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D J Tolhurst

Publications and source records attributed to D J Tolhurst.

71 records · Page 4Linked to original sources
PubMed1975

Concealed colour opponency in ganglion cells of the rhesus monkey retina.

Criteria for distinguishing colour-opponent from spectrally non-opponent cells and identifying colour-opponent subtypes on the basis of the cone inputs they receive, have been examined in ganglion cells of the macaque retina using threshold and suprathreshold stimuli, with and without chromatic adaptation. 2. Criteria based on suprathreshold responses were found to be insufficient for distinguishing between opponent and non-opponent cells in one-third of the sample. Criteria based on a 560 nm neutral point were found to be insufficient for distinguishing between colour-opponent subtypes in one-half of the remaining cells. 3. The neutral point of colour-opponent ganglion cells varies with the geometry and intensity of the stimulus, as well as with the amount of centre-surround interaction and the receptive-field location of a cell. As a result, the neutral point is often an ambiguous criterion for identifying colour-opponent subtypes on the basis of their cone inputs. 4. About one third of the colour-opponent ganglion cells did not show colour opponency in the presence of neutral backgrounds, and only revealed this behaviour in the presence of chromatic adaptation (concealed colour opponency). 5. The proportion of these concealed colour-opponent cells increased towards the peripheral areas of the retina.

Adaptation, Ocular↗
PubMed1974

Is spatial adaptation an after-effect of prolonged inhibition?

1. The elevation of the thresholds for sinusoidal gratings of 4 c/deg and 6.7 c/deg was examined after adapting to gratings of 4 c/deg. Threshold elevation was determined as a function of the adapting contrast.2. It was confirmed that, when the adapting and testing spatial-frequencies were the same, the threshold elevation curve extrapolated to zero elevation at an adapting contrast equal to the pre-adaptation threshold for the adapting grating.3. It was found that the threshold elevation curve for 6.7 c/deg gratings also extrapolated to zero elevation at the pre-adaptation threshold for the adapting grating, even though the testing and adapting frequencies were different.4. It is argued that the latter result shows that adaptation is not simply an after-effect of prolonged excitation of a channel. Threshold elevation curves may represent the bandwidths of inhibitory interactions between channels.

Adaptation, Physiological↗
PubMed1973

Edge detectors in human vision.

1. The spatial properties of edge detectors were measured psychophysically with the technique of subthreshold addition. Subthreshold patterns used to add to an edge were lines, sine gratings, Gaussian edges, and ramps.2. The sensitivity profile, determined from experiments on subthreshold addition of lines to an edge was an antisymmetric function, with peak sensitivity approximately +/- 1.5' from its midpoint. Its total extent was about +/- 6'.3. The spatial frequency response of edge detectors was measured in experiments on subthreshold addition of sine gratings to an edge. The spatial frequency response was peaked at about 3 c/deg, and was broadly tuned in frequency. It was approximately equal to the Fourier transform of the sensitivity profile, implying linearity of edge detectors.4. The visibility of Gaussian edges and ramps could be explained largely in terms of the activation of edge detector neurones.5. The role of edge detectors in perception, in creating apparent brightness, and as an explanation of contour illusions, is discussed.

Form Perception↗
PubMed1973

Separate channels for the analysis of the shape and the movement of moving visual stimulus.

1. The effects of temporal modulation on the properties of spatial frequency channels have been investigated using adaptation.2. Adapting to drifting sinusoidal gratings caused threshold elevation that was both spatial frequency and direction specific. Little systematic difference was found between the band widths of the elevation curves for drifting and stationary gratings.3. It was confirmed that adaptation fails to reveal channels at low spatial frequencies when stationary gratings are used. However, channels were revealed at frequencies at least as low as 0.66 c/deg when the test gratings were made to move. These channels are adapted only a little by stationary gratings, confirming their dependence on movement.4. The existence of movement-sensitive channels at low spatial frequencies explains the well known observation that temporal modulation greatly increases the sensitivity of the visual system to low spatial frequencies.5. Temporal modulation was effective at revealing these channels only when the flicker or movement of the test patterns was apparent to the observer; only at low spatial frequencies did patterns, modulated at low rates, actually appear to be temporarily modulated at threshold. At higher spatial frequencies, they were indistinguishable from stationary patterns until the contrast was some way above the detection threshold.6. It is suggested, therefore, that the movement-sensitive channels are responsible for signalling the occurrence of movement; the channels at higher spatial frequencies give no information about temporal changes. These two systems of channels are compared to the Y- and X-cells respectively of the cat.

Animals↗
PubMed1973

Psychophysical evidence for sustained and transient detectors in human vision.

1. The sensitivity to temporally modulated sinusoidal gratings was determined. Two thresholds could be distinguished for the modulated gratings: the contrast at which flicker could be perceived and the contrast at which the spatial structure became distinct.2. The flicker detection thresholds and pattern recognition threshold varied independently as functions of the spatial and temporal frequencies, suggesting that the two thresholds represent the activity of two independent systems of channels.3. The channels detecting flicker prefer low and medium spatial frequencies. They have a pronounced decline in sensitivity at low temporal frequencies of sinusoidal modulation. They respond twice as well to gratings whose phase is alternated repetitively as to gratings turned on and off at the same rate.4. The channels responsible for the discrimination of spatial structure are most responsive at high and medium spatial frequencies. There is no decline in sensitivity at low temporal frequencies. These channels respond equally well to alternating and on/off gratings up to about 8 Hz.5. The temporal properties as revealed with sinusoidal modulation, suggest that the flicker-detecting channels would give transient responses to prolonged presentation of stimuli: the channels responsible for analysing the spatial structure would give sustained responses. The responses of the two types of channel to alternating and on/off gratings confirm this suggestion.

