[neuro] [biomed] wired: on Allen's brain atlas project

[Alejandro Dubrovsky]

(
pictures and video on site
http://www.wired.com/medtech/health/magazine/17-04/ff_brainatlas?currentPage=all
)

Scientists Map the Brain, Gene by Gene
By Jonah Lehrer Email 03.28.09
"The brain is details on top of details on top of details." — Michael
Hawrylycz
Photo: David Clugston
Gallery
Creating an Atlas of the Human Mind

The human brain is surprisingly bloody. I've worked in neuroscience
labs, and I'm used to seeing brains that are stored in glass jars filled
with formaldehyde, the preserved tissue a lifeless gray. But this brain—
removed from a warm body just a few hours ago—looks bruised, its folds
stained purple. Blood drips from the severed stem, forming puddles on
the stainless steel table.

I'm in the dissection room of the Allen Institute for Brain Science in
Seattle, and the scientist next to me is in a hurry: His specimen—this
fragile cortex—is falling apart. Dying, the gray matter turns acidic and
begins to eat away at itself; nucleic acids unravel, cell membranes
dissolve. He takes a thin, sterilized knife and slices into the tissue
with disconcerting ease. I'm reminded of Jell-O and guillotines and the
meat counter at the supermarket. He saws repeatedly until the brain is
reduced to a series of thin slabs, which are then photographed and
rushed to a freezer. All that remains is a pool of blood, like the scene
of a crime.

Behind all the gore there's a profound purpose: The scientists here are
mapping the brain. And while conventional brain maps describe distinct
anatomical areas, like the frontal lobes and the hippocampus—many of
which were first outlined in the 19th century—the Allen Brain Atlas
seeks to describe the cortex at the level of specific genes and
individual neurons. Slices of tissue containing billions of brain cells
will be analyzed to see which snippets of DNA are turned on in each
cell.

If the institute succeeds, its maps will help scientists decipher the
function of the thousands of genes that help produce the human brain.
(Although the Human Genome Project was completed more than five years
ago, scientists still have little idea which genes are used to make the
brain, let alone where in the brain they are expressed.) For the first
time, it will be possible to understand how such a complex object is
assembled from a basic four-letter code.

"The maps of the brain we currently have are like those antique maps
people used to draw of the New World," says Allan Jones, chief
scientific officer at the Allen Institute. "We can see the crude
outlines of the structure, but we have no idea what's happening on the
inside." Jones is in charge of making sure the atlas gets finished. He
wears starched button-up shirts and crisply pleated khakis, and he looks
like the kind of guy who has a drawer full of bow ties. "Studying the
brain now is like trying to navigate a vast city without any driving
instructions," he says. "You don't know where you are, and you have no
idea how to find what you're looking for."
Author Jonah Lehrer spoke at San Francisco's Commonwealth Club on
February 19, 2009 about the black box of the human mind.
For more from FORA.tv, visit wired.com/video.

When the project is completed in 2012, at an expected cost of $55
million, its data sets will list the roughly 20,000 genes that, switched
on in the exact right place at the exact right time, give rise to this
self-aware tangle of neurons. And because the vast majority of mental
illnesses and disorders, from schizophrenia to autism, have a
significant genetic component, scientists at the institute hope that the
atlas will eventually lead to new methods of diagnosis and more
effective medical treatments. To map the brain is to map its
afflictions.

This enterprise is unique in one other respect: scale. "People ask me
why we didn't start with a more modest goal, like trying to map some
small brain area," Jones says. "The point of doing the whole brain,
though, is that it allows us to really develop theories about how the
brain works. Sometimes, the only way to make sense of a complex system
is to be systematic."

To achieve this, the Allen Institute reimagined the scientific process.
There was no grand hypothesis, or even a semblance of theory. The
researchers just wanted the data, and, given the amount needed, it
quickly became apparent that the work couldn't be done by hand. So,
shortly after the institute was founded in 2003, Jones and his team
started thinking about how to industrialize the experimental process.
While modern science remains, for the most part, a field of artisans—
scientists performing their own experiments at their own benches—the
atlas required a high-throughput model, in which everything would be
done on an efficient assembly line. Thanks to a team of new laboratory
robots, what would have taken a thousand technicians several years can
now be accomplished in less than 20 months.

