Sluggish and brisk ganglion cells detect contrast with similar sensitivity

Coding Properties of Mouse Retinal Ganglion Cells with Dual-Peak Patterns with Respect to Stimulus Intervals

How visual information is encoded in spikes of retinal ganglion cells (RGCs) is essential in visual neuroscience. In the present study, we investigated the coding properties of mouse RGCs with dual-peak patterns with respect to visual stimulus intervals. We first analyzed the response properties, and observed that the latencies and spike counts of the two response peaks in the dual-peak pattern exhibited systematic changes with the preceding light-OFF interval. We then applied linear discriminant analysis (LDA) to assess the relative contributions of response characteristics of both peaks in information coding regarding the preceding stimulus interval. It was found that for each peak, the discrimination results were far better than chance level based on either latency or spike count, and were further improved by using the combination of the two parameters. Furthermore, the best discrimination results were obtained when latencies and spike counts of both peaks were considered in combination. In addition, the correct rate for stimulation discrimination was higher when RGC population activity was considered as compare to single neuron's activity, and the correct rate was increased with the group size. These results suggest that rate coding, temporal coding, and population coding are all involved in encoding the different stimulus-interval patterns, and the two response peaks in the dual-peak pattern carry complementary information about stimulus interval.

Frequency Responses of Rat Retinal Ganglion Cells

There are 15–20 different types of retinal ganglion cells (RGC) in the mammalian retina, each encoding different aspects of the visual scene. The mechanism by which post-synaptic signals from the retinal network generate spikes is determined by each cell’s intrinsic electrical properties. Here we investigate the frequency responses of morphologically identified rat RGCs using intracellular injection of sinusoidal current waveforms, to assess their intrinsic capabilities with minimal contributions from the retinal network. Recorded cells were classified according to their morphological characteristics (A, B, C or D-type) and their stratification (inner (i), outer (o) or bistratified) in the inner plexiform layer (IPL). Most cell types had low- or band-pass frequency responses. A2, C1 and C4o cells were band-pass with peaks of 15–30 Hz and low-pass cutoffs above 56 Hz (A2 cells) and ~42 Hz (C1 and C4o cells). A1 and C2i/o cells were low-pass with peaks of 10–15 Hz (cutoffs 19–25 Hz). Bistratified D1 and D2 cells were also low-pass with peaks of 5–10 Hz (cutoffs ~16 Hz). The least responsive cells were the B2 and C3 types (peaks: 2–5 Hz, cutoffs: 8–11 Hz). We found no difference between cells stratifying in the inner and outer IPL (i.e., ON and OFF cells) or between cells with large and small somas or dendritic fields. Intrinsic physiological properties (input resistance, spike width and sag) had little impact on frequency response at low frequencies, but account for 30–40% of response variability at frequencies >30 Hz.

Temporal properties of dual-peak responses of mouse retinal ganglion cells and effects of inhibitory pathways

Dual-peak responses of retinal ganglion cells (RGCs) are observed in various species, previous researches suggested that both response peaks were involved in retinal information coding. In the present study, we investigated the temporal properties of the dual-peak responses recorded in mouse RGCs elicited by spatially homogeneous light flashes and the effect of the inhibitory inputs mediated by GABAergic and/or glycinergic pathways. We found that the two peaks in the dual-peak responses exhibited distinct temporal dynamics, similar to that of short-latency and long-latency single-peak responses respectively. Pharmacological studies demonstrated that the application of exogenous GABA or glycine greatly suppressed or even eliminated the second peak of the cells' firing activities, while little change was induced in the first peak. Co-application of glycine and GABA led to complete elimination of the second peak. Moreover, application of picrotoxin or strychnine induced dual-peak responses in some cells with transient responses by unmasking a second response phase. These results suggest that both GABAergic and glycinergic pathways are involved in the dual-peak responses of the mouse RGCs, and the two response peaks may arise from distinct pathways that would converge on the ganglion cells.

