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J A Roufs

Publications and source records attributed to J A Roufs.

14 recordsLinked to original sources
PubMed1992

Evidence for a generalized Laguerre transform of temporal events by the visual system.

It is generally assumed that the early visual processing is constituted by a set of filters operating in parallel. In this respect the visual system performs a transform, generating a code of the characteristics of the input signal. Recently, it has been suggested that the coding of the spatial characteristics by the visual system can be described by a Hermite transform (Martens, 1990a, b). It was also suggested that a three-dimensional Hermite transform can be used to code spatiotemporal events. In contrast to this latter suggestion, we argue that the coding of temporal events takes the form of a generalized Laguerre transform. We review psychophysical evidence supporting this hypothesis.

Algorithms↗
PubMed1989

Nonlinear parameter estimation applied to psychophysically measured impulse responses.

A technique is presented for the estimation of the impulse response, based on data from a psychophysical experiment on threshold vision. A two-step method is used for the estimation of the model parameters. The first step is a Hankel matrix approach, and the second an unweighted least squares method. Results of this estimation technique are presented. The model with the estimated parameters corroborates other psychophysical data. The estimates obtained are adequate for the intended purposes of simulation and modeling.

Mathematics↗
PubMed1987

Prediction of thresholds and latency on the basis of experimentally determined impulse responses.

As was shown before (Roufs and Blommaert 1981), temporal impulse responses and step responses can be obtained psychophysically using a drift-correcting perturbation technique. In this paper, experimentally determined impulse responses are given for eight subjects using different experimental conditions, i.e. a 1 deg stimulus field at background luminances of 1200 Td and 100 Td, and a point source superimposed on an extended background of the same luminances, which is a possibility to separate transient and sustained processing. For a large class of stimuli, predictions of threshold curves and latency of different time functions are calculated on the basis of these measured impulse responses. Predictions are tested against experimental data. It will be shown that a simple model, only consisting of a linear filter followed by a noisy peak detector, suffices for a fair quantitative description of the available data.

Humans↗
PubMed1987

Point spread functions and detail detection.

Point spread functions, intended to characterize local spatial transfer of the visual system, can be obtained psychophysically using a perturbation technique. Data of such point spread functions are shown for three experimental conditions: foveally at adaptation levels of 1200 and 10 Td, and in the parafovea at an eccentricity of 2 deg using a 1200 Td adaptation level. The results are consistent with earlier findings (Blommaert, F. J.J. and Roufs, J.A.J. 1981, Vision Res. 21, 1223-1233). On the basis of such point spread functions a simplified multiple unit model was constructed, the parameters of which were fitted to thresholds of discs with varying diameter. Threshold predictions from this model for annuli, thin lines and broad lines were found to be in fair quantitative agreement with experimental results. It is argued that for a certain class of slender stimuli, including alphanumeric characters, thresholds can be described with a single channel model containing only the experimentally determined point spread function as a basic component.

Humans↗
PubMed1980

Instabilities in a continuous medium model for the retina.

The shape of the spatial response of the retina on a small light stimulus as found by Rodieck (1965) for the cat, and proposed for the human retina among others by Korn and von Seelen (1972), resembles a Mexican hat known as a sombrero. A model presented by Röhler (1976), using a continuous medium as a description of the retina, can lead to such a "Mexican hat" response function for a specific choice of parameters. The spatial Fourier transform of this response function has a general appearance that corresponds to that calculated for stationary signals. However, such an analysis of the model for stationary signals is incomplete. Inspection of the time-dependent equations shows that it is unstable precisely for those parameter values that give the stationary response function its desired shape. Such stationary situations cannot be physically realized since the model is unstable.

Animals↗