Contrast gain control in the primate retina: P cells are not X-like, some M cells are

1992 ◽  
Vol 8 (5) ◽  
pp. 483-486 ◽  
Author(s):  
Ethan A. Benardete ◽  
Ehud Kaplan ◽  
Bruce W. Knight
Keyword(s):  
Retinal Ganglion Cells ◽  
Ganglion Cells ◽  
Temporal Frequency ◽  
Gain Control ◽  
M Cells ◽  
Retinal Ganglion ◽  
M Cell ◽  
Contrast Gain ◽  
Contrast Gain Control ◽  
P Cells

AbstractPrimate retinal ganglion cells that project to the magnocellular layers of the lateral geniculate nucleus (M) are much more sensitive to luminance contrast than those ganglion cells projecting to the parvocellular layers (P). We now report that increasing contrast modifies the temporal-frequency response of M cells, but not of P cells. With rising contrast, the M cells' responses to sinusoidal stimuli show an increasing attenuation at low temporal frequencies while the P cells' responses scale uniformly. The characteristic features of M-cell dynamics are well described by a model originally developed for the X and Y cells of the cat, where the hypothesized nonlinear feedback mechanism responsible for this behavior has been termed the contrast gain control (Shapley & Victor, 1978, 1981; Victor, 1987, 1988). These data provide further physiological evidence that the M-cell pathway differs from the P-cell pathway with regard to the functional elements in the retina. Furthermore, the similarity in dynamics between primate M cells and cat X and Y retinal ganglion cells suggests the possibility that P cells, being different from either group, are a primate specialization not found in the retinae of lower mammals.

The dynamics of primate M retinal ganglion cells

1999 ◽  
Vol 16 (2) ◽  
pp. 355-368 ◽  
Author(s):  
ETHAN A. BENARDETE ◽  
EHUD KAPLAN
Keyword(s):  
Frequency Response ◽  
Retinal Ganglion Cells ◽  
Ganglion Cells ◽  
Temporal Frequency ◽  
Gain Control ◽  
Linear Filter ◽  
M Cells ◽  
Retinal Ganglion ◽  
Contrast Gain ◽  
Contrast Gain Control

The retinal ganglion cells (RGCs) of the primate form at least two classes—M and P—that differ fundamentally in their functional properties. M cells have temporal-frequency response characteristics distinct from P cells (Benardete et al., 1992; Lee et al., 1994). In this paper, we elaborate on the temporal-frequency responses of M cells and focus in detail on the contrast gain control (Shapley & Victor, 1979a,b). Earlier data showed that the temporal-frequency response of M cells is altered by the level of stimulus contrast (Benardete et al., 1992). Higher contrast shifts the peak of the frequency-response curve to higher temporal frequency and produces a phase advance. In this paper, by fitting the data to a linear filter model, the effect of contrast on the temporal-frequency response is subsumed into a change in a single parameter in the model. Furthermore, the model fits are used to predict the response of M cells to steps of contrast, and these predictions demonstrate the dynamic effect of contrast on the M cells' response. We also present new data concerning the spatial organization of the contrast gain control in the primate and show that the signal that controls the contrast gain must come from a broadly distributed network of small subunits in the surround of the M-cell receptive field.

scholarly journals Dependence of center radius on temporal frequency for the receptive fields of X retinal ganglion cells of cat.

1989 ◽  
Vol 94 (6) ◽  
pp. 987-995 ◽  
Author(s):  
J B Troy ◽  
C Enroth-Cugell
Keyword(s):  
Retinal Ganglion Cells ◽  
Ganglion Cells ◽  
Signal To Noise Ratio ◽  
Temporal Frequency ◽  
Receptive Fields ◽  
Retinal Ganglion ◽  
Spatial Expansion ◽  
Neuronal Membranes ◽  
Inductive Elements ◽  
X Cells

We examined the dependence of the center radius of X cells on temporal frequency and found that at temporal frequencies above 40 Hz the radius increases in a monotonic fashion, reaching a size approximately 30% larger at 70 Hz. This kind of spatial expansion has been predicted with cable models of receptive fields where inductive elements are included in modeling the neuronal membranes. Hence, the expansion of the center radius is clearly important for modeling X cell receptive fields. On the other hand, we feel that it might be of only minor functional significance, since the responsivity of X cells is attenuated at these high temporal frequencies and the signal-to-noise ratio is considerably worse than at low and midrange temporal frequencies.

