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Stephen Grossberg - One of the best experts on this subject based on the ideXlab platform.
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how visual illusions illuminate complementary brain processes Illusory depth from brightness and apparent motion of Illusory Contours
Frontiers in Human Neuroscience, 2014Co-Authors: Stephen GrossbergAbstract:Neural models of perception clarify how visual illusions arise from adaptive neural processes. Illusions also provide important insights into how adaptive neural processes work. This article focuses on two illusions that illustrate a fundamental property of global brain organization; namely, that advanced brains are organized into parallel cortical processing streams with computationally complementary properties. That is, in order to process certain combinations of properties, each cortical stream cannot process complementary properties. Interactions between these streams, across multiple processing stages, overcome their complementary deficiencies to compute effective representations of the world, and to thereby achieve the property of complementary consistency. The two illusions concern how Illusory depth can vary with brightness, and how apparent motion of Illusory Contours can occur. Illusory depth from brightness arises from the complementary properties of boundary and surface processes, notably boundary completion and surface-filling in, within the parvocellular form processing cortical stream. This illusion depends upon how surface contour signals from the V2 thin stripes to the V2 interstripes ensure complementary consistency of a unified boundary/surface percept. Apparent motion of Illusory Contours arises from the complementary computations of form and motion processing across the parvocellular and magnocellular cortical processing streams. This illusion depends upon how Illusory Contours help to complete boundary representations for object recognition, how apparent motion signals can help to form continuous trajectories for target tracking and prediction, and how formotion interactions from V2-to-MT enable completed object representations to be continuously tracked even when they move behind intermittently occluding objects through time.
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how do object reference frames and motion vector decomposition emerge in laminar cortical circuits
Attention Perception & Psychophysics, 2011Co-Authors: Stephen Grossberg, Jasmin Leveille, Massimiliano VersaceAbstract:How do spatially disjoint and ambiguous local motion signals in multiple directions generate coherent and unambiguous representations of object motion? Various motion percepts, starting with those of Duncker (Induced motion, 1929/1938) and Johansson (Configurations in event perception, 1950), obey a rule of vector decomposition, in which global motion appears to be subtracted from the true motion path of localized stimulus components, so that objects and their parts are seen as moving relative to a common reference frame. A neural model predicts how vector decomposition results from multiple-scale and multiple-depth interactions within and between the form- and motion-processing streams in V1–V2 and V1–MST, which include form grouping, form-to-motion capture, figure–ground separation, and object motion capture mechanisms. Particular advantages of the model are that these mechanisms solve the aperture problem, group spatially disjoint moving objects via Illusory Contours, capture object motion direction signals on real and Illusory Contours, and use interdepth directional inhibition to cause a vector decomposition, whereby the motion directions of a moving frame at a nearer depth suppress those directions at a farther depth, and thereby cause a peak shift in the perceived directions of object parts moving with respect to the frame.
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fast synchronization of perceptual grouping in laminar visual cortical circuits
Neural Networks, 2004Co-Authors: Arash Yazdanbakhsh, Stephen GrossbergAbstract:Perceptual grouping is well known to be a fundamental process during visual perception, notably grouping across scenic regions that do not receive contrastive visual inputs. Illusory Contours are a classical example of such groupings. Recent psychophysical and neurophysiological evidence have shown that the grouping process can facilitate rapid synchronization of the cells that are bound together by a grouping, even when the grouping must be completed across regions that receive no contrastive inputs. Synchronous grouping can hereby bind together different object parts that may have become desynchronized due to a variety of factors, and can enhance the efficiency of cortical transmission. Neural models of perceptual grouping have clarified how such fast synchronization may occur by using bipole grouping cells, whose predicted properties have been supported by psychophysical, anatomical, and neurophysiological experiments. These models have not, however, incorporated some of the realistic constraints in which groupings in the brain are conditioned, notably the measured spatial extent of long-range interactions in layer 2/3 of a grouping network, and realistic synaptic and axonal signaling delays within and across cells in different cortical layers. This work addresses the question: Can long-range interactions that obey the bipole constraint achieve fast synchronization under realistic anatomical and neurophysiological constraints that initially desynchronize grouping signals? Can the cells that synchronize retain their analog sensitivity to changing input amplitudes? Can the grouping process complete and synchronize Illusory Contours accross gaps in bottom-up inputs? Our simulations show that the answer to these questions is Yes.