Flicker Fusion↗
PubMed1972

Adaptation to square-wave gratings: inhibition between spatial frequency channels in the human visual system.

1. The observation that the detection threshold for a square-wave grating depends only on that of its fundamental was confirmed by showing that adapting to the fundamental spatial frequency caused elevation of the square-wave threshold, to the same extent as the fundamental threshold was elevated by the same adapting pattern. Adapting to the third harmonic frequency had no effect on the square-wave threshold.2. Adapting to a square-wave grating should elevate the thresholds for both the fundamental and third harmonic frequencies (Blakemore & Campbell, 1969), and the amount of elevation at each frequency should be predictable from the contrast of that frequency within the square-wave.3. It was found, however, that both the fundamental and third harmonic, when present in the square-wave, were much less effective as suprathreshold adapting stimuli than would be predicted from their effects when viewed in isolation.4. Adapting to a mixture of two sinusoidal gratings (with 3:1 frequency ratio) demonstrated that the fall in adapting power was not due to the higher harmonics of the square-wave nor to nonlinearities in the stimulus display. Similar effects were found when the phase relations of the adapting gratings were changed, showing that the interaction is not a special property of square-waves or of edges.5. It is suggested that the spatial frequency channels subserving the fundamental and third harmonic frequencies inhibit each other when the patterns are some way suprathreshold. At or near threshold, there is no such reciprocal inhibition.

Adaptation, Ocular↗
PubMedDate not supplied

Contrast normalization and a linear model for the directional selectivity of simple cells in cat striate cortex.

Previous tests of the linearity of spatiotemporal summation in cat simple cells have compared the responses to moving sinusoidal gratings and to gratings whose contrast was modulated sinusoidally in time. In particular, since a moving grating can be expressed as a sum of modulated gratings, the response to a moving grating should be predictable (assuming linearity) from the responses to modulated gratings. However, these simple linear predictions have shown varying degrees of failure (e.g. Reid et al., 1987, 1991), depending on the directional selectivity of the neurons (Tolhurst & Dean, 1991). We demonstrate here that the failures of these linear predictions are, in fact, explained by the contrast-normalization model of Heeger (1993). We concentrate on the ratio of the measured to predicted moving grating responses. In the context of the contrast-normalization model, calculating this ratio turns out to be particularly appropriate, since the ratio is independent of the precise details of the linear front-end mechanisms ultimately responsible for directional selectivity. Hence, the contrast-normalization model can be compared quantitatively with this ratio measure, by varying only one free parameter. When account is taken both of the expansive output nonlinearity and of contrast normalization, the directional selectivity of simple cells seems to be dependent only on linear spatiotemporal filtering.

Animals↗
PubMedDate not supplied

Comparison of contrast-normalization and threshold models of the responses of simple cells in cat striate cortex.

In almost every study of the linearity of spatiotemporal summation in simple cells of the cat's visual cortex, there have been systematic mismatches between the experimental observations and the predictions of the linear theory. These mismatches have generally been explained by supposing that the initial spatiotemporal summation stage is strictly linear, but that the following output stage of the simple cell is subject to some contrast-dependent nonlinearity. Two main models of the output nonlinearity have been proposed: the threshold model (e.g. Tolhurst & Dean, 1987) and the contrast-normalization model (e.g. Heeger, 1992a,b). In this paper, the two models are fitted rigorously to a variety of previously published neurophysiological data, in order to determine whether one model is a better explanation of the data. We reexamine data on the interaction between two bar stimuli presented in different parts of the receptive field; on the relationship between the receptive-field map and the inverse Fourier transform of the spatial-frequency tuning curve; on the dependence of response amplitude and phase on the spatial phase of stationary gratings; on the relationships between the responses to moving and modulated gratings; and on the suppressive action of gratings moving in a neuron's nonpreferred direction. In many situations, the predictions of the two models are similar, but the contrast-normalization model usually fits the data slightly better than the threshold model, and it is easier to apply the equations of the normalization model. More importantly, the normalization model is naturally able to account very well for the details and subtlety of the results in experiments where the total contrast energy of the stimuli changes; some of these phenomena are completely beyond the scope of the threshold model. Rigorous application of the models' equations has revealed some situations where neither model fits quite well enough, and we must suppose, therefore, that there are some subtle nonlinearities still to be characterized.

Animals↗
PubMedDate not supplied

Contrast constancy in natural scenes in shadow or direct light: A proposed role for contrast-normalisation (non-specific suppression) in visual cortex.

The range of contrasts in natural scenes is generally thought to far exceed the limited dynamic ranges of individual contrast-encoding neurons in the primary visual cortex. The visual system may employ gain-control mechanisms (Ohzawa et al. 1985) to compensate for the mismatch between the range of natural contrast energies and the limited dynamic range of visual neurons; one proposed mechanism is contrast normalisation or non-specific suppression (Heeger 1992a). This paper aims to evaluate the role of contrast normalisation in human contrast perception, using a computer model of primary visual cortex. The model uses orthogonal pairs of Gabor patches to simulate simple-cell receptive-fields to calculate local, band-limited contrast in a series of 50 digitised photographs of natural scenes. The average range of contrast energies in each image was 2.29 log units, while the "lifetime range" each model simple cell would see across all images was 2.98 log units. These ranges are greater than the dynamic range of real mammalian simple cells. Contrast normalisation (dividing contrast responses by the summed responses of all nearby neurons) reduces contrast ranges, perhaps sufficiently to match them to neurons' limited dynamic ranges. Comparison of images taken under diffuse and direct lighting conditions showed that contrast normalisation can sometimes match these conditions effectively. This may lead to perceptual contrast constancy in the face of spurious changes in contrast caused by natural environmental conditions.

Computer Simulation↗