Effects Of Neuronal Correlations On Population Decoding And Encoding Models
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Effects Of Neuronal Correlations On Population Decoding And Encoding Models
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Author : Ami M. Patel
language : en
Publisher:
Release Date : 2013
Effects Of Neuronal Correlations On Population Decoding And Encoding Models written by Ami M. Patel and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
In this thesis, we analyze the effect of the correlations in neural activity on the information that is encoded in and can be decoded from a population of neurons. Various noise models describing these correlations are considered - in particular, we use models that take into account the pairwise correlations and other, simpler models that assume shared global additive and/or multiplicative noise factors. The performance of these models on firing rate prediction (encoding) and population decoding are studied. Our analyses show a significant beneficial effect of pairwise correlations on encoding models, with much of this benefit being explained by the global noise models. However, the effects of correlations on decoding vary among our datasets, providing an empirical justification to the theoretical results suggesting correlations can be either helpful or harmful to decoding.
The Effect Of Correlations And Conditional Independence Relations On Neural Information Coding
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Author : Nasr Madi
language : en
Publisher:
Release Date : 2009
The Effect Of Correlations And Conditional Independence Relations On Neural Information Coding written by Nasr Madi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.
Cognitive Electrophysiology
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Author : H.-J. Heinze
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Cognitive Electrophysiology written by H.-J. Heinze 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 2012-12-06 with Medical categories.
MICHAEL S. GAZZANIGA The investigation of the human brain and mind involves a myriad of ap proaches. Cognitive neuroscience has grown out of the appreciation that these approaches have common goals that are separate from other goals in the neural sciences. By identifying cognition as the construct of interest, cognitive neuro science limits the scope of investigation to higher mental functions, while simultaneously tackling the greatest complexity of creation, the human mind. The chapters of this collection have their common thread in cognitive neuroscience. They attack the major cognitive processes using functional stud ies in humans. Indeed, functional measures of human sensation, perception, and cognition are the keystone of much of the neuroscience of cognitive sci ence, and event-related potentials (ERPs) represent a methodological "coming of age" in the study of the intricate temporal characteristics of cognition. Moreover, as the field of cognitive ERPs has matured, the very nature of physiology has undergone a significant revolution. It is no longer sufficient to describe the physiology of non-human primates; one must consider also the detailed knowledge of human brain function and cognition that is now available from functional studies in humans-including the electrophysiological studies in humans described here. Together with functional imaging of the human brain via positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), ERPs fill our quiver with the arrows required to pierce more than the single neuron, but the networks of cognition.
Independent Component Analysis
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Author : Aapo Hyvärinen
language : en
Publisher: John Wiley & Sons
Release Date : 2004-04-05
Independent Component Analysis written by Aapo Hyvärinen and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-04-05 with Science categories.
A comprehensive introduction to ICA for students and practitioners Independent Component Analysis (ICA) is one of the most exciting new topics in fields such as neural networks, advanced statistics, and signal processing. This is the first book to provide a comprehensive introduction to this new technique complete with the fundamental mathematical background needed to understand and utilize it. It offers a general overview of the basics of ICA, important solutions and algorithms, and in-depth coverage of new applications in image processing, telecommunications, audio signal processing, and more. Independent Component Analysis is divided into four sections that cover: * General mathematical concepts utilized in the book * The basic ICA model and its solution * Various extensions of the basic ICA model * Real-world applications for ICA models Authors Hyvarinen, Karhunen, and Oja are well known for their contributions to the development of ICA and here cover all the relevant theory, new algorithms, and applications in various fields. Researchers, students, and practitioners from a variety of disciplines will find this accessible volume both helpful and informative.
Decoding Neural Mechanisms Of Surround Suppression In Feature Based Attention
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Author : Wanghaoming Fang
language : en
Publisher:
Release Date : 2021
Decoding Neural Mechanisms Of Surround Suppression In Feature Based Attention written by Wanghaoming Fang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Electronic dissertations categories.
Feature-based attention (FBA) selectively enhances processing of an attended feature at the expense of unattended or task-irrelevant features. Recent studies showed that FBA modulates the perceptual space with both a monotonic profile (i.e., feature-similarity gain) and a non-monotonic profile (i.e., surround suppression). A significant question arises regarding the neural mechanism of the non-monotonic surround suppression effect. Previous studies have suggested that two candidate neuronal mechanisms could underlie these attentional modulations: a shift of neuronal tuning preference toward the attended feature, or a multiplicative gain modulation that scales the overall responses without changing their tuning property. Yet the empirical evidence for these mechanisms is still lacking. In the current work, we explored how these neuronal mechanism manifest at the level of fMRI BOLD measurement using a simulation approach. Specifically, we employed an encoding/decoding approach by first simulating voxel responses from neuronal population assuming either mechanism and then applying a regression-based inverted encoding model (IEM) and a Bayesian method to decode population representations. We found that both methods captured the signature patterns associated with these different neuronal mechanisms. In our second aim, we systematically varied the correlation structure of voxel noise to further compare these different multivariate methods in a stimulus classification task. Our results showed a clear advantage of the Bayesian method over IEM, suggesting that the Bayesian method was superior for deciphering neural representation given the prevalent noise correlation and variable tuning width in the brain. In sum, our current simulation work may provide a proof of concept for future empirical studies investigating cortical mechanism of FBA using non-invasive methods, as well as guidance for choosing suitable methods in these investigations.
