Neural Mechanisms Of Visual Segmentation Using Motion And Depth Cues In Cortical Area Mt
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Neural Mechanisms Of Visual Segmentation Using Motion And Depth Cues In Cortical Area Mt
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Author : Venkta Lakshmi Anjani Chakrala
language : en
Publisher:
Release Date : 2023
Neural Mechanisms Of Visual Segmentation Using Motion And Depth Cues In Cortical Area Mt written by Venkta Lakshmi Anjani Chakrala and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
Our dynamic world requires us to discern objects in complex environments to effectively interact with our surroundings. Our visual system has the remarkable ability to seamlessly segment objects from each other, unmatched by current machine vision systems, that enables us to understand visual scenes and guides actions. In natural vision, visual motion combined with other features like depth and cognitive abilities like attention is important to segment objects. Visual motion processing is widely studied at both perceptual and physiological levels. However, the neural mechanisms underlying the segmentation of multiple objects aided by motion combined with other features like depth and spatial location are not fully understood. The goal of this dissertation is to elucidate the neural mechanisms underlying the segmentation of multiple objects using motion direction, speed, depth (binocular disparity), and spatial location. Toward this, in chapter 2, I determined the neural representation of multiple objects, that differed in depth and motion direction and investigated the effect of selective attention on this representation. We designed a novel motion discrimination task, in which macaque monkeys selectively attended to one of two moving surfaces separated in depth. The task was paired with electrophysiological recordings from the middle temporal area (MT), known for its selectivity to visual motion and binocular disparity. Our results suggest that to represent multiple surfaces with different depths and motion direction, MT neurons leverage their preference to the binocular disparity of the constituent surfaces, so that the information about the two motion directions is distributed over neuronal subgroups defined by their disparity preferences (near and far-preferred neurons). Selective attention to one disparity enhanced the representation of the attended surface and its motion direction. In chapter 3, I investigated how MT neurons encoded two spatially separated stimuli moving at different speeds. Akin to chapter 2, we found that the MT neurons' spatial and speed preferences to single motion were preserved in their responses to two spatially separated speeds, which might help in their segmentation. Together, our results elucidate prevailing neural strategies of encoding multiple visual stimuli, and how the visual system exploits spatial cues either two-dimensional or three-dimensional, together with motion cues to segment multiple objects.
Neural Mechanisms Of Motion Based Image Segmentation In Cortical Area Mt
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Author : Steven Wiesner
language : en
Publisher:
Release Date : 2021
Neural Mechanisms Of Motion Based Image Segmentation In Cortical Area Mt written by Steven Wiesner and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
Natural scenes often contain multiple visual entities. A fundamental function of vision, referred to as image segmentation, is to segregate visual objects from the background and each other to generate visual perception and guide behavior. Visual motion cues are particularly powerful for segmentation. In this dissertation, I studied how neurons in the middle temporal (MT) cortex, a cortical area important for processing visual motion information, encode multiple moving stimuli. I also investigated how the encoding rules characterized in my studies benefit the extraction of information about individual stimulus components from population neuronal responses. In the first project, I revealed the neural basis for the well-known perceptual phenomenon of direction repulsion, and demonstrated how direction repulsion benefits the segmentation of overlapping moving stimuli. I found that the shape of the population neuronal responses elicited by overlapping random-dot stimuli are widened at direction separations of 45℗ʻ and 60℗ʻ, compared to if neurons linearly pool responses to individual stimulus components. In the second project, I investigated how neurons in area MT represent multiple visual stimuli that compete in more than one feature domain. I found that MT neurons showed a bias towards a stimulus component with a higher contrast and lower motion coherence when overlapping, even though that stimulus component evoked a weaker response in MT compared to a stimulus with a lower contrast and higher coherence. I also found that how MT neurons represent multiple stimuli is dependent on the spatial arrangement, highlighting the impact of hierarchical processing on the representation of multiple stimuli. In the third project, I investigated the neural representation of multiple moving stimuli that are spatially separated within the receptive fields of MT neurons. I found that neurons in area MT showed a spatial bias towards the stimulus that elicited a stronger response when presented alone. These studies made several novel findings about how MT neurons pool inputs from multiple stimuli in a nonlinear fashion and the impact on population neuronal responses. Thanks to these response nonlinearities, the visual system is equipped with a population neural code that facilitates the segmentation of multiple visual entities in natural environments.
