Here is a very nice instructional video from Thompson at UCLA, whose images I have shown in previous posts, showing brain developmental differences in normal and schizophrenic children between the ages of 4 and 21. It also shows how recently developed drugs inhibit the degenerative changes.
Here is a fascinating result from Xu and Garcia, a demonstration that our brains begin to employ statistics at a very young age. Here are some (slightly edited) clips from their paper:
One hallmark of human learning is that human learners are able to make inductive inferences given a small amount of data. Our hunter–gatherer ancestors may have tasted a few berries on a tree and then decided that all berries from the same kind of tree are edible. They may have encountered a few friendly people from a neighboring tribe and made the inference that people in that tribe are likely to be friendly in general. Once such generalizations are made, the inferences may go in the other direction as well. This type of statistical inference (going from samples to populations, and from populations to samples) is present in virtually every domain of learning, be it foraging, social interaction, visual perception, word learning, or causal reasoning . Inductive learning in general requires some understanding of intuitive statistics, perhaps a simpler version of what scientists do in laboratory experiments or field studies.Here is one of the experiments, which asked whether 8-month-old infants could use the information in a sample to make inferences about a larger population:
Xu and Garcia performed six experiments investigating whether 8-month-old infants are "intuitive statisticians." Their results show that, given a sample, the infants are able to make inferences about the population from which the sample had been drawn. Conversely, given information about the entire population of relatively small size, the infants are able to make predictions about the sample...This ability to make inferences based on samples or information about the population develops early and in the absence of schooling or explicit teaching. Human infants may be rational learners from very early in development.
...8-month-old infants watched some events unfold on a puppet stage. Each infant was first given a set of six ping-pong balls in a small container to play with for a few seconds; half of the ping-pong balls were red, half were white. Then the infant was shown four familiarization trials. On each trial, a large box was brought onto the stage. The experimenter opened the front panel of the box and drew the infant's attention to the box. The box contained either mostly red ping-pong balls and a few white ping-pong balls or mostly white ping-pong balls and a few red ping-pong balls. The experimenter showed the infants these two displays alternately; thus the infants were equally familiarized with each display. Then the test trials began (see Fig. 1 for a schematic representation of the test events). On each test trial, the same box was brought onto the stage, its content not known to the infants. The experimenter shook the box for a few seconds, closed her eyes, reached into the top opening, and pulled out a ping-pong ball. She then placed it into a transparent sample display container next to the large box. A total of five ping-pong balls were drawn from the box, one at a time. In half of the test trials, a sample of four red and one white ping-pong balls were drawn. In the other half of the test trials, a sample of one red and four white ping-pong balls were drawn. After the five ping-pong balls were placed in the sample display container, the experimenter opened the front panel of the box to reveal its content. The infant's looking time was recorded. The experimenter then cleared the stage and started the next test trial until a total of eight test trials were completed. Only one outcome display was shown for each infant, either the mostly white or the mostly red one. On alternate test trials, the infants were shown the two samples (four red and one white or one red and four white). For an infant who saw the mostly red outcome display when the box was opened, the four red and one white sample was more probable and therefore expected, whereas the four white and one red ball sample was much less probable and therefore unexpected,{dagger} assuming each set was a random sample from the box. For an infant who saw the mostly white outcome display, the converse was true.Figure - Schematic representation of the test events (Images 1, 3, and 5) The experimenter shook the box for a few seconds, closed her eyes, reached into the top opening, and pulled out a ping-pong ball. (Images 2, 4, and 6) She then placed the ball into a transparent sample display container next to the large box. Test outcomes are shown at the bottom.
The infants looked reliably longer at the unexpected outcome (M = 9.9s) than the expected outcome (M = 7.5 s). It appears that infants were able to predict the content of the box from which the samples had been drawn.
