Download or read book Nonlinear Vision Determination of Neural Receptive Fields Function and Networks written by Robert B. Pinter and published by CRC Press. This book was released on 2018-05-04 with total page 563 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text brings to vision research a treatment different from that often found in books on the subject in its emphasis on nonlinear aspects of vision, from human perception to eye cells of the fly. There is considerable emphasis on mathematics, which forms not only models but the algorithms for processing data.
Download or read book Nonlinear Vision Determination of Neural Receptive Fields Function and Networks written by Robert B. Pinter and published by CRC Press. This book was released on 2018-05-04 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text brings to vision research a treatment different from that often found in books on the subject in its emphasis on nonlinear aspects of vision, from human perception to eye cells of the fly. There is considerable emphasis on mathematics, which forms not only models but the algorithms for processing data.
Download or read book Nonlinear Subunit Models of Neuronal Receptive Fields in the Early Visual Pathway written by Amol Gharat and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Our visual system is sensitive to boundaries defined by differences in cues such as luminance (first-order cue), as well as texture, contrast, or motion (second-order cues). Gradients in these cues can be utilized to perform tasks such as figure-ground segregation and 3D shape perception. A significant fraction of neurons in the early visual cortex of cats and monkeys have been shown to be selective to both first- and second-order boundaries. These neurons are thought to be the neural correlate for perceptual encoding of such boundaries. They are selective for the same boundary orientation irrespective of the cue (first- or second-order) that defines it ("form cue-invariance"), which makes these neurons powerful candidates for the task of segmentation. However, the neural circuitry that gives rise to this selectivity for the early stages of visual processing remains unclear. To address this question, I perform neurophysiological recordings at the early stages of the visual pathway in cats, and then build biologically inspired neural circuit models that can account for visual response properties of neurons at subcortical as well as early cortical stages. In Chapter 2, I use multi-electrode recordings to demonstrate the presence of a significant fraction of neurons in cat Area 18 with nonlinear receptive fields like those of subcortical Y-type cells. These neurons have receptive field properties intermediate between subcortical Y cells and cortical orientation selective cue-invariant neurons. These are strong candidates for building cue-invariant orientation-selective neurons. Furthermore I present a novel neural circuit model that pools such Y-like neurons in an unbalanced "push-pull" manner, to generate orientation-selective cue-invariant receptive fields.In Chapter 3, I estimate biologically constrained neural network models of cat LGN receptive fields using recent machine learning methods (deep learning). The receptive fields are modeled as arising from a two-stage convolutional neural network model. The first stage, corresponding to retinal bipolar cell subunits, is modeled as a convolutional filter layer, and the second stage is modeled as a pooling layer. These two layers are separated by an intermediate parametric nonlinearity. I train such a neural network model for each recorded LGN neuron, using its spiking responses to naturalistic texture stimuli. These models are not only better in comparison to the standard linear-nonlinear models at predicting response to arbitrary stimuli, but they also recover biologically interpretable subunit models.In chapter 4, I evaluate the integration of ON- and OFF-pathway inputs by individual neurons in early cortical areas of the cat (Area 17 and Area 18). In this study, I model receptive fields of cortical simple cells as a linear weighted sum of rectified inputs from model ON- and OFF-center LGN afferents, with the weights estimated using a regression framework. The estimated models reveal significant asymmetries in spatiotemporal integration of ON and OFF signals within simple cell receptive fields. These observed asymmetries could provide the neural mechanism for generating cue-invariant receptive fields from Y-pathway inputs.In summary, I put together our knowledge of retinal as well as early cortical processing to show how spatial nonlinearities emerging from the retina could provide an essential basis for cortical visual processing. I further evaluate these neural mechanisms by estimating single neuron receptive field models, using modern system identification methods. Finally I propose, and provide supportive evidence for, a novel neural circuit mechanism that could explain the cue-invariant processing of luminance- and texture-defined boundaries through a common pathway." --
Download or read book Nonlinear Image Processing written by Sanjit Mitra and published by Academic Press. This book was released on 2001 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: This state-of-the-art book deals with the most important aspects of non-linear imaging challenges. The need for engineering and mathematical methods is essential for defining non-linear effects involved in such areas as computer vision, optical imaging, computer pattern recognition, and industrial automation challenges.
