Effects of dark adaptation on spatial and temporal properties of receptive fields in cat lateral geniculate nucleus.

Kaplan, Ehud; Marcus, Stephen M.; So, Yuen T.

doi:10.1113/jphysiol.1979.sp012946

Cited by 103 publications

(67 citation statements)

References 31 publications

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“…A similar alteration also occurs in cat cortex. Bisti et al (1977) report reorganization of RFs similar to that found in the LGN by Kaplan et al (1979). Therefore at low luminances, the cat visual system has the ability to act as a low SF filter at several different levels of the CNS.…”

Section: Luminance Affects Receptive Fieldssupporting

confidence: 53%

“…Barlow, Fitzhugh, and Kuffler (1957) report the disappearance of the antagonistic surround of retinal receptive fields in cats, while Enroth-Cugell and Lennie (1975) demonstrated only diminished sensitivity. These alterations in organization occur even at the level of the lateral geniculate nucleus (LGN) of the thalamus (Kaplan, Marcus, and So, 1979) with a sufficiently large reduction in luminance (4 log units). In addition to the reduction in the surround response, Kaplan also reports increases in the size of receptive field centers recorded from both retinal ganglion cells and LGN cells.…”

Section: Luminance Affects Receptive Fieldsmentioning

confidence: 99%

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Spatial contrast sensitivity of birds

2006

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Contrast sensitivity (CS) is the ability of the observer to discriminate between adjacent stimuli on the basis of their differences in relative luminosity (contrast) rather than their absolute luminances. Prior to this study, birds had been thought to have low contrast detection thresholds relative to mammals and fishes. This was a surprising phenomenon because birds had been traditionally attributed with superior vision. In addition, the low CS of birds could not be explained by retinal or optical factors, or secondary stimulus characteristics. Unfortunately, avian contrast sensitivity functions (CSFs) were sparse in the literature, so it was unknown whether low contrast sensitivity was a general phenomenon in birds. This study measured CS in six species of birds The quail and pigeon data obtained in this experiment fit well with existing CS data for these species. The kestrel data were not similar to kestrel data in the literature; however the data in the literature were collected from a single subject. All of the birds studied had contrast sensitivities that were consistent with their retinal or optical morphologies relative to other birds (in species for which such data exists) and seem well suited for their natural environments. In addition, all of these birds exhibited low CS relative to humans and most mammals, which suggests that low CS is a general phenomenon of birds.Explanations for this avian low CS phenomenon include a possible trade-off between contrast mechanisms and UV mechanisms in cone systems, and lateral inhibitory mechanisms that are perhaps categorically different from mammals. Lateral inhibition affects contrast gain, and has been shown to differ according to ganglion cell types, which in turn will differ in vertebrate species.

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Section: Luminance Affects Receptive Fieldssupporting

confidence: 53%

Section: Luminance Affects Receptive Fieldsmentioning

confidence: 99%

Spatial contrast sensitivity of birds

2006

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“…The linear receptive field accurately predicts the basic selectivity of LGN neuron measured with gratings. For instance, the spatial profile of the receptive field predicts the selectivity for spatial frequency (Kaplan et al, 1979;So and Shapley, 1981;Shapley and Lennie, 1985), whereas the temporal weighting function predicts the selectivity for temporal frequency (Saul and Humphrey, 1990;Kremers et al, 1997;Benardete and Kaplan, 1999). The linear receptive field does not describe only responses to simple laboratory stimuli but also captures the basic features in the responses to complex video sequences (Dan et al, 1996).…”

Section: Understanding Lgn Responsesmentioning

confidence: 99%

Do We Know What the Early Visual System Does?