Siok et al show that the brain changes associated with dyslexia in an alphabetic versus an ideographic language can be different. In alphabetic language, a reader sees a letter and associates it with a sound. Chinese characters correspond to syllables and require much more memorization. Both Chinese and English dyslexics find it harder to make their way through even fairly simple written material. This study suggests that their brain mechanics as they try to read may be as different as Chinese is from English. Here is their abstract:
Developmental dyslexia is a neurobiologically based disorder that affects approximately 5–17% of school children and is characterized by a severe impairment in reading skill acquisition. For readers of alphabetic (e.g., English) languages, recent neuroimaging studies have demonstrated that dyslexia is associated with weak reading-related activity in left temporoparietal and occipitotemporal regions, and this activity difference may reflect reductions in gray matter volume in these areas. Here, we find different structural and functional abnormalities in dyslexic readers of Chinese, a nonalphabetic language. Compared with normally developing controls, children with impaired reading in logographic Chinese exhibited reduced gray matter volume in a left middle frontal gyrus region previously shown to be important for Chinese reading and writing. Using functional MRI to study language-related activation of cortical regions in dyslexics, we found reduced activation in this same left middle frontal gyrus region in Chinese dyslexics versus controls, and there was a significant correlation between gray matter volume and activation in the language task in this same area. By contrast, Chinese dyslexics did not show functional or structural (i.e., volumetric gray matter) differences from normal subjects in the more posterior brain systems that have been shown to be abnormal in alphabetic-language dyslexics. The results suggest that the structural and functional basis for dyslexia varies between alphabetic and nonalphabetic languages.
Check out this interesting site, illustrating how the brain changes on aging.
In a recent Nature Reviews Neuroscience, Sarah-Jayne Blakemore does a summary of changes in the social brain during adolescence and I put down here the slightly edited capsule summary and one summary figure that offers a review of the relevant brain structures:
The 'social brain', the network of brain regions involved in understanding other people, includes the medial prefrontal cortex (mPFC) and the posterior superior temporal sulcus (pSTS). These regions are key to the process of mentalizing — that is, the attribution of mental states to oneself and to other people...Recent functional neuroimaging studies have shown that activity in parts of the social brain during social cognitive tasks changes during adolescence... activity in the PFC during face-processing tasks increases from childhood to adolescence and then decreases from adolescence to adulthood. Consistent with this, activity in the mPFC during mentalizing tasks decreases between adolescence and adulthood.
The prefrontal cortex is one of the brain regions that undergo structural development, including synaptic reorganization, during adolescence. Synaptic density, reflected in grey-matter volume in MRI scans, decreases during adolescence...Synaptic reorganization in the PFC might underlie the functional changes that are seen in the social brain during adolescence, as well as the social cognitive changes during this period.
Figure - Regions that are involved in social cognition include the medial prefrontal cortex (mPFC) and the temporoparietal junction (TPJ), which are involved in thinking about mental states, and the posterior superior temporal sulcus (pSTS), which is activated by observing faces and biological motion. Other regions of the social brain on the lateral surface are the inferior frontal gyrus (IFG) and the interparietal sulcus (IPS). Regions on the medial surface that are involved in social cognition include the amygdala, the anterior cingulate cortex (ACC) and the anterior insula (AI).
In a Nature journal club note, Devlin points out work by O'Neill and colleagues, who examined whether language development in preschool children might be a predictor of later math ability, given that early aptitude for arithmetic is not a terribly good indicator of future math performance.
O'Neill and her team showed three- and four-year-old children a picture book and asked them to tell a story about what they saw...narrative measures of conjunction use, event content, perspective shift, and mental state reference were significantly predictive of later Math scores. The sophistication with which the children told their stories was important. The most significant feature of this sophistication was children's ability to switch perspectives as they related the stories. Crucially, this correlation pertained not to later performance in reading, spelling or general knowledge, but to future mathematical ability.
