Different ways of modeling spatial-frequency uncertainty in visual signal detection

Inferior human signal-detection behavior compared with that of ideal observers has been explained by intrinsic uncertainty of the human observer with respect to certain signal parameters. One way to model this uncertainty is to assume that the observer simultaneously monitors multiple channels, corresponding to possible parameters. However, it is also conceivable to assume that an observer, uncertain about which channel to monitor, chooses a suboptimally tuned single filter. Finally, uncertainty may also cause the filter underlying a single channel to broaden. In this paper these different models are investigated with respect to spatial-frequency uncertainty for matched filters detecting Gabor signals. All three mechanisms predict a decrease in detection performance. However, it is shown that the resulting psychometric functions are different. While the slopes increase with uncertainty for the multiple-channel models, they decrease for a randomly chosen single channel. Broadening a single filter leads to parallel psychometric functions.     

Interhemispheric differences in the spatial-frequency description of images and the consequences for visual recognition

Visual perception of images transformed by spatial-frequency filtering was investigated in tachistoscopic experiments. Evidences have been received that the left hemisphere describes preferentially low harmonics of an image, and right hemisphere--the high ones. A hypothesis is suggested that these differences are based on different sizes of the receptive fields of cortical modules. Some consequences of the proposed model are discussed--the consequences for the invariance of visual recognition (innate invariance mechanisms in the left hemisphere and learned invariance in the right hemisphere) and for the methods of visual image classification (discriminant or structural methods in the left and right hemisphere respectively). Some data confirming these predictions are presented.     

Three processing characteristics of visual texture segmentation

Three mechanisms are outlined which are sufficient to determine texture segmentation or discrimination. They are: (1) convolution of detector profiles with the input image; (2) impletion, where the perceptual 'filling in' of the input surface occurs via a nonlinear filtering operation on each detector's output (3) grouping, where areas are segregated according to their differences in detector responses after impletion occurs. These mechanisms are compared with those proposed to occur in human visual texture discrimination.     

Pre-attentive segmentation in the primary visual cortex

The activities of neurons in primary visual cortex have been shown to be significantly influenced by stimuli outside their classical receptive fields. We propose that these contextual influences serve pre-attentive visual segmentation by causing relatively higher neural responses to important or conspicuous image locations, making them more salient for perceptual pop-out. These locations include boundaries between regions, smooth contours, and pop-out targets against backgrounds. The mark of these locations is the breakdown of spatial homogeneity in the input. for instance, at the border between two texture regions of equal mean luminance. This breakdown causes changes in contextual influences, often resulting in higher responses at the border than at surrounding locations. This proposal is implemented in a biologically based model of VI in which contextual influences are mediated by intra-cortical horizontal connections. The behavior of the model is demonstrated using examples of texture segmentation, figure-ground segregation, target-distractor asymmetry, and contour enhancement, and is compared with psychophysical and physiological data. The model predicts (1) how neural responses should be tuned to the orientation of nearby texture borders, (2) a set of qualitative constraints on the structure of the intracortical connections, and (3) stimulus-dependent biases in estimating the locations of the region borders by pre-attentive vision.     

Dynamic filtration of the expression pattern variability of Drosophila zygotic segmentation genes

Analysis of the quantitative data obtained by processing the confocal images showed that the initial variability of the expression pattern of Drosophila zygotic segmentation genes was strongly reduced by the onset of gastrulation. The following variability components were studied: the range of gene expression intensity in different embryos, the time and succession of the formation of expression domain, types of formation, and domain positioning. At the level of zygotic genes, the positioning error proved to be dynamically filtered with time.     

The time course of segmentation and cue-selectivity in the human visual cortex

Texture discontinuities are a fundamental cue by which the visual system segments objects from their background. The neural mechanisms supporting texture-based segmentation are therefore critical to visual perception and cognition. In the present experiment we employ an EEG source-imaging approach in order to study the time course of texture-based segmentation in the human brain. Visual Evoked Potentials were recorded to four types of stimuli in which periodic temporal modulation of a central 3° figure region could either support figure-ground segmentation, or have identical local texture modulations but not produce changes in global image segmentation. The image discontinuities were defined either by orientation or phase differences across image regions. Evoked responses to these four stimuli were analyzed both at the scalp and on the cortical surface in retinotopic and functional regions-of-interest (ROIs) defined separately using fMRI on a subject-by-subject basis. Texture segmentation (tsVEP: segmenting versus non-segmenting) and cue-specific (csVEP: orientation versus phase) responses exhibited distinctive patterns of activity. Alternations between uniform and segmented images produced highly asymmetric responses that were larger after transitions from the uniform to the segmented state. Texture modulations that signaled the appearance of a figure evoked a pattern of increased activity starting at ～143 ms that was larger in V1 and LOC ROIs, relative to identical modulations that didn't signal figure-ground segmentation. This segmentation-related activity occurred after an initial response phase that did not depend on the global segmentation structure of the image. The two cue types evoked similar tsVEPs up to 230 ms when they differed in the V4 and LOC ROIs. The evolution of the response proceeded largely in the feed-forward direction, with only weak evidence for feedback-related activity.     