Carandini

Demb²,

Mante³

et al. 2005

J. Neurosci.

561

546

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We can claim that we know what the visual system does once we can predict neural responses to arbitrary stimuli, including those seen in nature. In the early visual system, models based on one or more linear receptive fields hold promise to achieve this goal as long as the models include nonlinear mechanisms that control responsiveness, based on stimulus context and history, and take into account the nonlinearity of spike generation. These linear and nonlinear mechanisms might be the only essential determinants of the response, or alternatively, there may be additional fundamental determinants yet to be identified. Research is progressing with the goals of defining a single "standard model" for each stage of the visual pathway and testing the predictive power of these models on the responses to movies of natural scenes. These predictive models represent, at a given stage of the visual pathway, a compact description of visual computation. They would be an invaluable guide for understanding the underlying biophysical and anatomical mechanisms and relating neural responses to visual perception.Key words: contrast; lateral geniculate nucleus; luminance; primary visual cortex; receptive field; retina; visual system; natural imagesThe ultimate test of our knowledge of the visual system is prediction: we can say that we know what the visual system does when we can predict its response to arbitrary stimuli. How far are we from this end result? Do we have a "standard model" that can predict the responses of at least some early part of the visual system, such as the retina, the lateral geniculate nucleus (LGN), or primary visual cortex (V1)? Does such a model predict responses to stimuli encountered in the real world?A standard model existed in the early decades of visual neuroscience, until the 1990s: it was given by the linear receptive field. The linear receptive field specifies a set of weights to apply to images to yield a predicted response. A weighted sum is a linear operation, so it is simple and intuitive. Moreover, linearity made the receptive field mathematically tractable, allowing the fruitful marriage of visual neuroscience with image processing (Robson, 1975) and with linear systems analysis (De Valois and De Valois, 1988). It also provided a promising parallel with research in visual perception (Graham, 1989). Because it served as a standard model, the receptive field could be used to decide which findings were surprising and which were not: if a phenomenon was not predictable from the linear receptive field, it was particularly worthy of publication.Research aimed at testing the linear receptive field led to the discovery of important nonlinear phenomena, which cannot be explained by a linear receptive field alone. These phenomena have been discovered at all stages of the early visual system, including the retina (for review, see Shapley and Enroth-Cugell, 1984;Demb, 2002), the LGN (for review, see Carandini, 2004), and area V1 (for review, see Carandini et al., 1999;Fitzpatrick, 2000;Albright and Stoner,...

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“…For both the X and Y cells, on-and off-center RGCs form their own lattices, and the on and off lattices are superimposed independently of each other (8,9). Since the signals from RGCs are relayed through the lateral geniculate nucleus (LGN) without substantial modification (16)(17)(18)(19), the RGC mosaic represents the pattern of visual input to the cortex. Thus, as emphasized by Wassle et al (8), the RGC mosaic serves as an important constraint on the construction of cortical receptive fields.…”

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The retinal ganglion cell mosaic defines orientation columns in striate cortex.

Soodak¹

1987

Proc. Natl. Acad. Sci. U.S.A.

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A computer simulation was used to demonstrate that the tangential organization of orientation columns is a natural consequence of the orderly projection of the mosaic of retinal ganglion cells onto the visual cortex. Parameters of the simulation were taken from published anatomical and electrophysiological data, and the resulting columnar organization of the simulated visual cortex shows many similarities with observations from animals. The model is able to account for a variety of experimental observations, including the presence of orientation columns in visually inexperienced animals.One of the striking features of the cortical representation of the visual field is the grouping of neurons with similar preferred orientations into the orientation columns described by Hubel and Wiesel (1,2). This columnar organization is already present in kittens at the time ofeye opening and must, therefore, be determined by intrinsic developmental processes that are independent of visual experience (3-6). In a previous report, I showed how the orientation tuning of visual cortex neurons could be calculated from the pattern of convergence of on-and off-center afferents (7). Using this calculation procedure, I show here that the tangential organization of the orientation columns is a natural consequence of the orderly projection of the retinal ganglion cell mosaic onto the cortex.Wissle and his collaborators (8, 9) have shown that retinal ganglion cells (RGCs) of the cat are arranged in a lattice-like mosaic with regular cell-to-cell spacings. Similar arrangements were found for both the P (8) and a (9) morphological types, which Boycott and Wassle (10) and Wassle et al. (11) have shown to correspond to the X and Y physiological types (12-15), respectively. For both the X and Y cells, on-and off-center RGCs form their own lattices, and the on and off lattices are superimposed independently of each other (8,9). Since the signals from RGCs are relayed through the lateral geniculate nucleus (LGN) without substantial modification (16)(17)(18)(19), the RGC mosaic represents the pattern of visual input to the cortex. Thus, as emphasized by Wassle et al. (8), the RGC mosaic serves as an important constraint on the construction of cortical receptive fields. THE SIMULATIONWhat I present here is the result, by computer simulation, of the developmental process whereby the RGC mosaic projects retinotopically by way of the LGN onto the cortex. The simulation begins with two sets of coordinates, corresponding to the retinal positions of the on-and off-center RGCs.The receptive fields of the cortical neurons are then defined as a convergence of RGC inputs, and their responses are calculated using the procedure described in a previous report (7). The positions of the RGCs in the retinal mosaic were measured from figure 9 of Wassle et al. (8) after photographic enlargement and were corrected for tissue shrinkage by the areal shrinkage factor of 0.5 provided by the authors. Other parameters of the simulation were also obtained from exper...

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Effects of dark adaptation on spatial and temporal properties of receptive fields in cat lateral geniculate nucleus.

Cited by 103 publications

References 31 publications

Spatial contrast sensitivity of birds

Spatial contrast sensitivity of birds

Do We Know What the Early Visual System Does?

The retinal ganglion cell mosaic defines orientation columns in striate cortex.

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