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Top Ten Myths About the Brain
When it comes to this complex, mysterious, fascinating organ, what do—and don’t—we know?
[计时一]
1. We use only 10 percent of our brains.
This one sounds so compelling—a precise number, repeated in pop culture for a century, implying that we have huge reserves of untapped mental powers. But the supposedly unused 90 percent of the brain is not some vestigial appendix. Brains are expensive—it takes a lot of energy to build brains during fetal and childhood development and maintain them in adults. Evolutionarily, it would make no sense to carry around surplus brain tissue. Experiments using PET or fMRI scans show that much of the brain is engaged even during simple tasks, and injury to even a small bit of brain can have profound consequences for language, sensory perception, movement or emotion.
True, we have some brain reserves. Autopsy studies show that many people have physical signs of Alzheimer’s disease (such as amyloid plaques among neurons) in their brains even though they were not impaired. Apparently we can lose some brain tissue and still function pretty well. And people score higher on IQ tests if they’re highly motivated, suggesting that we don’t always exercise our minds at 100 percent capacity.
2. “Flashbulb memories” are precise, detailed and persistent.
We all have memories that feel as vivid and accurate as a snapshot, usually of some shocking, dramatic event—the assassination of President Kennedy, the explosion of the space shuttle Challenger, the attacks of September 11, 2001. People remember exactly where they were, what they were doing, who they were with, what they saw or heard. But several clever experiments have tested people’s memory immediately after a tragedy and again several months or years later. The test subjects tend to be confident that their memories are accurate and say the flashbulb memories are more vivid than other memories. Vivid they may be, but the memories decay over time just as other memories do. People forget important details and add incorrect ones, with no awareness that they’re recreating a muddled scene in their minds rather than calling up a perfect, photographic reproduction.
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[计时二]
3. It’s all downhill after 40 (or 50 or 60 or 70).
It’s true, some cognitive skills do decline as you get older. Children are better at learning new languages than adults—and never play a game of concentration against a 10-year-old unless you’re prepared to be humiliated. Young adults are faster than older adults to judge whether two objects are the same or different; they can more easily memorize a list of random words, and they are faster to count backward by sevens.
But plenty of mental skills improve with age. Vocabulary, for instance—older people know more words and understand subtle linguistic distinctions. Given a biographical sketch of a stranger, they’re better judges of character. They score higher on tests of social wisdom, such as how to settle a conflict. And people get better and better over time at regulating their own emotions and finding meaning in their lives.
4. We have five senses.
Sure, sight, smell, hearing, taste and touch are the big ones. But we have many other ways of sensing the world and our place in it. Proprioception is a sense of how our bodies are positioned. Nociception is a sense of pain. We also have a sense of balance—the inner ear is to this sense as the eye is to vision—as well as a sense of body temperature, acceleration and the passage of time.
Compared with other species, though, humans are missing out. Bats and dolphins use sonar to find prey; some birds and insects see ultraviolet light; snakes detect the heat of warmblooded prey; rats, cats, seals and other whiskered creatures use their “vibrissae” to judge spatial relations or detect movements; sharks sense electrical fields in the water; birds, turtles and even bacteria orient to the earth’s magnetic field lines.
By the way, have you seen the taste map of the tongue, the diagram showing that different regions are sensitive to salty, sweet, sour or bitter flavors? Also a myth.
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[计时三]
5. Brains are like computers.
We speak of the brain’s processing speed, its storage capacity, its parallel circuits, inputs and outputs. The metaphor fails at pretty much every level: the brain doesn’t have a set memory capacity that is waiting to be filled up; it doesn’t perform computations in the way a computer does; and even basic visual perception isn’t a passive receiving of inputs because we actively interpret, anticipate and pay attention to different elements of the visual world.
There’s a long history of likening the brain to whatever technology is the most advanced, impressive and vaguely mysterious. Descartes compared the brain to a hydraulic machine. Freud likened emotions to pressure building up in a steam engine. The brain later resembled a telephone switchboard and then an electrical circuit before evolving into a computer; lately it’s turning into a Web browser or the Internet. These metaphors linger in clichés: emotions put the brain “under pressure” and some behaviors are thought to be “hard-wired.” Speaking of which...
