The goal of this work was to provide a detailed quantitative description of the receptive-field properties of one of the types of rarely encountered retinal ganglion cells of cat; the cell named the Q-cell by Enroth-Cugell et al. (1983). Quantitative comparisons are made between the discharge statistics and between the spatial receptive properties of Q-cells and the most common of cat retinal ganglion cells, the X-cells. The center-surround receptive field of the Q-cell is modeled here quantitatively and the typical Q-cell is described. The temporal properties of the Q-cell receptive field were also investigated and the dynamics of the center mechanism of the Q-cell modeled quantitatively. In addition, the response vs. contrast relationship for a Q-cell at optimal spatial and temporal frequencies is shown, and Q-cells are also demonstrated to have nonlinear spatial summation somewhat like that exhibited by Y-cells, although much higher contrasts are required to reveal this nonlinear behavior. Finally, the relationship between Q-cells and Barlow and Levick's (1969) luminance units was investigated and it was found that most Q-cells could not be luminance units.
"scotopic or photopic regime). Other ganglion cell types, such as the so-called luminance units (Barlow and Levick, 1969; Troy et al., 1995) or intrinsically photosensitive ganglion cells (Dacey et al., 2005), may signal the illumination level via the mean firing rate of the cell, while the mean firing rate of X and Y-cells are not thought to signal light level (Troy and Enroth- Cugell, 1993). Thus, changes in the oscillation frequency of X and Y-cells provide an alternative method for signaling a dramatic change in light level. "
[Show abstract][Hide abstract] ABSTRACT: Action potentials were recorded from rat retinal ganglion cell fibers in the presence of a uniform field, and the maintained discharge pattern was characterized. Spike trains recorded under ketaminexylazine. The majority of cells had multimodal interval distributions, with the first peak in the range of 25.00.97). Both ON and OFF cells show serial correlations between adjacent interspike intervals, while ON cells also showed second-order correlations. Cells with multimodal interval distribution showed a strong peak at high frequencies in the power spectra in the range of 28.9-41.4 Hz. Oscillations were present under both anesthetic conditions and persisted in the dark at a slightly lower frequency, implying that the oscillations are generated independent of any light stimulus but can be modulated by light level. The oscillation frequency varied slightly between cells of the same type and in the same eye, suggesting that multiple oscillatory generating mechanisms exist within the retina. Cells with high-frequency oscillations were described well by an integrate-and-fire model with the input consisting of Gaussian noise plus a sinusoid where the phase was jittered randomly to account for the bandwidth present in the oscillations.
"Thus, despite the fact that both X and Y ganglion cells exhibit robust HFRs, the underlying mechanisms may be quite different. HFRs have also been observed in other ganglion cell types (Troy et al., 1995), although further characterization will be necessary to determine whether distinct mechanisms are involved. "
[Show abstract][Hide abstract] ABSTRACT: Brisk Y-type ganglion cells in the cat retina exhibit a high frequency resonance (HFR) in their responses to large, rapidly modulated stimuli. We used a computer model to test whether negative feedback mediated by axon-bearing amacrine cells onto ganglion cells could account for the experimentally observed properties of HFRs. Temporal modulation transfer functions (tMTFs) recorded from model ganglion cells exhibited HFR peaks whose amplitude, width, and locations were qualitatively consistent with experimental data. Moreover, the wide spatial distribution of axon-mediated feedback accounted for the observed increase in HFR amplitude with stimulus size. Model phase plots were qualitatively similar to those recorded from Y ganglion cells, including an anomalous phase advance that in our model coincided with the amplification of low-order harmonics that overlapped the HFR peak. When axon-mediated feedback in the model was directed primarily to bipolar cells, whose synaptic output was graded, or else when the model was replaced with a simple cascade of linear filters, it was possible to produce large HFR peaks but the region of anomalous phase advance was always eliminated, suggesting the critical involvement of strongly non-linear feedback loops. To investigate whether HFRs might contribute to visual processing, we simulated high frequency ocular tremor by rapidly modulating a naturalistic image. Visual signals riding on top of the imposed jitter conveyed an enhanced representation of large objects. We conclude that by amplifying responses to ocular tremor, HFRs may selectively enhance the processing of large image features.
"In guinea pig, all cells we have studied so far (ϳ7 wide-field types) express a nonlinear receptive field (Sterling et al., 1999). In cat retina, Y and W cells express a nonlinear receptive field (Hochstein and Shapley, 1976; Troy et al., 1989; Rowe and Cox, 1993; Pu et al., 1994; Troy et al., 1995), and even X cells, generally considered to be linear, express nonlinear responses from the periphery (Barlow et al., 1977; Hamasaki and Maguire, 1985). Furthermore, nonlinear receptive fields are expressed by ganglion cell types in rabbit (C aldwell and Daw, 1978; Watanabe and Tasaki, 1980), mouse (Stone and Pinto, 1993), and monkey (Kruger et al., 1975; Kaplan and Shapley, 1982). "
[Show abstract][Hide abstract] ABSTRACT: ers beyond the ganglion cell were eliminated by tetrodotoxin. Thus, to relay the response from distant regions of the receptive field requires a spiking interneuron. Nonlinear responses from different regions of the receptive field added linearly. Key words: in vitro retina; guinea pig; nonlinear subunit; shift effect; spiking amacrine cell; bipolar cell; tetrodotoxin; L-AP-4 A retinal ganglion cell encodes information from at least two computational mechanisms. One is familiar, the "linear" receptive field, which computes local temporal contrast by combining excitatory and inhibitory signals over both a narrow region (the "center") and a wider region (the antagonistic "surround") (Barlow, 1953; Kuffler, 1953; Rodieck, 1965; Enroth-Cugell and Pinto, 1970). The other mechanism is less familiar, the "nonlinear" receptive field, which computes global changes in contrast magnitude by summing signals from independent regions ("subunits") (En
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