Principles of Neural Design

Principles of Neural Design
Author: Peter Sterling
Publisher: MIT Press
Total Pages: 567
Release: 2017-06-09
Genre: Science
ISBN: 0262534681

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Two distinguished neuroscientists distil general principles from more than a century of scientific study, “reverse engineering” the brain to understand its design. Neuroscience research has exploded, with more than fifty thousand neuroscientists applying increasingly advanced methods. A mountain of new facts and mechanisms has emerged. And yet a principled framework to organize this knowledge has been missing. In this book, Peter Sterling and Simon Laughlin, two leading neuroscientists, strive to fill this gap, outlining a set of organizing principles to explain the whys of neural design that allow the brain to compute so efficiently. Setting out to “reverse engineer” the brain—disassembling it to understand it—Sterling and Laughlin first consider why an animal should need a brain, tracing computational abilities from bacterium to protozoan to worm. They examine bigger brains and the advantages of “anticipatory regulation”; identify constraints on neural design and the need to “nanofy”; and demonstrate the routes to efficiency in an integrated molecular system, phototransduction. They show that the principles of neural design at finer scales and lower levels apply at larger scales and higher levels; describe neural wiring efficiency; and discuss learning as a principle of biological design that includes “save only what is needed.” Sterling and Laughlin avoid speculation about how the brain might work and endeavor to make sense of what is already known. Their distinctive contribution is to gather a coherent set of basic rules and exemplify them across spatial and functional scales.

Neural Network Design and the Complexity of Learning

Neural Network Design and the Complexity of Learning
Author: J. Stephen Judd
Publisher: MIT Press
Total Pages: 188
Release: 1990
Genre: Computers
ISBN: 9780262100458

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Using the tools of complexity theory, Stephen Judd develops a formal description of associative learning in connectionist networks. He rigorously exposes the computational difficulties in training neural networks and explores how certain design principles will or will not make the problems easier.Judd looks beyond the scope of any one particular learning rule, at a level above the details of neurons. There he finds new issues that arise when great numbers of neurons are employed and he offers fresh insights into design principles that could guide the construction of artificial and biological neural networks.The first part of the book describes the motivations and goals of the study and relates them to current scientific theory. It provides an overview of the major ideas, formulates the general learning problem with an eye to the computational complexity of the task, reviews current theory on learning, relates the book's model of learning to other models outside the connectionist paradigm, and sets out to examine scale-up issues in connectionist learning.Later chapters prove the intractability of the general case of memorizing in networks, elaborate on implications of this intractability and point out several corollaries applying to various special subcases. Judd refines the distinctive characteristics of the difficulties with families of shallow networks, addresses concerns about the ability of neural networks to generalize, and summarizes the results, implications, and possible extensions of the work. Neural Network Design and the Complexity of Learning is included in the Network Modeling and Connectionism series edited by Jeffrey Elman.

Principles of Neural Development

Principles of Neural Development
Author: Dale Purves
Publisher: Sinauer Associates, Incorporated
Total Pages: 456
Release: 1985
Genre: Medical
ISBN:

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Principles of Neural Science

Principles of Neural Science
Author: Eric R. Kandel
Publisher:
Total Pages: 1646
Release: 2021
Genre: Neurology
ISBN: 9781264267682

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The goal of this sixth edition of Principles of Neural Science is to provide readers with insight into how genes, molecules, neurons, and the circuits they form give rise to behavior. With the exponential growth in neuroscience research over the 40 years since the first edition of this book, an increasing challenge is to provide a comprehensive overview of the field while remaining true to the original goal of the first edition, which is to elevate imparting basic principles over detailed encyclopedic knowledge.

Principles of Neural Science

Principles of Neural Science
Author: Eric R. Kandel
Publisher:
Total Pages: 1135
Release: 1991
Genre: Anatomy
ISBN: 9780838580684

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What Is Health?

What Is Health?
Author: Peter Sterling
Publisher: MIT Press
Total Pages: 259
Release: 2020-02-25
Genre: Science
ISBN: 0262043300

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An argument that health is optimal responsiveness and is often best treated at the system level. Medical education centers on the venerable “no-fault” concept of homeostasis, whereby local mechanisms impose constancy by correcting errors, and the brain serves mainly for emergencies. Yet, it turns out that most parameters are not constant; moreover, despite the importance of local mechanisms, the brain is definitely in charge. In this book, the eminent neuroscientist Peter Sterling describes a broader concept: allostasis (coined by Sterling and Joseph Eyer in the 1980s), whereby the brain anticipates needs and efficiently mobilizes supplies to prevent errors. Allostasis evolved early, Sterling explains, to optimize energy efficiency, relying heavily on brain circuits that deliver a brief reward for each positive surprise. Modern life so reduces the opportunities for surprise that we are driven to seek it in consumption: bigger burgers, more opioids, and innumerable activities that involve higher carbon emissions. The consequences include addiction, obesity, type 2 diabetes, and climate change. Sterling concludes that solutions must go beyond the merely technical to restore possibilities for daily small rewards and revivify the capacities for egalitarianism that were hard-wired into our nature. Sterling explains that allostasis offers what is not found in any medical textbook: principled definitions of health and disease: health as the capacity for adaptive variation and disease as shrinkage of that capacity. Sterling argues that since health is optimal responsiveness, many significant conditions are best treated at the system level.

