Search

Converging evidence from behavioral, neural, and computational investigations has led to the theory that rapid scene categorization can be performed based on the extraction of simple features (e.g. oriented edges, colors, etc.) and does not necessarily require an organization of these features into coherent parts, objects, or surfaces. This is consistent with findings that many perceptual grouping tasks and image segmentation in general are computationally expensive processes requiring multiple iterations of feedback. Therefore, these grouping and segmentation processes must take place after scene category information has already been computed (a process assumed to be rapid and feedforward). In a series of three experiments, we questioned whether segmentation processes indeed did not play a role in the rapid scene categorization. In particular, if categorization were only based on feature extraction, with relations between features or objects playing only a minor role, segmentation cues should not influence categorization accuracy. If, however, categorization was also based on the relations between these features, misleading segmentation cues should impede categorization performance. In each trial, we presented participants with two scenes divided into four parts, using segmentation cues displayed for 300 ms prior to image onset. These cues established either a congruent (supporting the correct image segmentation into two scenes) or incongruent (pushing observers to incorrectly group scene segments) figure-ground segmentation on the display. We found that participants were less accurate in scene categorization when incongruent segmentation cues were presented, indicating that segmentation plays a role in rapid categorization decisions. Moreover, the effect remained robust even when the cues were presented concurrently with the images, suggesting that whilst scene categorization might be rapid, it also interacts with equally fast mechanisms of scene segmentation.

Visual information that reaches the eye is complex and highly multidimensional. How is our visual system capable of extracting meaning from these inputs? In this thesis, we explored the mechanisms behind configural processing where separate parts (or features) from the inputs are organized into larger wholes. While such perceptual organization is well documented in psychology, less is known about its neural basis and possible computations leading to the structured outputs of the visual system.First, we presented participants with the so-called configural superiority task where an organization of parts into wholeshapes leads to a robust behavioral advantage in a visual search task. We found that the wholes elicited more distinct neural pattern of response than parts in higher visual areas, namely, the shape-selective lateral occipital cortex (LOC). Furthermore, by testing a neuropsychological patient DF who lacks LOC, we established a causal role of LOC in producing thisnbsp;advantage.Next, we asked what configural information in particular might be encoded in the visual system. In an fMRI experiment, we presented participants with various configurations of two lines. Some configurations were rather generic (e.g., a random placement of two lines), while others were very regular (e.g., a + sign). We found that LOC was sensitive to the amount of regularity in configurations. Moreover, in a behavioral experiment, we found that participants were also highly sensitive to changes in nonaccidental configurations that are thought to contribute to object recognition.What computations in the visual system might lead tonbsp;processing? By reviewing a large body of literature, we provide a novel synthesis of available empirical and theoretical work into a coherent framework of basic computations in the early visual processing, namely, computation of similarity between features and pooling of highly similar ones.Taken together, this thesis brings forward the idea that configural processing might be a fast and possibly feedforward process (although undoubtedly refined via recurrent loops) that is an inherent part of early visual processing. Summary Samenvatting Preface 1 | General introduction 2 | Brain-decoding fMRI reveals how wholes relate to the sum of parts 3 | Emergence of perceptual Gestalts in the human visual cortex 4 | Configural Gestalts remain nothing more than the sum of their parts in visual agnosia 5 | Encoding of configural regularity in the human visual system 6 | Sensitivity to nonaccidental configurations of two-line stimuli 7 | A conceptual framework of computations in mid-level vision 8 | General discussion Appendix A | From what scale of representation does multivariate pattern analysis decode information? Appendix B | A framework for streamlining research workflow in neuroscience and psychology Appendix C | Sharing code Acknowledgments nrpages: 241 status: published

Sharing code is becoming increasingly important in the wake of Open Science. In this review I describe and compare two popular code-sharing utilities, GitHub and Open Science Framework (OSF). GitHub is a mature, industry-standard tool but lacks focus towards researchers. In comparison, OSF offers a one-stop solution for researchers but a lot of functionality is still under development. I conclude by listing alternative lesser-known tools for code and materials sharing. ispartof: i-Perception vol:5 issue:1 pages:75-78 ispartof: location:United States status: published

Successful accumulation of knowledge is critically dependent on the ability to verify and replicate every part of a scientific conduct. However, such principles are difficult to enact when researchers continue to resort on ad hoc workflows resulting in a poorly maintained code base. Based on a critical examination of the needs of neuroscience and psychology community, I introduce psychopy_ext, a unifying framework that seamlessly integrates experiment building, analysis and manuscript preparation by choosing reasonable defaults and implementing relatively rigid patterns of workflow. This structure allows automation of multiple tasks, such as automatic user interfaces, unit testing, stimulus control analyses, single-command access to descriptive statistics, and publication quality plotting. Taken together, psychopy_ext opens an exciting possibility for faster, more robust code development and collaboration for researchers.

