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A retinal ganglion cell receptive field is made up of an excitatory center and an inhibitory surround. The surround has two components: one driven by horizontal cells at the first synaptic layer and one driven by amacrine cells at the second synaptic layer. Here we characterized how amacrine cells inhibit the center response of on- and off-center Y-type ganglion cells in the in vitro guinea pig retina. A high spatial frequency grating (4-5 cyc/mm), beyond the spatial resolution of horizontal cells, drifted in the ganglion cell receptive field periphery to stimulate amacrine cells. The peripheral grating suppressed the ganglion cell spiking response to a central spot. Suppression of spiking was strongest and observed most consistently in off cells. In intracellular recordings, the grating suppressed the subthreshold membrane potential in two ways: a reduced slope (gain) of the stimulus-response curve by approximately 20-30% and, in off cells, a tonic approximately 1-mV hyperpolarization. In voltage clamp, the grating increased an inhibitory conductance in all cells and simultaneously decreased an excitatory conductance in off cells. To determine whether center response inhibition was presynaptic or postsynaptic (shunting), we measured center response gain under voltage-clamp and current-clamp conditions. Under both conditions, the peripheral grating reduced center response gain similarly. This result suggests that reduced gain in the ganglion cell subthreshold center response reflects inhibition of presynaptic bipolar terminals. Thus amacrine cells suppressed ganglion cell center response gain primarily by inhibiting bipolar cell glutamate release.

Under normal viewing conditions, retinal ganglion cells transmit to the brain an encoded version of the visual world. The retina parcels the visual scene into an array of spatiotemporal features, and each ganglion cell conveys information about a small set of these features. We study the temporal features represented by salamander retinal ganglion cells by stimulating with dynamic spatially uniform flicker and recording responses using a multi-electrode array. While standard reverse correlation methods determine a single stimulus feature—the spike-triggered average—multiple features can be relevant to spike generation. We apply covariance analysis to determine the set of features to which each ganglion cell is sensitive. Using this approach, we found that salamander ganglion cells represent a rich vocabulary of different features of a temporally modulated visual stimulus. Individual ganglion cells were sensitive to at least two and sometimes as many as six features in the stimulus. While a fraction of the cells can be described by a filter-and-fire cascade model, many cells have feature selectivity that has not previously been reported. These reverse models were able to account for 80–100% of the information encoded by ganglion cells.

Our goal was to understand how patterns of excitation and inhibition, interacting across arrays of ganglion cells in space and time, generate the spiking output pattern for each ganglion cell type. We presented the retina with a 1-s flashed square, 600 μm on a side, and measured patterns of excitation and inhibition over an 1,800-μm–wide region encompassing many ganglion cells. Excitatory patterns of on ganglion cells resembled rectified versions of the voltage patterns of on bipolar cells. Inhibitory patterns in on ganglion cells resembled the rectified versions of voltage patterns of off bipolar cells. off ganglion cells received off excitation and on inhibition. Many ganglion cells also received an additional wide field transient inhibition derived from the activity of both on and off bipolar cells. Ganglion cell spiking was suppressed in those space-time regions dominated by inhibition. We classified each ganglion cell type by correlating its space-time patterns with its dendritic morphology. These studies suggest the bipolar and amacrine cell circuitry underlying the interplay between on and off signals that generate spiking patterns in ganglion cells. They reveal a surprising synergistic interaction between excitation and inhibition in most ganglion cells.

Recently, we reported a novel technique for recording all of the ganglion cells in a retinal patch and showed that their receptive fields cover visual space roughly 60 times over in the tiger salamander. Here, we carry this analysis further and divide the population of ganglion cells into functional classes using quantitative clustering algorithms that combine several response characteristics. Using only the receptive field to classify ganglion cells revealed six cell types, in agreement with anatomical studies. Adding other response measures served to blur the distinctions between these cell types rather than resolve further classes. Only the biphasic off type had receptive fields that tiled the retina. Even when we attempted to split these classes more finely, ganglion cells with almost identical functional properties were found to have strongly overlapping spatial receptive fields. A territorial spatial organization, where ganglion cell receptive fields tend to avoid those of other cells of the same type, was only found for the biphasic off cell. We further studied the functional segregation of the ganglion cell population by computing the amount of visual information shared between pairs of cells under natural movie stimulation. This analysis revealed an extensive mixing of visual information among cells of different functional type. Together, our results indicate that the salamander retina uses a population code in which every point in visual space is represented by multiple neurons with subtly different visual sensitivities.

Retinal ganglion cells and their target neurons in the principal layers of the lateral geniculate nucleus (LGN) of the thalamus have very similar, center-surround receptive fields. Although some geniculate neurons are dominated by a single retinal afferent, others receive both strong and weak inputs from several retinal afferents. In the present study, experiments were performed in the cat that examined the specificity and strength of monosynaptic connections between retinal ganglion cells and their target neurons. The responses of 205 pairs of retinal ganglion cells and geniculate neurons with overlapping receptive-field centers or surrounds were studied. Receptive fields were mapped quantitatively using a white-noise stimulus; connectivity was assessed by cross-correlating the retinal and geniculate spike trains. Of the 205 pairs, 12 were determined to have monosynaptic connections. Both the likelihood that cells were connected and the strength of connections increased with increasing similarity between retinal and geniculate receptive fields. Connections were never found between cells with

Magnocellular (M-), but not parvocellular (P-), neurons of the macaque lateral geniculate nucleus (LGN) differ distinctively in their responses to counterphase-modulated and drifting gratings. Relative to stimulation with drifting gratings, counterphase modulation reduces the responses of M- cells in a band around 25 Hz, producing a “notch” in the temporal modulation transfer function (tMTF). The notch is prominent in nearly every M- cell with little variation in the temporal frequency at which it is deepest. The machinery responsible for the notch lies mostly outside the classical linear center. Directly driving the notching mechanism with annular gratings evokes no linear response but elicits a second harmonic (F2) modulation of the discharge accompanied by a drop in the mean discharge (F0). Analysis of the S- potential, which reveals inputs from ganglion cells, shows that 1) tMTFs of the afferent retinal ganglion cells are not notched and 2) during stimulation with annular gratings, the second harmonic component is present, but the drop in the F0 is largely absent from the responses of parasol ganglion cells. These results suggest that the notch is caused by the combined action of the linear response and the second harmonic response, both inherited from retina, and a suppression that originates after the retina. Our results reveal a distinctive signal transformation in the LGN and they show that nearly every M- cell exhibits a spatial nonlinearity like that observed in Y cells of the cat.

The function of a neuron is usually understood to be a consequence of the pattern of its synaptic inputs. The well-studied retinal ganglion cells in the monkey's retina are examples of this principle. Many of the retinal ganglion cells in the monkey's retina will give different signed responses to