An interesting article by Franklin et al. shows that our perception of color categories (CP) starts in the right hemisphere, but then switches to the left hemisphere as it develops the lexical color codes of language. They suggest that language-driven CP in adults may not build on prelinguistic CP, but that language instead imposes its categories on a left hemisphere that is not categorically prepartitioned.
Jim Holt has written an excellent article in the New Yorker focusing on the work of Stanislas Dehaene, who argues that humans (and higher animals) have an inbuilt “number sense” capable of some basic calculations and estimates. Evidence from cognitive deficits in brain-damaged patients has shown that we have a sense of number that is independent of language, memory, and reasoning in general.
When we see numerals or hear number words, our brains appear to automatically map them onto a number line that grows increasingly fuzzy above 3 or 4. A few chunks from Holt's article:
... it is generally agreed that infants come equipped with a rudimentary ability to perceive and represent number. (The same appears to be true for many kinds of animals, including salamanders, pigeons, raccoons, dolphins, parrots, and monkeys.) And if evolution has equipped us with one way of representing number, embodied in the primitive number sense, culture furnishes two more: numerals and number words. These three modes of thinking about number, Dehaene believes, correspond to distinct areas of the brain. The number sense is lodged in the parietal lobe, the part of the brain that relates to space and location; numerals are dealt with by the visual areas; and number words are processed by the language areas.
Dehaene has been able to bring together the experimental and the theoretical sides of his quest, and, on at least one occasion, he has even theorized the existence of a neurological feature whose presence was later confirmed by other researchers. In the early nineteen-nineties, working with Jean-Pierre Changeux, he set out to create a computer model to simulate the way humans and some animals estimate at a glance the number of objects in their environment. In the case of very small numbers, this estimate can be made with almost perfect accuracy, an ability known as “subitizing” (from the Latin word subitus, meaning “sudden”). Some psychologists think that subitizing is merely rapid, unconscious counting, but others, Dehaene included, believe that our minds perceive up to three or four objects all at once, without having to mentally “spotlight” them one by one. Getting the computer model to subitize the way humans and animals did was possible, he found, only if he built in “number neurons” tuned to fire with maximum intensity in response to a specific number of objects. His model had, for example, a special four neuron that got particularly excited when the computer was presented with four objects. The model’s number neurons were pure theory, but almost a decade later two teams of researchers discovered what seemed to be the real item, in the brains of macaque monkeys that had been trained to do number tasks. The number neurons fired precisely the way Dehaene’s model predicted—a vindication of theoretical psychology. “Basically, we can derive the behavioral properties of these neurons from first principles,” he told me. “Psychology has become a little more like physics.”
Monkeys very rapidly learn to fear snakes simply from seeing another monkey react fearfully to the presence of a snake. There has been a question of whether our human aversion to snake forms requires such learning, or might develop autonomously. Experiments by LoBue and DeLoache support the idea that our visual systems employ an innate developmental sequence to develop a heightened awareness of snake like forms very early in development, independent of actual direct or indirect experience of snakes. 3-5 year olds preferentially attended to snake pictures, even compared with pictures of caterpillars (as well as pictures of flowers or frogs), and this preference was the same in the presence or absence of previous exposure to snakes or snake images.
A preschool child identifying the single flower target among eight snake distractors by touching the flower image on a touch-screen monitor.
