Neural mechanisms of human texture processing: texture boundary detection and visual search

Texture of various appearances, geometric distortions, spatial frequency content and densities is utilized by the human visual system to segregate items from background and to enable recognition of complex geometric forms. For automatic, or pre-attentive, segmentation of a visual scene, sophisticated analysis and comparison of surface properties over wide areas of the visual field are required. We investigated the neural substrate underlying human texture processing, particularly the computational mechanisms of texture boundary detection. We present a neural network model which uses as building blocks model cortical areas that are bi-directionally linked to implement cycles of feedforward and feedback interaction for signal detection, hypothesis generation and testing within the infero-temporal pathway of form processing. In the spirit of Jake Beck's early investigations our model particularly builds upon two key hypotheses, namely that (i) texture segregation is based on boundary detection, rather than clustering homogeneous items, and (ii) texture boundaries are detected mainly on the basis of larger scenic contexts mediated by higher cortical areas, such as area V4. The latter constraint provides a basis for element grouping in accordance to the Gestalt laws of similarity and good continuation. It is shown through simulations that the model integrates a variety of psychophysical findings on texture processing and provides a link to the underlying physiology. The functional role of feedback processing is demonstrated by context dependent modulation of V1 cell activation, leading to sharply localized detection of texture boundaries. It furthermore explains why pre-attentive processing in visual search tasks can be directly linked to texture boundary processing as revealed by recent EEG studies on visual search.     

Stochastic correlative firing for figure-ground segregation

Segregation of sensory inputs into separate objects is a central aspect of perception and arises in all sensory modalities. The figure-ground segregation problem requires identifying an object of interest in a complex scene, in many cases given binaural auditory or binocular visual observations. The computations required for visual and auditory figure-ground segregation share many common features and can be cast within a unified framework. Sensory perception can be viewed as a problem of optimizing information transmission. Here we suggest a stochastic correlative firing mechanism and an associative learning rule for figure-ground segregation in several classic sensory perception tasks, including the cocktail party problem in binaural hearing, binocular fusion of stereo images, and Gestalt grouping in motion perception.     

Integrating biological motion: the role of grouping in the perception of point-light actions

The human visual system is highly sensitive to biological motion and manages to organize even a highly reduced point-light stimulus into a vivid percept of human action. The current study investigated to what extent the origin of this saliency of point-light displays is related to its intrinsic Gestalt qualities. In particular, we studied whether biological motion perception is facilitated when the elements can be grouped according to good continuation and similarity as Gestalt principles of perceptual organization. We found that both grouping principles enhanced biological motion perception but their effects differed when stimuli were inverted. These results provide evidence that Gestalt principles of good continuity and similarity also apply to more complex and dynamic meaningful stimuli.     

A neural network model for visual motion detection that can explain psychophysical and neurophysiological phenomena

This paper proposes a new neural network model for visual motion detection. The model can well explain both psychophysical findings (the changes of displacement thresholds with stimulus velocity and the perception of apparent motion) and neurophysiological findings (the selectivity for the direction and the velocity of a moving stimulus). To confirm the behavior of the model, numerical examinations were conducted. The results were consistent with both psychophysical and neurophysiological findings.     

A laminar cortical model of stereopsis and 3D surface perception: closure and da Vinci stereopsis

A laminar cortical model of stereopsis and 3D surface perception is developed and simulated. The model describes how monocular and binocular oriented filtering interact with later stages of 3D boundary formation and surface filling-in in the LGN and cortical areas V1, V2, and V4. It proposes how interactions between layers 4, 3B, and 2/3 in V1 and V2 contribute to stereopsis, and how binocular and monocular information combine to form 3D boundary and surface representations. The model includes two main new developments: (1) It clarifies how surface-to-boundary feedback from V2 thin stripes to pale stripes helps to explain data about stereopsis. This feedback has previously been used to explain data about 3D figure-ground perception. (2) It proposes that the binocular false match problem is subsumed under the Gestalt grouping problem. In particular, the disparity filter, which helps to solve the correspondence problem by eliminating false matches, is realized using inhibitory interneurons as part of the perceptual grouping process by horizontal connections in layer 2/3 of cortical area V2. The enhanced model explains all the psychophysical data previously simulated by Grossberg and Howe (2003), such as contrast variations of dichoptic masking and the correspondence problem, the effect of interocular contrast differences on stereoacuity, Panum's limiting case, the Venetian blind illusion, stereopsis with polarity-reversed stereograms, and da Vinci stereopsis. It also explains psychophysical data about perceptual closure and variations of da Vinci stereopsis that previous models cannot yet explain.     

