Perceptual dominance time distributions in multistable visual perception

Perceptual multistability, alternative perceptions of an unchanging stimulus, gives important clues to neural dynamics. The present study examined 56 perceptual dominance time series for a Necker cube stimulus, for ambiguous motion, and for binocular rivalry. We made histograms of the perceptual dominance times, based on from 307 to 2478 responses per time series (median=612), and compared these histograms to gamma, lognormal and Weibull fitted distributions using the Kolmogorov–Smirnov goodness-of-fit test. In 40 of the 56 tested cases a lognormal distribution provided an acceptable fit to the histogram (in 24 cases it was the only fit). In 16 cases a gamma distribution, and in 11 cases a Weibull distribution, were acceptable but never as the only fit in either case. Any of the three distributions were acceptable in three cases and none provided acceptable fits in 12 cases. Considering only the 16 cases in which a lognormal distribution was rejected (p<0.05) revealed that minor adjustments to the fourth-moment term of the lognormal characteristic function restored good fits. These findings suggest that random fractal theory might provide insight into the underlying mechanisms of multistable perceptions.     

Continuous phase transitions in the perception of multistable visual patterns

The phenomenon of stroboscopic alternative motion exhibits five different percepts that are seen with an increase in the frequency of presentation: (a) succession, (b) fluttering motion, (c) reversible clockwise and counter-clockwise turning motion, (d) oppositional motion and (e) simultaneity. From a synergetic point of view the increase in frequency is a control parameter and the different percepts are order parameters with phase transitions in between. The neural network model of Carmesin and Arndt is applied to receive predictions about hysteresis and phase transitions between these order parameters. Empirical data show the different motion percepts (b), (c) and (e) have lognormal distributions. Following the theoretical model, it is argued that there are three different phases, (a), (c) and (e), with two continuous phase transitions, (b) and (d), between them. The experimental data substantially match the theoretical ssumptions. Received: 29 December 1995 / Accepted in revised form: 3 June 1996     

A model of visual perception

In this paper we propose a model of visual perception in which a positive feedback mechanism can reproduce the pattern stimulus on a neurons screen. The pattern stimulus reproduction is based on informations coming from the spatial derivatives of visual pattern. This information together with the response of the feature extractors provides to the reproduction of the visual pattern as neuron screen electric activity. We simulate several input patterns and prove that the model reproduces the percept.     

Mathematical model of visual perception

A mathematical model of visual perception is presented with the intention of throwing some light on the problem of perceptual invariance. Two types of differential manifolds (receptive and effector) are associated with the repertoire which is the fundamental concept in the model. The elements of the repertoire carry weights which control the input-output relation in the repertoire and which can be modified by a learning process. It is shown that, under reasonable conditions, these repertoires possess good stability properties and can adjust to the various environments to which they may be subjected. In particular cases, it is shown that the stochastic learning process can be considered as deterministic to a first approximation.     

Camouflage and visual perception

How does an animal conceal itself from visual detection by other animals? This review paper seeks to identify general principles that may apply in this broad area. It considers mechanisms of visual encoding, of grouping and object encoding, and of search. In most cases, the evidence base comes from studies of humans or species whose vision approximates to that of humans. The effort is hampered by a relatively sparse literature on visual function in natural environments and with complex foraging tasks. However, some general constraints emerge as being potentially powerful principles in understanding concealment—a ‘constraint’ here means a set of simplifying assumptions. Strategies that disrupt the unambiguous encoding of discontinuities of intensity (edges), and of other key visual attributes, such as motion, are key here. Similar strategies may also defeat grouping and object-encoding mechanisms. Finally, the paper considers how we may understand the processes of search for complex targets in complex scenes. The aim is to provide a number of pointers towards issues, which may be of assistance in understanding camouflage and concealment, particularly with reference to how visual systems can detect the shape of complex, concealed objects.     

Music alters visual perception

Background

Visual perception is not a passive process: in order to efficiently process visual input, the brain actively uses previous knowledge (e.g., memory) and expectations about what the world should look like. However, perception is not only influenced by previous knowledge. Especially the perception of emotional stimuli is influenced by the emotional state of the observer. In other words, how we perceive the world does not only depend on what we know of the world, but also by how we feel. In this study, we further investigated the relation between mood and perception.

Methods and Findings

We let observers do a difficult stimulus detection task, in which they had to detect schematic happy and sad faces embedded in noise. Mood was manipulated by means of music. We found that observers were more accurate in detecting faces congruent with their mood, corroborating earlier research. However, in trials in which no actual face was presented, observers made a significant number of false alarms. The content of these false alarms, or illusory percepts, was strongly influenced by the observers'' mood.

Conclusions

As illusory percepts are believed to reflect the content of internal representations that are employed by the brain during top-down processing of visual input, we conclude that top-down modulation of visual processing is not purely predictive in nature: mood, in this case manipulated by music, may also directly alter the way we perceive the world.     

