Towards an Integrated Model of Feedforward-feedback Processing in the Visual Cortex PDF Download
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Author: Ivaylo P. Riskov
Publisher:
ISBN:
Category :
Languages : en
Pages : 174
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Book Description
The goal of this work is to explore a potential improvement on a visual recognition system. The system is a biologically-plausible computational model of the feedforward part of the ventral stream in the visual cortex and successfully models human performance on visual recognition tasks for the first 50-100 milliseconds since the presentation of the visual stimulus. We make the first steps to a possible augmentation of the system that will account for both feedforward and feedback processes in the ventral stream. We explore the plausibility of Bayesian network models for feedback. Our results show that although the resulting system under performs the original, it has a better rate of improvement as more and more training examples are added to it.
Author: Hulusi Kafaligonul
Publisher: Frontiers Media SA
ISBN: 2889195945
Category : Feedback
Languages : en
Pages : 153
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Book Description
The visual system consists of hierarchically organized distinct anatomical areas functionally specialized for processing different aspects of a visual object (Felleman & Van Essen, 1991). These visual areas are interconnected through ascending feedforward projections, descending feedback projections, and projections from neural structures at the same hierarchical level (Lamme et al., 1998). Accumulating evidence from anatomical, functional and theoretical studies suggests that these three projections play fundamentally different roles in perception. However, their distinct functional roles in visual processing are still subject to debate (Lamme & Roelfsema, 2000). The focus of this Research Topic is the roles of feedforward and feedback projections in vision. Even though the notions of feedforward, feedback, and reentrant processing are widely accepted, it has been found difficult to distinguish their individual roles on the basis of a single criterion. We welcome empirical contributions, theoretical contributions and reviews that fit into any one (or a combination) of the following domains: 1) their functional roles for perception of specific features of a visual object 2) their contributions to the distinct modes of visual processing (e.g., pre-attentive vs. attentive, conscious vs. unconscious) 3) recent techniques/methodologies to identify distinct functional roles of feedforward and feedback projections and corresponding neural signatures. We believe that the current Research Topic will not only provide recent information about feedforward/feedback processes in vision but also contribute to the understanding fundamental principles of cortical processing in general.
Author: Ivaylo P. Riskov
Publisher:
ISBN:
Category :
Languages : en
Pages : 174
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Book Description
The goal of this work is to explore a potential improvement on a visual recognition system. The system is a biologically-plausible computational model of the feedforward part of the ventral stream in the visual cortex and successfully models human performance on visual recognition tasks for the first 50-100 milliseconds since the presentation of the visual stimulus. We make the first steps to a possible augmentation of the system that will account for both feedforward and feedback processes in the ventral stream. We explore the plausibility of Bayesian network models for feedback. Our results show that although the resulting system under performs the original, it has a better rate of improvement as more and more training examples are added to it.
Author: Thomas Joseph Sullivan
Publisher:
ISBN:
Category :
Languages : en
Pages : 296
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Book Description
Author: Antonio Rodríguez-Sánchez
Publisher: Frontiers Media SA
ISBN: 2889197980
Category : Neurosciences. Biological psychiatry. Neuropsychiatry
Languages : en
Pages : 292
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Book Description
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.
Author: Mark Jeremy Nolt
Publisher:
ISBN: 9781109848007
Category :
Languages : en
Pages : 90
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Book Description
The thalamus has often been viewed as the "gateway" to visual cortex. This idea suggests that all sensory information entering the brain must first pass through the thalamus before arriving in the cortex. More recent studies have shown that significant processing also occurs in the thalamus, although the contributions of feedback connections from cortex to this processing are largely unknown. Here, we explore the contributions of feedforward and feedback input to visual processing in the lateral geniculate nucleus (LGN), the thalamic relay nucleus of the visual system. Conclusions are reached using two approaches. The first is to record simultaneously from LGN cells and one of their excitatory RGC inputs. This is accomplished by recording S-potentials, the extracellularly recorded postsynaptic signature of RGCs. Our second approach is to record extracellularly from LGN cells before, during, and after cooling of a large, retinotopically corresponding portion of visual cortex (areas 17 and 18). In the first set of experiments, we find that LGN cells exhibit contrast dependent spatial summation and that this property originates in the RGC input to relay cells. This suggests that this property is simply relayed by the LGN on to visual cortex. In the second set of experiments, we show that surround suppression at high spatial frequencies is present in the receptive fields of LGN X-cells. We show that half of this suppression arises from the retinal input, and that surround suppression in LGN cells is greater than that in RGCs, regardless of spatial frequency. We also inactivated the ipsilateral visual cortex and show that one quarter of the surround suppression at high spatial frequencies arises from the corticothalamic feedback. We show that this suppression is co-localized with the classical surround, is not dependent on the relative orientation of the center and surround stimuli, and that the cortical component of this suppression is divisive. When taken together, this work shows that the LGN is more than a simple relay nucleus, and more importantly, it defines a functional role of corticothalamic feedback in sensory processing.
