The concept comes from early ethologists, scientists such as Oskar Heinroth and Konrad Lorenz, who defined it as an instinctive response—usually a series of predictable behavior patterns—that would occur reliably in the presence of a specific bit of input, often called a “releaser.” Fixed-action patterns, as such patterns were known, were thought to be devoid of cognitive processing. As it turned out, fixed-action patterns were not nearly as fixed as the ethologists believed, but the concept has remained as part of the historical literature—as a way of scientifically describing what in the vernacular might be called “knee-jerk” responses. The concept of a fixed-action pattern, despite its simplicity, may prove valuable as a metaphorical means to study and change human behavior.
If we look into the literature on fixed-action patterns, we see that many such instinctive responses were actually learned, based on the most elementary of signals. For example, the newly hatched herring gull chick’s supposed fixed-action pattern of hitting the red spot on its parent’s beak for food was far more complex. Ornithologist and ethologist Jack P. Hailman demonstrated that what was innate was only a tendency to peck at an oscillating object in the field of view. The ability to target the beak, and the red spot on the beak, though a pattern that developed steadily and fairly quickly, was acquired experientially. Clearly, certain sensitivities must be innate, but the specifics of their development into various behavioral acts likely depend on how the organism interacts with its surroundings and what feedback it receives. The system need not, especially for humans, be simply a matter of conditioning response R to stimulus S but rather of evaluating as much input as possible.
The relevance is that if we wish to understand why, as humans, we often act in certain predictable ways (and particularly if there is a desire or need to change these behavioral responses), we can remember our animal heritage and look for the possible releasers that seem to stimulate our fixed-action patterns. Might the fixed-action pattern actually be a response learned over time, initially with respect to something even more basic than we expect? The consequences could affect several aspects of our lives, from our social interactions to the quick decision-making processes in our professional roles. Given an understanding of our fixed-action pattern, and those of the individuals with whom we interact, we—as humans with cognitive processing powers—could begin to rethink our behavior patterns.
Powers of 10
Terrence Sejnowski
Computational neuroscientist; Francis Crick Professor, the Salk Institute; coauthor (with Patricia Churchland), The Computational Brain
An important part of my scientific toolkit is how to think about things in the world over a wide range of magnitudes and time scales. This involves, first, understanding powers of ten; second, visualizing data over a wide range of magnitudes on graphs using logarithmic scales; and third, appreciating the meaning of magnitude scales, such as the decibel (dB) scale for the loudness of sounds and the Richter scale for the strength of earthquakes.
This toolkit ought to be a part of everyone’s thinking, but sadly I have found that even well-educated nonscientists are flummoxed by log scales and can only vaguely grasp the difference between an earthquake of 6 on the Richter scale and one of 8 (a thousand times more energy released). Thinking in powers of 10 is such a basic skill that it ought to be taught along with integers in elementary school.
Scaling laws are found throughout nature. Galileo in 1638 pointed out that large animals have disproportionately thicker leg bones than small animals to support the weight of the animal. The heavier the animal, the stouter their legs need to be. This leads to a prediction that the thickness of the leg bone should scale with the 3/2 power of the length of the bone.
Another interesting scaling law is that between the volume of the brain’s cortical white matter, corresponding to the long-distance wires between cortical areas, and the gray matter, where the computing takes place. For mammals ranging over 5 orders of magnitude in weight—from a pygmy shrew to an elephant—the white matter scales as the 5/4 power of the gray matter. This means that the bigger the brain, the disproportionately larger the fraction of the volume taken up by cortical wiring used for communication compared to the computing machinery.
I am concerned that students I teach have lost the art of estimating with powers of 10. When I was a student, I used a slide rule to compute, but students now use calculators. A slide rule lets you carry out a long series of multiplications and divisions by adding and subtracting the logs of numbers; but at the end you need to figure out the powers of 10 by making a rough estimate. A calculator keeps track of this for you, but if you make a mistake in keying in a number, you can be off by 10 orders of magnitude, which happens to students who don’t have a feeling for orders of magnitude.