Relationship between uniform connectedness and proximity in perceptual grouping

Palmer and Rock proposed that uniform connectedness (UC) occurs prior to classical Gestalt factors to define the primitive units for visual perception. Han, Humphreys and Chen, however, found that grouping by proximity can take place as quickly as that based on UC in a letter discrimination task. The present study employed a letter detection task to examine the relationship between UC and proximity grouping in 3 experiments. We showed that reaction times to targets defined by proximity or UC were equally fast when one or two global objects were presented in the visual field. However, as the number of global objects was increased, responses were faster to targets defined by UC than to targets defined by proximity. In addition, the advantage of UC over proximity was not affected by the space between global objects. The results suggest that UC was more effective than proximity in forming perceptual units under multiple object conditions. Possible reasons for this finding are discussed.     

Relationship between uniform connectedness and proximity in perceptual grouping

1 Introduction The visual world is composed of complex visual scenes that are projected, as two-dimen- sional images, onto the retina. Chunking of visual information is critical for object recognition, because it produces primitive perceptual units for subsequent analyses[1]. Integration of discrete local elements into a global configuration is one of the functions of perceptual grouping (e.g., combining local rectangles into a global letter as shown in fig. 1(b)). When multiple global object…     

A Bayesian model of stereopsis depth and motion direction discrimination

 The extraction of stereoscopic depth from retinal disparity, and motion direction from two-frame kinematograms, requires the solution of a correspondence problem. In previous psychophysical work [Read and Eagle (2000) Vision Res 40: 3345–3358], we compared the performance of the human stereopsis and motion systems with correlated and anti-correlated stimuli. We found that, although the two systems performed similarly for narrow-band stimuli, broad-band anti-correlated kinematograms produced a strong perception of reversed motion, whereas the stereograms appeared merely rivalrous. I now model these psychophysical data with a computational model of the correspondence problem based on the known properties of visual cortical cells. Noisy retinal images are filtered through a set of Fourier channels tuned to different spatial frequencies and orientations. Within each channel, a Bayesian analysis incorporating a prior preference for small disparities is used to assess the probability of each possible match. Finally, information from the different channels is combined to arrive at a judgement of stimulus disparity. Each model system – stereopsis and motion – has two free parameters: the amount of noise they are subject to, and the strength of their preference for small disparities. By adjusting these parameters independently for each system, qualitative matches are produced to psychophysical data, for both correlated and anti-correlated stimuli, across a range of spatial frequency and orientation bandwidths. The motion model is found to require much higher noise levels and a weaker preference for small disparities. This makes the motion model more tolerant of poor-quality reverse-direction false matches encountered with anti-correlated stimuli, matching the strong perception of reversed motion that humans experience with these stimuli. In contrast, the lower noise level and tighter prior preference used with the stereopsis model means that it performs close to chance with anti-correlated stimuli, in accordance with human psychophysics. Thus, the key features of the experimental data can be reproduced assuming that the motion system experiences more effective noise than the stereoscopy system and imposes a less stringent preference for small disparities. Received: 2 March 2001 / Accepted in revised form: 5 July 2001     

Grouping in auditory temporal perception and vocal production is mutually adapted: the case of wriggling calls of mice

Auditory Gestalt perception by grouping of species-specific vocalizations to a perceptual stream with a defined meaning is typical for human speech perception but has not been studied in non-human mammals so far. Here we use synthesized models of vocalizations (series of wriggling calls) of mouse pups (Mus domesticus) and show that their mothers perceive the call series as a meaningful Gestalt for the release of instinctive maternal behavior, if the inter-call intervals have durations of 100–400 ms. Shorter or longer inter-call intervals significantly reduce the maternal responsiveness. We also show that series of natural wriggling calls have inter-call intervals mainly in the range of 100–400 ms. Thus, series of natural wriggling calls of pups match the time-domain auditory filters of their mothers in order to be optimally perceived and recognized. A similar time window exists for the production of human speech and the perception of series of sounds by humans. Neural mechanisms for setting the boundaries of the time window are discussed.     

