Biomedical subjects

A C den Brinker

Publications and source records attributed to A C den Brinker.

5 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↗

PubMed1991

A pseudomatched filter model applied to the transient system of human vision.

A pseudomatched filter configuration is presented as a model for the transient system of the human visual perception. This model has resemblances to the Reichardt [1] and the Rashbass [2] model, but on the other hand the pseudomatched filter model is linear. The choice of the model is based on the shape of the psychophysically measured impulse response and on physiological and functional arguments. The parameters of the model are estimated for different data sets. The behavior of the model agrees with the experimental data in all essential aspects, and can be used for prediction and further modeling of the human visual system.

Confidence Intervals↗

PubMed1990

Changes with background in the linear model of the transient visual system.

There is evidence that the transient channel of temporal human vision behaves as a linear filter for small excursions around a steady background level. The linear filter characteristics depend on the background level. From experimentally obtained impulse responses of the transient channel the linear filter can be modelled and parametrized. This has been done for two different background levels. The two sets of estimated parameters at these two levels show a shift in the parameters which can be described by a single multiplication factor. This result was extrapolated to arbitrary background levels by postulating that each change in background level can be described by a multiplication factor. This leads to an assumption on the variation of the parameters of the linear filter of the transient channel with changes in the background level. This assumption is tested by simulating the system for different parameter sets of the linear filter. The simulations give a good agreement with experimental data on threshold-versus-duration curves and de Lange curves. The (minor) quantitative differences in simulations and experimental data can be explained.

Computer Simulation↗

PubMed1989

A comparison of results from parameter estimations of impulse responses of the transient visual system.

Parameter estimations of a fourth-order linear model are applied to data from subthreshold measurements of impulse responses of the transient visual system. These impulse responses were obtained experimentally by several subjects, at two different background luminance levels and for different field sizes. The parameter estimations show consistent results over different subjects. For both different background levels and field sizes there are consequent changes in the estimated parameters. On the basis of these changes a proposal is made for a spatiotemporal model of the transient visual system.

Humans↗

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↗