A final reason why familiarity with powers of 10 would improve everyone’s cognitive toolkit is that it helps us comprehend our life and the world in which we live:
How many seconds are there in a lifetime? 109 sec
A second is an arbitrary time unit, but one that is based on our experience. Our visual system is bombarded by snapshots at a rate of around three per second, caused by rapid eye movements called saccades. Athletes often win or lose a race by a fraction of a second. If you earned a dollar for every second in your life, you would be a billionaire. However, a second can feel like a minute in front of an audience, and a quiet weekend can disappear in a flash. When I was a child, a summer seemed to last forever, but now the summer is over almost before it begins. William James speculated that subjective time was measured in novel experiences, which become rarer as you get older. Perhaps life is lived on a logarithmic time scale, compressed toward the end.
What is the GDP of the world? $1014
A billion dollars was once worth a lot, but there is now a long list of multibillionaires. The U.S. government recently stimulated the world economy by loaning several trillion dollars to banks. It is difficult to grasp how much a trillion dollars ($1012) represents, but several clever videos on YouTube (key words: trillion dollars) illustrate this with physical comparisons (a giant pile of $100 bills) and what you can buy with it (ten years of U.S. response to 9/11). When you start thinking about the world economy, the trillions of dollars add up. A trillion here, a trillion there, pretty soon you’re talking about real money. But so far there aren’t any trillionaires.
How many synapses are there in the brain? 1015
Two neurons can communicate with each other at a synapse, which is the computational unit in the brain. The typical cortical synapse is less than a micron in diameter (10-6 meter), near the resolution limit of the light microscope. If the economy of the world is a stretch for us to contemplate, thinking about all the synapses in your head is mind-boggling. If I had a dollar for every synapse in your brain, I could support the current economy of the world for ten years. Cortical neurons on average fire once a second, which implies a bandwidth of around 1015 bits per second, greater than the total bandwidth of the Internet backbone.
How many seconds will the sun shine? 1017 sec
Our sun has shined for billions of years and will continue to shine for billions more. The universe seems to be standing still during our lifetime, but on longer time scales the universe is filled with events of enormous violence. The spatial scales are also immense. Our space-time trajectory is a very tiny part of the universe, but we can at least attach powers of 10 to it and put it into perspective.
Life Code
Juan Enriquez
Managing director, Excel Venture Management; author, As the Future Catches You: How Genomics & Other Forces Are Changing Your Life, Work, Health & Wealth; coauthor (with Steve Gullans), Homo Evolutis: Please Meet the Next Human Species
Everyone is familiar with digital code, the shorthand IT. Soon all may be discoursing about life code.
It took a while to learn how to read life code; Mendel’s initial cookbook was largely ignored. Darwin knew
but refused for decades to publish such controversial material. Even DNA, a term that now lies within every cheesy PR description of a firm, on jeans, and in pop psych books, was largely ignored after its 1953 discovery. For close to a decade, very few cited Watson and Crick. They were not even nominated, by anyone, for a Nobel until after 1960, despite their discovery of how life code is written.
First ignorance, then controversy, continued dogging life code as humanity moved from reading it to copying it. Tadpoles were cloned in 1952, but few focused on that process until 1997, when the announcement of the cloning of Dolly the sheep begat wonder, consternation, and fear. Much the same occurred with in-vitro fertilization and Louise Brown, a breakthrough that got the Nobel in 2010, a mere thirty-two years after the first birth. Copying genes of dozens of species, leading to hundreds of thousands of almost identical animals, is now commonplace. The latest controversy is no longer “How do we deal with clones?” but “Should we eat them?”
Much has occurred as we learned to read and copy life code, but there is still little understanding of recent developments. Yet it is this third stage—writing and rewriting life code—that is by far the most important and profound.
