Current understanding of many neural circuits is limited by our ability to explore the vast number of potential interactions between different cells. We present a new approach that dramatically reduces the complexity of this problem. Large-scale multi-electrode recordings were used to measure electrical activity in nearly complete, regularly spaced mosaics of several hundred ON and OFF parasol retinal ganglion cells in macaque monkey retina. Parasol cells exhibited substantial pairwise correlations, as has been observed in other species, indicating functional connectivity. However, pairwise measurements alone are insufficient to determine the prevalence of multi-neuron firing patterns, which would be predicted from widely diverging common inputs and have been hypothesized to convey distinct visual messages to the brain. The number of possible multi-neuron firing patterns is far too large to study exhaustively, but this problem may be circumvented if two simple rules of connectivity can be established: (1) multi-cell firing patterns arise from multiple pairwise interactions, and (2) interactions are limited to adjacent cells in the mosaic. Using maximum entropy methods from statistical mechanics, we show that pairwise and adjacent interactions accurately accounted for the structure and prevalence of multi-neuron firing patterns, explaining ϳ98% of the departures from statistical independence in parasol cells and ϳ99% of the departures that were reproducible in repeated measurements. This approach provides a way to define limits on the complexity of network interactions and thus may be relevant for probing the function of many neural circuits.

We investigated the impact of rod-bipolar signal transfer on visual sensitivity. Two observations indicate that rod-rod bipolar signal transfer is nonlinear. First, responses of rods increased linearly with flash strength, while those of rod bipolars increased supralinearly. Second, fluctuations in the responses of rod bipolars were larger than expected from linear summation of the rod inputs. Rod-OFF bipolar signal transfer did not share this strong nonlinearity. Surprisingly, nonlinear rod-rod bipolar signal transfer eliminated many of the rod's single-photon responses. The impact on sensitivity, however, was more than compensated for by rejection of noise from rods that did not absorb photons. As a consequence, rod bipolars provide a near-optimal readout of rod signals at light levels near visual threshold.

To understand a neural circuit requires knowing its connectivity. This paper reports measurements of functional connectivity between the input and ouput layers of the retina at single cell resolution and its implications for color vision. Multi-electrode technology was employed to record simultaneously from complete populations of the retinal ganglion cell types (midget, parasol, small bistratified) that transmit high-resolution visual signals to the brain. Fine-grained visual stimulation was used to identify the location, type and strength of the functional input of each cone photoreceptor to each ganglion cell. The populations of ON and OFF midget and parasol cells each sampled the complete population of long and middle wavelength sensitive cones. However, only OFF midget cells frequently received strong input from short wavelength sensitive cones. ON and OFF midget cells exhibited a small non-random tendency to selectively sample from either long or middle wavelength sensitive cones, to a degree not explained by clumping in the cone mosaic. These measurements reveal computations in a neural circuit at the elementary resolution of individual neurons.Color vision requires neural circuitry to compare signals from spectrally distinct cone types. For example, the signature of primate color vision -red-green and blue-yellow color opponency -implies that neural circuits pit signals from different cone types against one another. However, the pattern of connectivity between the (L)ong, (M)iddle, and (S)hort Users may view, print, copy, download and text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms Contact: E.J. Chichilnisky, Systems Neurobiology, The Salk Institute, 10010 North Torrey Pines Road, La Jolla, CA 92037, USA. ej@salk.edu, phone: (858) 453-4100 x1286. * Equal contributionsAuthor Contributions: G.D.F., J.L.G., A.S., and E.J.C. conceived the experiments. G.D.F., J.L.G., A.S., M.G., J.S., and E.J.C. performed the electrophysiological experiments. G.D.F, J.L.G., A.S., M.G., T.A.M., and L.P., analyzed the data. A.S., D.E.G., K.M., W.D., A.M.L. provided and supported the large-scale multielectrode array system. G.D.F. and E.J.C. wrote the manuscript. To resolve the fine structure of RFs, stimuli with 10-fold smaller pixels (5×5 μm) were used. At this resolution, RFs did not conform to the smooth Gaussian approximation used in Fig. 1a (center) and in previous studies 18 . Instead, each RF was composed of punctate islands of light sensitivity (Fig. 1a, flanking). The separation between islands was roughly equal to the spacing of the cone lattice, consistent with the idea that each island reflected the contribution of a single cone 10 , 19 . To test this hypothesis, locations of islands were compared to photographs of cone outer segments labeled with peanut agglutinin; a close alignment was observed (Fig. 1b, see Supplementary Methods). HHS Public AccessTh...

The function of any neural circuit is governed by connectivity of neurons in the circuit and the computations performed by the neurons. Recent research on retinal function has substantially advanced understanding in both areas. First, visual information is transmitted to the brain by at least 17 distinct retinal ganglion cell types defined by characteristic morphology, light response properties, and central projections. These findings provide a much more accurate view of the parallel visual pathways emanating from the retina than do previous models, and they highlight the importance of identifying distinct cell types and their connectivity in other neural circuits. Second, encoding of visual information involves significant temporal structure and interactions in the spike trains of retinal neurons. The functional importance of this structure is revealed by computational analysis of encoding and decoding, an approach that may be applicable to understanding the function of other neural circuits.

No abstract