Biomedical subjects

Wolfgang Einhäuser

Publications and source records attributed to Wolfgang Einhäuser.

10 recordsLinked to original sources

PubMed2006

The relation of phase noise and luminance contrast to overt attention in complex visual stimuli.

Models of attention are typically based on difference maps in low-level features but neglect higher order stimulus structure. To what extent does higher order statistics affect human attention in natural stimuli? We recorded eye movements while observers viewed unmodified and modified images of natural scenes. Modifications included contrast modulations (resulting in changes to first- and second-order statistics), as well as the addition of noise to the Fourier phase (resulting in changes to higher order statistics). We have the following findings: (1) Subjects' interpretation of a stimulus as a "natural" depiction of an outdoor scene depends on higher order statistics in a highly nonlinear, categorical fashion. (2) Confirming previous findings, contrast is elevated at fixated locations for a variety of stimulus categories. In addition, we find that the size of this elevation depends on higher order statistics and reduces with increasing phase noise. (3) Global modulations of contrast bias eye position toward high contrasts, consistent with a linear effect of contrast on fixation probability. This bias is independent of phase noise. (4) Small patches of locally decreased contrast repel eye position less than large patches of the same aggregate area, irrespective of phase noise. Our findings provide evidence that deviations from surrounding statistics, rather than contrast per se, underlie the well-established relation of contrast to fixation.

Adult↗

PubMed2005

Differences of monkey and human overt attention under natural conditions.

Rhesus monkeys are widely used as animal models of human attention. Such research rests upon the assumption that similar mechanisms underlie attention in both species. Here, we directly compare the influence of low-level stimulus features on overt attention in monkeys and humans under natural conditions. We recorded eye-movements in humans and rhesus monkeys during free-viewing of natural images. We find that intrinsic low-level features, such luminance-contrast, texture-contrast and saliency-as predicted by a standard model, are elevated at fixation points in the majority of images. These correlative effects are not significantly different between species. However, local image modifications affect both species differently: moderate modifications, which are in the range of natural fluctuations, attract overt attention in monkeys significantly stronger than they do in humans. In addition, humans show a higher inter-individual consistency regarding which locations they fixate than monkeys, in spite of the similarity for intrinsic low-level features. Taken together, these data demonstrate that-under natural conditions-low-level stimulus features affect attention in monkeys and humans differently.

Animals↗

PubMed2005

Learning viewpoint invariant object representations using a temporal coherence principle.

Invariant object recognition is arguably one of the major challenges for contemporary machine vision systems. In contrast, the mammalian visual system performs this task virtually effortlessly. How can we exploit our knowledge on the biological system to improve artificial systems? Our understanding of the mammalian early visual system has been augmented by the discovery that general coding principles could explain many aspects of neuronal response properties. How can such schemes be transferred to system level performance? In the present study we train cells on a particular variant of the general principle of temporal coherence, the "stability" objective. These cells are trained on unlabeled real-world images without a teaching signal. We show that after training, the cells form a representation that is largely independent of the viewpoint from which the stimulus is looked at. This finding includes generalization to previously unseen viewpoints. The achieved representation is better suited for view-point invariant object classification than the cells' input patterns. This property to facilitate view-point invariant classification is maintained even if training and classification take place in the presence of an--also unlabeled--distractor object. In summary, here we show that unsupervised learning using a general coding principle facilitates the classification of real-world objects, that are not segmented from the background and undergo complex, non-isomorphic, transformations.

Action Potentials↗

PubMed2004

The world from a cat's perspective--statistics of natural videos.

The mammalian visual system is one of the most intensively investigated sensory systems. However, our knowledge of the typical input it is operating on is surprisingly limited. To address this issue, we seek to learn about the natural visual environment and the world as seen by a cat. With a CCD camera attached to their head, cats explore several outdoor environments and videos of natural stimuli are recorded from the animals' perspective. The statistical analysis of these videos reveals several remarkable properties. First, we find an anisotropy of oriented contours with an enhanced occurrence of horizontal orientations, earlier described in the "oblique effect" as a predominance of the two cardinal orientations. Second, contrast is not elevated in the center of the images, suggesting different mechanisms of fixation point selection as compared to humans. Third, analyzing a sequence of images we find that the precise position of contours varies faster than their orientation. Finally, collinear contours prevail over parallel shifted contours, matching recent physiological and anatomical results. These findings demonstrate the rich structure of natural visual stimuli and its direct relation to extensively studied anatomical and physiological issues.

Animals↗

PubMed2004

Are switches in perception of the Necker cube related to eye position?

The issue of the relation of eye position to perceptual reversals of the ambiguous figure of the 'Necker cube' dates back to Necker's original article [L.A. Necker (1832) The London & Edinburgh Philosophical Magazine and Journal of Science, 1, 329-337]. Despite the investigations of many distinguished psychophysicists since then, the question of whether perceptual switching is a cause or a consequence of associated changes in eye position has remained a matter of debate. In the present study we overcame methodological problems that have bedevilled many previous studies. We avoided any instruction that could interfere with the human subjects' free viewing of the Necker cube, tracked the eye position precisely and used biased versions of the cube that produced unambiguous percepts to determine how each subject actually looked at the cube. We show that, under these free-viewing conditions, there is a close link between the perception of the Necker cube and eye position. The average eye position of most subjects is at an extreme value at about the time when the subject's perception switches. From the biased cube trials we can infer that the polarity of the extreme corresponds to the percept which the subject had before the switch. These data indicate a bidirectional coupling between eye position and perceptual switching so that, after a subject's perceptual state changes, their eye position shifts to view the newly established percept. When the eye position approaches the corresponding extreme, the percept, in turn, becomes more and more likely to switch. This result suggests that the changed eye position itself might provide a negative feedback signal that suppresses the percept.

