Signal sampling and propagation through multiple cell layers in the retina: modeling and analysis with multirate filtering

Evidence for spatial aliasing effects in the Y-like cells of the magnocellular visual pathway

Several lines of evidence are provided indicating that our visual percept can be dominated by spatial aliasing for viewing conditions near those needed to see the spatial frequency doubled illusion. The apparent aliasing effect indicates that the underlying sampling array has a density 15-30% of that of M-cells, in agreement with the known proportion of Y-like M-cells (M(y)-cells). The presence of aliasing indicates, that there is a separate irregular array of M(y)-cells, and that their role is to rapidly convey information on retinal gain control to the brain rather than to act primarily as inputs to image motion computation.

Syncytial integration by a network of coupled bipolar cells in the retina

A model system for syncytial integration is the outer vertebrate retina, where graded signals or electrotonic potentials interact laterally via gap junctions to form an integrated response that is relayed by chemical synapses to the next layer of interconnected cells. Morphological and physiological experiments confirm that bipolar cells form quasisyncytial lattices, and so this review will aim to address two important issues: the function of coupling in visual information processing and the construction of a robust mathematical model that can adequately simulate signal spread in the bipolar cell syncytium. It is shown that the role of coupling in bipolar cells differs from that associated in the presynaptic networks, namely, loss in spatial resolution in order to increase the signal-to-noise ratio. The intrinsic membrane properties of bipolar cells which give rise to voltage-dependent currents are inactive over the normal in vivo operating range of membrane potential and may be shunted as a direct result of electrotonic coupling, suppressing any possibility of action potential propagation in the bipolar cell syncytium. It is therefore speculated that the mechanisms underlying processing of information in bipolar networks are dependent on the structure of bipolar cells and in particular, on the presence of gap junctions. It is proposed that a three-dimensional model which incorporates the spatial properties of each bipolar cell in the network in the form of a leaky cable is the most likely model to simulate signal spread in the bipolar cell syncytium in vivo. This is because discrete network models represent each bipolar cell in the syncytium as isopotential units without any spatial structure, and thus are unable to reproduce the temporal characteristics of electrotonic potential spread within the central receptive field of bipolar cells.

Parallel cone bipolar to on-beta ganglion cell pathways in the cat retina: spatial responses, spatial aliasing, and spatial variance

An important issue in understanding the retina is finding candidate functional roles for different cell pathways and the details of their anatomy and physiology. We consider various spatial properties of the three main cone ==> cone bipolar cell ==> on-beta ganglion cell pathways in the cat retina and possible roles for the particulars of their anatomy. The cone bipolar cells in these pathways have distinct morphologies and modest differences in their convergence, divergence, densities, and synaptic weighting; and it is unclear whether the pathways differ in their spatial properties or in some other manner. Since differences in spatial processing of cells are best studied on a systemwide level, we developed the multirate filter-based method of retinal modeling, a technique for relating the anatomy of multiple cell layers to its systemic effects. We demonstrate that (1) despite the anatomic distinctions among the three main cone bipolar cell pathways, their spatial responses are essentially identical; (2) despite the spatial averaging in the pathways, there is essentially no filtering of the nonaliasing signal components after the cone layer; (3) instead, this averaging combined with prefiltering by the eye's optics and cone gap junctions prevents spatial aliasing; and (4) the averaging and prefiltering combined allow cell responses to be similar despite significant cell-to-cell anatomic differences.

Simulation of an anatomically defined local circuit: the cone-horizontal cell network in cat retina

The outer plexiform layer of the retina contains a neural circuit in which cone synaptic terminals are electrically coupled and release glutamate onto wide-field and narrow-field horizontal cells. These are also electrically coupled and feed back through a GABAergic synapse to cones. In cat this circuit's structure is known in some detail, and much of the chemical architecture and neural responses are also known, yet there has been no attempt to synthesize this knowledge. We constructed a large-scale compartmental model (up to 50,000 compartments) to incorporate the known anatomical and biophysical facts. The goal was to discover how the various circuit components interact to form the cone receptive field, and thereby what possible function is implied. The simulation reproduced many features known from intracellular recordings: (1) linear response of cone and horizontal cell to intensity, (2) some aspects of temporal responses of cone and horizontal cell, (3) broad receptive field of the wide-field horizontal cell, and (4) center-surround cone receptive field (derived from a "deconvolution model"). With the network calibrated in this manner, we determined which of its features are necessary to give the cone receptive field a Gaussian center-surround shape. A Gaussian-like center that matches the center derived from the ganglion cell requires both optical blur and cone coupling: blur alone is too narrow, coupling alone gives an exponential shape without a central dome-shaped peak. A Gaussian-like surround requires both types of horizontal cell: the narrow-field type for the deep, proximal region and the wide-field type for the shallow, distal region. These results suggest that the function of the cone-horizontal cell circuit is to reduce the influence of noise by spatio-temporally filtering the cone signal before it passes through the first chemical synapse on the pathway to the brain.