Whittle et al. have done fMRI experiments on adolescents that focused on three key brain regions which are known to represent critical nodes in neural networks supporting affective regulation: the amygdala, anterior cingulate cortex (ACC), and orbitofrontal cortex (OFC). Increased amygdala volume and a relative decrease of left versus right paralimbic ACC volumes were associated with increased duration of aggressive behaviors during parent-child interactions, with the latter association being apparent in males but not females. Decreased relative volume of left vs. right OFC was associated with greater reciprocity of dysphoric behaviors, the association also being specific to males. An absence of mean gender differences in affective behaviors suggests that the neural circuits underlying affective behaviors may differ for male and female adolescents during this age period. Here are some (slightly edited) comments by the authors:
The maturation of the prefrontal cortex and its inhibitory connections with the subcortex are key outcomes of the adolescent neurodevelopment that underlies the development of emotional and behavioral regulatory abilities. The associations of increased amygdala volume and decreased left frontal asymmetries with more negative affective behaviors may represent a delay in brain maturation. Longitudinal research would be needed to examine whether these findings have implications for the development of affective and behavioral dysregulation later in life.Here is a useful figure that shows you the locations and variations in the anatomy of the cingulate structures being discussed:
The male specificity of this finding adds to a growing body of evidence that the neural mechanisms underlying affective processing differ between males and females. Males have been found to exhibit structural and functional brain asymmetries to a greater extent than females in a number of prefrontal areas, including the cingulate region. It has been suggested that these asymmetries may render males more vulnerable to certain disorders involving dysfunction of the frontal lobes such as ADHD, autism, and dyslexia. Although males in the present study did not display more aggressive behavior than females, the more pronounced relationship between ACCP asymmetry and aggressive affective behaviors in males suggests that aggressive affect in male adolescents may function as a mechanism by which their brain asymmetry is implicated in their risk for psychopathology.
Figure-Example of changes in the location and extent of the limbic (ACCL; highlighted in green) and paralimbic (ACCP; highlighted in blue) anterior cingulate cortices as a function of variations in the cingulate sulcus (CS; green arrow, Upper row) and paracingulate sulcus (PCS; blue arrow, Upper row). A PCS is absent in the left-hand case and present in the right-hand case. The Upper row presents parasagittal slices through an individual's T1-weighted image. The coronal section illustrates the distinction between absent (left-hand side) and present (right-hand side) cases. Notice that the ACCP is buried in the depths of the CS when the PCS is absent and extends over the paracingulate gyrus when the PCS is present. The same principle applies throughout consecutive coronal sections.
A group of collaborators reports in PLOS ONE a specific and rapid neural signature for our parental instinct:
Darwin originally pointed out that there is something about infants which prompts adults to respond to and care for them, in order to increase individual fitness, i.e. reproductive success, via increased survivorship of one's own offspring. Lorenz proposed that it is the specific structure of the infant face that serves to elicit these parental responses, but the biological basis for this remains elusive. Here, we investigated whether adults show specific brain responses to unfamiliar infant faces compared to adult faces, where the infant and adult faces had been carefully matched across the two groups for emotional valence and arousal, as well as size and luminosity. The faces also matched closely in terms of attractiveness. Using magnetoencephalography (MEG) in adults, we found that highly specific brain activity occurred within a seventh of a second in response to unfamiliar infant faces but not to adult faces. This activity occurred in the medial orbitofrontal cortex (mOFC), an area implicated in reward behaviour, suggesting for the first time a neural basis for this vital evolutionary process. We found a peak in activity first in mOFC and then in the right fusiform face area (FFA)....These findings provide evidence in humans of a potential brain basis for the “innate releasing mechanisms” described by Lorenz for affection and nurturing of young infants.
The group analysis reveals a significant peak in the medial orbitofrontal cortex in the 10–30 Hz band in the 0–250 ms (first two columns), 100–350 ms (third column) and 200–450 ms (fourth column) windows when participants viewed infant (upper row) and not when they viewed adult faces (lower row). The fifth column shows the integrated map over the three time windows...In order to see the extent of the spread of activity over the fusiform cortices elicited by faces, the group activity is superimposed on a ventral view of the human brain (with the cerebellum removed).
Video games trigger reward and addiction centers of the brain, just like cocaine. Hoeft et. al. at Stanford have compared the activation of these centers in men's and women's brains as they played video games and found them to be more active in male than in female participants. Males showed greater activation and functional connectivity compared to females in the mesocorticolimbic system. The more the men won, the stronger their brain activity. Women's responses were less intense and didn't correlate with winning. This may have something to do with why men seem to become addicted to video games much more easily than women.