The institute can produce more than a terabyte of data per day. (In
comparison, the 3 billion base pairs in the human genome can fit in a
text file that's only 3 gigabytes.) And the project is just getting
started.
Preparing a fresh specimen for analysis.
Photo: David Clugston


In March 2002, Paul Allen—cofounder of Microsoft and 41st-richest person
in the world—brought together a dozen neuroscientists for a three-day
meeting aboard his 300-foot yacht, Tatoosh, which was anchored in
Nassau, Bahamas. At the time, Allen's philanthropic work consisted of an
eclectic (some say frivolous) set of endeavors. There was the Experience
Music Project in Seattle, a rock-and-roll museum designed by Frank
Gehry; the Allen Telescope Array, 350 radio telescopes dedicated to
deep-space observation and the search for extraterrestrial life; and
SpaceShipOne, the first privately funded plane developed to put a human
in space. But Allen was eager to start something new: a project
involving neuroscience. He was excited by the sheer uncharted mystery of
the mind—one of the last, great scientific frontiers—hoping a single
large-scale endeavor could transform the field.

"I first got interested in the brain through computers," Allen says.
"There's a long history of artificial intelligence programs that try to
mimic what the brain is doing, but they've all fallen short. Here's this
incredible computer, a really astonishing piece of engineering, and we
have no idea how it works."

Over several days, Allen asked the neuroscientists to imagine a way to
move their field forward dramatically. "I wanted them to think big," he
says. "Like the Human Genome Project, only for the brain." Some
advocated focusing on a single disease, like Alzheimer's. Others argued
for more investment in brain imaging technology. But a consensus emerged
that what neuroscience most needed was a map, a vast atlas of gene
expression that would reconcile the field's disparate experimental
approaches. It's not that scientists don't know a lot about the brain—
it's that they have no idea how it all fits together.

Today, you can measure the electrical activity of individual neurons,
which involves plunging a microelectrode into the tissue and hoping to
find an interesting cell. You can image the brain in an fMRI machine and
isolate the areas that are active during certain types of mental
activity. Or you can use the tools of molecular biology and study
specific kinase enzymes, synaptic proteins, or RNA splices.

The problem with this multiplicity of techniques is that they fail to
explain how the brain's essential elements—the wet stuff, the genetic
text, the electric loom of cells—conspire to create a sentient piece of
matter. Allen decided that what neuroscience needed was a tool to help
get beyond these obsolete boundaries. "It became apparent to me that
there were lots of scientists studying their own little area of brain,
pursuing these very specific questions," he says. "But I wanted to
develop something that would focus on making these crosscutting
connections, so that everybody in the field could benefit."

Say, for instance, someone is investigating the anatomy of autism. The
scientist has done an fMRI study that reveals abnormalities in a
cortical area in autistic subjects—a bit of brain is not functioning
properly—and this might help explain the symptoms of the disease. But
now what? The problem has been isolated, but at a very abstract level.
The research has hit a dead end.

Meanwhile, another scientist is looking at autism from a very different
perspective, conducting large-scale genetic studies that identify a few
of the fragments of DNA associated with the disease. (Autism is one of
the most heritable psychiatric disorders.) The problem with these
efforts is that they often highlight obscure genes that haven't been
studied. Nobody knows what these genes do, or whether they're even
expressed in the brain. As a result, the research stalls and it remains
completely unclear how this genetic defect might lead to the particular
problems seen in the fMRIs.

But now imagine that this scientist has access to the Allen atlas. By
looking at the map, he should be able to quickly see whether any of the
genes known to be associated with autism—several have already been
identified—are expressed in the brain areas that appear abnormal in the
fMRI scans. This means that the disease can be pinpointed at a very
precise level, reduced to a few dysfunctional circuits expressing the
wrong set of genes. "That's what having a huge database lets you do,"
Allen says. "It becomes a tool that will really accelerate the pace of
research." Such a map can also help neuroscientists better target their
genetic searches. Instead of looking at every gene expressed in the
brain—according to the institute's research, that may include nearly 80
percent of the human genome—they can focus only on those that are
present in the relevant brain areas.

Then there's the mystery of the developing brain. How does something so
complex manage to build itself? The Allen Institute is also measuring
genetic expression in the mouse brain, from embryo to adult, to explore
how the orchestra of genes is switched on and off in different areas
during development. Which snippets of DNA transform the hippocampus into
a center of long-term memory? Which make the amygdala a warehouse of
fear and anxiety? "One of the things I've come to appreciate about the
brain is the importance of location," Allen says. "It's not just a set
of interchangeable parts that you can swap in and out. These brain areas
are all so distinct, and for reasons we can finally begin to
understand."
 