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cortical dynamics of form and motion integration persistence apparent motion and Illusory Contours
Vision Research, 1996Co-Authors: Gregory Francis, Stephen GrossbergAbstract:How does the visual system generate percepts of moving forms? How does this happen when the forms are emergent percepts, such as Illusory Contours or segregated textures, and the motion percept is apparent motion between the emergent forms? We develop a neural model of form-motion interactions to explain and simulate parametric properties of psychophysical motion data and to make predictions about how the parallel cortical processing streams V1 → MT and V1 → V2 → MT control form-motion interactions. The model explains how an Illusory contour can move in apparent motion to another Illusory contour or to a luminance-derived contour; how Illusory contour persistence motion to the upper interstimulus interval (ISI) threshold for apparent motion; and how upper and lower ISI thresholds for seeing apparent motion between two flashes decrease with stimulus duration and narrow with spatial separation (Korte's laws). The model acounts for these data by suggesting how the persistence of a boundary segmentation in the V1 → V2 processing stream influences the quality of apparent motion in the V1 → MT stream through V2 → MT interactions. These data may all be explained by an analysis of how orientationally tuned form perception mechanisms and directionally tuned motion perception mechanisms interact.
Rufin Vanrullen - One of the best experts on this subject based on the ideXlab platform.
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predictive coding feedback results in perceived Illusory Contours in a recurrent neural network
Neural Networks, 2021Co-Authors: Zhaoyang Pang, Callum Biggs Omay, Bhavin Choksi, Rufin VanrullenAbstract:Abstract Modern feedforward convolutional neural networks (CNNs) can now solve some computer vision tasks at super-human levels. However, these networks only roughly mimic human visual perception. One difference from human vision is that they do not appear to perceive Illusory Contours (e.g. Kanizsa squares) in the same way humans do. Physiological evidence from visual cortex suggests that the perception of Illusory Contours could involve feedback connections. Would recurrent feedback neural networks perceive Illusory Contours like humans? In this work we equip a deep feedforward convolutional network with brain-inspired recurrent dynamics. The network was first pretrained with an unsupervised reconstruction objective on a natural image dataset, to expose it to natural object contour statistics. Then, a classification decision head was added and the model was finetuned on a form discrimination task: squares vs. randomly oriented inducer shapes (no Illusory contour). Finally, the model was tested with the unfamiliar “Illusory contour” configuration: inducer shapes oriented to form an Illusory square. Compared with feedforward baselines, the iterative “predictive coding” feedback resulted in more Illusory Contours being classified as physical squares. The perception of the Illusory contour was measurable in the luminance profile of the image reconstructions produced by the model, demonstrating that the model really “sees” the illusion. Ablation studies revealed that natural image pretraining and feedback error correction are both critical to the perception of the illusion. Finally we validated our conclusions in a deeper network (VGG): adding the same predictive coding feedback dynamics again leads to the perception of Illusory Contours.
Micah M. Murray - One of the best experts on this subject based on the ideXlab platform.
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Visual processing deficits in 22q11.2 Deletion Syndrome
NeuroImage. Clinical, 2017Co-Authors: Marjan Biria, Miralena I. Tomescu, Anna Custo, Lucia M. Cantonas, Kun-wei Song, Maude Schneider, Micah M. Murray, Stephan Eliez, Christoph M. Michel, Tonia A. RihsAbstract:Carriers of the rare 22q11.2 microdeletion present with a high percentage of positive and negative symptoms and a high genetic risk for schizophrenia. Visual processing impairments have been characterized in schizophrenia, but less so in 22q11.2 Deletion Syndrome (DS). Here, we focus on visual processing using high-density EEG and source imaging in 22q11.2DS participants (N = 25) and healthy controls (N = 26) with an Illusory contour discrimination task. Significant differences between groups emerged at early and late stages of visual processing. In 22q11.2DS, we first observed reduced amplitudes over occipital channels and reduced source activations within dorsal and ventral visual stream areas during the P1 (100-125 ms) and within ventral visual cortex during the N1 (150-170 ms) visual evoked components. During a later window implicated in visual completion (240-285 ms), we observed an increase in global amplitudes in 22q11.2DS. The increased surface amplitudes for Illusory Contours at this window were inversely correlated with positive subscales of prodromal symptoms in 22q11.2DS. The reduced activity of ventral and dorsal visual areas during early stages points to an impairment in visual processing seen both in schizophrenia and 22q11.2DS. During intervals related to perceptual closure, the inverse correlation of high amplitudes with positive symptoms suggests that participants with 22q11.2DS who show an increased brain response to Illusory Contours during the relevant window for contour processing have less psychotic symptoms and might thus be at a reduced prodromal risk for schizophrenia.
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Illusory Contours a window onto the neurophysiology of constructing perception
Trends in Cognitive Sciences, 2013Co-Authors: Micah M. Murray, Christoph HerrmannAbstract:Seeing seems effortless, despite the need to segregate and integrate visual information that varies in quality, quantity, and location. The extent to which seeing passively recapitulates the external world is challenged by phenomena such as Illusory Contours, an example of visual completion whereby borders are perceived despite their physical absence in the image. Instead, visual completion and seeing are increasingly conceived as active processes, dependent on information exchange across neural populations. How this is instantiated in the brain remains controversial. Divergent models emanate from single-unit and population-level electrophysiology, neuroimaging, and neurostimulation studies. We reconcile discrepant findings from different methods and disciplines, and underscore the importance of taking into account spatiotemporal brain dynamics in generating models of brain function and perception.