Few realize, so far, that life code is spreading across industries, economies, countries, and cultures. As we begin to rewrite existing life, strange things evolve. Bacteria can be programmed to solve Sudoku puzzles. Viruses begin to create electronic circuits. As we write life from scratch, J. Craig Venter, Hamilton Smith, et al., partner with Exxon to try to change the world’s energy markets. Designer genes introduced by retroviruses, organs built from scratch, the first synthetic cells—these are further examples of massive change.
We see more and more products derived from life code changing fields as diverse as energy, textiles, chemicals, IT, vaccines, medicines, space exploration, agriculture, fashion, finance, and real estate. And gradually, “life code,” a concept with only 559 Google hits in 2000 and fewer than 50,000 in 2009, becomes a part of everyday public discourse.
Much has occurred over the past decades with digital code, leading to the likes of Digital, Lotus, HP, IBM, Microsoft, Amazon, Google, and Facebook. Many of the Fortune 500 companies within the next decade will be based on the understanding and application of life code.
But this is just the beginning. The real change will become apparent as we rewrite life code to morph the human species. We are already transitioning from a humanoid that is shaped by and shapes its environment into a Homo evolutis, a species that directly and deliberately designs and shapes its own evolution and that of other species.
Constraint Satisfaction
Stephen M. Kosslyn
Director, Center for Advanced Study in the Behavioral Sciences, Stanford University; author, Image and Mind
The concept of constraint satisfaction is crucial for understanding and improving human reasoning and decision making. A “constraint” is a condition that must be taken into account when solving a problem or making a decision, and “constraint satisfaction” is the process of meeting the relevant constraints. The key idea is that often there are only a few ways to satisfy a full set of constraints simultaneously.
For example, when moving into a new house, my wife and I had to decide how to arrange the furniture in the bedroom. We had an old headboard, which was so rickety that it had to be leaned against a wall. This requirement was a constraint on the positioning of the headboard. The other pieces of furniture also had requirements (constraints) on where they could be placed. Specifically, we had two small end tables that had to be next to either side of the headboard; a chair that needed to be somewhere in the room; a reading lamp that needed to be next to the chair; and an old sofa that was missing one of its rear legs and hence rested on a couple of books—and we wanted to position it so that people couldn’t see the books. Here was the remarkable fact about our exercises in interior design: Virtually always, as soon as we selected the wall for the headboard, bang! The entire configuration of the room was determined. There was only one other wall large enough for the sofa, which in turn left only one space for the chair and lamp.
In general, the more constraints, the fewer the possible ways of satisfying them simultaneously. And this is especially the case when there are many “strong” constraints. A strong constraint is like the positioning of the end tables: There are very few ways to satisfy it. In contrast, a “weak” constraint, such as the location of the headboard, can be satisfied in many ways. (Many positions along different walls would work.)
What happens when some constraints are incompatible with others? For instance, say that you live far from a gas station and so you want to buy an electric automobile—but you don’t have enough money to buy one. Not all constraints are equal in importance, and as long as the most important ones are satisfied “well enough,” you may have reached a satisfactory solution. In this case, although an optimal solution to your transportation needs might be an electric car, a hybrid that gets excellent gas mileage might be good enough.
In addition, once you begin the constraint-satisfaction process, you can make it more effective by seeking out additional constraints. For example, when you’re deciding what car to buy, you might start with the constraints of (a) your budget and (b) your desire to avoid going to a gas station. You then might consider the size of car needed for your purposes, length of the warranty, and styling. You may be willing to make tradeoffs—for example, by satisfying some constraints very well (such as mileage) but just barely satisfying others (e.g., styling). Even so, the mere fact of including additional constraints could be the deciding factor. Constraint satisfaction is pervasive. For example:
• This is how detectives—from Sherlock Holmes to the Mentalist—crack their cases, treating each clue as a constraint and looking for a solution that satisfies them all.