Lower visual field advantage for motion segmentation during high competition for selection

A series of visual enumeration tasks were conducted investigating the role of the dorsal visual stream in motion segmentation. Cortical areas representing the lower visual field have greater connections with the parietal cortex and should therefore show an advantage for processes driven by the dorsal stream (Previc, 1990). We looked for differences in processing displays in the upper versus lower visual field when targets required segmentation from distractors in an enumeration task. In a baseline condition, random configurations of moving and static items were presented briefly (200 ms) to the upper or lower visual field. Fast and efficient enumeration took place both for moving targets and for static targets presented alone; there was no effect of visual field. In contrast, for moving targets, a lower visual field advantage was found when the inclusion of static distractors demanded segmentation by motion. This disappeared at the smaller display sizes when the targets were presented in canonical patterns. The results are consistent with segmentation of moving targets from static distractors being mediated by dorsal regions of the visual cortex, particularly under conditions of high load (non-canonical patterns). These regions show greater sensitivity to the lower visual field and to magnocellular-based input.     

A spherical model for orientation and spatial-frequency tuning in a cortical hypercolumn

A theory is presented of the way in which the hypercolumns in primary visual cortex (V1) are organized to detect important features of visual images, namely local orientation and spatial-frequency. Given the existence in V1 of dual maps for these features, both organized around orientation pinwheels, we constructed a model of a hypercolumn in which orientation and spatial-frequency preferences are represented by the two angular coordinates of a sphere. The two poles of this sphere are taken to correspond, respectively, to high and low spatial-frequency preferences. In Part I of the paper, we use mean-field methods to derive exact solutions for localized activity states on the sphere. We show how cortical amplification through recurrent interactions generates a sharply tuned, contrast-invariant population response to both local orientation and local spatial frequency, even in the case of a weakly biased input from the lateral geniculate nucleus (LGN). A major prediction of our model is that this response is non-separable with respect to the local orientation and spatial frequency of a stimulus. That is, orientation tuning is weaker around the pinwheels, and there is a shift in spatial-frequency tuning towards that of the closest pinwheel at non-optimal orientations. In Part II of the paper, we demonstrate that a simple feed-forward model of spatial-frequency preference, unlike that for orientation preference, does not generate a faithful representation when amplified by recurrent interactions in V1. We then introduce the idea that cortico-geniculate feedback modulates LGN activity to generate a faithful representation, thus providing a new functional interpretation of the role of this feedback pathway. Using linear filter theory, we show that if the feedback from a cortical cell is taken to be approximately equal to the reciprocal of the corresponding feed-forward receptive field (in the two-dimensional Fourier domain), then the mismatch between the feed-forward and cortical frequency representations is eliminated. We therefore predict that cortico-geniculate feedback connections innervate the LGN in a pattern determined by the orientation and spatial-frequency biases of feed-forward receptive fields. Finally, we show how recurrent cortical interactions can generate cross-orientation suppression.     

Masking efficiency as a function of stimulus onset asynchrony for spatial-frequency detection and identification

Detection and identification thresholds for grating targets were measured in the presence of a compound mask grating as a function of the stimulus onset asynchrony (SOA). The detection and identification SOA functions are both reversed U-shaped but they are not parallel. The detection-to-identification ratio is itself a reversed U-shaped function of SOA, even for stimuli two octaves apart, with a peak between +20 and +60 ms SOA (backward masking). It is argued that these results support the hypothesis according to which detection and identification are serial processes.     