According to recognition-by-components theory, object recognition relies on a specific subset of three-dimensional shapes called geons. In particular, these configurations are a powerful cue to a three dimensional object reconstruction because their two dimensional projection remains viewpoint-invariant. While a large body of literature has demonstrated sensitivity to changes in these so-called non-accidental configurations, it remains unclear what information is used in establishing such sensitivity. In this study, we explored a possibility that non-accidental configurations can already be inferred from the basic constituents of objects, namely, their edges. We constructed a set of stimuli composed of two lines corresponding to various non-accidental properties and configuration of geons, including collinearity, alignment, curvature of contours, curvature of configuration axis, expansion, cotermination, and junction type. Using a simple visual search paradigm, we demonstrated that participants were faster at detecting targets that differed from distractors in a non-accidental configuration than in a metric one. Given that such sensitivity emerged from a configuration of only two lines, our results open a possibility that non-accidental configurations could be encoded at the earliest stages of the visual information processing.&nbsp

While multiple studies investigate the properties of the earliest and final stages of visual information processing, the underlying transformations leading from simple edge detection to object recognition remain seemingly intractable. To tackle this problem, we take a step back and ask what mechanisms could lead to a successful figure-ground segmentation of a given image. We propose the following conceptual framework: (i) alternating steps of feature detection and feature pooling (grouping) in a hierarchical manner; (ii) segmentation into (provisional) objects by an unsupervised learning procedure using the computed feature grouping strengths. We present an initial implementation of this model where grouping principles such as proximity or good continuation are leveraged to discover grouped objects in an image. Model simulations reveal a promising performance on classical Gestalt displays of dot lattices, contour integration, and texture segregation.

Gestalt grouping principles provide important cues for organizing visual inputs into coherent percepts. While a number of models for each grouping principle have been proposed, a unifying architecture that would flexibly incorporate all of them is still lacking. Moreover, many of these models operate in mathematical terms, rendering them unsuitable for a wider testing on real input images. Here we present a generic biologically plausible unsupervised architecture, which we term gmin (https://github.com/qbilius/gmin), geared towards a unified implementation of the grouping principles. The model operates by extracting a certain feature of interest from an input image (e.g., edges) and selecting maximally informative units to decrease computational load; then it proceeds to iteratively compute grouping strength between all pairs of units and update informative unit selection using a particular grouping principle (e.g., good continuation). This process is repeated for all features of interest. Finally, a segmentation of an image into (provisional) objects is provided by an unsupervised learning procedure on the computed grouping strengths, such as clustering or belief propagation. We illustrate the validity and the general usefulness of our approach by testing it on a few very different grouping displays. Using the cues of proximity, good continuation, or orientation similarity, we were able to obtain a satisfying model performance on the classic Gestalt displays of dot lattices, contour integration, and texture segregation.

The visual system is very efficient in encoding stimulus properties. To explore the underlying encoding strategies in the early stages of visual information processing, we presented participants with L-, T-, and X-junctions in a functional magnetic resonance imaging (fMRI) experiment. For each junction type, we manipulated the amount of configuration regularity (or degrees of constraint), ranging from a generic junction configuration to stimuli resembling an ‘L’ (i.e., a right angle L-junction), a ‘T’ (i.e., a right angle midpoint T-junction), or a ‘+’. We found that the response strength in the shape-selective lateral occipital area was consistently lower for a higher degree of regularity in the stimuli. In the second experiment, using multivoxel pattern analysis we further show that regularity is encoded in terms of the fMRI signal strength but not in the distributed pattern of responses. Finally, we found that the results of these experiments could not be accounted for by two well-known theoretical proposals for constructing stimulus interpretation, namely, the Structural Information Theory and the Minimal Model Theory, at least not without additional assumptions in those theories. Our results suggest that regularity plays an important role in stimulus encoding in the ventral visual processing stream.

