Computational studies on the interaction between red cone and H1 horizontal cell

Real-time emulator for reproducing graded potentials in vertebrate retina

In most parts of the retina, neuronal circuits process visual signals represented by slowly changing membrane potentials, or so-called graded potentials. A feasible approach to speculate about the functional roles of retinal neuronal circuits is to reproduce the graded potentials of retinal neurons in response to natural scenes. In this study, we developed a simulation platform for reproducing graded potentials with the following features: real-time reproduction of retinal neural activities in response to natural scenes, a configurable model structure, and compact hardware. The spatio-temporal properties of neurons were emulated efficiently by a mixed analog-digital architecture that consisted of analog resistive networks and a field-programmable gate array. The neural activities on sustained and transient pathways were emulated from 128 × 128 inputs at 200 frames per second.

The influence of different retinal subcircuits on the nonlinearity of ganglion cell behavior

Y-type retinal ganglion cells show a pronounced, nonlinear, frequency-doubling behavior in response to modulated sinewave gratings. This is not observed in X-type cells. The source of this spatial nonlinear summation is still under debate. We have designed a realistic biophysical model of the cat retina to test the influence of different retinal cell classes and subcircuits on the linearity of ganglion cell responses. The intraretinal connectivity consists of the fundamental feedforward pathway via bipolar cells, lateral horizontal cell connectivity, and two amacrine circuits. The wiring diagram of X- and Y-cells is identical apart from two aspects: (1) Y-cells have a wider receptive field and (2) they receive input from a nested amacrine circuit consisting of narrow- and wide-field amacrine cells. The model was tested with contrast-reversed gratings. First and second harmonic response components were determined to estimate the degree of nonlinearity. By means of circuit dissection, we found that a high degree of the Y-cell nonlinear behavior arises from the spatial integration of temporal photoreceptor nonlinearities. Furthermore, we found a weaker and less uniform influence of the nested amacrine circuit. Different sources of nonlinearities interact in a multiplicative manner, and the influence of the amacrine circuit is approximately 25% weaker than that of the photoreceptor. The model predicts that significant nonlinearities occur already at the level of horizontal cell responses. Pharmacological inactivation of the amacrine circuit is expected to exert a milder effect in reducing ganglion cell nonlinearity.

Spatio-temporal receptive fields in carp retinal horizontal cells

1. The dynamics of the receptive fields of retinal horizontal cells were examined by applying a spatio-temporal modulated light signal to the retina. 2. The spatio-temporal receptive fields of both cone- and rod-driven horizontal cells, estimated through cross-correlation between the modulated light signal and the cells' responses, showed their receptive fields (the space-dependent component) to be reduced in size with time. 3. In cone-driven horizontal cells, the reduction in receptive field size was initially small but then rapidly became prominent with time. The time to peak of the time-dependent component of spatio-temporal receptive fields did not depend on the distance from the centre. 4. Application of a small amount of Co2+, an agent blocking the cone-driven horizontal cells' feedback action on cones, or GABA, resulted in a reversal of the time-dependent shrinkage of receptive fields to time-dependent expansion. 5. In rod-driven horizontal cells, the receptive field shrinkage was slow. The time to peak of the time-dependent component decreased with the distance from the centre. 6. Image processing experiments examining the response pattern in the horizontal cell layer (neural image) to a moving square of light showed smudging of the neural image when the time-dependent receptive field expansion was present, while there was essentially no smudging under conditions of receptive field shrinkage.

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.

A neural model of foveal light adaptation and afterimage formation

Psychophysical research has documented the existence of three processes in light adaptation: a fast subtractive process, a divisive process that is fast at light onset and slower at light offset, and a very slow subtractive process (Hayhoe et al., 1987). In the neural model developed here, the fast subtractive process is identified with horizontal cell feedback onto cones and the divisive process with amacrine cell feedback onto bipolar cells. The very slow subtractive process is identified with the modulatory feedback circuit from amacrines via interplexiform cells to horizontal cells. A nonlinear dynamical model is developed incorporating these aspects of retinal circuitry along with both ON- and OFF-center M and P pathways. This model is shown to account for many aspects of foveal light adaptation, including negative afterimage formation, and to explain a number of the physiological differences between M and P ganglion cells, including their differing contrast-response functions.

Modulation of horizontal cell receptive fields in the light adapted goldfish retina

In the isolated goldfish retina, 700 nm background illumination increases the horizontal cell receptive field size, as measured with 565 nm slits of light, but decreases the receptive field size, when measured with 660 nm slits. These background-induced changes in receptive field size are absent when the depolarizing responses in bi- and triphasic horizontal cells are blocked by lowering the [Ca2+] in the Ringer's solution from 1.0 to 0.1 mM. These results cannot be explained by the linear properties of the horizontal cell layers, nor by slow adaptational processes, but are consistent with the concept that feedback from horizontal cells to cones modifies the horizontal cell receptive field properties.