Neural Engineering

Neural Engineering
Author: Chris Eliasmith
Publisher: MIT Press
Total Pages: 384
Release: 2003
Genre: Bioinformatics
ISBN: 9780262550604

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A synthesis of current approaches to adapting engineering tools to the study of neurobiological systems.

Biophysics of Computation

Biophysics of Computation
Author: Christof Koch
Publisher: Oxford University Press
Total Pages: 587
Release: 2004-10-28
Genre: Medical
ISBN: 0195181999

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Neural network research often builds on the fiction that neurons are simple linear threshold units, completely neglecting the highly dynamic and complex nature of synapses, dendrites, and voltage-dependent ionic currents. Biophysics of Computation: Information Processing in Single Neurons challenges this notion, using richly detailed experimental and theoretical findings from cellular biophysics to explain the repertoire of computational functions available to single neurons. The author shows how individual nerve cells can multiply, integrate, or delay synaptic inputs and how information can be encoded in the voltage across the membrane, in the intracellular calcium concentration, or in the timing of individual spikes.Key topics covered include the linear cable equation; cable theory as applied to passive dendritic trees and dendritic spines; chemical and electrical synapses and how to treat them from a computational point of view; nonlinear interactions of synaptic input in passive and active dendritic trees; the Hodgkin-Huxley model of action potential generation and propagation; phase space analysis; linking stochastic ionic channels to membrane-dependent currents; calcium and potassium currents and their role in information processing; the role of diffusion, buffering and binding of calcium, and other messenger systems in information processing and storage; short- and long-term models of synaptic plasticity; simplified models of single cells; stochastic aspects of neuronal firing; the nature of the neuronal code; and unconventional models of sub-cellular computation.Biophysics of Computation: Information Processing in Single Neurons serves as an ideal text for advanced undergraduate and graduate courses in cellular biophysics, computational neuroscience, and neural networks, and will appeal to students and professionals in neuroscience, electrical and computer engineering, and physics.

Neuroprosthetics

Neuroprosthetics
Author: Justin C. Sanchez
Publisher: CRC Press
Total Pages: 236
Release: 2018-09-03
Genre: Medical
ISBN: 1466553243

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Master the tools of design thinking using Neuroprosthetics: Principles and Applications. Developed from successfully tested material used in an undergraduate and graduate level course taught to biomedical engineering and neuroscience students, this book focuses on the use of direct neural sensing and stimulation as a therapeutic intervention for complex disorders of the brain. It covers the theory and applications behind neuroprosthetics and explores how neuroprosthetic design thinking can enhance value for users of a direct neural interface. The book explains the fundamentals of design thinking, introduces essential concepts from neuroscience and engineering illustrating the major components of neuroprosthetics, and presents practical applications. In addition to describing the approach of design thinking (based on facts about the user’s needs, desires, habits, attitudes, and experiences with neuroprosthetics), it also examines how effectively "human centered" neuroprosthetics can address people’s needs and interactions in their daily lives. Identifying concepts and features of devices that work well with users of a direct neural interface, this book: Outlines the signal sensing capabilities and trade-offs for common electrode designs, and determines the most appropriate electrode for any neuroprosthetic application Specifies neurosurgical techniques and how electronics should be tailored to capture neural signals Provides an understanding of the mechanisms of neural–electrode performance and information contained in neural signals Provides understanding of neural decoding in neuroprosthetic applications Describes the strategies that can be used to promote long-term therapeutic interventions for humans through the use of neuroprosthetics The first true primary text for undergraduate and graduate students in departments of neuroscience and bioengineering that covers the theory and applications behind this science, Neuroprosthetics: Principles and Applications provides the fundamental knowledge needed to understand how electrodes translate neural activity into signals that are useable by machines and enables readers to master the tools of design thinking and apply them to any neuroprosthetic application.

Principles of Neural Information Theory

Principles of Neural Information Theory
Author: James V Stone
Publisher:
Total Pages: 214
Release: 2018-05-15
Genre: Computers
ISBN: 9780993367922

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In this richly illustrated book, it is shown how Shannon's mathematical theory of information defines absolute limits on neural efficiency; limits which ultimately determine the neuroanatomical microstructure of the eye and brain. Written in an informal style this is an ideal introduction to cutting-edge research in neural information theory.