6. The brain is hard-wired.
This is one of the most enduring legacies of the old “brains are electrical circuits” metaphor. There’s some truth to it, as with many metaphors: the brain is organized in a standard way, with certain bits specialized to take on certain tasks, and those bits are connected along predictable neural pathways (sort of like wires) and communicate in part by releasing ions (pulses of electricity).
But one of the biggest discoveries in neuroscience in the past few decades is that the brain is remarkably plastic. In blind people, parts of the brain that normally process sight are instead devoted to hearing. Someone practicing a new skill, like learning to play the violin, “rewires” parts of the brain that are responsible for fine motor control. People with brain injuries can recruit other parts of the brain to compensate for the lost tissue.
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[计时四]
7. A conk on the head can cause amnesia.
Next to babies switched at birth, this is a favorite trope of soap operas: Someone is in a tragic accident and wakes up in the hospital unable to recognize loved ones or remember his or her own name or history. (The only cure for this form of amnesia, of course, is another conk on the head.)
In the real world, there are two main forms of amnesia: anterograde (the inability to form new memories) and retrograde (the inability to recall past events). Science’s most famous amnesia patient, H.M., was unable to remember anything that happened after a 1953 surgery that removed most of his hippocampus. He remembered earlier events, however, and was able to learn new skills and vocabulary, showing that encoding “episodic” memories of new experiences relies on different brain regions than other types of learning and memory do. Retrograde amnesia can be caused by Alzheimer’s disease, traumatic brain injury (ask an NFL player), thiamine deficiency or other insults. But a brain injury doesn’t selectively impair autobiographical memory—much less bring it back.
8. We know what will make us happy.
In some cases we haven’t a clue. We routinely overestimate how happy something will make us, whether it’s a birthday, free pizza, a new car, a victory for our favorite sports team or political candidate, winning the lottery or raising children. Money does make people happier, but only to a point—poor people are less happy than the middle class, but the middle class are just as happy as the rich. We overestimate the pleasures of solitude and leisure and underestimate how much happiness we get from social relationships.
On the flip side, the things we dread don’t make us as unhappy as expected. Monday mornings aren’t as unpleasant as people predict. Seemingly unendurable tragedies—paralysis, the death of a loved one—cause grief and despair, but the unhappiness doesn’t last as long as people think it will. People are remarkably resilient.
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9. We see the world as it is.
We are not passive recipients of external information that enters our brain through our sensory organs. Instead, we actively search for patterns (like a Dalmatian dog that suddenly appears in a field of black and white dots), turn ambiguous scenes into ones that fit our expectations (it’s a vase; it’s a face) and completely miss details we aren’t expecting. In one famous psychology experiment, about half of all viewers told to count the number of times a group of people pass a basketball do not notice that a guy in a gorilla suit is hulking around among the ball-throwers.
We have a limited ability to pay attention (which is why talking on a cellphone while driving can be as dangerous as drunk driving), and plenty of biases about what we expect or want to see. Our perception of the world isn’t just “bottom-up”—built of objective observations layered together in a logical way. It’s “top-down,” driven by expectations and interpretations.
10. Men are from Mars, women are from Venus.
Some of the sloppiest, shoddiest, most biased, least reproducible, worst designed and most overinterpreted research in the history of science purports to provide biological explanations for differences between men and women. Eminent neuroscientists once claimed that head size, spinal ganglia or brain stem structures were responsible for women’s inability to think creatively, vote logically or practice medicine. Today the theories are a bit more sophisticated: men supposedly have more specialized brain hemispheres, women more elaborate emotion circuits. Though there are some differences (minor and uncorrelated with any particular ability) between male and female brains, the main problem with looking for correlations with behavior is that sex differences in cognition are massively exaggerated.
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[自由阅读]
Women are thought to outperform men on tests of empathy. They do—unless test subjects are told that men are particularly good at the test, in which case men perform as well as or better than women. The same pattern holds in reverse for tests of spatial reasoning. Whenever stereotypes are brought to mind, even by something as simple as asking test subjects to check a box next to their gender, sex differences are exaggerated. Women college students told that a test is something women usually do poorly on, do poorly. Women college students told that a test is something college students usually do well on, do well. Across countries—and across time—the more prevalent the belief is that men are better than women in math, the greater the difference in girls’ and boys’ math scores. And that’s not because girls in Iceland have more specialized brain hemispheres than do girls in Italy.