Interpretable Machine Learning
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Author : Christoph Molnar
language : en
Publisher: Lulu.com
Release Date : 2020
Interpretable Machine Learning written by Christoph Molnar and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Artificial intelligence categories.
This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
Coherent Behavior In Neuronal Networks
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Author : Krešimir Josic
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-08-22
Coherent Behavior In Neuronal Networks written by Krešimir Josic 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 2009-08-22 with Medical categories.
Recent experimental research advances have led to increasingly detailed descriptions of how networks of interacting neurons process information. With these developments, it has become clear that dynamic network behaviors underlie information processing, and that the observed activity patterns cannot be fully explained by simple concepts such as synchrony and phase locking. These new insights raise significant challenges and offer exciting opportunities for experimental and theoretical neuroscientists. Coherent Behavior in Neuronal Networks features a review of recent research in this area from some of the world’s foremost experts on systems neuroscience. The book presents novel methodologies and interdisciplinary perspectives, and will serve as an invaluable resource to the research community. Highlights include the results of interdisciplinary collaborations and approaches as well as topics, such as the interplay of intrinsic and synaptic dynamics in producing coherent neuronal network activity and the roles of globally coherent rhythms and oscillations in the coordination of distributed processing, that are of significant research interest but have been underrepresented in the review literature. With its cutting-edge mathematical, statistical, and computational techniques, this volume will be of interest to all researchers and students in the field of systems neuroscience.
Statistical Analysis Of Multi Cell Recordings Linking Population Coding Models To Experimental Data
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Author : Matthias Bethge
language : en
Publisher: Frontiers E-books
Release Date : 2012-01-01
Statistical Analysis Of Multi Cell Recordings Linking Population Coding Models To Experimental Data written by Matthias Bethge and has been published by Frontiers E-books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-01 with categories.
Modern recording techniques such as multi-electrode arrays and 2-photon imaging are capable of simultaneously monitoring the activity of large neuronal ensembles at single cell resolution. This makes it possible to study the dynamics of neural populations of considerable size, and to gain insights into their computations and functional organization. The key challenge with multi-electrode recordings is their high-dimensional nature. Understanding this kind of data requires powerful statistical techniques for capturing the structure of the neural population responses and their relation with external stimuli or behavioral observations. Contributions to this Research Topic should advance statistical modeling of neural populations. Questions of particular interest include: 1. What classes of statistical methods are most useful for modeling population activity? 2. What are the main limitations of current approaches, and what can be done to overcome them? 3. How can statistical methods be used to empirically test existing models of (probabilistic) population coding? 4. What role can statistical methods play in formulating novel hypotheses about the principles of information processing in neural populations? This Research Topic is connected to a one day workshop at the Computational Neuroscience Meeting 2009 in Berlin (http://www.cnsorg.org/2009/workshops.shtml and http://www.kyb.tuebingen.mpg.de/bethge/workshops/cns2009/)
Advances In Neural Information Processing Systems 12
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Author : Sara A. Solla
language : en
Publisher: MIT Press
Release Date : 2000
Advances In Neural Information Processing Systems 12 written by Sara A. Solla and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Computers categories.
The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented includes computer science, neuroscience, statistics, physics, cognitive science, and many branches of engineering, including signal processing and control theory. Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. These proceedings contain all of the papers that were presented.
Principles Of Neural Coding
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Author : Rodrigo Quian Quiroga
language : en
Publisher: CRC Press
Release Date : 2013-05-06
Principles Of Neural Coding written by Rodrigo Quian Quiroga and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-06 with Medical categories.
Understanding how populations of neurons encode information is the challenge faced by researchers in the field of neural coding. Focusing on the many mysteries and marvels of the mind has prompted a prominent team of experts in the field to put their heads together and fire up a book on the subject. Simply titled Principles of Neural Coding, this book covers the complexities of this discipline. It centers on some of the major developments in this area and presents a complete assessment of how neurons in the brain encode information. The book collaborators contribute various chapters that describe results in different systems (visual, auditory, somatosensory perception, etc.) and different species (monkeys, rats, humans, etc). Concentrating on the recording and analysis of the firing of single and multiple neurons, and the analysis and recording of other integrative measures of network activity and network states—such as local field potentials or current source densities—is the basis of the introductory chapters. Provides a comprehensive and interdisciplinary approach Describes topics of interest to a wide range of researchers The book then moves forward with the description of the principles of neural coding for different functions and in different species and concludes with theoretical and modeling works describing how information processing functions are implemented. The text not only contains the most important experimental findings, but gives an overview of the main methodological aspects for studying neural coding. In addition, the book describes alternative approaches based on simulations with neural networks and in silico modeling in this highly interdisciplinary topic. It can serve as an important reference to students and professionals.