 

Industrial-Strength Science
 

To create a complete genetic map of the brain, scientists at the Allen
Institute had to invent a high-throughput system that can process tissue
and data on an unprecedented scale. Traditional methods would have taken
decades, but by using assembly-line robots and new protocols, they
expect to finish the human brain atlas in four years. Here's how it's
done.

1) As soon as the institute receives a fresh human brain—fewer than 15
specimens will ultimately be used to create the atlas—it's immediately
hand-sliced into 5-mm slabs, which are frozen.
 

2) Using a machine called a microtome, technicians shave each slab into
thousands of transparent slices only a few microns thick. These are
mounted on 2 x 3-inch barcoded glass slides.
 

3) In a process called in situ hybridization, specialized robots work
round the clock using fragments of RNA to probe each sample for a
particular gene, which is stained with colored dye.
 

4) Robotic microscopes equipped with high-speed loaders take digital
photographs of each slide. The intensity of dye color is used to
quantify the amount of gene expression in the tissue.
 

5) The complete atlas, correlated by both gene and location, is stored
on the institute's servers. Powerful tools to explore the data will be
available for free to all researchers at brain-map.org.

There's something ironic about Allen, cofounder of a software empire,
funding an exhaustive atlas of our neural hardware. (He established the
institute with a donation of $100 million.) For decades, many cognitive
scientists insisted that the physical brain was largely irrelevant to
the study of the mind. It didn't matter whether the human operating
system was running on a real cortex or a set of silicon microchips—the
software was everything. Given Allen's background—this was the man who
helped develop MS-DOS 1.0, after all—he might have been expected to ally
with the software crowd in the belief that the 1s and 0s were more
important than the anatomical details. Instead, Allen decided that our
operating system could run only on one very particular kind of computer.
"There are so many intricacies to our brain that won't be understood
unless we start to look at the system as a whole," he says. "All these
different details don't operate in isolation. But how do they work
together to create such a powerful machine?"

The cavernous and antiseptic main lab on the second floor of the Allen
Institute is dominated by five big black boxes, each the size of a Smart
Car. These are robots, specially constructed by lab-automation company
Tecan. At the center of each is a glass window, through which all the
action can be observed: A metal arm equipped with a series of long
plastic pipettes moves endlessly back and forth, squirting a variety of
liquids onto slices of brain. The accompanying mechanical noises—a
comforting chorus of squeaks, clanks, and beeps—sound like the androids
from WALL-E. At the moment, each robot is processing 192 brain slices
per day, allowing the lab to analyze nearly a thousand every 24 hours.
(Other bots perform more specialized tasks, like delicately adding glass
covers to the tissue samples.) They work through the night, continuing
to do science while their human counterparts sleep.

Before a single brain was dissected, back when the atlas was still
purely hypothetical, Allan Jones realized that the most difficult
challenges wouldn't be scientific. All the necessary tools were
available, and there were no theoretical obstacles. Instead, Jones
worried about the seemingly infinite amount of data required. "There
really was no model for this type of project," he says. "There was no
earlier map that we were trying to improve or update. And the reason
there wasn't another map was because it didn't seem possible."

What the institute needed was someone who could translate its epic
ambition into an efficient production process, in which thousands of
brain slices would be collected and assessed every day. This led Jones
to hire Paul Wohnoutka, a former Boeing engineer with decades of
experience managing complex manufacturing systems. ("I thought a
commercial airliner was the most challenging thing I'd help build," he
says. "I was wrong.") Wohnoutka has an earnest Midwestern demeanor; his
speech quickens with excitement when he starts describing the details of
his assembly line, like the colored barcodes used to classify microscope
slides. His first priority was to standardize everything so that each
slice was put through the exact same process, which he detailed in thick
binders filled with instructions. "Scientists are used to working by
themselves, so they can get pretty suspicious when you start talking
about industrialization," Wohnoutka says. "But all we're really doing
here is applying some basic principles that manufacturing companies
learned decades ago. It only seems strange because we're making science,
not widgets."