The internal representation of solid shape with respect to vision

It is argued that the internal model of any object must take the form of a function, such that for any intended action the resulting reafference is predictable. This function can be derived explicitly for the case of visual perception of rigid bodies by ambulant observers. The function depends on physical causation, not physiology; consequently, one can make a priori statements about possible internal models. A posteriori it seems likely that the orientation sensitive units described by Hubel and Wiesel constitute a physiological substrate subserving the extraction of the invariants of this function. The function is used to define a measure for the visual complexity of solid shape. Relations with Gestalt theories of perception are discussed.     

Independent responses of Pacinian and Non-Pacinian systems with hand-transmitted vibration detected from masked thresholds

This study was designed to identify psychophysical channels responsible for the detection of hand-transmitted vibration. Perception thresholds for vibration (16, 31.5, 63 and 125 Hz sinusoidal for 600 ms) at the distal phalanx of the middle finger and the whole hand were determined with and without simultaneous masking stimuli (1/3 octave bandwidth Gaussian random vibration centered on either 16 Hz or 125 Hz for 3000 ms, varying in magnitude 0 to 30 dB above threshold). At all frequencies from 16 to 125 Hz, absolute thresholds for the hand were significantly lower than those for the finger. Changes in threshold as a function of masker level were used to estimate the thresholds of three psychophysical channels (i.e. P, NP I, and NP II channels). Increased vibrotactile sensitivity of the hand compared to the finger seems to be not entirely due to increased spatial summation via the Pacinian system (P channel); non-Pacinian system (NP I and NP II channels) also contributed to perception. Differing transmission of vibration between the hand and the finger may have also influenced the thresholds.     

Independent responses of Pacinian and Non-Pacinian systems with hand-transmitted vibration detected from masked thresholds

This study was designed to identify psychophysical channels responsible for the detection of hand-transmitted vibration. Perception thresholds for vibration (16, 31.5, 63 and 125?Hz sinusoidal for 600?ms) at the distal phalanx of the middle finger and the whole hand were determined with and without simultaneous masking stimuli (1/3 octave bandwidth Gaussian random vibration centered on either 16?Hz or 125?Hz for 3000?ms, varying in magnitude 0 to 30?dB above threshold). At all frequencies from 16 to 125?Hz, absolute thresholds for the hand were significantly lower than those for the finger. Changes in threshold as a function of masker level were used to estimate the thresholds of three psychophysical channels (i.e. P, NP I, and NP II channels). Increased vibrotactile sensitivity of the hand compared to the finger seems to be not entirely due to increased spatial summation via the Pacinian system (P channel); non-Pacinian system (NP I and NP II channels) also contributed to perception. Differing transmission of vibration between the hand and the finger may have also influenced the thresholds.     

Grouping by Proximity in Haptic Contour Detection

We investigated the applicability of the Gestalt principle of perceptual grouping by proximity in the haptic modality. To do so, we investigated the influence of element proximity on haptic contour detection. In the course of four sessions ten participants performed a haptic contour detection task in which they freely explored a haptic random dot display that contained a contour in 50% of the trials. A contour was defined by a higher density of elements (raised dots), relative to the background surface. Proximity of the contour elements as well as the average proximity of background elements was systematically varied. We hypothesized that if proximity of contour elements influences haptic contour detection, detection will be more likely when contour elements are in closer proximity. This should be irrespective of the ratio with the proximity of the background elements. Results showed indeed that the closer the contour elements were, the higher the detection rates. Moreover, this was the case independent of the contour/background ratio. We conclude that the Gestalt law of proximity applies to haptic contour detection.     

