings help explain how human cone vision encodes everyday scenes, and, more generally, how sensory systems handle the challenges posed by a diverse physical environment.

This paper offers an analysis of the recruitment and normalized power output of the slow oxidative (red) axial muscles of the carp, during swimming in two different modes. Recruitment patterns of the muscle fibres and swimming movements were measured by synchronized electromyography and cinematography. The ultrastructure of the muscle fibres along the trunk was measured by electron microscopy. Strain fluctuations and normalized power along the trunk were estimated using a model, as direct measurement was impossible. The model takes into account structural parameters of the sarcomeres, modulation of sarcomere force as a result of changing sarcomere length, modulation of cross-bridge force owing to the force-velocity relationship, and rate of tension rise and of tension decline as a result of fibre properties and stimulation. In continuous swimming, the amplitude of the fluctuations in the strain was constant along the trunk, owing to a remarkable coherence between the amplitude of body curvature and the position along the body of the red muscle fibres with respect to the vertebral column. However, the strain range and speed of contraction at which the fibres were active changed along the trunk in continuous swimming as well as in 'kick and glide swimming'. During continuous swimming, the fibres along the trunk had a period of negative active power production followed by a period ofpositive power production. Anteriorly, the positive phase was most important, with a close to optimal power production in a plateau phase, so that net positive work was produced in a swimming cycle. Posteriorly, net negative work was done. In the anal region, the amounts of positive and negative work almost balanced each other. During the first tail strike in intermittent swimming, peak positive normalized work for an activated fibre was produced in the anal region. For this initial tail strike, fast muscle fibres were calculated to work more effectively than slow fibres. Fast fibres were needed to generate kick and glide swimming.

Summary When approaching a landing surface, many flying animals use visual feedback to control their landing. Here, we studied how foraging bumblebees ( Bombus terrestris ) use radial optic expansion cues to control in-flight decelerations during landing. By analyzing the flight dynamics of 4,672 landing maneuvers, we showed that landing bumblebees exhibit a series of deceleration bouts, unlike landing honeybees that continuously decelerate. During each bout, the bumblebee keeps its relative rate of optical expansion constant, and from one bout to the next, the bumblebee tends to shift to a higher, constant relative rate of expansion. This modular landing strategy is relatively fast compared to the strategy described for honeybees and results in approach dynamics that is strikingly similar to that of pigeons and hummingbirds. The here discovered modular landing strategy of bumblebees helps explaining why these important pollinators in nature and horticulture can forage effectively in challenging conditions; moreover, it has potential for bio-inspired landing strategies in flying robots.

We have studied the effects of voluntary attention on the induction of motion aftereffects (MAEs). While adapting, observers paid attention to one of two transparently displayed random dot patterns, moving concurrently in opposite directions. Selective attention was found to modulate the susceptibility to motion adaptation very substantially. To measure the strength of the induced MAEs we modulated the signal-to-noise ratio of a real motion signal in a random dot pattern that was used to balance the aftereffect. Results obtained for adapting to single motion vectors show that the MAE can be represented as a shift of the psychometric function for motion direction discrimination. Selective attention to the different components of transparent motion altered the susceptibility to adaptation. Shifting attention from one component to the other caused a large shift of the psychometric curves, about 70-75% of the shift measured for the separate components of the transparent adapting stimulus. We conclude that attention can differentiate between spatially superimposed motion vectors and that attention modulates the activity of motion mechanisms before or at the level where adaptation gives rise to MAEs. The results are discussed in light of the role of attention in visual perception and the physiological site for attentional modulation of MAEs.

When the visual system is confronted with incompatible images in the same part of the visual field, the conscious percept switches back and forth between the rivaling stimuli. Such spontaneous flips provide important clues to the neuronal basis for visual awareness. The general idea is that two representations compete for dominance in a process of mutual inhibition, in which adaptation shifts the balance to and fro. The inherent nonlinear nature of the rivalrous flip-flop and its stochastic behavior, however, made it impossible to disentangle inhibition and adaptation. Here we report a general method to measure the time course, and asymmetries, of mechanisms involved in perceptual rivalry. Supported by model simulations, we show the dynamics of opponent interactions between mutual inhibition and adaptation. The findings not only provide new insight into the mechanism underlying rivalry but also offer new opportunities to study and compare a wide range of bistable processes in the brain and their relation to visual awareness.