Author: Bartlett Doe Moore
Publisher:
ISBN: 9781124025605
Category :
Languages : en
Pages :
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Book Description
The unique ecological utility provided by the complex sensory processing that occurs in the brains of visual animals cannot be over appreciated. Psychologists, physiologists, mathematicians, and philosophers, among others, have subjected vision in humans and non-human animals to intense scrutiny. Perhaps the most studied regions of the mammalian visual system are the early visual pathways: the retina, the dorsal lateral geniculate nucleus of the thalamus (LGN), and area 17 of the primary visual cortex (V1). This dissertation was conceived and conducted to elucidate some of the contributions of feedforward processes to sensory responses in the early visual system. Extracellular recordings were collected from individual neurons in the retina, visual thalamus, and primary visual cortex of cats, and the primary visual cortex of ferrets while controlling the sensory input to the system. These methods were used to characterize five distinct features of information processing: 1) the influence of stimulus temporal frequency on orientation tuning in V1 neurons, 2) the influence of stimulus temporal frequency on direction selectivity in V1 neurons, 3) the response properties of LGN neurons in the absence of On-center retinal input, 4) the orientation tuning in V1 neurons in the absence of On-center LGN input, and 5) the direction selectivity of V1 neurons in the absence of On-center LGN input. The results presented in the following chapters show that the paradigmatic feedforward model of processing in the early visual system and its contribution to neuronal response properties requires further refinement. The work presented in chapter 2 show that the direction selectivity--but not orientation tuning--of ferret V1 neurons is dependant on the temporal frequency of stimuli, suggesting that stability of orientation tuning is an important aspect of early visual processing. The work presented in chapter 3 suggest there is more frequent divergence of connections in the retinogeniculate pathway of the cat than previously recognized and that functionally silent, non-specific retinal inputs can undergo rapid plasticity when the On pathway is disrupted. The work presented in chapter 4 investigates the response properties of V1 neurons in the absence of On-center LGN activity. The results show that while orientation tuning is resilient to the reduction in feedforward input, direction selectivity behaves more erratically. The early visual system is the computational foundation upon which more complex features are detected in the visual environment. In order to understand how visual processing in later visual pathways is accomplished, it is critical that the feedforward contributions to response properties in the early visual pathways be understood.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 224
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Author: Marina Arall
Publisher:
ISBN: 9789535107606
Category :
Languages : en
Pages :
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Author: Snehlata Jaswal
Publisher: Frontiers E-books
ISBN: 2889191400
Category :
Languages : en
Pages : 137
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Book Description
Feature binding is the process whereby different features such as shape, colour, size, orientation, location, etc. are linked together to form a coherent representation of the object. It is a ubiquitous physiological sequence and an essential phase in information processing, for it provides the basis of mental representations, which in turn, are requisite for all cognitive functions. It is important to realize though, that binding is not an isolated process. There are myriad stimuli impinging on our senses at all times, vying to gain entry into our consciousness. Further, not only does sensory input emanate from a complex, dynamic environment, but it also enters a neural system that is already activated by previous inputs and is oriented towards future goals. Which aspects of the momentary sensory input are selected for further processing depends as much on the state of the system as it does on the sensory input itself. Indeed, some fundamental questions one may ask about binding are whether, why, and how, some features are selected for binding at the cost of others. The bottom-up view of information processing is that the input received by the brain is processed in a largely automatic way to the higher centers in the brain. The physiological basis of binding is postulated to be either conjunctively coding neurons, or synchrony among participating neural networks to encode features and out of phase neural activity to encode separate objects. But, mere perceptual integration of features, whether by synchrony or by specialized neurons, does not even begin to capture the implication that binding results in coherent objects, fundamental for further information processing. An object is not only a bundle of features. At the very least, the features need to be integrated so that the object can be distinguished from other objects. This implies selection and manipulation of the basic information supplied by separate features. The top-down view of information processing contends that binding is more influenced by the reentrant processes (the downward and lateral feedback to the lower areas, emanating from the higher centers of the brain). Reentrant processes not only help to confirm what is correct but also resolve competition. These top-down processes are linked to attention and higher cognitive functions help select relevant input. We aim to debate what happens to the irrelevant information in the process of binding. Are irrelevant features simply lost from the system over time, or are they deliberately deleted? Is there any inhibitory process involved in binding? What is the empirical evidence for such a process at the behavioral level? Is such a process active and resource-demanding or relatively passive and automatic? What do neuropsychological studies show? What are the physiological underpinnings of such a process? How is it incorporated in computational models to increase our understanding of the binding process? The idea is to bring together diverse views on ‘Inhibition in Feature Binding’ with the ultimate aim of better understanding the process of binding and invoking informed and insightful future research.
Author: Alistair J. Bray
Publisher:
ISBN:
Category : Bionics
Languages : en
Pages : 84
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Abstract: "This document describes an activity-based model of information processing in the early mammalian visual pathway. The work has been published previously in an abbreviated form [9], so this report is intended to present a more complete story. The model describes the retina, lateral geniculate nucleus (LGN), and development of simple cells in visual cortex (layer IVc of V1). In the retina we employ a non-adaptive model of on-centre and off-centre retinal ganglion cells (the tonic cells only) that is a non-linear approximation to difference-of-Gaussian processing. The output of this provides input to the LGN where the On and Off channels are kept separate. Here we simulate the effects of local inhibitory lateral interactions; this stage is also non-adaptive. Simple cells in the cortical model receive feedforward excitation from both the On and Off channels projecting out of the LGN. We propose a dual population model in which one population excites close neighbours while the other inhibits all neighbours within a greater area. We simulate this dynamic feedback using an iterative method, and when the network activity is stable we adapt all feedforward weights connecting simple cells to the LGN using a Hebbian (correlation-based) learning rule. We find that when presenting the network with many samples from natural images, the simple cells' feedforward weights adapt to become 'edge' and 'bar' detectors with receptive fields extremely similar to Gabor functions. These edge and bar detectors are orientation selective, and the orientation preference of different simple cells varies smoothly across the cortical surface. When plotting preferred orientation we get 'orientation maps' qualitatively similar to those documented in neurophysiological literature (in terms of smoothness & singularities). We examine these maps (and others) in terms of their auto-correlation matrix and orientation distribution. Finally we describe preliminary experiments in which the lateral connections within the cortex are adaptive; we find that regions of simple cells develop within which the cells have similar receptive fields but between which the cells have different receptive fields."