Activity in the primary visual cortex reduces when certain stimuli can be perceptually organized as a unified Gestalt. This reduction could offer important insights into the nature of feedback computations within the human visual system; however, the properties of this response reduction have not yet been investigated in detail.Here we replicate this reduced V1 response, but find that the modulation in V1 (and V2) to the perceived organization of the input is not specific to the retinotopic location at which the sensory input from that stimulus is represented. Instead, we find a response modulation that is equally evident across the primary visual cortex. Thus in contradiction to some models of hierarchical predictive coding, the perception of an organized Gestalt causes a broad feedback effect that does not act specifically on the part of the retinotopic map representing the sensory input.

Activity in the primary visual cortex reduces when certain stimuli can be perceptually organized as a unified Gestalt. This reduction could offer important insights into the nature of feedback computations within the human visual system; however, the properties of this response reduction have not yet been investigated in detail. Here we replicate this reduced V1 response, but find that the modulation in V1 (and V2) to the perceived organization of the input is not specific to the retinotopic location at which the sensory input from that stimulus is represented. Instead, we find a response modulation that is equally evident across the primary visual cortex. Thus in contradiction to some models of hierarchical predictive coding, the perception of an organized Gestalt causes a broad feedback effect that does not act specifically on the part of the retinotopic map representing the sensory input. ispartof: Journal of Vision vol:12 issue:11 pages:1-14 ispartof: location:United States status: published

How does our visual system combine the features or parts in a complex display to provide a percept of a whole? Intense behavioral work in Gestalt psychology has described a number of phenomena where this whole is not equal to a mere sum of its parts. However, precise unifying principles of such Gestalt effects have remained elusive. Current neuroscientific models suggest that these phenomena are the consequence of the interplay between bottom-up, feedback, and lateral connections in the hierarchical visual system. Here we approach this question from a different perspective by investigating the neural basis of Gestalt formation. In our functional magnetic resonance imaging (fMRI) paradigm, we utilized a configural superiority effect, where a visual search task for the odd element in a display of three lines oriented at 45 degrees and one at 135 degrees (parts) is facilitated by adding an irrelevant corner to each of the lines, forming three arrows and a triangle (whole shapes). To assess the extent of grouping in early and higher visual areas, we compared multivariate pattern analysis performance on the same task, detection of the odd element, using the fMRI activity pattern in the primary visual cortex (V1) and shape-selective lateral occipital complex (LOC). The behavioral advantage for searching among shapes rather than lines was reflected in a better classification performance in LOC but not in V1, where decoding of parts was more pronounced. This suggests that the configural superiority effect may arise by predominantly feedforward processes. Moreover, even when we trained the classifier on whole shapes in LOC, its decoding performance on parts remained as poor as when we trained on those parts, indicating that the representation of a whole shape bears no similarity to the representation of its parts at these higher stages of visual processing. Simulations confirm that these findings are consistent with a feedforward model of vision, HMAX. Taken together, these results show how at least some Gestalt phenomena in vision are consistent with and caused by the feedforward processing of visual shape.

The article gives a survey of activities of the Lithuanian Mathematical Society during the past three years. Some problems of the mathematical life in Lithuania are raised.

Reminescences about the doctoral studies of G. Žilinskas at the Manchester University and his work at Vilnius University.

A survey of the activities of the Lithuanian Mathematical Society is given.

The article gives a survey of activities of the Mathematical Society during last three years. Some poblems of he mathematical life in Lithuania are rised.

Vyskupas Antanas Baranauskas buvo pačių interesų asmenybė. Domėjosi daugeliu dalykų ir savo kūrybine veikla reiškėsi daugelyje sričių. Būdamas beveik savamokslis, jis savarankiškai atrado ne vieną matematikos faktą, ypač pirminių skaičių teorijoje. Sudarė nemažai lietuviškų matematikos terminų. Pranešime trumpai apžvelgiama jo matematinė veikla ir jos vieta Lietuvos mokslo istorijoje. Bishop A. Baranauskas was a prominent personality. His interests and creative activities covered many subjects. He was self-educated person in mathematics. However he succeeded in finding many known and some new mathematical laws, especially in prime number theory. He proposed many Lithuanian mathematical terms. In the paper a short overview of his mathematical activities and their place in the history of Lithuanian science is given.