There is an interesting and more general article by Robin Henig on play in animals and humans in the New York Times Magazine. The general consensus is that play activity is very important in the development of social intelligence and the ability to respond to rapidly changing situations. It turns out that the rise and decay of play activity in animals corresponds closely to the development curve of the cerebellum, which is important in skilled movements. In one interesting study, experimenters:
...raised 12 female rats from the time they were weaned until puberty under one of two conditions. In the control group, each rat was caged with three other female juveniles. In the experimental group, each rat was caged with three female adults. Pellis knew from previous studies that the rats caged with adults would not play, since adult rats rarely play with juveniles, even their own offspring. They would get all the other normal social experiences the control rats had — grooming, nuzzling, touching, sniffing — but they would not get play... (in) the rats raised in a play-deprived environment, they found a more immature pattern of neuronal connections in the medial prefrontal cortex... less selective pruning of cells and a more tangled, immature medial prefrontal cortex in play-deprived rats might mean that the rat will be less able to make subtle adjustments to the social world.There are numerous theories about the function of play. It doesn't seem unreasonable that that the fragmentary, disorderly, unpredictable, exaggerated, improvised, vertiginous, and nonsensical nature of play trains the brain allows for a wider behavioral repertory and perhaps more competence in responding to novel or unforeseen situations.
Michael Beran writes a brief review of the evolutionary and developmental foundations of mathematics. Humans and other higher animals are born with a dedicated systems for numerical processing.
Alison Gopnik has an interesting take on why children pretend much of the time and spend time in imaginary worlds:
Recently, I've had to change my mind about the very nature of knowledge because of an obvious, but extremely weird fact about children - they pretend all the time. Walk into any preschool and you'll be surrounded by small princesses and superheroes in overalls - three-year-olds literally spend more waking hours in imaginary worlds than in the real one. Why? Learning about the real world has obvious evolutionary advantages and kids do it better than anyone else. But why spend so much time thinking about wildly, flagrantly unreal worlds? The mystery about pretend play is connected to a mystery about adult humans - especially vivid for an English professor's daughter like me. Why do we love obviously false plays and novels and movies?
The greatest success of cognitive science has been our account of the visual system. There's a world out there sending information to our eyes, and our brains are beautifully designed to recover the nature of that world from that information. I've always thought that science, and children's learning, worked the same way. Fundamental capacities for causal inference and learning let scientists, and children, get an accurate picture of the world around them - a theory. Cognition was the way we got the world into our minds.
But fiction doesn't fit that picture - its easy to see why we want the truth but why do we work so hard telling lies? I thought that kids' pretend play, and grown-up fiction, must be a sort of spandrel, a side-effect of some other more functional ability. I said as much in a review in Science and got floods of e-mail back from distinguished novel-reading scientists. They were all sure fiction was a Good Thing - me too, of course, - but didn't seem any closer than I was to figuring out why.
So the anomaly of pretend play has been bugging me all this time. But finally, trying to figure it out has made me change my mind about the very nature of cognition itself.
I still think that we're designed to find out about the world, but that's not our most important gift. For human beings the really important evolutionary advantage is our ability to create new worlds. Look around the room you're sitting in. Every object in that room - the right angle table, the book, the paper, the computer screen, the ceramic cup was once imaginary. Not a thing in the room existed in the pleistocene. Every one of them started out as an imaginary fantasy in someone's mind. And that's even more true of people - all the things I am, a scientist, a philosopher, an atheist, a feminist, all those kinds of people started out as imaginary ideas too. I'm not making some relativist post-modern point here, right now the computer and the cup and the scientist and the feminist are as real as anything can be. But that's just what our human minds do best - take the imaginary and make it real. I think now that cognition is also a way we impose our minds on the world.