Distinct roles for inhibition in spatial and temporal tuning of local edge detectors in the rabbit retina

This paper examines the role of inhibition in generating the receptive-field properties of local edge detector (LED) ganglion cells in the rabbit retina. We confirm that the feed-forward inhibition is largely glycinergic but, contrary to a recent report, our data demonstrate that the glycinergic inhibition contributes to temporal tuning for the OFF and ON inputs to the LEDs by delaying the onset of spiking; this delay was more pronounced for the ON inputs (∼340 ms) than the OFF inputs (∼12 ms). Blocking glycinergic transmission reduced the delay to spike onset and increased the responses to flickering stimuli at high frequencies. Analysis of the synaptic conductances indicates that glycinergic amacrine cells affect temporal tuning through both postsynaptic inhibition of the LEDs and presynaptic modulation of the bipolar cells that drive the LEDs. The results also confirm that presynaptic GABAergic transmission contributes significantly to the concentric surround antagonism in LEDs; however, unlike presumed LEDs in the mouse retina, the surround is only partly generated by spiking amacrine cells.

Cross inhibition from ON to OFF pathway improves the efficiency of contrast encoding in the mammalian retina

The retina is divided into parallel and mostly independent ON and OFF pathways, but the ON pathway "cross" inhibits the OFF pathway. Cross inhibition was thought to improve signal processing by the OFF pathway, but its effect on contrast encoding had not been tested experimentally. To quantify the effect of cross inhibition on the encoding of contrast, we presented a dark flash to an in vitro preparation of the mammalian retina. We then recorded excitatory currents, inhibitory currents, membrane voltages, and spikes from OFF α-ganglion cells. The recordings were subjected to an ideal observer analysis that used Bayesian methods to determine how accurately the recordings detected the dark flash. We found that cross inhibition increases the detection accuracy of currents and membrane voltages. Yet these improvements in encoding do not fully reach the spike train, because cross inhibition also hyperpolarizes the OFF α-cell below spike threshold, preventing small signals in the membrane voltages at low contrast from reaching the spike train. The ultimate effect of cross inhibition is to increase the accuracy with which the spike train detects moderate contrast, but reduce the accuracy with which it detects low contrast. In apparent compensation for the loss of accuracy at low contrast, cross inhibition, by hyperpolarizing the OFF α-cell, reduces the number of spikes required to detect the dark flash and thereby increases encoding efficiency.

Retinal synaptic pathways underlying the response of the rabbit local edge detector

We studied the circuitry that underlies the behavior of the local edge detector (LED) retinal ganglion cell in rabbit by measuring the spatial and temporal properties of excitatory and inhibitory currents under whole cell voltage clamp. Previous work showed that LED excitation is suppressed by activity in the surround. However, the contributions of outer and inner retina to this characteristic and the neurotransmitters used are currently unknown. Blockage of retinal inhibitory pathways (GABA(A), GABA(C), and glycine) eliminated edge selectivity. Inverting gratings in the surround with 50-microm stripe sizes did not stimulate horizontal cells, but suppressed on and off excitation by roughly 60%, indicating inhibition of bipolar terminals (feedback inhibition). On pharmacologic blockage, we showed that feedback inhibition used both GABA(A) and GABA(C) receptors, but not glycine. Glycinergic inhibition suppressed GABAergic feedback inhibition in the center, enabling larger excitatory currents in response to luminance changes. Excitation, feedback inhibition, and direct (feedforward) inhibition responded to luminance-neutral flipping gratings of 20- to 50-microm widths, showing they are driven by independent subunits within their receptive fields, which confers sensitivity to borders between areas of texture and nontexture. Feedforward inhibition was glycinergic, its rise time was faster than decay time, and did not function to delay spiking at the onset of a stimulus. Both the on and off phases could be triggered by luminance shifts as short in duration as 33 ms and could be triggered during scenes that already produced a high baseline level of feedforward inhibition. Our results show how LED circuitry can use subreceptive field sensitivity to detect visual edges via the interaction between excitation and feedback inhibition and also respond to rapid luminance shifts within a rapidly changing scene by producing feedforward inhibition.

Receptive fields and functional architecture in the retina

Functional architecture of the striate cortex is known mostly at the tissue level--how neurons of different function distribute across its depth and surface on a scale of millimetres. But explanations for its design--why it is just so--need to be addressed at the synaptic level, a much finer scale where the basic description is still lacking. Functional architecture of the retina is known from the scale of millimetres down to nanometres, so we have sought explanations for various aspects of its design. Here we review several aspects of the retina's functional architecture and find that all seem governed by a single principle: represent the most information for the least cost in space and energy. Specifically: (i) why are OFF ganglion cells more numerous than ON cells? Because natural scenes contain more negative than positive contrasts, and the retina matches its neural resources to represent them equally well; (ii) why do ganglion cells of a given type overlap their dendrites to achieve 3-fold coverage? Because this maximizes total information represented by the array--balancing signal-to-noise improvement against increased redundancy; (iii) why do ganglion cells form multiple arrays? Because this allows most information to be sent at lower rates, decreasing the space and energy costs for sending a given amount of information. This broad principle, operating at higher levels, probably contributes to the brain's immense computational efficiency.

