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Author: Sepide Movaghati Publisher: ISBN: Category : Languages : en Pages :
Book Description
"According to classical models of visual information processing, the visual cortex acts as a hierarchical structure in which information flow is unidirectional and transmitted from the primary visual cortex (V1) to higher visual areas. This model considers V1 as an inflexible processing unit, which filters local basic features of visual input, such as the spatial frequency and orientation of the changes in luminance. Contrary to this classical model, recent studies have reported variant activity in V1 based on the presence of higher-order features within visual inputs. In other words, specific characteristics, such as phase content or spatial coherence, potentially modulate the activity of V1. However, the explicit characteristics and the precise timing of their modulatory effect remain unclear. In this study, MagnetoEncephaloGraphy (MEG) was used to test whether the spatiotemporal response to natural images of animals is different from the response to their phase-shuffled counterparts. The frequency content and the total contrast of the images were maintained throughout the phase-scrambling approach. Meanwhile, higher-order image statistics, such as Kurtosis, were manipulated. We investigated the effect of this manipulation on the evoked response of V1 by taking advantage of (1) the high temporal resolution of the MEG technique and (2) the Minimum norm source localization method. The results of this thesis show that the modulation of activity associated with the presentation of natural images appears as early as 50ms post-stimulation. This effect can be observed in the power of the signals recorded by MEG sensors as well as in sources localized in the primary visual cortex. The phase scrambling of visual input increased the amplitude of the early response (30-70ms post-stimulation) and the M170 component (140-200ms post-stimulation). The weaker population response to natural images during the early response is consistent with a model proposing sparse neuronal coding for natural images. The increased M170 activation of V1 to non-natural phase-scrambled images is consistent with the predictive coding model. According to this model, the prediction error in lower order sensory areas increases with decreasing predictability of the sensory input. An increase in the power of gamma frequency (60-80Hz) was observed in response to phase-scrambled images. These findings are in accordance with a previous study that found prediction errors in auditory cortex to be predominantly conveyed via the high (gamma) frequency range. In addition, spatially coherent features in visual input induce a stronger surround suppression effect and reduce the population activity in V1. Therefore, the mechanisms underlying the late modulatory effect on the M170 component may also involve surround suppression in the visual cortex. Our findings suggest that feedback modulates the neuronal response of the primary visual cortex. Further, they identify V1 as a dynamic filter that can be modulated by the higher-order characteristics of visual input, as opposed to previous models that deem V1 to be an inflexible low-level processing unit." --
Author: Sepide Movaghati Publisher: ISBN: Category : Languages : en Pages :
Book Description
"According to classical models of visual information processing, the visual cortex acts as a hierarchical structure in which information flow is unidirectional and transmitted from the primary visual cortex (V1) to higher visual areas. This model considers V1 as an inflexible processing unit, which filters local basic features of visual input, such as the spatial frequency and orientation of the changes in luminance. Contrary to this classical model, recent studies have reported variant activity in V1 based on the presence of higher-order features within visual inputs. In other words, specific characteristics, such as phase content or spatial coherence, potentially modulate the activity of V1. However, the explicit characteristics and the precise timing of their modulatory effect remain unclear. In this study, MagnetoEncephaloGraphy (MEG) was used to test whether the spatiotemporal response to natural images of animals is different from the response to their phase-shuffled counterparts. The frequency content and the total contrast of the images were maintained throughout the phase-scrambling approach. Meanwhile, higher-order image statistics, such as Kurtosis, were manipulated. We investigated the effect of this manipulation on the evoked response of V1 by taking advantage of (1) the high temporal resolution of the MEG technique and (2) the Minimum norm source localization method. The results of this thesis show that the modulation of activity associated with the presentation of natural images appears as early as 50ms post-stimulation. This effect can be observed in the power of the signals recorded by MEG sensors as well as in sources localized in the primary visual cortex. The phase scrambling of visual input increased the amplitude of the early response (30-70ms post-stimulation) and the M170 component (140-200ms