• This is what dating services strive to do—find the clients’ constraints, identify which constraints are most important to him or her, and then see which of the available candidates best satisfies the constraints.
• This is what you go through when finding a new place to live, weighing the relative importance of constraints such as the size, price, location, and type of neighborhood.
• And this is what you do when you get dressed in the morning: You choose clothes that “go with each other” (both in color and style).
Constraint satisfaction is pervasive in part because it does not require “perfect” solutions. It’s up to you to decide what the most important constraints are and just how many of the constraints in general must be satisfied (and how well). Moreover, constraint satisfaction need not be linear: You can appreciate the entire set of constraints at the same time, throwing them into your mental stewpot and letting them simmer. And this process need not be conscious. “Mulling it over” seems to consist of engaging in all-but-unconscious constraint satisfaction.
Finally, much creativity emerges from constraint satisfaction. Many new recipes have been created when chefs discovered that only certain ingredients were available—and they thus were either forced to substitute for those missing or come up with a new dish. Creativity can also emerge when you decide to change, exclude, or add a constraint. Einstein had one of his major breakthroughs when he realized that time need not pass at a constant rate. Perhaps paradoxically, adding constraints can actually enhance creativity—if a task is too open or unstructured, it may be so unconstrained that it’s difficult to devise any solution.
Cycles
Daniel C. Dennett
Philosopher; professor and codirector, Center for Cognitive Studies, Tufts University; author, Breaking the Spell: Religion as a Natural Phenomenon
Everybody knows about the familiar large-scale cycles of nature: Day follows night follows day, summer-fall-winter-spring-summer-fall-winter-spring, the water cycle of evaporation and precipitation that refills our lakes, scours our rivers, and restores the water supply of every living thing on the
planet. But not everybody appreciates how cycles—every spatial and temporal scale from the atomic to the astronomic—are quite literally the hidden spinning motors that power all the wonderful phenomena of nature.
Nikolaus Otto built and sold the first internal-combustion gasoline engine in 1861, and Rudolf Diesel built his engine in 1897, two brilliant inventions that changed the world. Each exploits a cycle, the four-stroke Otto cycle or the two-stroke Diesel cycle, that accomplishes some work and then restores the system to the original position so that it is ready to accomplish some more work. The details of these cycles are ingenious, and they have been discovered and optimized by an R & D cycle of invention that is several centuries old. An even more elegant, micro-miniaturized engine is the Krebs cycle, discovered in 1937 by Hans Krebs but invented over millions of years of evolution at the dawn of life. It is the eight-stroke chemical reaction that turns fuel into energy in the process of metabolism that is essential to all life, from bacteria to redwoods.
Biochemical cycles like the Krebs cycle are responsible for all the motion, growth, self-repair, and reproduction in the living world, wheels within wheels within wheels, a clockwork with trillions of moving parts, and each clock has to be rewound, restored to step one so that it can do its duty again. All of these have been optimized by the grand Darwinian cycle of reproduction, generation after generation, picking up fortuitous improvements over the eons.
At a completely different scale, our ancestors discovered the efficacy of cycles in one of the great advances of human prehistory: the role of repetition in manufacture. Take a stick and rub it with a stone and almost nothing happens—a few scratches are the only visible sign of change. Rub it a hundred times and there is still nothing much to see. But rub it just so, for a few thousand times, and you can turn it into an uncannily straight arrow shaft. By the accumulation of imperceptible increments, the cyclical process creates something altogether new. The foresight and self-control required for such projects was itself a novelty, a vast improvement over the repetitive but largely instinctual and mindless building and shaping processes of other animals. And that novelty was, of course, itself a product of the Darwinian cycle, enhanced eventually by the swifter cycle of cultural evolution, in which the reproduction of the technique wasn’t passed on to offspring through the genes but transmitted among non-kin conspecifics who picked up the trick of imitation.
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