Adult↗

PubMed2003

How are complex cell properties adapted to the statistics of natural stimuli?

Sensory areas should be adapted to the properties of their natural stimuli. What are the underlying rules that match the properties of complex cells in primary visual cortex to their natural stimuli? To address this issue, we sampled movies from a camera carried by a freely moving cat, capturing the dynamics of image motion as the animal explores an outdoor environment. We use these movie sequences as input to simulated neurons. Following the intuition that many meaningful high-level variables, e.g., identities of visible objects, do not change rapidly in natural visual stimuli, we adapt the neurons to exhibit firing rates that are stable over time. We find that simulated neurons, which have optimally stable activity, display many properties that are observed for cortical complex cells. Their response is invariant with respect to stimulus translation and reversal of contrast polarity. Furthermore, spatial frequency selectivity and the aspect ratio of the receptive field quantitatively match the experimentally observed characteristics of complex cells. Hence, the population of complex cells in the primary visual cortex can be described as forming an optimally stable representation of natural stimuli.

Animals↗

PubMed2003

Does luminance-contrast contribute to a saliency map for overt visual attention?

In natural environments, humans select a subset of visual stimuli by directing their gaze to locations attended. In previous studies it has been found that at fixation points luminance-contrast is higher than average. This led to the hypothesis that luminance-contrast makes a major contribution to a saliency map of visual overt attention, consistent with a computation of stimulus saliency in early visual cortical areas. We re-evaluate this hypothesis by using natural and modified natural images to uncover the causal effects of luminance-contrast to human overt visual attention and: (i) we confirm that when viewing natural images, contrasts are elevated at fixation points. This, however, only holds for low spatial frequencies and in a limited temporal window after stimulus onset; (ii) however, despite this correlation between overt attention and luminance-contrast, moderate modifications of contrast in natural images do not measurably affect the selection of fixation points. Furthermore, strong local reductions of luminance-contrast do not repel but attract fixation; (iii) neither contrast nor contrast modification is correlated to fixation duration; and (iv), even the moderate contrast modifications used fall into the physiologically relevant range, and subjects are well able to detect them in a forced choice paradigm. In summary, no causal contribution of luminance-contrast to a saliency map of human overt attention is detectable. In conjunction with recent results on the relation of contrast sensitivity of neuronal activity to the level in the visual cortical hierarchy, the present study provides evidence that, for natural scenes, saliency is computed not early but late during processing.

Adult↗

PubMed2003

Learning distinct and complementary feature selectivities from natural colour videos.

Many biological and artificial neural networks require the parallel extraction of multiple features, and meet this requirement with distinct populations of neurons that are selective to one property of the stimulus while being non-selective to another property. In this way, several populations can resolve a set of features independently of each other, and thus achieve a parallel mode of processing. This raises the question how an initially homogeneous population of neurons segregates into groups with distinct and complementary response properties. Using a colour image sequence recorded from a camera mounted on the head of a freely behaving cat, we train a network of neurons to achieve optimally stable responses, that is, responses that change minimally over time. This objective leads to the development of colour-selective neurons. Adding a second objective, decorrelating activity within the network, a subpopulation of neurons develops with achromatic response properties. Colour selective neurons tend to be non-oriented while achromatic neurons are orientation-tuned. The proposed objective thus successfully leads to the segregation of neurons into complementary populations that are either selective for colour or orientation.

Animals↗

PubMed2002

Learning the invariance properties of complex cells from their responses to natural stimuli.

Neurons in primary visual cortex are typically classified as either simple or complex. Whereas simple cells respond strongly to grating and bar stimuli displayed at a certain phase and visual field location, complex cell responses are insensitive to small translations of the stimulus within the receptive field [Hubel & Wiesel (1962) J. Physiol. (Lond.), 160, 106-154; Kjaer et al. (1997) J. Neurophysiol., 78, 3187-3197]. This constancy in the response to variations of the stimuli is commonly called invariance. Hubel and Wiesel's classical model of the primary visual cortex proposes a connectivity scheme which successfully describes simple and complex cell response properties. However, the question as to how this connectivity arises during normal development is left open. Based on their work and inspired by recent physiological findings we suggest a network model capable of learning from natural stimuli and developing receptive field properties which match those of cortical simple and complex cells. Stimuli are drawn from videos obtained by a camera mounted to a cat's head, so they should approximate the natural input to the cat's visual system. The network uses a competitive scheme to learn simple and complex cell response properties. Employing delayed signals to learn connections between simple and complex cells enables the model to utilize temporal properties of the input. We show that the temporal structure of the input gives rise to the emergence and refinement of complex cell receptive fields, whereas removing temporal continuity prevents this processes. This model lends a physiologically based explanation of the development of complex cell invariance response properties.

Animals↗

PubMedDate not supplied

Learning of somatosensory representations for texture discrimination using a temporal coherence principle.

In order to perform appropriate actions, animals need to quickly and reliably classify their sensory input. How can representations suitable for classification be acquired from statistical properties of the animal's natural environment? Akin to behavioural studies in rats, we investigate this question using texture discrimination by the vibrissae system as a model. To account for the rat's active sensing behaviour, we record whisker movements in a hardware model. Based on these signals, we determine the response of primary neurons, modelled as spatio-temporal filters. Using their output, we train a second layer of neurons to optimise a temporal coherence objective function. The performance in classifying textures using a single cell strongly correlates with the cell's temporal coherence; hence output cells outperform primary cells. Using a simple, unsupervised classifier, the performance on the output cell population is same as if using a sophisticated supervised classifier on the primary cells. Our results demonstrate that the optimisation of temporal coherence yields a representation that facilitates subsequent classification by selectively conveying relevant information.

Animals↗