Neural Representation Of Multiple Moving Features In Extrastriate Visual Cortical Area Mt
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Author : Jianbo Xiao
language : en
Publisher:
Release Date : 2017
Neural Representation Of Multiple Moving Features In Extrastriate Visual Cortical Area Mt written by Jianbo Xiao and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Natural scenes often contain multiple entities. The ability to segregate visual scenes into distinct objects and surfaces, referred to as visual segmentation, is fundamental to vision. Transparent motion perception is the perception of multiple motion vectors within the same visual space. Transparent motion presents a difficult case for visual segmentation. Understanding neural representation of transparent motion is important to elucidating how the brain distinguishes multiple stimuli. In this dissertation, I studied the neural representation of transparent motion by recording from neurons in the middle temporal (MT) cortex of macaque monkeys while they performed either a visual fixation task or a motion discrimination task. In the first project, I investigated the neural representation of two transparently moving stimuli that have different signal strengths. I found that neuronal responses to the transparent motion stimuli can be well accounted for by the weighted summation of the component responses plus a non-linear interaction term between the component responses, and MT neurons weight the stimulus component that has the higher signal strength more strongly. In the second project, I investigated how MT neurons represent overlapping random-dot stimuli moving transparently in slightly different directions. I found that, although the population-averaged neuronal activity represents the vector-averaged direction of the two motion components, more than half of MT neurons preferentially represent the component directions. In the third project, I studied the neural representation of overlapping stimuli moving transparently at different depths and the effects of feature-based attention to understand how different motion features, which in this case are motion direction and binocular disparity, interact with each other to achieve visual segmentation. I found a tuned feature-based attention effect and that MT neurons preferentially represent the near stimulus component regardless of the attentional state and the neuron's binocular disparity selectivity. This dissertation research demonstrated the success of divisive normalization model in characterizing the neuronal representation of transparent motion, and discovered soub-populations of MT neurons that were capable of discriminating similar motion directions, and illustrated the dominant neural representation of the near component stimulus in response to multiple stimuli moving transparently at different depths.
Contextual Interactions In Cortical Motion And Surface Perception
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Author : Julia Berzhanskaya
language : en
Publisher:
Release Date : 2005
Contextual Interactions In Cortical Motion And Surface Perception written by Julia Berzhanskaya and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.
Abstract: This dissertation describes neural modeling and psychophysical experiments that clarify how ambiguous visual signals can be disambiguated by contextual interactions. A neural model of the V1-V2-MT-MST areas of the visual cortex is developed to explain how context can influence motion percepts. Psychophysical experiments clarify how context can influence the perception of gloss on a 3D surface and support earlier model predictions about perceptual surface formation. To process object motion in cluttered environments, the brain has to solve multiple problems. One concerns aperture ambiguity. If a featureless line is observed through an aperture in an occluding surface, the perceived direction of motion is perpendicular to the line and may differ from the real motion direction. Integration of motion across apertures helps to determine the true direction of motion. If multiple moving objects overlap, motion segmentation and motion separation in depth help to limit the areas of motion integration. Figure-ground constraints also help to disambiguate the object to which a moving feature belongs. Thus, both form and motion information are combined in the current 3D FORMOTION model to accurately determine object motion. The model simulates effects of visible and invisible occluders on segregation of motion signals within and across depth, and how object shape and nearby objects can influence motion percepts. The psychophysical experiments clarify how percepts of gloss in an image can change as a function distance on the depicted surface rather than of distance in the image plane. Data suggest that the perception of gloss depends on a spatially local filling-in process, or gloss propagation, that is triggered by distinctive highlight features in the context of a 3D surface representation. Space-variant gloss ratings can be explained by generalizing previous models of brightness perception.
Cortical Neural Network Models Of Visual Motion Perception For Decision Making And Reactive Navigation
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Author : Michael Beyeler
language : en
Publisher:
Release Date : 2016
Cortical Neural Network Models Of Visual Motion Perception For Decision Making And Reactive Navigation written by Michael Beyeler and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Animals use vision to traverse novel cluttered environments with apparent ease. Evidence suggests that the mammalian brain integrates visual motion cues across a number of remote but interconnected brain regions that make up a visual motion pathway. Although much is known about the neural circuitry that is concerned with motion perception in the Primary Visual Cortex (V1) and the Middle Temporal area (MT), little is known about how relevant perceptual variables might be represented in higher-order areas of the motion pathway, and how neural activity in these areas might relate to the behavioral dynamics of locomotion.The main goal of this dissertation is to investigate the computational principles that the mammalian brain might be using to organize low-level motion signals into distributed representations of perceptual variables, and how neural activity in the motion pathway might mediate behavior in reactive navigation tasks. I first investigated how the aperture problem, a fundamental conceptual challenge encountered by all low-level motion systems, can be solved in a spiking neural network model of V1 and MT (consisting of 153,216 neurons and 40 million synapses), relying solely on dynamics and properties gleaned from known electrophysiological and neuroanatomical evidence, and how this neural activity might influence perceptual decision-making. Second, when used with a physical robot performing a reactive navigation task in the real world, I found that the model produced behavioral trajectories that closely matched human psychophysics data. Essential to the success of these studies were software implementations that could execute in real time, which are freely and openly available to the community. Third, using ideas from the efficient-coding and free-energy principles, I demonstrated that a variety of response properties of neurons in the dorsal sub-region of the Medial Superior Temporal area (MSTd) area could be derived from MT-like input features. This finding suggests that response properties such as 3D translation and rotation selectivity, complex motion perception, and heading selectivity might simply be a by-product of MSTd neurons performing dimensionality reduction on their inputs. The hope is that these studies will not only further our understanding of how the brain works, but also lead to novel algorithms and brain-inspired robots capable of outperforming current artificial systems.