Download or read book Nonlinear Dynamic Modeling of Physiological Systems written by Professor Vasilis Z. Marmarelis and published by John Wiley & Sons. This book was released on 2004-09-03 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: The study of nonlinearities in physiology has been hindered by the lack of effective ways to obtain nonlinear dynamic models from stimulus-response data in a practical context. A considerable body of knowledge has accumulated over the last thirty years in this area of research. This book summarizes that progress, and details the most recent methodologies that offer practical solutions to this daunting problem. Implementation and application are discussed, and examples are provided using both synthetic and actual experimental data. This essential study of nonlinearities in physiology apprises researchers and students of the latest findings and techniques in the field.
Download or read book Seeing written by Karen K. De Valois and published by Academic Press. This book was released on 2000-04-28 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the most remarkable things about seeing is how effortless this complex task appears to be. This book provides a comprehensive overview of research on the myriad complexities of this task. Coverage includes such classic topics as color, spatial, and binocular vision, areas that have seen a recent explosion of new information such as motion vision, image formation and sampling, and areas where new tools have allowed a better investigation into processes (e.g. neural representation of shape, visual attention).Seeing is a needed reference for researchers specializing in visual perception and is suitable for advance courses on vision.
Download or read book Vision written by Jeanny Hrault and published by World Scientific. This book was released on 2010 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: At the fascinating frontiers of neurobiology, mathematics and psychophysics, this book addresses the problem of human and computer vision on the basis of cognitive modeling. After recalling the physics of light and its transformation through media and optics, Hrault presents the principles of the primate's visual system in terms of anatomy and functionality. Then, the neuronal circuitry of the retina is analyzed in terms of spatio?temporal filtering. This basic model is extended to the concept of neuromorphic circuits for motion processing and to the processing of color in the retina. For more in-depth studies, the adaptive non-linear properties of the photoreceptors and of ganglion cells are addressed, exhibiting all the power of the retinal pre-processing of images as a system of information cleaning suitable for further cortical processing. As a target of retinal information, the primary visual area is presented as a bank of filters able to extract valuable descriptors of images, suitable for categorization and recognition and also for local information extraction such as saliency and perspective. All along the book, many comparisons between the models and human perception are discussed as well as detailed applications to computer vision.
Download or read book Visual Population Codes written by Nikolaus Kriegeskorte and published by MIT Press. This book was released on 2012 with total page 659 pages. Available in PDF, EPUB and Kindle. Book excerpt: How visual content is represented in neuronal population codes and how to analyze such codes with multivariate techniques. Vision is a massively parallel computational process, in which the retinal image is transformed over a sequence of stages so as to emphasize behaviorally relevant information (such as object category and identity) and deemphasize other information (such as viewpoint and lighting). The processes behind vision operate by concurrent computation and message passing among neurons within a visual area and between different areas. The theoretical concept of "population code" encapsulates the idea that visual content is represented at each stage by the pattern of activity across the local population of neurons. Understanding visual population codes ultimately requires multichannel measurement and multivariate analysis of activity patterns. Over the past decade, the multivariate approach has gained significant momentum in vision research. Functional imaging and cell recording measure brain activity in fundamentally different ways, but they now use similar theoretical concepts and mathematical tools in their modeling and analyses. With a focus on the ventral processing stream thought to underlie object recognition, this book presents recent advances in our understanding of visual population codes, novel multivariate pattern-information analysis techniques, and the beginnings of a unified perspective for cell recording and functional imaging. It serves as an introduction, overview, and reference for scientists and students across disciplines who are interested in human and primate vision and, more generally, in understanding how the brain represents and processes information.