Loss of sensitivity in an analog neural circuit

A low-contrast spot that activates just one ganglion cell in the retina is detected in the spike train of the cell with about the same sensitivity as it is detected behaviorally. This is consistent with Barlow's proposal that the ganglion cell and later stages of spiking neurons transfer information essentially without loss. Yet, when losses of sensitivity by all preneural factors are accounted for, predicted sensitivity near threshold is considerably greater than behavioral sensitivity, implying that somewhere in the brain information is lost. We hypothesized that the losses occur mainly in the retina, where graded signals are processed by analog circuits that transfer information at high rates and low metabolic cost. To test this, we constructed a model that included all preneural losses for an in vitro mammalian retina, and evaluated the model to predict sensitivity at the cone output. Recording graded responses postsynaptic to the cones (from the type A horizontal cell) and comparing to predicted preneural sensitivity, we found substantial loss of sensitivity (4.2-fold) across the first visual synapse. Recording spike responses from brisk-transient ganglion cells stimulated with the same spot, we found a similar loss (3.5-fold) across the second synapse. The total retinal loss approximated the known overall loss, supporting the hypothesis that from stimulus to perception, most loss near threshold is retinal.

Different types of ganglion cell share a synaptic pattern

Retinal ganglion cells comprise about 10 morphological types that also differ functionally. To determine whether functional differences might arise partially from differences in excitatory input, we quantified the distributions of ribbon contacts to four mammalian ganglion cell types [brisk-transient (BT), brisk-sustained (BS), local edge (LE), directionally selective (DS)], comparing small vs. large and "sluggish" vs. "brisk." Cells in guinea pig retina were filled with fluorescent dye, immunostained for synaptic ribbons, and reconstructed with their ribbon contacts by confocal microscopy. False-positive contacts were corrected by performing the same analysis on processes that lack synapses: glial stalks and rod bipolar axons. All types shared a domed distribution of membrane that was well fit by a Gaussian function (R(2) = 0.96 +/- 0.01); they also shared a constant density of contacts on the dendritic membrane, both across each arbor and across cell types (19 +/- 1 contacts/100 microm(2) membrane). However, the distributions of membrane across the retina differed markedly in width (BT > DS approximately BS > LE) and peak density (BS > DS > LE > BT). Correspondingly, types differed in peak density of contacts (BS > DS approximately LE > BT) and total number (BS approximately BT > DS > LE). These differences between cell types in spatial extent and local concentration of membrane and synapses help to explain certain functional differences.

Microcircuitry for two types of achromatic ganglion cell in primate fovea

Synaptic circuits in primate fovea have been quantified for midget/parvocellular ganglion cells. Here, based on partial reconstructions from serial electron micrographs, we quantify synaptic circuits for two other types of ganglion cell: the familiar parasol/magnocellular cell and a smaller type, termed "garland." The excitatory circuits both derive from two types of OFF diffuse cone bipolar cell, DB3 and DB2, which collected unselectively from at least 6 +/- 1 cones, including the S type. Cone contacts to DB3 dendrites were usually located between neighboring triads, whereas half of the cone contacts to DB2 were triad associated. Ribbon outputs were as follows: DB3, 69 +/- 5; DB2, 48 +/- 4. A complete parasol cell (30 microm dendritic field diameter) would collect from approximately 50 cones via approximately 120 bipolar and approximately 85 amacrine contacts; a complete garland cell (25 microm dendritic field) would collect from approximately 40 cones via approximately 75 bipolar and approximately 145 amacrine contacts. The bipolar types contributed differently: the parasol cell received most contacts (60%) from DB3, whereas the garland cell received most contacts (67%) from DB2. We hypothesize that DB3 is a transient bipolar cell and that DB2 is sustained. This would be consistent with their relative inputs to the brisk-transient (parasol) ganglion cell. The garland cell, with its high proportion of DB2 inputs plus its high proportion of amacrine synapses (70%) and dense mosaic, might correspond to the local-edge cell in nonprimate retinas, which serves finer acuity at low temporal frequencies. The convergence of S cones onto both types could contribute S-cone input for cortical areas primary visual cortex and the middle temporal area.