In fact, I think now that the two abilities - finding the truth about the world and creating new worlds-are two sides of the same coins. Theories, in science or childhood, don't just tell us what's true - they tell us what's possible, and they tell us how to get to those possibilities from where we are now. When children learn and when they pretend they use their knowledge of the world to create new possibilities. So do we whether we are doing science or writing novels. I don't think anymore that Science and Fiction are just both Good Things that complement each other. I think they are, quite literally, the same thing.
Here is a chilling little item from Pieperhoff et al., who examined MRI images of the brains of 51 healthy male subjects from 18 to 51 years old. They found age-related volume declines in circumscribed brain regions: the sensorimotor system, encompassing the cerebellum, thalamus, somatosensory and motor cortices, and the prefrontal system, encompassing the anterior cingulate as well as the lateral and basomedial frontal cortices. Regions belonging to other functional systems, such as the auditory system or the visual system, did not show such age–volume relationships.
Horizontal sections of the reference brain with statistical maps, showing the t values of age-related volume decline and increase. t values were calculated by a two-sided t test for a linear regression in the voxels of the LVR maps, depending on age.
Blanceflower and Oswald have done a fascinating study (PDF here) showing that across cultures, from Azerbaijan to Zimbabwe, we are happiest towards the beginning and end of our lives, leaving us most miserable in middle years between 40 and 50. For both men and women in the UK, the probability of depression peaked at around the age of 44. In the US, men were most likely to be unhappiest at 50, while for women the age was 40. The cause of the apparent U-shaped curve is not known. Quoting Oswald (the graphic is from his website):
...one possibility is that individuals learn to adapt to their strengths and weaknesses, and in mid-life quell their infeasible aspirations. Another possibility is that cheerful people live systematically longer...A third possibility is that older people might compare their lives with their peers'. Seeing their friends die could mean people value their remaining years more highly...It looks from the data like something happens deep inside humans. For the average person in the modern world, the dip in mental health and happiness comes on slowly, not suddenly in a single year...Only in their 50s do most people emerge from the low period. But encouragingly, by the time you are 70, if you are still physically fit then on average you are as happy and mentally healthy as a 20-year-old. Perhaps realising that such feelings are completely normal in mid-life might even help individuals survive this phase better.
Here are a few excerpts from a brief essay by Steve Kosslyn in the Edge.org series "What have you changed your mind about?
There is a really elegant solution to the problem that the genes can't know in advance how far apart the eyes will be. To cope with this problem, the genes overpopulate the brain, giving us options for different environments (where the distance between eyes and length of the arms are part of the brain's "environment," in this sense), and then the environment selects which connections are appropriate, and the useless connections are pruned away. In other words, the genes take advantage of the environment to configure the brain.A similar, more brief, response to the edge.org question was offered by Jeffrey Epstein, A science Philanthropist:
This overpopulate-and-select mechanism is not limited to stereovision. In general, the environment sets up the brain (above and beyond any role it may have had in the evolution of the species), configuring it to work well in the world a person inhabits. And by environment I'm including everything outside the brain — including the social environment. For example, it's well known that children can learn multiple languages without an accent and with good grammar, if they are exposed to the language before puberty. But after puberty, it's very difficult to learn a second language so well.
This perspective leads me to wonder whether we can assume that the brains of people living in different cultures process information in precisely the same ways. Yes, people the world over have much in common (we are members of the same species, after all), but even small changes in the wiring may lead us to use the common machinery in different ways. If so, then people from different cultures may have unique perspectives on common problems, and be poised to make unique contributions toward solving such problems... to understand how any specific brain functions, we need to understand how that person was raised, and currently functions, in the surrounding culture.
The question presupposes a well defined "you", and an implied ability that is under "your" control to change your "mind". The "you" I now believe is distributed amongst others (family friends , in hierarchal structures,) i.e. suicide bombers, believe their sacrifice is for the other parts of their "you". The question carries with it an intention that I believe is out of one's control. My mind changed as a result of its interaction with its environment. Why? because it is a part of it.