In biology, most experiments are done in small batches by postdocs and
grad students. That would never work here. Just consider the technical
difficulty of mapping the entire brain: Each organ must be cut into thin
slices that are measured in microns. These slices—several thousand per
brain—are then immersed in a concentrated RNA solution to probe for a
specific gene. The basic idea is that the RNA will bind to its
complement in the brain cells. (This is made possible by the interwoven
nature of the double helix, with one strand automatically attaching to
the other.) The tissue is then washed with a series of antibodies and
chemicals that attach to the RNA, causing the molecule to become
visible. In the Allen Brain Atlas protocol, the cells containing the RNA
are stained a washed-out violet, the color of spilled wine, with higher
levels of gene expression leading to darker shades. This experimental
method is known as in situ hybridization, and it has been a staple of
bench science for nearly 40 years. But doing it on this scale is utterly
without precedent, possible only because the institute perfected its
high-throughput protocol.

There are no robots on the first floor of the Allen Institute. Instead,
it's dominated by a surprisingly antiquated piece of furniture. It
looks, at first glance, like the card catalog for a vast library—large
cabinets with hundreds of small, meticulously labeled drawers. Opening
one triggers a clattering of glass, the shifting of microscope slides.
Each slide is blank except for what appears to be a greasy fingerprint
in the center. Not until it's held up to the light does the content
become clear: The smudge is actually a sagittal slice of mouse brain.

These slides—there are more than 250,000—provided the raw data for the
mouse brain atlas, the first neural map constructed by the institute.
While the mouse atlas is sometimes described as a mere precursor to the
human version—a way to perfect the protocols and show that the robots
were ready—it's actually been an invaluable resource for gaining insight
into the human brain. After all, natural selection is an inveterate
tinkerer, and every animal brain is made out of the same basic shopping
list of used biological parts. "It might be disconcerting for some
people to think about how much our brain has in common with the brains
of rodents," Jones says, "but that's just how it is."
Traditional methods would have taken decades, but by using assembly-line
robots and new protocols, the Allen Institute expects to finish the
human brain atlas in four years.
Photo: David Clugston


The mice were exquisitely standardized: Only 56-day-old males of the
C57BL/6J strain were used. To keep track of all the samples, the glass
slides were labeled with unique barcodes identifying where in the brain
they came from and which genes they were being tested for. When
scientists want to check a specific slide, they simply whip out a
handheld barcode reader and all the relevant information instantly
appears on a computer screen. If it weren't for this data-management
system, designed by Wohnoutka, the institute would be utterly
overwhelmed by its own experimental results. "The barcodes are just our
version of the lab notebook," Wohnoutka says. "When you have a
million-plus samples, you simply can't write stuff out by hand."

Once the in situ hybridization protocols were tweaked for the Tecan
robots, the gene mapping was relatively straightforward. The mouse atlas
project soon became a matter of efficient repetition, as the factory
floor churned out more than 1,000 slices of mouse brain every 24 hours.

But the flood of data exceeded the ability of scientists to analyze it.
Glass slides started to gather in neglected piles; there were too many
mouse brains and not enough microscopes to study them. "We quickly
realized that you can't industrialize just one part of the system,"
Jones says. "You have to industrialize everything, or else you'll be
stuck with all this information that you can't understand."

So the next challenge was finding a way to digitally photograph every
slide. Given the output of the lab, it was obvious that robotic
microscopes would be required. Unfortunately, no such technology
existed, which meant that the institute had to build its own. The
researchers rigged 10 Leica 600B microscopes with glass-slide loaders,
barcode readers, and small computers running image-analysis software.
The machines are mesmerizing to watch—the lenses constantly zoom in and
out like metal eyes. Every two seconds, a new snapshot of a stained
brain slice enters the atlas. To date, these microscopes have taken more
than 85 million photographs.

The data then travels downstairs to the massive computer room, where
rows of hard drives and CPUs are stacked in metal racks connected by
thick tangles of black wires, like nerve fibers. Two 20-ton air
conditioners make the space sound like a wind tunnel. (When the AC
briefly failed last year, the room went from 68 to 92 degrees Fahrenheit
in less than 20 minutes.) Once an image enters the cluster, an algorithm
quantifies billions of individual neurons and translates them into a
statistical "heat map" of gene expression. This is the heart of the
project, the part that turns the data into something that actually looks
like an atlas.

