Detection sensitivity and temporal resolution of visual signals near absolute threshold in the salamander retina

Abstract

Several studies have suggested that the visual system can detect dim lights with a fidelity limited only by Poisson fluctuations in photon absorption and spontaneous activation of rhodopsin. If correct, this implies that neural processing of responses produced by rod photoreceptors is efficient and effectively noiseless. However, experimental uncertainty makes this conclusion tenuous. Furthermore, previous work provided no information about how accurately stimulus timing is represented. Here, the detection sensitivity and temporal resolution of salamander rods and retinal ganglion cells (RGCs) are compared in nearly matched experimental conditions by using recorded responses to identify the time of a flash. At detection threshold, RGCs could reliably signal the absorption of 20-50 photons, but the rods within the RGC receptive field could signal stimuli 3-10 times weaker. For flash strengths 10 times higher than detection threshold, some RGCs could distinguish stimulus timing with a resolution finer than 100 msec, within a factor of 2 of the rod limit. The relationship between RGC and rod sensitivity could not be explained by added noise in the retinal circuitry but could be explained by a threshold acting after pooling of rod signals. Simulations of rod signals indicated that continuous noise, rather than spontaneous activation of rhodopsin or fluctuations in the single-photon response, limited temporal resolution. Thus, detection of dim lights was limited by retinal processing, but, at higher light levels, synaptic transmission, cellular integration of synaptic inputs, and spike generation in RGCs faithfully conveyed information about the time of photon absorption.

Figure 8.

Summary of RGC sensitivity relative to rod limit. A-E, Each panel shows discrimination contours for all ON (red) and OFF (black) RGCs recorded simultaneously in one retina and the corresponding rod limit. Rod and RGC discrimination contours were shifted along the flash strength axis to align the rod limit contours. F, Collected results from all 85 recorded cells (17 ON and 68 OFF). Data from recordings in 1 mm Ca²⁺ (A, B) were shifted along the time offset axis to align the rod limit contours with those obtained in 2 mm Ca²⁺ (C-E).

Figure 3.

Rod discrimination performance across flash strengths (ϕ) and time offsets (ΔT). A, Discrimination performance plotted against flash strength for time offsets of 5 sec (•) and 0.2 sec (○). B, Discrimination surface summarizing performance across flash strengths and time offsets. C, Fit to discrimination surface computed according to Equations 1 and 2. The thick line indicates the contour corresponding to SNR = 1. D, Comparison of discrimination contours from surface fit (line) and interpolated linearly from measured surface (○). E, Discrimination contours for 15 different rods (thin lines) and mean across cells (thick line). F, Comparison of discrimination contours for several alternative discrimination procedures (see Materials and Methods). standard, Standard procedure; euc clust, Euclidean clustering; covar norm, covariance normalization; var norm, variance normalization.

Figure 2.

Early-late discrimination with rod responses. A, Discriminants (thick traces) formed by subtracting average late response from average early response and example individual responses for flashes separated by 5 sec (top) and 0.2 sec (bottom). B, Distribution of correlations for flashes producing an average of 0.9 Rh^* (left) or 3.6 Rh^* (right). Distributions are shown for flashes separated by 5 sec (top) and 0.2 sec (bottom). Same cell as Figure 1.

Figure 5.

RGC discrimination performance across flash strengths (ϕ) and time offsets (ΔT) (see Fig. 3). A, Probability correct plotted against flash strength for large and small time offsets. B, Surface summarizing discrimination performance across a range of flash strengths and time offsets. C, Fit to discrimination surface from Equations 1 and 2. D, Discrimination contour (SNR = 1) interpolated from the measured surface in B (○) and calculated from the surface fit in C (smooth line). E, Discrimination contours from 21 RGCs recorded simultaneously. F, Discrimination contours for a single RGC using several discrimination procedures (see Materials and Methods). standard, Standard procedure; euc clust, Euclidean clustering; non-euc clust, non-Euclidean clustering; covar norm, covariance normalization; var norm, variance normalization.

Figure 6.

Model for rod discrimination signals. A, Measured (stepped curves) and fitted (smooth curves) correlation distributions for rod responses to a flash with strength 0.9 Rh^* and time offset of 5 sec. B, Measured and fitted correlation distributions for a flash with strength 3.6 Rh^* and time offset of 0.2 sec. C, Discrimination contour obtained from the rod responses (thin line) or from the fits to the correlation distribution (thick line). D, Control for errors extrapolating model parameters to low flash strengths (see Materials and Methods). Discrimination contours from the original model (thick line) and from the fit to samples generated by the model (thin line).

Figure 1.

Task used to characterize rod detection sensitivity and temporal resolution. A, Responses to a flash producing an average of 0.9 Rh^* at 6 either 2 sec (left) or 7 sec (right). Average responses to 145 trials are shown at the bottom. Responses at 2 and 7 sec were obtained by circularly time shifting the same data; hence, the average traces are time shifted copies of one another. The first 10 sec of the 12-sec-long responses are plotted. B, Responses to a flash producing 3.6 Rh^* at either 2 sec (left) or 7 sec (right). C, Responses to a flash producing 0.9 Rh^* at either 4.9 sec (left) or 5.1 sec (right). D, Responses to a flash producing 3.6 Rh^* at either 4.9 sec (left) or 5.1 sec (right).

Figure 4.

Task used to characterize RGC detection sensitivity and temporal resolution (see Fig. 1). Responses are shown for time shifts of 2 sec (top) and 0.2 sec (bottom) at flash strengths of 0.20 Rh^*/rod (left) and 0.39 Rh^*/rod (right). Ten individual responses are shown for the early and late stimuli for each flash strength and time shift combination. Average responses below the individual rasters were calculated across 160 trials. Responses at different times were obtained by time shifting the same data; hence, the average traces are time shifted copies of one another.

Figure 7.

Comparison of RGC discrimination performance with rod limit. A, Schematic of model used to estimate sensitivity of rod pool. Samples drawn from the distribution of discrimination signals for early and late flashes were weighted by the receptive field (RF) profile and summed. Discrimination was based on the sign of the difference of these summed signals. B, RGC receptive field measured with white noise stimulation. Ellipse shows the 2 SD contour of an elliptical Gaussian fit to the receptive field (see Materials and Methods). C-E, Discrimination contours for individual RGCs from three retinas (thick lines) and corresponding rod limits (thin lines). The estimated number of rods within the 2 SD boundary for each RGC was 630, 780, and 450. Estimated detection thresholds (vertical asymptote of discrimination curve) were 0.30, 0.06, and 0.27 Rh^*/rod.

Figure 9.

Sensitivity of rod limit to increased noise and limits in retinal processing. A, Rod limit contours calculated for a 160-μm-diameter receptive field with (thin trace) and without (thick trace) additive noise with an SD of 4σ_d (see Eq. 3). B, Rod limit contours with (thin trace) and without (thick trace) high-pass filtering and added noise with SD of 0.2σ_d. The impulse response of the filter is indicated in the inset. C, Rod limit contours with (thin trace) and without (thick trace) a threshold that eliminated rod pool responses smaller than 0.08 Rh^*/rod. D, Sensitivity of rod limit contours to increases in each source of rod noise.