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Do you need a special mind to do mathematics, and if so, why has such a mind evolved? What has been its reproductive advantage? Devlin argues that a. Why is math so hard? And why, despite this difficulty, are some people so good at it? If there's some inborn capacity for mathematical thinking—which there must. The Math Gene: How. Mathematical Thinking Evolved and Why Numbers Are Like. Gossip. Reviewed by Allyn Jackson. FEBRUARY NOTICES OF THE.

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The Math Gene Pdf

The Math Gene: A Ticket to. Wealth or Nerdiness? To say that a person has the Math Gene1 is to attribute to him an unusual propensity to handle numbers and. of Mathematics, Drexel University,. Philadelphia, PA USA. The Math Gene: How. Mathematical Thinking. Evolved and Why Numbers. Are Like Gossip. This book is a fascinating and thought-provoking exposition of the development of the human ability to think mathematically. Of course we do.

This book is a fascinating and thought-provoking exposition of the development of the human ability to think mathematically. Of course we do not know and probably cannot ever know precisely how we humans developed our mathematical ability, and Devlin acknowledges this fact. Nevertheless, the book lays out a quite plausible sequence of events which could have led to the acquisition of the ability to think mathematically. Keith Devlin is a fine writer as evidenced by the fact that the Joint Policy Board for Mathematics awarded him the JPBM Communications Award for his many contributions to public understanding of mathematics , and this latest book continues his string of well-written books. Before one can address the evolutionary origins of the capacity for mathematical thought, one must of course define what is meant by "mathematics" and "mathematical thought. If the typical adult opens an advanced mathematics book, he or she is likely to be turned off by the flood of symbols and may well believe that mathematics is nothing more than the symbols they see on the page. As Devlin says in the book, "Modern mathematics books are awash with symbols, but mathematical notation no more is mathematics than musical notation is music. As Devlin says, "Mathematics is not about numbers, but about life. It is about the world in which we live. It is about ideas. And far from being dull and sterile, as it is so often portrayed, it is full of creativity. For this reason alone, I would recommend this book to those who are curious about what it is that mathematicians do. We don't spend much time discovering new numbers. From the book: Along the way, I shall examine the questions of what exactly is mathematics, what exactly is language, and how they arose.

It is not obvious that all of these capacities his list is even longer are related, but, again, he gives a very plausible argument that a single change in the brain could account for all of them.

He also gives evidence from the archaeological record that all of these capacities arose at essentially the same time. So, how does the development of a capacity for language give rise automatically to a capacity for mathematical thought?

To help us understand this part of his argument, Devlin first tells us the primary use of language. In short, gossip. Furthermore, we are able to routinely access this information and use it to understand or predict their behavior, pass judgement, etc.

Importantly, we do all of this without effort. We do not stay up late trying to memorize facts about those we interact with, we simply file the information away for ready use.

The same is true for those who get caught up in a soap opera. They know vast amounts of information about the various characters in the soap and about how those characters fit together. They do not work hard to memorize this information, it simply gets filed away as they watch.

Mathematics is not so different from this.

The Math Gene : NPR

In Devlin's words: We have discovered the secret that enables mathematicians to be able to do mathematics: The characters in the mathematical soap opera are not people but mathematical objects — numbers, geometric figures, groups, topological spaces, and so forth. The facts and relationships that are the focus of attention are Whatever it is that causes the interest, it is that interest in mathematics that constitutes the main difference between those who can do mathematics and whose who claim to find it impossible.

I have tried to share some of what Keith Devlin has written about so well in this enlightening book, but I urge interested readers to read the book for themselves. This book will likely be well received by a wide audience, and it would certainly find a comfortable home in any library. Carl D. Mueller cmueller canes.

The Math Gene: How Mathematical Thinking Evolved and Why Numbers Are Like Gossip

Mathematical Association of America P: Skip to main content. Search form Search. Login Join Give Shops.

Halmos - Lester R. Ford Awards Merten M. Keith Devlin. Publication Date: Signaling molecules called morphogens then diffuse through the embryonic tissues, eventually defining the formation of body parts.

The Math Gene : How Mathematical Thinking Evolved And Why Numbers Are Like Gossip

The stripes establish the groundwork for the later division of the body into segments. How cells make sense of these diffusion gradients has always been a mystery.

The widespread assumption was that after being pointed in roughly the right direction so to speak by the protein levels, cells would continuously monitor their changing surroundings and make small corrective adjustments as development proceeded, locking in on their planned identity relatively late.

He likened the process of a cell homing in on its fate to a ball rolling down a series of ever-steepening valleys and forked paths. Such a system could be accident prone, however: Some cells would inevitably take the wrong paths and be unable to get back on track. That prompted a group at Princeton University, led by the biophysicists Thomas Gregor and William Bialek , to suspect something else: that the cells could instead get all the information they needed to define the positions of pair-rule stripes from the expression levels of the gap genes alone, even though those are not periodic and therefore not an obvious source for such precise instructions.

Over the course of 12 years, they measured morphogen and gap-gene protein concentrations, cell by cell, from one embryo to the next, to determine how all four gap genes were most likely to be expressed at every position along the head-to-tail axis. The team found that the fluctuations of the four gap genes could indeed be used to predict the locations of cells with single-cell precision. Versions of the decoder that used less of the information from all four gap genes — that, for instance, responded only to whether each gene was on or off — made worse predictions, too.

The biophysicists teamed up with the Nobel Prize-winning biologist Eric Wieschaus to test whether the cells were actually making use of the information potentially at their disposal. They created mutant embryos by modifying the gradients of morphogens in the very young fly embryos, which in turn altered the expression patterns of the gap genes and ultimately caused pair-rule stripes to shift, disappear, get duplicated or have fuzzy edges.

Even so, the researchers found that their decoder could predict the changes in mutated pair-rule expression with surprising accuracy.

Even so, the work provides a new way of thinking about early development, gene regulation and, perhaps, evolution in general. All the information is already there.

To really cement whether this is something more general, then, researchers will have to test the decoder in other species, including those that develop more slowly.

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