Customer Reviews

Decisions, Uncertainty, and the Brain: The Science of Neuroeconomics (Bradford Books)

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One of this book's greatest gifts is to clearly explain how our thinking about our thinking (neuroscience) has evolved over the past 2000 years. This book makes a significant contribution to the readers' historical understanding of psychology, philosophy, mathematics, and game theory.

One weakness of the book's approach is the lack of references to affect (emotion), which is suggested to have an impact on human utility and probability estimations in (Loewenstein, Loewenstein, Weber, & Welch, 2000), (Slovic, Finucane, Peters, and MacGregor, 2002), and (Knutson and Peterson, 2003). In fact, Glimcher states: "Neuroeconomics provides a model of the architecture that links brain and behavior. Mind, though it may very much exist, simply does not figure in that equation (p343)."

The author's conclusions are limited to a logical, computational frame of reference - a form of computational behaviorism. This style certainly has applications within limited experimental games, but it is doubtful that it will provide significant insight into the workings of complex dynamic systems, such as the financial markets, without incorporating symbolic psychological concepts (such as affect).

This book is an excellent introduction to the field of neuroeconomics. Glimcher's exposition of the evolution of neuroscientific thought is fascinating and worth savoring. Glimcher's discussion of game theory is fascinating, but applications to real-world environments are not directly posited.

The latter half of the book, while intellectually interesting, reads much like an expanded academic journal article. Glimcher explains his lab's experimental trials and tribulations in much of the second half...

Deisions, Uncertainty, and the Brain feels undigested, as if the author crammed in the library for a month and wrote a book on his notes.

Part I covers the neuro-, Part II covers the -economics, but instead of Part III, covering neuroeconomics, there's a 17-page-short chapter called "Putting It All Together."

For most of the book, things don't merge. For example, chapter 5 describes important experiments by Newsome and Shadlen that are not really neuroeconomics. Four seemingly tacked-on paragraphs at the end of the chapter argue that neuroeconomics has something to say about the experiments. But it's not clear what that is, and it's not clear why Glimcher didn't choose a more obviously relevant example.

A more general problem is that Glimcher argues throughout that current approaches to neuroscience are all reflex-based, and we need a major paradigm shift to make any more progress in brain research. But the examples he gives that employ his new paradigm seem to be well within the realm of normal cognitive neurophysiology. For example, the Ciaramitaro et al. attention experiments described in chapter 13 are elegant, but don't come across as paradigm shifting, in either the chapter, or the original Vision Research paper. Neuroeconomics comes to seem like just another tool in the toolbox, instead of a big new theory.

It may be that there is no Part III because the science has not yet happened. In which case, not writing more about it was a good thing to do. Parsimony is a virtue, but if there is not enough of a story to tell, I would have liked to see the author present his ideas about the major problems for the field, a Hilbert's 23 for neuroscience in the 21st century. Instead chapter 13 gives us four toy problems in primate physiology.

The best parts of the book are the history. Some of the stories are familiar, but most are not, and all are told engagingly. Although they don't really come together into a cohesive whole, they are interesting on their own, and a reader with a detailed knowledge of the field can connect most of the dots.

70 years ago, behavioral economists were trapped outside the black box for the same reasons everyone was: science couldn't see inside the brain directly. Like behavioral psychologists, they decided to make a virtue out of a neccessity and ignore the black box.

Now behavioral economists can look inside the black box, but most choose to ignore it, perhaps because the learning curves on physiology and imaging are so steep.

Glimcher argues in this wonderful book that neuroscientists are unwittingly trapped inside the same black box, and need a way out. Maybe they can befriend those behavioral economists. Consider this book an arranged date that will hopefully turn into a long marriage.

It is rare for a book aimed at the public to be written by a young and active scientist. The obvious comparison is Spikes, by Reike, et al. But whereas Spikes was too mathematical for the general reader, Decisions, Uncertainty, and the Brain never gets
boring. It describes fascinating experiments, both 100 years old and being done right now. Experiments that you've never heard of, but you should. Best of all, it describes them passionately and non-scarily.