post-stimulation). The weaker population response to natural images during the early response is consistent with a model proposing sparse neuronal coding for natural images. The increased M170 activation of V1 to non-natural phase-scrambled images is consistent with the predictive coding model. According to this model, the prediction error in lower order sensory areas increases with decreasing predictability of the sensory input. An increase in the power of gamma frequency (60-80Hz) was observed in response to phase-scrambled images. These findings are in accordance with a previous study that found prediction errors in auditory cortex to be predominantly conveyed via the high (gamma) frequency range. In addition, spatially coherent features in visual input induce a stronger surround suppression effect and reduce the population activity in V1. Therefore, the mechanisms underlying the late modulatory effect on the M170 component may also involve surround suppression in the visual cortex. Our findings suggest that feedback modulates the neuronal response of the primary visual cortex. Further, they identify V1 as a dynamic filter that can be modulated by the higher-order characteristics of visual input, as opposed to previous models that deem V1 to be an inflexible low-level processing unit." --
Author: Vargha Talebi Publisher: ISBN: Category : Languages : en Pages :
Book Description
Collectively, the three studies in this thesis demonstrate the powerful potential of natural image stimuli and regularized regression system identification techniques, making them ideal candidates for routine use in visual neuroscience studies. RF models derived from natural images have revealed that physiological response..." --
Author: Melanie A. Woodin Publisher: Springer Science & Business Media ISBN: 1441969780 Category : Medical Languages : en Pages : 191
Book Description
This volume will explore the most recent findings on cellular mechanisms of inhibitory plasticity and its functional role in shaping neuronal circuits, their rewiring in response to experience, drug addiction and in neuropathology. Inhibitory Synaptic Plasticity will be of particular interest to neuroscientists and neurophysiologists.
Author: Donald T. Stuss Publisher: Oxford University Press ISBN: 0198030835 Category : Medical Languages : en Pages : 642
Book Description
This volume provides a comprehensive review of historical and current research on the function of the frontal lobes and frontal systems of the brain. The content spans frontal lobe functions from birth to old age, from biochemistry and anatomy to rehabilitation, and from normal to disrupted function. The book is intended to be a standard reference work on the frontal lobes for researchers, clinicians, and students in the field of neurology, neuroscience, psychiatry, psychology, and health care.
Author: David Poeppel Publisher: Springer Science & Business Media ISBN: 1461423139 Category : Science Languages : en Pages : 404
Book Description
We live in a complex and dynamically changing acoustic environment. To this end, the auditory cortex of humans has developed the ability to process a remarkable amount of diverse acoustic information with apparent ease. In fact, a phylogenetic comparison of auditory systems reveals that human auditory association cortex in particular has undergone extensive changes relative to that of other species, although our knowledge of this remains incomplete. In contrast to other senses, human auditory cortex receives input that is highly pre-processed in a number of sub-cortical structures; this suggests that even primary auditory cortex already performs quite complex analyses. At the same time, much of the functional role of the various sub-areas in human auditory cortex is still relatively unknown, and a more sophisticated understanding is only now emerging through the use of contemporary electrophysiological and neuroimaging techniques. The integration of results across the various techniques signify a new era in our knowledge of how human auditory cortex forms basis for auditory experience. This volume on human auditory cortex will have two major parts. In Part A, the principal methodologies currently used to investigate human auditory cortex will be discussed. Each chapter will first outline how the methodology is used in auditory neuroscience, highlighting the challenges of obtaining data from human auditory cortex; second, each methods chapter will provide two or (at most) three brief examples of how it has been used to generate a major result about auditory processing. In Part B, the central questions for auditory processing in human auditory cortex are covered. Each chapter can draw on all the methods introduced in Part A but will focus on a major computational challenge the system has to solve. This volume will constitute an important contemporary reference work on human auditory cortex. Arguably, this will be the first and most focused book on this critical neurological structure. The combination of different methodological and experimental approaches as well as a diverse range of aspects of human auditory perception ensures that this volume will inspire novel insights and spurn future research.