Columnar architecture and computational anatomy in primate visual cortex: segmentation and feature extraction via spatial frequency coded difference mapping

Columnar architecture is a well established organizational principle for a variety of cortical systems. If two topographically mapped receptor systems, which receive slightly different views of the same physical stimulus, are interlaced as columns, then the difference map of the afferent inputs is coded within a spatial frequency channel of the resultant map. The difference map of the left and right retinal views of a three dimensensional scene contains cues for the binocular disparity of the objects in the scene. Physical objects which are located at a common distance from the observer will be represented by area's of difference mapping which possesss common cortical textural values. Thus, segmentation of the cortical representation of the visual scene by values of positional disparity may be accomplished by conventional monocular segmentation techniques, applied to the cortical representation.The difference map is carried by a spatial frequency modulation determined by the period of the columnar interlacing. Ocular dominance columns in human striate cortex suggest a spatial frequency carrier which is roughly equal to the inverse of Panum's area. Since the difference mapping is a global attribute of the cortical representation, and is not contingent on the existence of labeled single cell feature extractors, the difference mapping algorithm represents a distinct alternative to conventional single cell approaches to feature extraction.The difference mapping algorithm is briefly discussed in relation to other difference channels, such as color opponent segmentation and binocular orientation disparity. It is suggested that difference mapping may reflect a general synergistic mechanism relating topographic mapping and columnar architecture, which reduces the problem of feature extraction and segmentation for depth and color opponent channels to a single textural mechanism.     

Scene segmentation by spike synchronization in reciprocally connected visual areas. I. Local effects of cortical feedback

 To investigate scene segmentation in the visual system we present a model of two reciprocally connected visual areas using spiking neurons. Area P corresponds to the orientation-selective subsystem of the primary visual cortex, while the central visual area C is modeled as associative memory representing stimulus objects according to Hebbian learning. Without feedback from area C, a single stimulus results in relatively slow and irregular activity, synchronized only for neighboring patches (slow state), while in the complete model activity is faster with an enlarged synchronization range (fast state). When presenting a superposition of several stimulus objects, scene segmentation happens on a time scale of hundreds of milliseconds by alternating epochs of the slow and fast states, where neurons representing the same object are simultaneously in the fast state. Correlation analysis reveals synchronization on different time scales as found in experiments (designated as tower, castle, and hill peaks). On the fast time scale (tower peaks, gamma frequency range), recordings from two sites coding either different or the same object lead to correlograms that are either flat or exhibit oscillatory modulations with a central peak. This is in agreement with experimental findings, whereas standard phase-coding models would predict shifted peaks in the case of different objects. Received: 22 August 2001 / Accepted in revised form: 8 April 2002     

The origin and evolution of segmentation

Arthropods, annelids and chordates all possess segments. It remains unclear, however, whether the segments of these animals evolved independently or instead were derived from a common ancestor. Considering this question involves examining not only the similarities and differences in the process of segmentation between these phyla, but also how this process varies within phyla, where the homology of segments is generally accepted. This article reviews what is known about the segmentation process and considers various proposals to explain its evolution.     

The origin and evolution of segmentation

Arthropods, annelids and chordates all possess segments. It remains unclear, however, whether the segments of these animals evolved independently or instead were derived from a common ancestor. Considering this question involves examining not only the similarities and differences in the process of segmentation between these phyla, but also how this process varies within phyla, where the homology of segments is generally accepted. This article reviews what is known about the segmentation process and considers various proposals to explain its evolution.     

Regionalization and segmentation of the leech

Regionalization and segmentation of the leech body plan have been examined by numerous approaches over the years. A wealth of knowledge has accumulated regarding the normally invariant cell lineages of the leech and the degree of developmental plasticity that is possible in each cell line in early development and in neurogenesis. Homologues of genes that control regionalization and segmentation in Drosophila have been cloned from the leech and the expression patterns reveal conserved features with those in Drosophila and other organisms. Possible developmental functions of the en-class proteins in spatial and temporal modes of segment formation are discussed in light of leech and Drosophila development. Annelida and Arthropoda cell lineages of engrailed-class gene expression are compared in leech blast cell clones and crustacean parasegments. In addition, future directions for molecular analysis of segmentation of the leech are summarized. © 1995 John Wiley & Sons, Inc.     

The origin and evolution of segmentation

Arthropods, annelids and chordates all possess segments. It remains unclear, however, whether the segments of these animals evolved independently or instead were derived from a common ancestor. Considering this question involves examining not only the similarities and differences in the process of segmentation between these phyla, but also how this process varies within phyla, where the homology of segments is generally accepted. This article reviews what is known about the segmentation process and considers various proposals to explain its evolution.