Download or read book Genomics and Proteomics Engineering in Medicine and Biology written by Metin Akay and published by John Wiley & Sons. This book was released on 2006-10-09 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: Current applications and recent advances in genomics and proteomics Genomics and Proteomics Engineering in Medicine and Biology presents a well-rounded, interdisciplinary discussion of a topic that is at the cutting edge of both molecular biology and bioengineering. Compiling contributions by established experts, this book highlights up-to-date applications of biomedical informatics, as well as advancements in genomics-proteomics areas. Structures and algorithms are used to analyze genomic data and develop computational solutions for pathological understanding. Topics discussed include: Qualitative knowledge models Interpreting micro-array data Gene regulation bioinformatics Methods to analyze micro-array Cancer behavior and radiation therapy Error-control codes and the genome Complex life science multi-database queries Computational protein analysis Tumor and tumor suppressor proteins interactions
Download or read book Advanced Methods of Physiological System Modeling written by V.Z. Marmarelis and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is the third in a series entitled" Advanced Methods of Physiological System Modeling" and the fifth in a series of research volumes published by Plenum under the sponsorship of the Biomedical Simulations Resource (BMSR) at the Uni versity of Southern California in the context of dissemination activities supported by the Biomedical Research Technology Program of the National Center for Research Resources at the National Institutes of Health under Grant No. P41 RR-OI861. These volumes are edited by BMSR principal scientists and report on recent research de velopments in the area of physiological systems modeling, as well as on advanced methods for analysis of physiological signals and data. As in the previous two volumes of this series, the work reported herein is con cerned with the development of advanced modeling methodologies and their novel application to problems of biomedical interest, with emphasis on nonlinear aspects of physiological function. The term "advanced methodologies" is used to indicate that the scope of this work extends beyond the ordinary type of analysis, which is confined traditionally to the linear domain. As the importance of nonlinearities in understanding the complex mechanisms of physiological function is increasingly recognized, the need for effective and practical modeling methodologies that address the issue of nonlinear dynamics in life sciences becomes more and more pressing.
Download or read book Encyclopedia of Optical and Photonic Engineering Print Five Volume Set written by Craig Hoffman and published by CRC Press. This book was released on 2015-09-22 with total page 3726 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first edition of the Encyclopedia of Optical and Photonic Engineering provided a valuable reference concerning devices or systems that generate, transmit, measure, or detect light, and to a lesser degree, the basic interaction of light and matter. This Second Edition not only reflects the changes in optical and photonic engineering that have occurred since the first edition was published, but also: Boasts a wealth of new material, expanding the encyclopedia’s length by 25 percent Contains extensive updates, with significant revisions made throughout the text Features contributions from engineers and scientists leading the fields of optics and photonics today With the addition of a second editor, the Encyclopedia of Optical and Photonic Engineering, Second Edition offers a balanced and up-to-date look at the fundamentals of a diverse portfolio of technologies and discoveries in areas ranging from x-ray optics to photon entanglement and beyond. This edition’s release corresponds nicely with the United Nations General Assembly’s declaration of 2015 as the International Year of Light, working in tandem to raise awareness about light’s important role in the modern world. Also Available Online This Taylor & Francis encyclopedia is also available through online subscription, offering a variety of extra benefits for researchers, students, and librarians, including: Citation tracking and alerts Active reference linking Saved searches and marked lists HTML and PDF format options Contact Taylor and Francis for more information or to inquire about subscription options and print/online combination packages. US: (Tel) 1.888.318.2367; (E-mail) [email protected] International: (Tel) +44 (0) 20 7017 6062; (E-mail) [email protected]
Download or read book Cerebral Cortex written by Philip S. Ulinski and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 587 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is devoted to mathematical models of the cortex. Computational models of individual neurons and ensembles of neurons are increasingly used in research on cortical organization and function. This is, in part, because of the now ubiquitous presence of powerful and affordable computers. The volume begins with a short history of models of cortical neurons and circuitry that introduces the principal modeling styles. An attempt has been made throughout the volume to make it accessible to readers with minimal mathematical backgrounds.
Download or read book Nonlinear Analysis of the Neural Basis for Natural Vision written by Stephen Vaclav David and published by . This book was released on 2004 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Advanced Mathematical Approach to Biology written by Takeyuki Hida and published by World Scientific. This book was released on 1997 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume consists of three papers, the first paper by T Ray aims to create an instantiation of evolution by natural selection in the computational medium. This creates a conceptual problem that requires considerable art to solve.The second paper by K-I Naka and V Bhanot discusses an interesting application of white noise analysis to the retinal physiology. It deals with identification of the retina mathematically, and one can see profound results that can be discovered only by using white noise analysis.The last paper by T Hida illustrates the use of white noise analysis for biologists. Readers will see the types of topics to which white noise analysis can be applied and how to apply the theory to actual phenomena.