Certain sex differences are enormously important to us when we’re looking for a mate, but when it comes to most of what our brains do most of the time—perceive the world, direct attention, learn new skills, encode memories, communicate (no, women don’t speak more than men do), judge other people’s emotions (no, men aren’t inept at this)—men and women have almost entirely overlapping and fully Earth-bound abilities.
Read more: http://www.smithsonianmag.com/science-nature/Top-Ten-Myths-About-the-Brain.html#ixzz1pXUqSc00
越障
在此强力推荐一段15min的演讲（可作为听力练习），是下文的主角Henry Markram在2009年做的TED talk
http://www.ted.com/talks/henry_markram_supercomputing_the_brain_s_secrets.html
（可在线收看，也可download，Interactive transcript是文本）
btw:最近发现TED网站很多启迪心智的演讲，包罗万象，强烈推荐给大家
http://www.ted.com/talks
Computer modelling: Brain in a box
Henry Markram wants ? billion to model the entire human brain. Sceptics don't think he should get it.
22 February 2012
It wasn't quite the lynching that Henry Markram had expected. But the barrage of sceptical comments from his fellow neuroscientists — “It's crap,” said one — definitely made the day feel like a tribunal.
Officially, the Swiss Academy of Sciences meeting in Bern on 20 January was an overview of large-scale computer modelling in neuroscience. Unofficially, it was neuroscientists' first real chance to get answers about Markram's controversial proposal for the Human Brain Project (HBP) — an effort to build a supercomputer simulation that integrates everything known about the human brain, from the structures of ion channels in neural cell membranes up to mechanisms behind conscious decision-making.
Markram, a South-African-born brain electrophysiologist who joined the Swiss Federal Institute of Technology in Lausanne (EPFL) a decade ago, may soon see his ambition fulfilled. The project is one of six finalists vying to win ? billion (US$1.3 billion) as one of the European Union's two new decade-long Flagship initiatives.
“Brain researchers are generating 60,000 papers per year,” said Markram as he explained the concept in Bern. “They're all beautiful, fantastic studies — but all focused on their one little corner: this molecule, this brain region, this function, this map.” The HBP would integrate these discoveries, he said, and create models to explore how neural circuits are organized, and how they give rise to behaviour and cognition — among the deepest mysteries in neuroscience. Ultimately, said Markram, the HBP would even help researchers to grapple with disorders such as Alzheimer's disease. “If we don't have an integrated view, we won't understand these diseases,” he declared.
As the response at the meeting made clear, however, there is deep unease about Markram's vision. Many neuroscientists think it is ill-conceived, not least because Markram's idiosyncratic approach to brain simulation strikes them as grotesquely cumbersome and over-detailed. They see the HBP as overhyped, thanks to breathless media reports about what it will accomplish. And they're not at all sure that they can trust Markram to run a project that is truly open to other ideas.
“We need variance in neuroscience,” declared Rodney Douglas, co-director of the Institute for Neuroinformatics (INI), a joint initiative of the University of Zurich and the Swiss Federal Institute of Technology in Zurich (ETH Zurich). Given how little is known about the brain, he said, “we need as many different people expressing as many different ideas as possible” — a diversity that would be threatened if so much scarce neuroscience research money were to be diverted into a single endeavour.
Markram was undeterred. Right now, he argued, neuroscientists have no plan for achieving a comprehensive understanding of the brain. “So this is the plan,” he said. “Build unifying models.”
Markram's big idea
Markram has been on a quest for unity since at least 1980, when he began undergraduate studies at the University of Cape Town in South Africa. He abandoned his first field of study, psychiatry, when he decided that it was mainly about putting people into diagnostic pigeonholes and medicating them accordingly. “This was never going to tell us how the brain worked,” he recalled in Bern.
His search for a new direction led Markram to the laboratory of Douglas, then a young neuroscientist at Cape Town. Markram was enthralled. “I said, 'That's it! For the rest of my life, I'm going to dig into the brain and understand how it works, down to the smallest detail we can possibly find.'”
That enthusiasm carried Markram to a PhD at the Weizmann Institute of Science in Rehovot, Israel; to postdoctoral stints at the US National Institutes of Health in Bethesda, Maryland, and at the Max Planck Institute for Medical Research in Heidelberg, Germany; and, in 1995, to a faculty position at Weizmann. He earned a formidable reputation as an experimenter, notably demonstrating spike-timing-dependent plasticity — in which the strength of neural connections changes according to when impulses arrive and leave.