More importantly, Decisions points throughout to directions for future research, rather than only describing past experiments.

Don't be fooled by the book's elegance. It is meticulously crafted to be enjoyable to the lay reader but also highly rewarding someone more familiar with the research described. In short, a masterpiece.

It begins with the subtitle "The Science of Neuroeconomics" - what does that term even mean? As far as I can tell, Glimcher never defines it. Somewhere along the line he does tell us, as if it's a novel insight, that the purpose of the brain is 'decision making'. Now, if we define decision-making as selection of behavior from multiple options, this is as obvious as saying that the function of the heart is to circulate blood. In studying 'neuroeconomics', Glimcher is really just studying neuroscience - how the brain controls behavior. The term is nothing but fancy repackaging for the business/econ crowd.

If it were just the term, I could easily forgive the oversell. However, Glimcher recounts an entire selective history of neuroscience to convince you that he is part of a group of scientists who are radically changing the way we think about ourselves. Glimcher first introduces Descartes' dualism with which to anchor his book. Various figures are introduced, culminating in Sherrington, who shift neuroscience to a deterministic, reflex-oriented framework (strangely, he never once mentions the name Skinner). While a few early 20th-century neurophysiologists are introduced who challenged these theories of sensory-driven reflex-like behavior, he then skips over half a century of neuroscience and psychology to inform us that certain recent models still have a 'reflex-like' flavor. Ignored is the entire cognitive revolution, and the foundation of cognitive neuroscience. David Marr is the lone exception, introduced as a prophet, apparently the first and only person to propose that the brain should be studied based on its computational goals.

Okay, I should forgive the simplification of history, right? It is set up to aggrandize 'neuroeconomists', but then again to some extent it is deserved - there was a revolution in decision-making research in the 1990s. So perhaps the most galling feature of this book is that Glimcher doesn't even address much of this work. How can you write a book about decision-making in 2003 without reference to reinforcement learning, the basal ganglia, and dopamine? Okay, in fairness it gets one measly page towards the end (as an example of 'neuroeconomics' applications), but the experimental focus is all on the parietal cortex, which Glimcher happened to study.

In addition to being selective and incomplete, Glimcher has a habit of making vague and tenuous connections. For example, he introduces Godel's incompleteness theorem, and makes vague allusions to it being somehow related to nondeterministic behavior. While he appears to be channeling Penrose, he never does pin this point down, so it is unclear exactly what he is saying. Similarly, he likes to make a big deal about 'Bayesian' approaches, while demonstrating only that probabilistic approaches are necessary. He claims that 'classical monism cannot explain nondeterministic behavior', and seems to be claiming that the mere introduction of probability into behavior radically revamps neuroscience (it doesn't - one can imagine reflex-like circuits that are probabilistic). Don't get me wrong, there appears to be a deep connection between many of these concepts - but Glimcher does not make that connection in this book. The book is ultimately far too bold for what it presents.

This book is much more than its title. It provides a fascinating history of neurobiology and probability/game theory, leading up to the thesis that the brain is a Bayesian probability calculator and game-theoretic randomizer.

The Bayesian part refers to the ability of the brain to combine current incoming sensory data with current priors to estimate probabilities relevant to current decision-making. The game-theoretic randomizer part refers to the fact that to succeed in the evolutionary game, an animal, say a caveman, needs to act somewhat unpredictably so as not to be eaten by a predator. If the caveman were totally predicable in his/her actions, then an evolutionary adversary could predict what he/she was going to do, and use that information to defeat him or her. This is consistent with optimal strategies which are derived through game theory a la von Neumann.

The science is not certain how the brain accomplishes this (yet); however, it appears to be through parts of the brain continually estimating likelihoods, with thresholds that, when exceeded, result in actions on the part of the individual.

I am very happy that I saw this book in the MIT Press display at the ASSA conferences this January, and that it had a cool-looking illustration on the cover, or I probably wouldn't have bought it. I highly recommend it.