Author: Vasilis Marmarelis Publisher: Springer Science & Business Media ISBN: 1461339707 Category : Medical Languages : en Pages : 495
Book Description
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.
Author: William D. Penny Publisher: Elsevier ISBN: 0080466508 Category : Psychology Languages : en Pages : 689
Book Description
In an age where the amount of data collected from brain imaging is increasing constantly, it is of critical importance to analyse those data within an accepted framework to ensure proper integration and comparison of the information collected. This book describes the ideas and procedures that underlie the analysis of signals produced by the brain. The aim is to understand how the brain works, in terms of its functional architecture and dynamics. This book provides the background and methodology for the analysis of all types of brain imaging data, from functional magnetic resonance imaging to magnetoencephalography. Critically, Statistical Parametric Mapping provides a widely accepted conceptual framework which allows treatment of all these different modalities. This rests on an understanding of the brain's functional anatomy and the way that measured signals are caused experimentally. The book takes the reader from the basic concepts underlying the analysis of neuroimaging data to cutting edge approaches that would be difficult to find in any other source. Critically, the material is presented in an incremental way so that the reader can understand the precedents for each new development. This book will be particularly useful to neuroscientists engaged in any form of brain mapping; who have to contend with the real-world problems of data analysis and understanding the techniques they are using. It is primarily a scientific treatment and a didactic introduction to the analysis of brain imaging data. It can be used as both a textbook for students and scientists starting to use the techniques, as well as a reference for practicing neuroscientists. The book also serves as a companion to the software packages that have been developed for brain imaging data analysis. An essential reference and companion for users of the SPM software Provides a complete description of the concepts and procedures entailed by the analysis of brain images Offers full didactic treatment of the basic mathematics behind the analysis of brain imaging data Stands as a compendium of all the advances in neuroimaging data analysis over the past decade Adopts an easy to understand and incremental approach that takes the reader from basic statistics to state of the art approaches such as Variational Bayes Structured treatment of data analysis issues that links different modalities and models Includes a series of appendices and tutorial-style chapters that makes even the most sophisticated approaches accessible
Author: Li Zhaoping Publisher: Oxford University Press, USA ISBN: 0199564663 Category : Medical Languages : en Pages : 397
Book Description
Vision science has grown hugely in the past decades, but there have been few books showing readers how to adopt a computional approach to understanding visual perception, along with the underlying mechanisms in the brain. This book explains the computational principles and models of biological visual processing, and in particular, primate vision.
Author: Jeffery A. Winer Publisher: Springer Science & Business Media ISBN: 0387270833 Category : Science Languages : en Pages : 720
Book Description
Connecting the auditory brain stem to sensory, motor, and limbic systems, the inferior colliculus is a critical midbrain station for auditory processing. Winer and Schreiner's The Inferior Colliculus, a critical, comprehensive reference, presents the current knowledge of the inferior colliculus from a variety of perspectives, including anatomical, physiological, developmental, neurochemical, biophysical, neuroethological and clinical vantage points. Written by leading researchers in the field, the book is an ideal introduction to the inferior colliculus and central auditory processing for clinicians, otolaryngologists, graduate and postgraduate research workers in the auditory and other sensory-motor systems.
Author: Nikolaus Kriegeskorte Publisher: MIT Press ISBN: 0262016249 Category : Mathematics Languages : en Pages : 659
Book Description
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.
Author: Sepide Movaghati
Author: Sepide Movaghati
Author: Vargha Talebi
Author: Melanie A. Woodin
Author: Donald T. Stuss
Author: David Poeppel
Author: Vasilis Marmarelis
Author: William D. Penny
Author: Li Zhaoping
Author: Jeffery A. Winer
Author: Nikolaus Kriegeskorte