By the mid-1990s, individual discoveries were leaving him dissatisfied. “I realized I could be doing this for the next 25, 30 years of my career, and it was still not going to help me understand how the brain works,” he said.
To do better, he reasoned, neuroscientists would have to pool their discoveries systematically. Every experiment at least tacitly involves a model, whether it is the molecular structure of an ion channel or the dynamics of a cortical circuit. With computers, Markram realized, you could encode all of those models explicitly and get them to work together. That would help researchers to find the gaps and contradictions in their knowledge and identify the experiments needed to resolve them.
Markram's insight wasn't original: scientists have been devising mathematical models of neural activity since the early twentieth century, and using computers for the task since the 1950s. But his ambition was vast. Instead of modelling each neuron as, say, a point-like node in a larger neural network, he proposed to model them in all their multi-branching detail — down to their myriad ion channels. And instead of modelling just the neural circuits involved in, say, the sense of smell, he wanted to model everything, “from the genetic level, the molecular level, the neurons and synapses, how microcircuits are formed, macrocircuits, mesocircuits, brain areas — until we get to understand how to link these levels, all the way up to behaviour and cognition”.
The computer power required to run such a grand unified theory of the brain would be roughly an exaflop, or 1018 operations per second — hopeless in the 1990s. But Markram was undaunted: available computer power doubles roughly every 18 months, which meant that exascale computers could be available by the 2020s. And in the meantime, he argued, neuroscientists ought to be getting ready for them.
Markram's ambitions fit perfectly with those of Patrick Aebischer, a neuroscientist who became president of the EPFL in 2000 and wanted to make the university a powerhouse in both computation and biomedical research. Markram was one of his first recruits, in 2002. “Henry gave us an excuse to buy a Blue Gene,” says Aebischer, referring to a then-new IBM supercomputer optimized for large-scale simulations. One was installed at the EPFL in 2005, allowing Markram to launch the Blue Brain Project: his first experiment in integrative neuroscience and, in retrospect, a prototype for the HBP.
Part of the project has been a demonstration of what a unifying model might mean, says Markram, who started with a data set on the rat cortex that he and his students had been accumulating since the 1990s. It included results from some 20,000 experiments in many labs, he says — “data on about every cell type that we had come across, the morphology, the reconstruction in three dimensions, the electrical properties, the synaptic communication, where the synapses are located, the way the synapses behave, even genetic data about what genes are expressed”.
By the end of 2005, his team had integrated all the relevant portions of this data set into a single-neuron model. By 2008, the researchers had linked about 10,000 such models into a simulation of a tube-shaped piece of cortex known as a cortical column. Now, using a more advanced version of Blue Gene, they have simulated 100 interconnected columns.
The effort has yielded some discoveries, says Markram, such as the as-yet unpublished statistical distribution of synapses in a column. But its real achievement has been to prove that unifying models can, as promised, serve as repositories for data on cortical structure and function. Indeed, most of the team's efforts have gone into creating “the huge ecosystem of infrastructure and software” required to make Blue Brain useful to every neuroscientist, says Markram. This includes automatic tools for turning data into simulations, and informatics tools such as http://channelpedia.net — a user-editable website that automatically collates structural data on ion channels from publications in the PubMed database, and currently incorporates some 180,000 abstracts.
The ultimate goal was always to integrate data across the entire brain, says Markram. The opportunity to approach that scale finally arose in December 2009, when the European Union announced that it was prepared to pour some ? billion into each of two high-risk, but potentially transformational, Flagship projects. Markram, who had been part of the 27-member advisory group that endorsed the initiative, lost no time in organizing his own entry. And in May 2011, the HBP was named as one of six candidates that would receive seed money and prepare a full-scale proposal, due in May 2012.
If the HBP is selected, one of the key goals will be to make it highly collaborative and Internet-accessible, open to researchers from around the world, says Markram, adding that the project consortium already comprises some 150 principal investigators and 70 institutions in 22 countries. “It will be lots of Einsteins coming together to build a brain,” he says, each bringing his or her own ideas and expertise.
[越障结束 1492 WORDS]
To continue reading, please refer to the attached original article.
Source:
Nature 482, 456–458 (23 February 2012)
http://www.nature.com/news/computer-modelling-brain-in-a-box-1.10066 |
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