Michael Hawrylycz, director of informatics at the institute, helped
design the software. Although colleagues often tease Hawrylycz for being
absentminded and messy—the day I met him, he was wearing his T-shirt
inside out and his office was a labyrinth of piles—his innovations have
allowed the atlas project to classify and categorize the astonishing
amount of data. "I make sure scientists can find what they're looking
for," he said, before trying in vain to find a scientific paper that was
lost somewhere on his desk.

At first, Hawrylycz and others assumed that the most common search would
be anatomical—in other words, that scientists would use the atlas to see
which genes were expressed in a particular brain area, like the
hippocampus. However, the unexpected complexity of the brain meant that
such broad searches returned way too much information; the old
boundaries were suddenly useless.

This led Hawrylycz and his team to invent a new set of search tools.
First, they divided the mouse brain into 53,000 voxels, or microscopic
cubes. This enabled scientists to quickly figure out the most important
genes in that bit of brain, since they could see which were most highly
expressed. They could also compare the gene expression patterns of
various voxels to one another. Do you want to know what other brain area
most resembles a particular circuit of layer-5 neurons in the left
cerebral cortex? Just click on the circuit and a colorful map is
superimposed on the mouse brain. The dark red areas represent voxels
that are similar, while navy blue signifies an area expressing a very
different set of genes. (Imagine if Google Maps let you compare any
street in Seattle with every other street in every other city in the
world for thousands of variables and you can begin to understand the
power of such a tool.) "We call it an 'unbiased' spatial search, because
it allows you to look past these old anatomical maps and pull out all
sorts of unexpected correlations," Hawrylycz says. "The goal is to let
people make their own maps."

This means that once the human atlas is complete, a scientist studying
autism or Alzheimer's or human intelligence will be able to quickly
generate a snapshot of the brain that reflects the specific genes
they're interested in.

In January 2007, after four years of high-throughput experiments and
painstaking programming (and a cost of $45 million), the institute
published a Nature paper describing the methods and results of the mouse
atlas. (When the project was completed on time and under budget, the
British medical journal The Lancet compared Allen's venture with his
former Microsoft partner's plan to cure malaria: The headline read "paul
allen 1, bill gates 0.") The entire database was made available for free
online at brain-map.org.

"The atlas has become an essential tool for the field very quickly,"
says Susumu Tonegawa, a Nobel laureate and professor of neuroscience at
MIT. He relies on the maps when creating "knockout" strains of mice—
rodents that are missing a specific set of neural genes. "These are
animals that at first appear normal," Tonegawa says, "but when you look
closer you notice that they have deficits in learning and memory
depending on what you have interfered with." By determining where each
of these deleted genes is expressed in the mouse atlas, Tonegawa can
quickly identify the circuit of cells he erased, which shows him exactly
which parts of the brain were affected by the genetic mutation. "I can
see what is broken," he says, "and that lets me understand how it
works."

One unexpected—even disheartening—aspect of the Allen Institute's effort
is that although its scientists have barely begun their work, early data
sets have already demonstrated that the flesh in our head is far more
complicated than anyone previously imagined.

The brain might look homogenous to the naked eye, but it's actually
filled with an array of cell types, each of which expresses a distinct
set of genes depending on its precise location. Consider the neocortex,
the so-called CPU of the brain: Scientists assumed for decades that most
cortical circuits were essentially the same—the brain was supposed to
rely on a standard set of microchips, like a typical supercomputer. But
the atlas has revealed a startling genetic diversity; different slabs of
cortex are defined by entirely different sets of genes. The
supercomputer analogy needs to be permanently retired.

Or look at the hippocampus, the crescent-shaped center of long-term
memory. Until recently, this small fold of tissue in the middle of the
brain was depicted as neatly divided into four distinct areas. But data
from the atlas has rendered the old maps not only obsolete but flat-out
misleading. Even a single hippocampal area can actually be subdivided
into at least nine discrete regions, each with its own genetic makeup.

Scientists at the institute are just starting to grapple with the
seemingly infinite regress of the brain, in which every new level of
detail reveals yet another level. "You can't help but be intimidated by
the complexity of it all," Jones says. "Just when you think you're
getting a handle on it, you realize that you haven't even scratched the
surface." This is the bleak part of working at the Allen Institute: What
you mostly discover is that the mind remains an immense mystery. We
don't even know what we don't know.