In the interest of completness, I should mention some of the things I didn't like so much. First of all, I wish that Glimcher had mentioned the research of DaMasio, who wrote a fascinating book named "DeCarte's Error". In that book DeMasio presents a thesis that emotions pay a key role in decision-making. As pointed out by other reviewers, Glimcher doesn't even mention this line of research. Secondly, the book was a bit dry and academic in tone from time to time, but that is a small complaint given how interesting the content was.

Opinion

I typically enjoy books combining my interests in science and economics. I am currently a dual major student in both biology and management and so a book like this really appeals to me. Paul W. Glimcher's book "Decisions, Uncertainty, and the Brain: The Science of Neuroeconomics" delves deep into advanced economic theories in an attempt to explain how the brain can calculate value and risk without a full set of information. The title of this book implies that the brain is constantly dealing with uncertainty during decision making processes, and the author argues that a transition away from a solely reflex-based model is necessary in understanding complex behaviors. The book itself leaves the reader a bit uncertain in the end with only a very small chapter "Putting It All Together" to explain the interplay between neuroscience and economics in decision making.

Structure of the Book

This book is written in two parts and contains a final chapter entitled "Putting It All Together." The first part, Part I, covers the history and background of the neuroscience related topics that the book is trying to address with specific examples about the brain and central nervous system's role in stimulus response. Part II of the book focuses on the key economic topics, particularly game theory, to show a mathematical basis for determining, and perhaps eventually predicting, the future of neuroeconomics.

Interesting Elements

The book does represent an emerging field of thinking and is on the forefront of a new movement that may come to define investing decision making. That being said, the major accomplishments that this book puts forward are the detailed experiments that Glimcher himself performed on monkeys and humans that characterize his theory that science should utilize economics to help explain complex decisions that incorporate uncertainty. Glimcher clearly believes that economic principles can help explain real world occurences where current science cannot. Glimcher goes beyond his own work to cite many other scientists experiments and findings that have yielded similar results to his own work. Glimcher does a good job using specific examples cited with almost every claim he makes, but some leave the reader wondering the relevance of the experiments to the claims that are supposed to support. Glimcher utilizes the history of the field to show the knowledge gaps that still exist that set the background for the necessity of his theory.

Interesting Quotes

"Until the 1970's very few neurobiologists had attempted to conceptualize neural function with regards to the kind of goals that both behavioral ecologists and experimental economists were beginning to employ in their research."

"The behavioral data produced by animals in these experiments, and in others like them, suggest that subjects never really perform optimally."

"Throughout this book I have argued that the limitations of classical dualism and physiological monism both stem from the inability of determinate mathematical tools to describe behavior in all its complexity."

Recommendation

This book is not for the faint of heart, especially from an economic standpoint due to the use of complex theories such as Bayes' theorem and stochastic differential equations. As such, I would be hesitant to widely recommend this book based almost entirely on the difficulty of the read. Only those who are truly passionate and that are well versed in both neuroscience and economics will really find satisfaction. The book offers a wide range of interesting elements but eventually comes up short on meshing the neuroscience with the economics. At many points throughout the book, references to experiments or stories to explain different phenomena were not helpful in dually defining the role of both neuroscience and economics. I realize that Glimcher really believes that neuroeconomics may be the future for explaining complex decision making behaviors, but very little is done in his book, to use the author's words, to "Put It All Together." While I found this a difficult read and therefore did not fully enjoy it, there were many examples to learn from Glimcher and for some this may be enough to salvage the book.

then we would not be writing books about "asking questions".

Good effort and a brilliant mind but no salient answers.

Kind of made me feel like spitting in the air trying to predict

where that s gonna go?

In fact PG is jumping ahead and throwing himself out of the plane

with a parachute he did not check before the jump.

But he s not jumping alone another guy is jumping along with him

out of the same plane.Basically PG figured that will improve the odds

of survival...

What are the chances PG will land safely on planet hearth?

That jump to me resumes PG's book...