This work demonstrates that when we are born, we have an innate bias towards attending to motions characteristic of other living things. Newborn chickens do this also. The abstract, a figure, and a video from Simion et al. :
An inborn predisposition to attend to biological motion has long been theorized, but had so far been demonstrated only in one animal species (the domestic chicken). In particular, no preference for biological motion was reported for human infants of less than 3 months of age. We tested 2-day-old babies' discrimination after familiarization and their spontaneous preferences for biological vs. nonbiological point-light animations. Newborns were shown to be able to discriminate between two different patterns of motion (Exp. 1) and, when first exposed to them, selectively preferred to look at the biological motion display (Exp. 2). This preference was also orientation-dependent: newborns looked longer at upright displays than upside-down displays (Exp. 3). These data support the hypothesis that detection of biological motion is an intrinsic capacity of the visual system, which is presumably part of an evolutionarily ancient and nonspecies-specific system predisposing animals to preferentially attend to other animals.Figure: Three sample frames taken from the animation sequences used in the study: the biological motion stimulus (i.e., the walking hen) (Top), the nonbiological motion stimulus (random motion) (Middle), and the inverted biological motion display (upside-down walking hen) (Bottom). Squares indicate the point-lights.
Here is an engaging article by Richard Freedman on the supposed crisis around age 50 (mainly in men) when the first signs of physical decline and the questions and doubts about one’s personal and professional accomplishments emerge.
..some find themselves seized by a seemingly irresistible impulse to do something dramatic, even foolish. Everything, it appears, is fair game for a midlife crisis: one’s job, spouse, lover — you name it.Freedman outlines:
a garden-variety case of a middle-aged narcissist grappling with the biggest insult he had ever faced: getting older...But you have to admit that “I’m having a midlife crisis” sounds a lot better than “I’m a narcissistic jerk having a meltdown.”Another source of the midlife 'crisis' :
...reaching a situation...of having to seriously take account of someone else’s needs, such as those of children, for the first time.Further clips:
Why do we have to label a common reaction of the male species to one of life’s challenges — the boredom of the routine — as a crisis? True, men are generally more novelty-seeking than women, but they certainly can decide what they do with their impulses.
The main culprit, I think, is our youth-obsessed culture, which makes a virtue of the relentless pursuit of self-renewal. The news media abound with stories of people who seek to recapture their youth simply by shedding their spouses, quitting their jobs or leaving their families. Who can resist?..Most middle-aged people, it turns out, if we are to believe the definitive survey...Except, of course, for the few — mainly men, it seems — who find the midlife crisis a socially acceptable shorthand for what you do when you suddenly wake up and discover that you’re not 20 anymore.
This clip from the Jan. 20 issue of Science:
Personal genomics revved into high gear last year thanks to DNA chips that make it possible to cheaply scan the entire genome (Science, 21 December 2007, p. 1842). You can track the flood of new discoveries at SNPedia (www.snpedia.com), a Web site run by two biotech veterans in Bethesda, Maryland, that catalogs SNPs culled from the literature.
SNPs are single-nucleotide polymorphisms: single-base variations in DNA that researchers are tying to traits and disease risks. Browse by medical conditions (77 so far) and discover, for example, that carrying two copies of the T version of a SNP called rs2273535 raises your risk of colon cancer by 50%; another SNP, rs6152, is associated with baldness. Visitors can also search by genetically influenced drug reactions (48) and genes (128). There are links to relevant papers and sites (including James Watson's and J. Craig Venter's respective genomes) and to blogs by people who are sending their DNA to a lab to be "SNP chipped." The site is also a wiki, which means anyone can contribute.
The site "could be a very valuable research tool," says computational biologist Mark Daly of the Broad Institute in Cambridge, Massachusetts. "It will be great to see how this develops."
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