Where's the Noise? Key Features of Neuronal Variability and Inference Emerge from Self-organized Learning
Author: Christoph Hartmann
Publisher:
Published: 2014
Total Pages: 0
ISBN-13:
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Connectome
Author: Sebastian Seung
Publisher: HMH
Published: 2012-02-07
Total Pages: 389
ISBN-13: 0547508174
DOWNLOAD EBOOK“Accessible, witty . . . an important new researcher, philosopher and popularizer of brain science . . . on par with cosmology’s Brian Greene and the late Carl Sagan” (The Plain Dealer). One of the Wall Street Journal’s 10 Best Nonfiction Books of the Year and a Publishers Weekly “Top Ten in Science” Title Every person is unique, but science has struggled to pinpoint where, precisely, that uniqueness resides. Our genome may determine our eye color and even aspects of our character. But our friendships, failures, and passions also shape who we are. The question is: How? Sebastian Seung is at the forefront of a revolution in neuroscience. He believes that our identity lies not in our genes, but in the connections between our brain cells—our particular wiring. Seung and a dedicated group of researchers are leading the effort to map these connections, neuron by neuron, synapse by synapse. It’s a monumental effort, but if they succeed, they will uncover the basis of personality, identity, intelligence, memory, and perhaps disorders such as autism and schizophrenia. Connectome is a mind-bending adventure story offering a daring scientific and technological vision for understanding what makes us who we are, as individuals and as a species. “This is complicated stuff, and it is a testament to Dr. Seung’s remarkable clarity of exposition that the reader is swept along with his enthusiasm, as he moves from the basics of neuroscience out to the farthest regions of the hypothetical, sketching out a spectacularly illustrated giant map of the universe of man.” —TheNew York Times “An elegant primer on what’s known about how the brain is organized and how it grows, wires its neurons, perceives its environment, modifies or repairs itself, and stores information. Seung is a clear, lively writer who chooses vivid examples.” —TheWashington Post
Metastable Dynamics of Neural Ensembles
Author: Emili Balaguer-Ballester
Publisher: Frontiers Media SA
Published: 2018-03-19
Total Pages: 152
ISBN-13: 2889454371
DOWNLOAD EBOOKA classical view of neural computation is that it can be characterized in terms of convergence to attractor states or sequential transitions among states in a noisy background. After over three decades, is this still a valid model of how brain dynamics implements cognition? This book provides a comprehensive collection of recent theoretical and experimental contributions addressing the question of stable versus transient neural population dynamics from complementary angles. These studies showcase recent efforts for designing a framework that encompasses the multiple facets of metastability in neural responses, one of the most exciting topics currently in systems and computational neuroscience.
Analysis of Neural Data
Author: Robert E. Kass
Publisher: Springer
Published: 2014-07-08
Total Pages: 663
ISBN-13: 1461496020
DOWNLOAD EBOOKContinual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles, and a handful of ubiquitous techniques, Analysis of Neural Data provides a unified treatment of analytical methods that have become essential for contemporary researchers. Throughout the book ideas are illustrated with more than 100 examples drawn from the literature, ranging from electrophysiology, to neuroimaging, to behavior. By demonstrating the commonality among various statistical approaches the authors provide the crucial tools for gaining knowledge from diverse types of data. Aimed at experimentalists with only high-school level mathematics, as well as computationally-oriented neuroscientists who have limited familiarity with statistics, Analysis of Neural Data serves as both a self-contained introduction and a reference work.
Interpretable Machine Learning
Author: Christoph Molnar
Publisher: Lulu.com
Published: 2020
Total Pages: 320
ISBN-13: 0244768528
DOWNLOAD EBOOKThis 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.
