Light adaptation in cone vision involves switching between receptor and post-receptor sites

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.     

Noise correlations improve response fidelity and stimulus encoding

Computation in the nervous system often relies on the integration of signals from parallel circuits with different functional properties. Correlated noise in these inputs can, in principle, have diverse and dramatic effects on the reliability of the resulting computations. Such theoretical predictions have rarely been tested experimentally because of a scarcity of preparations that permit measurement of both the covariation of a neuron's input signals and the effect on a cell's output of manipulating such covariation. Here we introduce a method to measure covariation of the excitatory and inhibitory inputs a cell receives. This method revealed strong correlated noise in the inputs to two types of retinal ganglion cell. Eliminating correlated noise without changing other input properties substantially decreased the accuracy with which a cell's spike outputs encoded light inputs. Thus, covariation of excitatory and inhibitory inputs can be a critical determinant of the reliability of neural coding and computation.     

No cold dust within the supernova remnant Cassiopeia A

A large amount (about three solar masses) of cold (18 K) dust in the prototypical type II supernova remnant Cassiopeia A was recently reported. It was concluded that dust production in type II supernovae can explain how the large quantities (approximately 10(8) solar masses) of dust observed in the most distant quasars could have been produced within only 700 million years after the Big Bang. Foreground clouds of interstellar material, however, complicate the interpretation of the earlier submillimetre observations of Cas A. Here we report far-infrared and molecular line observations that demonstrate that most of the detected submillimetre emission originates from interstellar dust in a molecular cloud complex located in the line of sight between the Earth and Cas A, and is therefore not associated with the remnant. The argument that type II supernovae produce copious amounts of dust is not supported by the case of Cas A, which previously appeared to provide the best evidence for this possibility.