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boundary completion is automatic and dissociable from shape discrimination
The Journal of Neuroscience, 2006Co-Authors: Micah M. Murray, Michelle L Imber, Daniel C Javitt, John J FoxeAbstract:Normal visual perception readily overcomes suboptimal or degraded viewing conditions through perceptual filling-in processes, enhancing object recognition and discrimination abilities. This study used visual evoked potential (VEP) recordings in conjunction with electrical neuroimaging analyses to determine the spatiotemporal brain dynamics of boundary completion and shape discrimination processes in healthy humans performing the so-called “thin/fat” discrimination task ([Ringach and Shapley, 1996][1]) with stimuli producing Illusory Contours. First, results suggest that boundary completion processes occur independent of subjects' accuracy on the discrimination task. Modulation of the VEP to the presence versus absence of Illusory Contours [the IC effect ([Murray et al., 2002][2])] was indistinguishable in terms of response magnitude and scalp topography over the 124–186 ms poststimulus period, regardless of whether task performance was correct. This suggests that failure on this discrimination task is not primarily a consequence of failed boundary completion. Second, the electrophysiological correlates of thin/fat shape discrimination processes are temporally dissociable from those of boundary completion, occurring during a substantially later phase of processing (∼330–406 ms). The earlier IC effect was unaffected by whether the perceived contour produced a thin or fat shape. In contrast, later time periods of the VEP modulated according to perceived shape only in the case of stimuli producing Illusory Contours, but not for control stimuli for which performance was at near-chance levels. Collectively, these data provide further support for a multistage model of object processing under degraded viewing conditions. [1]: #ref-44 [2]: #ref-34
Tonia A. Rihs - One of the best experts on this subject based on the ideXlab platform.
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Visual processing deficits in 22q11.2 Deletion Syndrome
NeuroImage. Clinical, 2017Co-Authors: Marjan Biria, Miralena I. Tomescu, Anna Custo, Lucia M. Cantonas, Kun-wei Song, Maude Schneider, Micah M. Murray, Stephan Eliez, Christoph M. Michel, Tonia A. RihsAbstract:Carriers of the rare 22q11.2 microdeletion present with a high percentage of positive and negative symptoms and a high genetic risk for schizophrenia. Visual processing impairments have been characterized in schizophrenia, but less so in 22q11.2 Deletion Syndrome (DS). Here, we focus on visual processing using high-density EEG and source imaging in 22q11.2DS participants (N = 25) and healthy controls (N = 26) with an Illusory contour discrimination task. Significant differences between groups emerged at early and late stages of visual processing. In 22q11.2DS, we first observed reduced amplitudes over occipital channels and reduced source activations within dorsal and ventral visual stream areas during the P1 (100-125 ms) and within ventral visual cortex during the N1 (150-170 ms) visual evoked components. During a later window implicated in visual completion (240-285 ms), we observed an increase in global amplitudes in 22q11.2DS. The increased surface amplitudes for Illusory Contours at this window were inversely correlated with positive subscales of prodromal symptoms in 22q11.2DS. The reduced activity of ventral and dorsal visual areas during early stages points to an impairment in visual processing seen both in schizophrenia and 22q11.2DS. During intervals related to perceptual closure, the inverse correlation of high amplitudes with positive symptoms suggests that participants with 22q11.2DS who show an increased brain response to Illusory Contours during the relevant window for contour processing have less psychotic symptoms and might thus be at a reduced prodromal risk for schizophrenia.
Takeo Watanabe - One of the best experts on this subject based on the ideXlab platform.
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the primary visual cortex fills in color
Proceedings of the National Academy of Sciences of the United States of America, 2004Co-Authors: Yuka Sasaki, Takeo WatanabeAbstract:One of the most important goals of visual processing is to reconstruct adequate representations of surfaces in a scene. It is thought that surface representation is produced mainly in the midlevel vision and that area V1 (the primary visual cortex) activity is solely due to feedback from the midlevel stage. Here, we measured functional MRI signals corresponding to “neon color spreading”: an Illusory transparent surface with long-range color filling-in, one of the important mediums in reconstructing a surface. The experiment was conducted with careful controls of attention, which can send feedback signals from higher visual areas. Activity for filling-in was observed only in V1, whereas activity for Illusory Contours was observed in multiple visual areas. These results indicate that surface representation is produced by multiple rather than single processing.
