How to Build a Brain: A Neural Architecture for Biological Cognition [Print Replica] [Format Kindle]
Author: Chris Eliasmith | Language: English | ISBN: B00HNSNSGK | Format: PDF, EPUB
How to Build a Brain: A Neural Architecture for Biological Cognition
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Présentation de l'éditeur
One goal of researchers in neuroscience, psychology, and artificial intelligence is to build theoretical models that are able to explain the flexibility and adaptiveness of biological systems. How to build a brain provides a detailed guided exploration of a new cognitive architecture that takes biological detail seriously, while addressing cognitive phenomena. The Semantic Pointer Architecture (SPA) introduced in this book provides a set of tools for constructing a wide range of biologically constrained perceptual, cognitive, and motor models.
Examples of such models are provided, and they are shown to explain a wide range of data including single cell recordings, neural population activity, reaction times, error rates, choice behavior, and fMRI signals. Each of these models introduces a major feature of biological cognition addressed in the book, including semantics, syntax, control, learning, and memory. These models are not introduced as independent considerations of brain function, but instead integrated to give rise to what is currently the world's largest functional brain model.
The last half of this book compares the Semantic Pointer Architecture with the current state-of-the-art, addressing issues of theory construction in the behavioral sciences, semantic compositionality, and scalability, among other considerations. The book concludes with a discussion of conceptual challenges raised by this architecture, and identifies several outstanding challenges for this, and other, cognitive architectures.
Along the way, the book considers neural coding, concept representation, neural dynamics, working memory, neuroanatomy, reinforcement learning, and spike-timing dependent plasticity. The book includes 8 detailed, hands-on tutorials exploiting the free Nengo neural simulation environment, providing practical experience with the concepts and models presented throughout.
Examples of such models are provided, and they are shown to explain a wide range of data including single cell recordings, neural population activity, reaction times, error rates, choice behavior, and fMRI signals. Each of these models introduces a major feature of biological cognition addressed in the book, including semantics, syntax, control, learning, and memory. These models are not introduced as independent considerations of brain function, but instead integrated to give rise to what is currently the world's largest functional brain model.
The last half of this book compares the Semantic Pointer Architecture with the current state-of-the-art, addressing issues of theory construction in the behavioral sciences, semantic compositionality, and scalability, among other considerations. The book concludes with a discussion of conceptual challenges raised by this architecture, and identifies several outstanding challenges for this, and other, cognitive architectures.
Along the way, the book considers neural coding, concept representation, neural dynamics, working memory, neuroanatomy, reinforcement learning, and spike-timing dependent plasticity. The book includes 8 detailed, hands-on tutorials exploiting the free Nengo neural simulation environment, providing practical experience with the concepts and models presented throughout.
Direct download links available for How to Build a Brain: A Neural Architecture for Biological Cognition
Détails sur le produit
- Format : Format Kindle
- Taille du fichier : 24846 KB
- Nombre de pages de l'édition imprimée : 480 pages
- Editeur : Oxford University Press, USA; àdition : 1 (16 mai 2013)
- Vendu par : Amazon Media EU S.à r.l.
- Langue : Anglais
- ASIN: B00HNSNSGK
- Synthèse vocale : Activée
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Here's the "real life," most robust and up to date neural cognition text available today, to add supplemental hard science to the numerous softer and more contemplative (less practically sim ready) "Kurzweil" like models, eg: (How to Create a Mind: The Secret of Human Thought Revealed.Par Let's Compare Options
The book doubles as an "owners manual" for the author's Nengo neuro sim program (meaning Neural ENgineering Objects, not the Japanese era). Videos are available on how the book and system integrate-- check out section 1.5 in Amazon's generous preview peek for the website address. While you're at it, there is a LOT of detail given in this worthwhile preview that will immediately help you determine if this is the book for you.
I design domain specific languages for robotics and am always interested in new and different views of neural vs. semiconductor cognitive sims. Unfortunately to be honest if not crass, most of the books out there today are big on speculation and light on anything you can model. That's where this book shines from my narrow frame-- you can build your own versions of the authors premises and "try" them on what has become the biggest, most active and accessed "online brain sim" on the planet!
Do you have an interest in sims of semantics or perception? My slice is more on "translation" from the compiler side, but this book is wonderful in its coverage of practical aspects of semantics, perception, memory, what the authors call "semantic pointers" and of course the must mention topics today of plasticity and fluid intelligence.
I'll wait for a Neurological researcher to opine on this from the biological side, but for pure "translational" delight between brain and robotic mechanisms, this book can't be beat. It really is the only up to date text on the topic, as extensive brain sims are mostly covered in journals. You should know that the majority of the book IS meant to present a new and coherent theory of brain architecture, but the amount of detail, history, where we have been and where we are going the author covers is worth the price of the book itself, and of course is architecture independent.
As an EE I love math, but if you're math adverse, don't dismiss this, as the author has relegated the most complex math to the appendices. (You can't read neuro without running into differential equations due to the importance of dynamical systems in the models. But from an EE viewpoint, asp and dsp also involve time vs. frequency and we use similar Fourier etc. methods for different reasons on the robotics side).
Very readable, enlightening, and frankly fun, since you really can get hands on with the sims. Highly recommended, but suggest you take advantage of the Amazon preview before investing. Hats off to authors and publishers who have enough pride and confidence in the value of their work to let us have a significant preview like this.
Emailer answer: "What does Eliasmith think of Newell?" A. He mentions him throughout, with respect, but with the objective of bringing Newell's architectures closer to biological underpinnings. SOAR and other production systems are covered, but Chris insists that bringing in dynamic systems is crucial. The example, from my field, is that roboticists use dynamics (PDEs, signal processing, stats) instead of the embedded if-thens of production systems, due to both the "need for speed" in dynamics as well as flexibility. This has the additional benefit of suggesting a more robust model that includes both biology and algorithmic models, and Eliasmith invites both computational Neurology AND psych to converge in testing his new architecture. Emailer's Reference: Unified Theories of Cognition (William James Lectures).
DO take advantage of the author's/ Amazon's wonderful look inside feature, Dr. Chris even gives an extensive history in that look of what led up to this new model. One interesting gap I found in the otherwise extensive bib (nearly 30 pages) is Bach. You might find his book/dissertation interesting in summary and contrast to many of Chris' unique perspectives: Principles of Synthetic Intelligence PSI: An Architecture of Motivated Cognition (Oxford Series on Cognitive Models and Architectures). Both of course mention Newell extensively.
As a completely unscientific, but fun exercise, whenever I evaluate a title on cognitive architecture, I immediately go to the index and look for the seminal (at least in programming/robotics) word: "recursion." Newell and Chris don't index it specifically, Bach has half a dozen entries and hundreds cross referencing hierarchy and reflection, similar concepts, as do Chris and Newell. If you like or are curious about this concept, ubiquitous in this field but not always re-cognized, you'll greatly enjoy Corballis: The Recursive Mind: The Origins of Human Language, Thought, and Civilization. In fact, mathematically, there are recent ("matrix like") theories extending recursion to the mathematics beneath the entire universe, and from a physicist's frame, Dr. Tegmark is one of the first to explore it extensively: Our Mathematical Universe: My Quest for the Ultimate Nature of Reality.
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I like this book very much, because it gives a very intuitive approach to neural scince as well as to large scale brain models. It is possible to read this book without a deep mathematical background. An interesting feature is that your can work on examples at the end of each chapter which are implemented in NENGO.Par Bernd J. Kröger
- Publié sur Amazon.com
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