Biomedical subjects

U Mortensen

Publications and source records attributed to U Mortensen.

6 recordsLinked to original sources

PubMed2002

Additive noise, Weibull functions and the approximation of psychometric functions.

The Weibull function is frequently chosen to define psychometric functions. Tyler and Chen (Vis. Res. 40 (2000) 3121) criticised the high-threshold postulate implied by the Weibull function and argued that this function implies the assumption of multiplicative noise. It will be shown in this paper that in fact the Weibull function is compatible with the assumption of additive noise, and that the Weibull function may be generalised to the case of detection not being high threshold. The derivations rest, however, on a representation of sensory activity lacking a satisfying degree of generality. Therefore, a more general representation of sensory activity in terms of stochastic processes will be suggested, with detection being defined as a level-crossing process, containing the original representation as a special case. Two classes of stochastic processes will be considered: one where the noise is assumed to be additive, stationary Gaussian, and another resulting from cascaded Poisson processes, representing a form of multiplicative noise. While Weibull functions turn out to approximate well psychometric functions generated by both types of stochastic processes, it also becomes obvious that there is no simple interpretation of the parameters of the fitted Weibull functions. Moreover, corresponding to Tyler and Chen's discussion of the role of multiplicative noise particular sources of this type of noise will be considered and shown to be compatible with the Weibull. It is indicated how multiplicative noise may be defined in general; however, it will be argued that in the light of certain empirical data the role of this type of noise may be negligible in most detection tasks.

Contrast Sensitivity↗

PubMed2001

Detection of simple radially symmetric targets: further evidence for the matched filter processing scheme in human pattern detection.

The detection of small radially symmetric targets was studied using a subthreshold summation paradigm. Small disc and disc-like patterns with diameters up to 0.60 were used for superposition on Bessel functions of zero order, subthreshold contrast and various spatial frequencies. Contrast interrelation functions prove linear over the whole range of contrasts used for the Bessel functions while their slopes show systematic variation with spatial frequency. An extrapolation of sensitivity from the slopes reveals that sensitivity can be predicted by a simple model assuming detection to be mediated by a transfer function made up as a cascade of an even bandpass function and the disc pattern spectrum, as has been found previously using one dimensional luminance distributions. Problems concerning the formation of pattern-specific radial symmetric filters are discussed.

Contrast Sensitivity↗

PubMed2000

Visual channels, Hebbian assemblies and the effect of Hebb's rule.

A model of sensory learning is proposed that is based upon Hebb's rule, where Hebb's rule has been generalised by introducing a stabilising function representing some feedback process within or at the adapting (cortical) neuron, preventing synaptic weights from increasing without limit. It will be shown that neurons adapting according to this stabilised Hebb rule will turn into a matched filter for that part of the stimulus pattern that covers the receptive field of a neuron. It follows that the presentation of a stimulus pattern may imply the formation of a set of neurons with overlapping receptive fields, where each neuron has adapted to a certain part of the stimulus. Making simplifying assumptions about the detection process, the model will be illustrated, fitting it to data from Meinhardt and Mortensen [Meinhardt G, Mortensen U (1998) Biol Cybern 79:413425] which are not compatible with the classical matched filter model introduced by Hauske et al.

Action Potentials↗

PubMed1998

Detection of aperiodic test patterns by pattern specific detectors revealed by subthreshold summation.

The hypothesis that the visual system detects, under certain conditions, stimulus patterns by means of filters matched to these patterns (Hauske et al. 1976) may be challenged by the argument that other coding mechanisms like spatial frequency channels, Gabor or Hermite filters mimic the behaviour of matched filters, a view supported by the finding of non-linear contrast-interrelationship functions (CIFs), as determined in superposition experiments. In this paper we argue that an overall non-linear CIF does not contradict the hypothesis of detection by a single matched filter: we find that the sensitivity functions determined in our experiments can be separated into two components reflecting (i) a bandpass filter and (ii) a filter characterized by the spectrum of the test-pattern.

Animals↗

PubMed1991

An evaluation of sensory noise in the human visual system.

It is assumed that the activity of a visual channel may be represented as V(t) = g(t) + xi(t), where g(t) is the deterministic response of the channel due to the presentation of a stimulus and xi(t) is the trajectory of a wide-sense stationary Gauss process. The stimulus is detected if the event (V(t) greater than S for at least one t epsilon[0, T]) occurs. Two approximations for the probability of this event are proposed, and it is demonstrated how they may be employed to estimate (i) the value of the second spectral moment lambda 2 of the noise process xi t, where lambda 2 reflects the speed of the fluctuations of the trajectories xi(t), and (ii) the value of the internal threshold S. The commonly made assumption of peak--detection is shown to serve as a very good first approximation in particular if the channel is of transient type or--in case of detection by a channel of sustained type--if the stimulus durations are not too long.

Humans↗

PubMed1988

Visual contrast detection by a single channel versus probability summation among channels.

It is now generally accepted that the human visual system consists of subsystems ("channels") that may be activated in parallel. According to some models of detection, detection is by probability summation among channels, while in other models it is assumed that detection is by a single channel that may even be tuned specifically to the stimulus pattern (detection by a matched filter). So far, arguments in particular for the hypothesis of probability summation are based on plausibility considerations and on demonstrations that the data from certain detection experiments are compatible with this hypothesis. In this paper it is shown that linear contrast interrelationship functions together with a property of a large class of distribution functions (strict log-concavity or log-convexity on the relevant set of contrasts/intensities) uniquely point to detection by a single channel. In particular, models of detection by probability summation based on Quick's Model are incompatible with linear contrast interrelationship functions. Sufficient (and observable) conditions for the strict log-concavity/log-convexity of distribution functions are presented.

Humans↗