scholarly journals Distinct expressions of contrast gain control in parallel synaptic pathways converging on a retinal ganglion cell

2008 ◽  
Vol 586 (22) ◽  
pp. 5487-5502 ◽  
Author(s):  
Deborah Langrill Beaudoin ◽  
Michael B. Manookin ◽  
Jonathan B. Demb
1992 ◽  
Vol 8 (5) ◽  
pp. 483-486 ◽  
Author(s):  
Ethan A. Benardete ◽  
Ehud Kaplan ◽  
Bruce W. Knight

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.


1999 ◽  
Vol 16 (2) ◽  
pp. 355-368 ◽  
Author(s):  
ETHAN A. BENARDETE ◽  
EHUD KAPLAN

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.


2010 ◽  
Vol 104 (2) ◽  
pp. 704-712 ◽  
Author(s):  
Daniel K. Freeman ◽  
Gilberto Graña ◽  
Christopher L. Passaglia

To accommodate the wide input range over which the visual system operates within the narrow output range of spiking neurons, the retina adjusts its sensitivity to the mean light level so that retinal ganglion cells can faithfully signal contrast, or relative deviations from the mean luminance. Given the large operating range of the visual system, the majority of work on luminance adaptation has involved logarithmic changes in light level. We report that luminance gain controls are recruited for remarkably small fluctuations in luminance as well. Using spike recordings from the rat optic tract, we show that ganglion cell responses to a brief flash of light are modulated in amplitude by local background fluctuations as little as 15% contrast. The time scale of the gain control is rapid (<125 ms), at least for on cells. The retinal locus of adaptation precedes the ganglion cell spike generator because response gain changes of on cells were uncorrelated with firing rate. The mechanism seems to reside within the inner retinal network and not in the photoreceptors, because the adaptation profiles of on and off cells differed markedly. The response gain changes follow Weber's law, suggesting that network mechanisms of luminance adaptation described in previous work modulates retinal ganglion cell sensitivity, not just when we move between different lighting environments, but also as our eyes scan a visual scene. Finally, we show that response amplitude is uniformly reduced for flashes on a modulated background that has spatial contrast, indicating that another gain control that integrates luminance signals nonlinearly over space operates within the receptive field center of rat ganglion cells.


2007 ◽  
Vol 30 (4) ◽  
pp. 77
Author(s):  
Y. Y. Chen ◽  
C. L. Hehr ◽  
K. Atkinson-Leadbeater ◽  
J. C. Hocking ◽  
S. McFarlane

Background: The growth cone interprets cues in its environment in order to reach its target. We want to identify molecules that regulate growth cone behaviour in the developing embryo. We investigated the role of A disintegrin and metalloproteinase 10 (ADAM10) in axon guidance in the developing visual system of African frog, Xenopus laevis. Methods: We first examined the expression patterns of adam10 mRNA by in situ hybridization. We then exposed the developing optic tract to an ADAM10 inhibitor, GI254023X, in vivo. Lastly, we inhibited ADAM10 function in diencephalic neuroepithelial cells (through which retinal ganglion cell (RGC) axons extend) or RGCs by electroporating or transfecting an ADAM10 dominant negative (dn-adam10). Results: We show that adam10 mRNA is expressed in the dorsal neuroepithelium over the time RGC axons extend towards their target, the optic tectum. Second, pharmacological inhibition of ADAM10 in an in vivo exposed brain preparation causes the failure of RGC axons to recognize their target at low concentrations (0.5, 1 μM), and the failure of the axons to make a caudal turn in the mid-diencephalon at higher concentration (5 μM). Thus, ADAM10 function is required for RGC axon guidance at two key guidance decisions. Finally, molecular inhibition of ADAM10 function by electroporating dn-adam10 in the brain neuroepithelium causes defects in RGC axon target recognition (57%) and/or defects in caudal turn (12%), as seen with the pharmacological inhibitor. In contrast, molecular inhibition of ADAM10 within the RGC axons has no effect. Conclusions: These data argue strongly that ADAM10 acts cell non-autonomously within the neuroepithelium to regulate the guidance of RGC axons. This study shows for the first time that a metalloproteinase acts in a cell non-autonomous fashion to direct vertebrate axon growth. It will provide important insights into candidate molecules that could be used to reform nerve connections if destroyed because of injury or disease. References Hattori M, Osterfield M, Flanagan JG. Regulated cleavage of a contact-mediated axon repellent. Science 2000; 289(5483):1360-5. Janes PW, Saha N, Barton WA, Kolev MV, Wimmer-Kleikamp SH, Nievergall E, Blobel CP, Himanen JP, Lackmann M, Nikolov DB. Adam meets Eph: an ADAM substrate recognition module acts as a molecular switch for ephrin cleavage in trans. Cell 2005; 123(2):291-304. Pan D, Rubin GM. Kuzbanian controls proteolytic processing of Notch and mediates lateral inhibition during Drosophila and vertebrate neurogenesis. Cell 1997; 90(2):271-80.


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