Attention and visual perception

Somewhere between the retina and our conscious visual experience, the majority of the information impinging on the eye is lost. We are typically aware of only either the most salient parts of a visual scene or the parts that we are actively paying attention to. Recent research on visual neurons in monkeys is beginning to show how the brain both selects and discards incoming visual information. For example, what happens to the responses of visual neurons when attention is directed to one element, such as an oriented colored bar, embedded among an array of other oriented bars? Some of this research shows that attention to the oriented bar restricts the receptive field of visual neurons down to this single element. However, other research shows that attention to this single element affects the responses of neurons with receptive fields throughout the visual field. In this review, these two seemingly contradictory results are shown to actually be mutually consistent. A simple computational model is described that explains these results, and also provides a framework for predicting a variety of additional neurophysiological, neuroimaging and behavioral studies of attention.     

The physics of visual perception

By measuring the contrast threshold for gratings of different waveform and spatial frequency, Campbell & Robson suggested in 1968 that there may be 'channels' tuned to different spatial frequencies. By using the technique of adapting to a high contrast grating, it was possible to measure the band-pass characteristics of these channels. Similar techniques were used to establish the orientational tuning of the channels. Reasons are put forward why it is advantageous to organize the visual system in this manner.     

A comparative psychophysical approach to visual perception in primates

Studies on the visual processing of primates, which have well developed visual systems, provide essential information about the perceptual bases of their higher-order cognitive abilities. Although the mechanisms underlying visual processing are largely shared between human and nonhuman primates, differences have also been reported. In this article, we review psychophysical investigations comparing the basic visual processing that operates in human and nonhuman species, and discuss the future contributions potentially deriving from such comparative psychophysical approaches to primate minds.     

A simple stochastic gene substitution model

If the fitnesses of n haploid alleles in a finite population are assigned at random and if the alleles can mutate to one another, and if the population is initially fixed for the kth most fit allele, then the mean number of substitutions that will occur before the most fit allele is fixed is shown to be

$\text{1}\text{2}\text{+}\text{1}\text{k}\text{+}\text{∑}\text{i=2}\text{k?1}\text{(i+3)}\text{(2i(i+1))}$

when selection is strong and mutation is weak. This result is independent of the parameters that went into the model. The result is used to provide a partial explanation for the large variance observed in the rates of molecular evolution.     

A one-compartment model with stochastic parameter

We consider a one-compartment system with stochastic transfer rate characterized either by Gaussian or by two-level jump process and study the time evolution of the (statistical) moments of the (random) amount of the substance present in the system. The effect of the coloured as well as of the white noise is investigated and it is found that the presence of stochasticity in the transfer rate parameter increases the relaxation time of the system. Finally, we obtain the conditions for the stability of the system in the moment sense.     

A stochastic model in tumor growth

A stochastic model of solid tumor growth based on deterministic Gompertz law is presented. Tumor cells evolution is described by a one-dimensional diffusion process limited by two absorbing boundaries representing healing threshold and patient death (carrying capacity), respectively. Via a numerical approach the first exit time problem is analysed for the process inside the region restricted by the boundaries. The proposed model is also implemented to simulate the effects of a time-dependent therapy. Finally, some numerical results are obtained for the specific case of a parathyroid tumor.     

A stochastic model for cancer risk

We propose a simple stochastic model based on the two successive mutations hypothesis to compute cancer risks. Assume that only stem cells are susceptible to the first mutation and that there are a total of D stem cell divisions over the lifetime of the tissue with a first mutation probability mu(1) per division. Our model predicts that cancer risk will be low if m = mu(1)D is low even in the case of very advantageous mutations. Moreover, if mu(1)D is low the mutation probability of the second mutation is practically irrelevant to the cancer risk. These results are in contrast with existing models but in agreement with a conjecture of Cairns. In the case where m is large our model predicts that the cancer risk depends crucially on whether the first mutation is advantageous or not. A disadvantageous or neutral mutation makes the risk of cancer drop dramatically.     

Internal models for visual perception

 Although the extrapolation of past perceptual history into the immediate and distant future is a fundamental phenomenon in everyday life, the underlying processing mechanisms are not well understood. A network model consisting of interacting excitatory and inhibitory cell populations coding for stimulus position is used to study the neuronal population response to a continuously moving stimulus. An adaptation mechanism is proposed that offers the possibility to control and modulate motion-induced extrapolation without changing the spatial interaction structure within the network. Using an occluder paradigm, functional advantages of an internally generated model of a moving stimulus are discussed. It is shown that the integration of such a model in processing leads to a faster and more reliable recognition of the input stream and allows for object permanence following occlusion. The modeling results are discussed in relation to recent experimental findings that show motion-induced extrapolation. Received: 19 December 2001 / Accepted: 26 November 2002 / Published online: 3 April 2003 Correspondence to: W. Erlhagen (e-mail: wolfram.erlhagen@mct.uminho.pt) Acknowledgements. The author would like to thank D. Jancke for useful discussions and two anonymous reviewers for helpful comments and suggestions on a previous version of this paper. This research was supported by a European grant (IST-2000-29689) and by the Portuguese Science Foundation (POSI/SRI/38051/2001).