Encoding and decoding amplitude-modulated cochlear implant stimuli—a point process analysis

Cochlear implant speech processors stimulate the auditory nerve by delivering amplitude-modulated electrical pulse trains to intracochlear electrodes. Studying how auditory nerve cells encode modulation information is of fundamental importance, therefore, to understanding cochlear implant function and improving speech perception in cochlear implant users. In this paper, we analyze simulated responses of the auditory nerve to amplitude-modulated cochlear implant stimuli using a point process model. First, we quantify the information encoded in the spike trains by testing an ideal observer’s ability to detect amplitude modulation in a two-alternative forced-choice task. We vary the amount of information available to the observer to probe how spike timing and averaged firing rate encode modulation. Second, we construct a neural decoding method that predicts several qualitative trends observed in psychophysical tests of amplitude modulation detection in cochlear implant listeners. We find that modulation information is primarily available in the sequence of spike times. The performance of an ideal observer, however, is inconsistent with observed trends in psychophysical data. Using a neural decoding method that jitters spike times to degrade its temporal resolution and then computes a common measure of phase locking from spike trains of a heterogeneous population of model nerve cells, we predict the correct qualitative dependence of modulation detection thresholds on modulation frequency and stimulus level. The decoder does not predict the observed loss of modulation sensitivity at high carrier pulse rates, but this framework can be applied to future models that better represent auditory nerve responses to high carrier pulse rate stimuli. The supplemental material of this article contains the article’s data in an active, re-usable format.     

Speech perception at the interface of neurobiology and linguistics

Speech perception consists of a set of computations that take continuously varying acoustic waveforms as input and generate discrete representations that make contact with the lexical representations stored in long-term memory as output. Because the perceptual objects that are recognized by the speech perception enter into subsequent linguistic computation, the format that is used for lexical representation and processing fundamentally constrains the speech perceptual processes. Consequently, theories of speech perception must, at some level, be tightly linked to theories of lexical representation. Minimally, speech perception must yield representations that smoothly and rapidly interface with stored lexical items. Adopting the perspective of Marr, we argue and provide neurobiological and psychophysical evidence for the following research programme. First, at the implementational level, speech perception is a multi-time resolution process, with perceptual analyses occurring concurrently on at least two time scales (approx. 20-80 ms, approx. 150-300 ms), commensurate with (sub)segmental and syllabic analyses, respectively. Second, at the algorithmic level, we suggest that perception proceeds on the basis of internal forward models, or uses an 'analysis-by-synthesis' approach. Third, at the computational level (in the sense of Marr), the theory of lexical representation that we adopt is principally informed by phonological research and assumes that words are represented in the mental lexicon in terms of sequences of discrete segments composed of distinctive features. One important goal of the research programme is to develop linking hypotheses between putative neurobiological primitives (e.g. temporal primitives) and those primitives derived from linguistic inquiry, to arrive ultimately at a biologically sensible and theoretically satisfying model of representation and computation in speech.     

Automatic counting of birds in a bird deterrence field trial

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Detection of a gabor patch superimposed on an illusory contour

Interactions between visual stimuli have been found to be specific to the spatial frequency, orientation and phase of the interacting stimuli. We asked if there are any interactions between luminance-defined Gabor patches and Kanizsa-type illusory contours. In psychophysical experiments we studied whether induction of a vertical illusory line affects detection thresholds for a Gabor patch superimposed on this line and whether these effects depend on the orientation, spatial frequency and phase of the Gabor elements. Employing a 2AFC method with a staircase procedure we measured contrast detection thresholds and varied the orientation, spatial frequency and phase of the test Gabor patch and the separation between the two pacmen in four experimental series. The results show that in a situation where the two inducers generate perception of an illusory line, the contrast detection of the Gabor patch is facilitated relative to a control condition where the rotated pacmen do not induce illusory contours. This facilitation was more pronounced for test Gabor signals that were collinear to the illusory line, but the observer's performance was not altered by changes in the spatial frequency or phase of the Gabor stimuli. With increasing spatial separation of the two pacmen (and, consequently, with a decreasing support ratio), the difference between performance in the test and control conditions diminished. From the data obtained we cannot infer that we have measured some neural interactions between Gabor patches and Kanizsa-type illusory contours, and nor can we draw a unique conclusion about what causes the facilitation of detection of the test Gabor patch in the experimental situation that allows induction of the illusory line. We discuss possible mechanisms of the facilitation, such as contextual influences or a reduction of uncertainty about spatial location of the test Gabor patch.