Ecology: the proximate cause of frog declines?

Pounds et al. argue that global warming contributes to amphibian declines by encouraging outbreaks of the chytrid fungus Batrachochytrium dendrobatidis. Although our findings agree with the climate-linked epidemic hypothesis, this pathogen is probably not the only proximate factor in such cases: in the Trasimeno Lake area of Umbria in central Italy, for example, the water frog Rana lessonae first declined in the late 1990s, yet chytridiomycosis was not observed until 2003 (refs 5, 6). Here we show that the chytrid was common there throughout 1999-2002, in a previously unknown form that did not cause disease. We therefore think that the focus by Pounds et al. on a single pathogen is hard to justify because the host-parasite ecology is at present so poorly understood.     

Perceiving visual expansion without optic flow

When an observer moves forward in the environment, the image on his or her retina expands. The rate of this expansion conveys information about the observer's speed and the time to collision. Psychophysical and physiological studies have provided abundant evidence that these expansionary motions are processed by specialized mechanisms in mammalian visual systems. It is commonly assumed that the rate of expansion is estimated from the divergence of the optic-flow field (the two-dimensional field of local translational velocities). But this rate might also be estimated from changes in the size (or scale) of image features. To determine whether human vision uses such scale-change information, we have synthesized stochastic texture stimuli in which the scale of image elements increases gradually over time, while the optic-flow pattern is random. Here we show, using these stimuli, that observers can estimate expansion rates from scale-change information alone, and that pure scale changes can produce motion after-effects. These two findings suggest that the visual system contains mechanisms that are explicitly sensitive to changes in scale.     

Spatio-temporal correlations and visual signalling in a complete neuronal population

Statistical dependencies in the responses of sensory neurons govern both the amount of stimulus information conveyed and the means by which downstream neurons can extract it. Although a variety of measurements indicate the existence of such dependencies, their origin and importance for neural coding are poorly understood. Here we analyse the functional significance of correlated firing in a complete population of macaque parasol retinal ganglion cells using a model of multi-neuron spike responses. The model, with parameters fit directly to physiological data, simultaneously captures both the stimulus dependence and detailed spatio-temporal correlations in population responses, and provides two insights into the structure of the neural code. First, neural encoding at the population level is less noisy than one would expect from the variability of individual neurons: spike times are more precise, and can be predicted more accurately when the spiking of neighbouring neurons is taken into account. Second, correlations provide additional sensory information: optimal, model-based decoding that exploits the response correlation structure extracts 20% more information about the visual scene than decoding under the assumption of independence, and preserves 40% more visual information than optimal linear decoding. This model-based approach reveals the role of correlated activity in the retinal coding of visual stimuli, and provides a general framework for understanding the importance of correlated activity in populations of neurons.