But Jones and others aren't ready to surrender. They remain excited by
the idea of working on the frontier of science, by the possibility that
their maps will allow others to make sense of this still inscrutable
landscape. In other words, they are waiting for the future, for some
scientist to invent an elegant theory that explains their enigmatic
data. Jones likes to compare the current state of neuroscience to
19th-century chemistry. At the time, chemists were strict empiricists;
they set substances on fire and then recorded the colors visible in the
flames. Different chemicals produced different spectrums of light, but
nobody could make sense of the spectrums. The data seemed completely
random. But then, with the discovery of quantum mechanics, scientists
were finally able to explain the colored light—the unique rainbows were
actually side effects of subatomic structure. Such is the faith of
scientists: Nature must always make sense.
The five specially constructed robots at the allen institute can each
process 192 brain slices a day.
Photo: David Clugston


But what if neuroscience isn't like chemistry? The brain, after all, is
a byproduct of evolution, an accumulation of genetic accidents. The data
that looks so arbitrary might actually be arbitrary. If that's the case,
having a precise atlas of the brain won't lead to a unified theory—
because such a thing can't exist.

Occasionally this doubt seeps into conversations about the atlas, as the
scientists wonder aloud whether these 3 pounds of tissue can ever be
understood. "The brain is just details on top of details on top of
details," Hawrylycz says. "You sometimes find yourself asking questions
that don't have answers, like 'Do we really need so many different
combinatorial patterns of genes?' Well, it doesn't matter if we need to
be this way. It's the way we are. The brain doesn't care about making
our job easy."

There are also several unresolved technical problems. For example, the
human brain is 2,000 times larger than the mouse brain, which means that
even the industrialized protocols of the Allen Institute can't generate
all the necessary amounts of data. The scientists are forced to augment
the refined maps of in situ hybridization with cruder techniques, which
provide a measurement of gene expression in particular brain areas but
not at the cellular level.

"The problem with this data," one researcher told me, "is that it's like
grinding up the paint on a Monet canvas and then thinking you understand
the painting." The scientists are stuck in a paradox: When they zoom in
and map the brain at a cellular level, they struggle to make sense of
what they see. But when they zoom out, they lose the necessary
resolution. "We're still trying to find that sweet spot," Jones says.
"What's the most useful way to describe the details of the brain? That's
what we need to figure out."

And then there are the theoretical questions. Although the scientists
are determined to create a universal map of the brain—a generic guide to
its gene expression—such an abstraction doesn't actually exist. There is
no single human brain, just as there is no single human genome. As a
result, the scientists must determine what sort of brains should be
included in the atlas. (These issues are especially important given the
limited supply of available human specimens. While thousands of nearly
identical mice were used to create the mouse atlas, its human
counterpart will be based on fewer than 15 highly distinct individuals.)
When I was at the institute, the scientists were struggling to define
what it meant to be "normal." Is it normal to smoke cigarettes? Is it
normal not to drink alcohol? What about a cortex of someone who has
taken antidepressants? Or spent years in psychoanalysis? Or committed a
violent felony? Is anybody normal? How do you standardize the
individual?

Although the human atlas is years from completion, a theme is beginning
to emerge: Every brain is profoundly unique, a landscape of cells that
has never existed before and never will again. The same gene that will
be highly expressed in some subjects will be completely absent in
others. Important drug targets, like serotonin receptors, will exist in
a disparate set of brain areas depending on the individual. This
variation is even visible at a gross anatomical level—different people
have differently shaped cortices, with different boundaries between
anatomical regions. (This is why, for instance, neurosurgeons have to
painstakingly probe the cortex during surgery.) If the human atlas is
like Google Maps, then every mind is its own city.

"It can seem like there's an infinite number of variables to consider
when you look at the human brain," says Elaine Shen, a manager at the
institute. "We're making a genetic map, but what if the map isn't
detailed enough? Or what if each brain is so different in expression
patterns that we can't make sense of it?" She and her colleagues are
convinced, however, that the only way to solve these unknowns is to look
at the data, to break the brain apart and try to measure everything.
"Once all the data is out there, someone else is going to connect the
dots," Jones says. "All we want to do is make that scientific leap
possible."

Jonah Lehrer(jonah.lehrer at gmail.com) is the author of How We Decide and
Proust Was a Neuroscientist.

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