Download or read book Analysis of Physiological Systems written by Vasilis Marmarelis and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: In studying physiological systems bioscientists are continually faced with the problem of providing descriptions of cause-effect relationships. This task is usually carried out through the performance of stimulus-response experiments. In the past, the design of such experiments has been ad hoc, incomplete, and certainly inefficient. Worse yet, bioscientists have failed to take advantage of advances in fields directly related to their problems (specifically, advances in the area of systems analysis). The raison d'etre of this book is to rectify this deficiency by providing the physiologist with methodological tools that will be useful to him or her in everyday labora tory encounters with physiological systems. The book was written so that it would be practical, useful, and up-to date. With this in mind, parts of it give step-by-step descriptions of in the laboratory. It is hoped that this systematic procedures to be followed will increase the usefulness of the book to the average research physiologist and, perhaps, reduce the need for in-depth knowledge of some of the associated mathematics. Even though the material deals with state-of-the art techniques in systems and signal analysis, the mathematical level has been kept low so as to be comprehensible to the average physiologist with no extensive training in mathematics. To this end, mathematical rigor is often sacrificed readily to intuitive simple arguments.
Download or read book From Statistics to Neural Networks written by Vladimir Cherkassky and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: The NATO Advanced Study Institute From Statistics to Neural Networks, Theory and Pattern Recognition Applications took place in Les Arcs, Bourg Saint Maurice, France, from June 21 through July 2, 1993. The meeting brought to gether over 100 participants (including 19 invited lecturers) from 20 countries. The invited lecturers whose contributions appear in this volume are: L. Almeida (INESC, Portugal), G. Carpenter (Boston, USA), V. Cherkassky (Minnesota, USA), F. Fogelman Soulie (LRI, France), W. Freeman (Berkeley, USA), J. Friedman (Stanford, USA), F. Girosi (MIT, USA and IRST, Italy), S. Grossberg (Boston, USA), T. Hastie (AT&T, USA), J. Kittler (Surrey, UK), R. Lippmann (MIT Lincoln Lab, USA), J. Moody (OGI, USA), G. Palm (U1m, Germany), B. Ripley (Oxford, UK), R. Tibshirani (Toronto, Canada), H. Wechsler (GMU, USA), C. Wellekens (Eurecom, France) and H. White (San Diego, USA). The ASI consisted of lectures overviewing major aspects of statistical and neural network learning, their links to biological learning and non-linear dynamics (chaos), and real-life examples of pattern recognition applications. As a result of lively interactions between the participants, the following topics emerged as major themes of the meeting: (1) Unified framework for the study of Predictive Learning in Statistics and Artificial Neural Networks (ANNs); (2) Differences and similarities between statistical and ANN methods for non parametric estimation from examples (learning); (3) Fundamental connections between artificial learning systems and biological learning systems.
Download or read book What can simple brains teach us about how vision works written by Davide Zoccolan and published by Frontiers Media SA. This book was released on 2015-11-18 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vision is the process of extracting behaviorally-relevant information from patterns of light that fall on retina as the eyes sample the outside world. Traditionally, nonhuman primates (macaque monkeys, in particular) have been viewed by many as the animal model-of-choice for investigating the neuronal substrates of visual processing, not only because their visual systems closely mirror our own, but also because it is often assumed that “simpler” brains lack advanced visual processing machinery. However, this narrow view of visual neuroscience ignores the fact that vision is widely distributed throughout the animal kingdom, enabling a wide repertoire of complex behaviors in species from insects to birds, fish, and mammals. Recent years have seen a resurgence of interest in alternative animal models for vision research, especially rodents. This resurgence is partly due to the availability of increasingly powerful experimental approaches (e.g., optogenetics and two-photon imaging) that are challenging to apply to their full potential in primates. Meanwhile, even more phylogenetically distant species such as birds, fish, and insects have long been workhorse animal models for gaining insight into the core computations underlying visual processing. In many cases, these animal models are valuable precisely because their visual systems are simpler than the primate visual system. Simpler systems are often easier to understand, and studying a diversity of neuronal systems that achieve similar functions can focus attention on those computational principles that are universal and essential. This Research Topic provides a survey of the state of the art in the use of animal models of visual functions that are alternative to macaques. It includes original research, methods articles, reviews, and opinions that exploit a variety of animal models (including rodents, birds, fishes and insects, as well as small New World monkey, the marmoset) to investigate visual function. The experimental approaches covered by these studies range from psychophysics and electrophysiology to histology and genetics, testifying to the richness and depth of visual neuroscience in non-macaque species.