Hierarchical Object Representations In The Visual Cortex And Computer Vision
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Author : Antonio Rodríguez-Sánchez
language : en
Publisher: Frontiers Media SA
Release Date : 2016-06-08
Hierarchical Object Representations In The Visual Cortex And Computer Vision written by Antonio Rodríguez-Sánchez and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-08 with Neurosciences. Biological psychiatry. Neuropsychiatry categories.
Over the past 40 years, neurobiology and computational neuroscience has proved that deeper understanding of visual processes in humans and non-human primates can lead to important advancements in computational perception theories and systems. One of the main difficulties that arises when designing automatic vision systems is developing a mechanism that can recognize - or simply find - an object when faced with all the possible variations that may occur in a natural scene, with the ease of the primate visual system. The area of the brain in primates that is dedicated at analyzing visual information is the visual cortex. The visual cortex performs a wide variety of complex tasks by means of simple operations. These seemingly simple operations are applied to several layers of neurons organized into a hierarchy, the layers representing increasingly complex, abstract intermediate processing stages. In this Research Topic we propose to bring together current efforts in neurophysiology and computer vision in order 1) To understand how the visual cortex encodes an object from a starting point where neurons respond to lines, bars or edges to the representation of an object at the top of the hierarchy that is invariant to illumination, size, location, viewpoint, rotation and robust to occlusions and clutter; and 2) How the design of automatic vision systems benefit from that knowledge to get closer to human accuracy, efficiency and robustness to variations.
Occlusion And The Interpretation Of Visual Motion
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Author : Robert O. Duncan
language : en
Publisher:
Release Date : 1999
Occlusion And The Interpretation Of Visual Motion written by Robert O. Duncan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Depth perception categories.
Foundations Of Vision
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Author : Brian A. Wandell
language : en
Publisher: Sinauer Associates, Incorporated
Release Date : 1995
Foundations Of Vision written by Brian A. Wandell and has been published by Sinauer Associates, Incorporated this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Medical categories.
Designed for students, scientists and engineers interested in learning about the core ideas of vision science, this volume brings together the broad range of data and theory accumulated in this field.
Motion Parallax Defined Segmentation And Depth Perception In Human Vision
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Author : Ahmad Yoonessi
language : en
Publisher:
Release Date : 2012
Motion Parallax Defined Segmentation And Depth Perception In Human Vision written by Ahmad Yoonessi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
Furthermore, eye movements were independent of the actual stimulus motion for shear, whereas they showed some dependence in dynamic occlusion. Psychophysical performance was significantly correlated with the accuracy of eye movements, primarily in the mid-range values of rendered depth. Taken together, these studies demonstrated distinct patterns of results for segmentation and depth performance across different ranges of rendered depth. These findings suggest that motion parallax information might be processed by distinct mechanisms, perhaps in separate areas of the visual cortex, depending upon the amount of depth in the visual stimulus." --
Dynamics Of Visual Motion Processing
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Author : Guillaume S. Masson
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-12-02
Dynamics Of Visual Motion Processing written by Guillaume S. Masson and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-02 with Medical categories.
Motion processing is an essential piece of the complex brain machinery that allows us to reconstruct the 3D layout of objects in the environment, to break camouflage, to perform scene segmentation, to estimate the ego movement, and to control our action. Although motion perception and its neural basis have been a topic of intensive research and modeling the last two decades, recent experimental evidences have stressed the dynamical aspects of motion integration and segmentation. This book presents the most recent approaches that have changed our view of biological motion processing. These new experimental evidences call for new models emphasizing the collective dynamics of large population of neurons rather than the properties of separate individual filters. Chapters will stress how the dynamics of motion processing can be used as a general approach to understand the brain dynamics itself.