Neurobiology of Interval Timing
Author: Hugo Merchant
Publisher: Springer
Published: 2014-10-30
Total Pages: 358
ISBN-13: 149391782X
DOWNLOAD EBOOKThe study of how the brain processes temporal information is becoming one of the most important topics in systems, cellular, computational, and cognitive neuroscience, as well as in the physiological bases of music and language. During the last and current decade, interval timing has been intensively studied in humans and animals using increasingly sophisticated methodological approaches. The present book will bring together the latest information gathered from this exciting area of research, putting special emphasis on the neural underpinnings of time processing in behaving human and non-human primates. Thus, Neurobiology of Interval Timing will integrate for the first time the current knowledge of both animal behavior and human cognition of the passage of time in different behavioral context, including the perception and production of time intervals, as well as rhythmic activities, using different experimental and theoretical frameworks. The book will the composed of chapters written by the leading experts in the fields of psychophysics, functional imaging, system neurophysiology, and musicology. This cutting-edge scientific work will integrate the current knowledge of the neurobiology of timing behavior putting in perspective the current hypothesis of how the brain quantifies the passage of time across a wide variety of critical behaviors.
Issues in Logic, Probability, Combinatorics, and Chaos Theory: 2011 Edition
Author:
Publisher: ScholarlyEditions
Published: 2012-01-09
Total Pages: 461
ISBN-13: 1464966176
DOWNLOAD EBOOKIssues in Logic, Probability, Combinatorics, and Chaos Theory: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Logic, Probability, Combinatorics, and Chaos Theory. The editors have built Issues in Logic, Probability, Combinatorics, and Chaos Theory: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Logic, Probability, Combinatorics, and Chaos Theory in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Logic, Probability, Combinatorics, and Chaos Theory: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.
Spiking Neuron Models
Author: Wulfram Gerstner
Publisher: Cambridge University Press
Published: 2002-08-15
Total Pages: 498
ISBN-13: 9780521890793
DOWNLOAD EBOOKNeurons in the brain communicate by short electrical pulses, the so-called action potentials or spikes. How can we understand the process of spike generation? How can we understand information transmission by neurons? What happens if thousands of neurons are coupled together in a seemingly random network? How does the network connectivity determine the activity patterns? And, vice versa, how does the spike activity influence the connectivity pattern? These questions are addressed in this 2002 introduction to spiking neurons aimed at those taking courses in computational neuroscience, theoretical biology, biophysics, or neural networks. The approach will suit students of physics, mathematics, or computer science; it will also be useful for biologists who are interested in mathematical modelling. The text is enhanced by many worked examples and illustrations. There are no mathematical prerequisites beyond what the audience would meet as undergraduates: more advanced techniques are introduced in an elementary, concrete fashion when needed.
Neuronal Dynamics
Author: Wulfram Gerstner
Publisher: Cambridge University Press
Published: 2014-07-24
Total Pages: 591
ISBN-13: 1107060834
DOWNLOAD EBOOKThis solid introduction uses the principles of physics and the tools of mathematics to approach fundamental questions of neuroscience.
Neuronal Stochastic Variability: Influences on Spiking Dynamics and Network Activity
Author: Mark D. McDonnell
Publisher: Frontiers Media SA
Published: 2016-07-18
Total Pages: 158
ISBN-13: 2889198847
DOWNLOAD EBOOKStochastic fluctuations are intrinsic to and unavoidable at every stage of neural dynamics. For example, ion channels undergo random conformational changes, neurotransmitter release at synapses is discrete and probabilistic, and neural networks are embedded in spontaneous background activity. The mathematical and computational tool sets contributing to our understanding of stochastic neural dynamics have expanded rapidly in recent years. New theories have emerged detailing the dynamics and computational power of the balanced state in recurrent networks. At the cellular level, novel stochastic extensions to the classical Hodgkin-Huxley model have enlarged our understanding of neuronal dynamics and action potential initiation. Analytical methods have been developed that allow for the calculation of the firing statistics of simplified phenomenological integrate-and-fire models, taking into account adaptation currents or temporal correlations of the noise. This Research Topic is focused on identified physiological/internal noise sources and mechanisms. By "internal", we mean variability that is generated by intrinsic biophysical processes. This includes noise at a range of scales, from ion channels to synapses to neurons to networks. The contributions in this Research Topic introduce innovative mathematical analysis and/or computational methods that relate to empirical measures of neural activity and illuminate the functional role of intrinsic noise in the brain.