Light adaptation in the primate retina: Analysis of changes in gain and dynamics of monkey retinal ganglion cells

1990 ◽  
Vol 4 (1) ◽  
pp. 75-93 ◽  
Author(s):  
Keith Purpura ◽  
Daniel Tranchina ◽  
Ehud Kaplan ◽  
Robert M. Shapley
Keyword(s):  
Retinal Ganglion Cells ◽  
Negative Feedback ◽  
Light Adaptation ◽  
Ganglion Cells ◽  
Human Subjects ◽  
Light Level ◽  
Retinal Ganglion ◽  
M Cell ◽  
Feedback Model ◽  
Light Levels

AbstractThe responses of monkey retinal ganglion cells to sinusoidal stimuli of various temporal frequencies were measured and analyzed at a number of mean light levels. Temporal modulation tuning functions (TMTFs) were measured at each mean level by varying the drift rate of a sine-wave grating of fixed spatial frequency and contrast. The changes seen in ganglion cell temporal responses with changes in adaptation state were similar to those observed in human subjects and in turtle horizontal cells and cones tested with sinusoidally flickering stimuli; “Weber's Law” behavior was seen at low temporal frequencies but not at higher temporal frequencies. Temporal responses were analyzed in two ways: (1) at each light level, the TMTFs were fit by a model consisting of a cascade of low- and high-pass filters; (2) the family of TMTFs collected over a range of light levels for a given cell was fit by a linear negative feedback model in which the gain of the feedback was proportional to the mean light level. Analysis (1) revealed that the temporal responses of one class of monkey ganglion cells (M cells) were more phasic at both photopic and mesopic light levels than the responses of P ganglion cells. In analysis (2), the linear negative feedback model accounted reasonably well for changes in gain and dynamics seen in three P cells and one M cell. From the feedback model, it was possible to estimate the light level at which the dark-adapted gain of the cone pathways in the primate retina fell by a factor of two. This value was two to three orders of magnitude lower than the value estimated from recordings of isolated monkey cones. Thus, while a model which includes a single stage of negative feedback can account for the changes in gain and dynamics associated with light adaptation in the photopic and mesopic ranges of vision, the underlying physical mechanisms are unknown and may involve elements in the primate retina other than the cone.

scholarly journals Systematic misestimation in a vernier task arising from contrast mismatch

2008 ◽  
Vol 25 (3) ◽  
pp. 365-370 ◽  
Author(s):  
HAO SUN ◽  
BARRY B. LEE ◽  
RIGMOR C. BARAAS
Keyword(s):  
Ganglion Cells ◽  
Gain Control ◽  
Phase Advance ◽  
Target Pair ◽  
Control Mechanisms ◽  
Low Contrast ◽  
Contrast Gain ◽  
Contrast Gain Control ◽  
Cell Responses ◽  
High Contrast Grating

Luminance signals mediated by the magnocellular (MC) pathway play an important role in vernier tasks. MC ganglion cells show a phase advance in their responses to sinusoidal stimuli with increasing contrast due to contrast gain control mechanisms. If the phase information in MC ganglion cell responses were utilized by central mechanisms in vernier tasks, one might expect systematic errors caused by the phase advance. This systematic error may contribute to the contrast paradox phenomenon, where vernier performance deteriorates, rather than improves, when only one of the target pair increases in contrast. Vernier psychometric functions for a pair of gratings of mismatched contrast were measured to seek such misestimation. In associated electrophysiological experiments, MC and parvocellular (PC) ganglion cells' responses to similar stimuli were measured to provide a physiological reference. The psychophysical experiments show that a high-contrast grating is perceived as phase advanced in the drift direction compared to a low-contrast grating, especially at a high drift rate (8 Hz). The size of the phase advance was comparable to that seen in MC cells under similar stimulus conditions. These results are consistent with the MC pathway supporting vernier performance with achromatic gratings. The shifts in vernier psychometric functions were negligible for pairs of chromatic gratings under the conditions tested here, consistent with the lack of phase advance both in responses of PC ganglion cells and in frequency-doubled chromatic responses of MC ganglion cells.

Complex Spike-Event Pattern of Transient on-off Retinal Ganglion Cells

2006 ◽  
Vol 96 (6) ◽  
pp. 2845-2856 ◽  
Author(s):  
Martin Greschner ◽  
Andreas Thiel ◽  
Jutta Kretzberg ◽  
Josef Ammermüller
Keyword(s):  
Retinal Ganglion Cells ◽  
Computational Models ◽  
Ganglion Cells ◽  
Temporal Structure ◽  
Gain Control ◽  
Saccadic Eye Movements ◽  
Cell Subpopulation ◽  
Retinal Ganglion ◽  
Filter Model ◽  
Spike Event

on-off transient ganglion cells of the turtle retina show distinct spike-event patterns in response to abrupt intensity changes, such as during saccadic eye movements. These patterns consist of two main spike events, with the latency of each event showing a systematic dependency on stimulus contrast. Whereas the latency of the first event decreases monotonically with increasing contrast, as expected, the second event shows the shortest latency for intermediate contrasts and a longer latency for high and low contrasts. These spike-event patterns improve the discrimination of different light-intensity transitions based on ensemble responses of the on-off transient ganglion cell subpopulation. Although the discrimination results are far better than chance using either spike counts or latencies of the first spikes, they are further improved by using properties of the second spike event. The best classification results are obtained when spike rates and latencies of both events are considered in combination. Thus spike counts and temporal structure of retinal ganglion cells carry complementary information about the stimulus condition, and thus spike-event patterns could be an important aspect of retinal coding. To investigate the origin of the spike-event patterns in retinal ganglion cells, two computational models of retinal processing are compared. A linear–nonlinear model consisting of separate filters for on and off response components fails to reproduce the spike-event patterns. A more complex cascade filter model, however, accurately predicts the timing of the spike events by using a combination of gain control loop and spike rate adaptation.

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