Local edge detectors: a substrate for fine spatial vision at low temporal frequencies in rabbit retina

Visual acuity is limited by the size and density of the smallest retinal ganglion cells, which correspond to the midget ganglion cells in primate retina and the beta-ganglion cells in cat retina, both of which have concentric receptive fields that respond at either light-On or light-Off. In contrast, the smallest ganglion cells in the rabbit retina are the local edge detectors (LEDs), which respond to spot illumination at both light-On and light-Off. However, the LEDs do not predominate in the rabbit retina and the question arises, what role do they play in fine spatial vision? We studied the morphology and physiology of LEDs in the isolated rabbit retina and examined how their response properties are shaped by the excitatory and inhibitory inputs. Although the LEDs comprise only approximately 15% of the ganglion cells, neighboring LEDs are separated by 30-40 microm on the visual streak, which is sufficient to account for the grating acuity of the rabbit. The spatial and temporal receptive-field properties of LEDs are generated by distinct inhibitory mechanisms. The strong inhibitory surround acts presynaptically to suppress both the excitation and the inhibition elicited by center stimulation. The temporal properties, characterized by sluggish onset, sustained firing, and low bandwidth, are mediated by the temporal properties of the bipolar cells and by postsynaptic interactions between the excitatory and inhibitory inputs. We propose that the LEDs signal fine spatial detail during visual fixation, when high temporal frequencies are minimal.

How much the eye tells the brain

In the classic "What the frog's eye tells the frog's brain," Lettvin and colleagues showed that different types of retinal ganglion cell send specific kinds of information. For example, one type responds best to a dark, convex form moving centripetally (a fly). Here we consider a complementary question: how much information does the retina send and how is it apportioned among different cell types? Recording from guinea pig retina on a multi-electrode array and presenting various types of motion in natural scenes, we measured information rates for seven types of ganglion cell. Mean rates varied across cell types (6-13 bits . s(-1)) more than across stimuli. Sluggish cells transmitted information at lower rates than brisk cells, but because of trade-offs between noise and temporal correlation, all types had the same coding efficiency. Calculating the proportions of each cell type from receptive field size and coverage factor, we conclude (assuming independence) that the approximately 10(5) ganglion cells transmit on the order of 875,000 bits . s(-1). Because sluggish cells are equally efficient but more numerous, they account for most of the information. With approximately 10(6) ganglion cells, the human retina would transmit data at roughly the rate of an Ethernet connection.

Voltage-gated sodium channels improve contrast sensitivity of a retinal ganglion cell

Voltage-gated channels in a retinal ganglion cell are necessary for spike generation. However, they also add noise to the graded potential and spike train of the ganglion cell, which may degrade its contrast sensitivity, and they may also amplify the graded potential signal. We studied the effect of blocking Na+ channels in a ganglion cell on its signal and noise amplitudes and its contrast sensitivity. A spot was flashed at 1-4 Hz over the receptive field center of a brisk transient ganglion cell in an intact mammalian retina maintained in vitro. We measured signal and noise amplitudes from its intracellularly recorded graded potential light response and measured its contrast detection thresholds with an "ideal observer." When Na+ channels in the ganglion cell were blocked with intracellular lidocaine N-ethyl bromide (QX-314), the signal-to-noise ratio (SNR) decreased (p < 0.05) at all tested contrasts (2-100%). Likewise, bath application of tetrodotoxin (TTX) reduced the SNR and contrast sensitivity but only at lower contrasts (< or = 50%), whereas at higher contrasts, it increased the SNR and sensitivity. The opposite effect of TTX at high contrasts suggested involvement of an inhibitory surround mechanism in the inner retina. To test this hypothesis, we blocked glycinergic and GABAergic inputs with strychnine and picrotoxin and found that TTX in this case had the same effect as QX-314: a reduction in the SNR at all contrasts. Noise analysis suggested that blocking Na+ channels with QX-314 or TTX attenuates the amplitude of quantal synaptic voltages. These results demonstrate that Na+ channels in a ganglion cell amplify the synaptic voltage, enhancing the SNR and contrast sensitivity.