Offhand one might think that the hybrid neologism "neuroeconomics" would refer to an interdisciplinary approach to economic theory where neuroscience contributes a novel insight of some sort. The book's title reinforces this view, giving top billing to the lexical inducers "decisions" and "uncertainty" while the word "brain" straggles at list's end. In point of fact, economics, properly speaking, has little to do with the new discipline's thematic content. Author Paul Glimcher, a professor and researcher who heads his own Glimcher Lab at the Center for Neural Science at NYU, begins this highly readable narrative not with a tale from economics but with an anecdote from the annals of automata, Jacques de Vaucanson's mechanical duck (1738), harking back to an epoch when economics had yet to see the light of day.

The much-ballyhooed duck quickly yields center stage to the star culprit of the show, its compatriot the polymath René Descartes, who a century earlier had fused the distinct realms of geometry and algebra into monistic analytic geometry --a cornerstone of modern mathematics-- before tearing asunder body and soul with his idea of physiological dualism. Descartes held that two categories of behaviors existed: simple behaviors in which sensory events triggered deterministic motor responses automatically (or reflexively), and complex behaviors where responses were not entirely predictable (nondeterministic). An explanation of the latter category, Descartes believed, required positing the soul as the requisite mechanism for producing volitional behavior. The former category of fully deterministic behaviors, where no volition or reasoning was necessary, became known as reflexes.

Alas, the reflexological paradigm long remained the only game in town for explanatory purposes and in due course preempted the soul in scientific discourse. Complex behaviors came to be seen as the product of complex chains of reflexes, notwithstanding the enormous difficulties of understanding volition in terms of mindless knee-jerk reactions. Eventually (the book admirably discusses the details I omit of this intellectual journey), the pioneering computational neuroscientist, David Marr, introduced a paradigm-shifting approach: the brain as a goal-seeking (i.e., cybernetic) system.

The second half of the book discusses developments after Marr's untimely passing. Laboratory experiments of visual-saccadic processing in the primate brain are amply discussed. Of particular interest, the role of economics in the newly proposed theory of neurophysiology is duly presented. According to the book, it boils down to two mathematical approaches to decision making: Bayesian decision-theoretic modeling, widely known as decision analysis, and game theory.

Now, decision analysis and game theory are excellent tools for analyzing economic problems, granted. But they are neither limited to economics nor did they arise within the confines of that field. They are actually the product of decision-theoretic mathematics that find application in economics but also in behavioral ecology, artificial intelligence, the theory of evolution, strategic management, military science, contemporary philosophy, public policy analysis, communication network engineering, politics, law, love, poker tournaments and what have you. On the other hand, standard economic concepts such as the law of demand, price elasticities, marginal revenues and costs, inflation, business cycles, market failure and the principal-agent problem, to mention a mere few, are conspicuously absent. Why then should economics get the credit?

I would have gone along with Marr's vision and christened the thing "neurocybernetics," which is, after all, the essence of the new paradigm. It also dovetails with Vaucanson's duck, which clearly owes nothing to economics. Aside from that, the book offers a great read in the history and current developments of neuroscience. If you think neurons are fairly interesting, you will most likely enjoy this book.

This book offers an outstanding survey of philosophy, psychology, brain science, economics, and the field that brings them all together, neuroeconomics. Paul W. Glimcher contends that Descartes' deterministic theory that simple behavior operates according to reflexes is influential far beyond its merits. He describes numerous experiments that support a very different understanding of behavior, which says that organisms seeking to fulfill their own goals (mostly to perpetuate their genes) must "choose" behaviors that somehow account for risk and return. In other words, they maximize "inclusive fitness" under conditions of uncertainty. Laboratory experiments and field research by behavioral ecologists lend considerable support to this view. We recommend this solid, layman's introduction to neuroeconomics and a remarkable series of discoveries.

Great book about history of neuroscience from Descartes to the present and where it moves next. Ideas are clearly expressed and convincing evidence is presented. Somewhat populist, though, but interesting to read. Good for beginners in neuroscience like myself.