The 6 Most Important Experiments in the World | DISCOVER Magazine
The 6 Most Important Experiments in the World
From the smartest artificial brain to the first artificial life
The Blue Brain Project
Scientists rely on computer models to understand the toughest concepts in science: the origin of the universe, the behavior of atoms, and the future climate of the planet. Now a computer model is being designed to take on the human brain. Neuroscientist Henry Markram of the Brain Mind Institute at the École Polytechnique Fédérale in Lausanne, Switzerland, has spent the last 15 years painstakingly mapping cells from the living brains of rats so that he can create a neuron-by-neuron simulation of the brain. With assistance from IBM (whose nickname, Big Blue, helped name the project), Markram hopes to have a virtual human brain, with all its 100 billion neurons, functioning by 2015.
Scientists still don’t understand many of the most essential functions of the brain, like memory or the fundamentals of brain disease and treatment. Markram’s model will electronically mirror the real brain’s biological behaviors, imitating mathematically the interactions among individual neurons and the effects of neurotransmitters on those cells. The model will also be adjustable so that it can explore unusual physiology (a higher-functioning left hemisphere, say, or a weakened hippocampus) and environmental changes (like the effects of taking a pharmaceutical). The data can then be interpreted via computer images. “We are building a generic template,” Markram says, “which will allow us to reconstruct a brain according to any specifications.”
To grind through the immense amount of data, IBM has custom-tailored one of its most powerful supercomputers, capable of processing more than 22 trillion operations per second. With this computer, Markram has created a preliminary model of a neocortical column—a set of about 10,000 cells that work together—equivalent to one in the brain of a 2-week-old rat. “We have achieved the ability to build a brain microcircuit, an elementary unit, and now it’s just a matter of scaling up,” he says.
Many of Markram’s colleagues think that he is too ambitious, that a model of billions of neurons, no matter how intricate, cannot tell much about the functions of a real brain. “People think that it is impossible,” he admits. “They believe that we don’t understand enough about the brain to build it.” He counters that mysteries of brain circuitry will be resolved as the project moves forward over the years.
If the Blue Brain team succeeds, scientists will for the first time have a meaningful physical model of the human brain. So could a fully functioning virtual brain have the ability to create thoughts of its own? Markram isn’t counting on it, but he will be watching closely if Blue Brain begins to make its own decisions, providing unique outputs to identical inputs in a way that is beyond chance or chaos theory and achieving something that has never been observed in a computer: consciousness. “Once we build the whole brain,” he says, “if consciousness emerges, we will be able to study it systematically and understand exactly how it emerges.”
The Earthtime Project
About 250 million years ago, some disaster wiped out 90 percent of life on Earth, a cataclysm known as the Permian-Triassic extinction. Around the same time, volcanoes a million times bigger than Mount Saint Helens erupted, spewing enormous clouds of dust and gas into the sky and covering the ground with 2 million square miles of molten lava. Did the volcanic eruptions cause the extinctions? The answer depends on which event occurred first and how long each took—and right now, scientists just don’t know.
Such is the case with most of the big questions about the history of the Earth, says Paul Renne, director of the Berkeley Geochronology Center: “Often, our arguments about causality depend on timing.” That’s why he and hundreds of other scientists around the world have joined Earthtime, a 10-year endeavor to nail down the sequence of past events on Earth by refining scientists’ techniques for measuring deep time. The project was started by Sam Bowring, an expert in geologic time at MIT, and Douglas Erwin, a paleontologist at the National Museum of Natural History, who conceived of Earthtime during a transcontinental flight together a decade ago. “If we really want to understand the history of the Earth, we have to push our dating tools to their limits,” Bowring says.
Over the past 10 years, such tools have become astonishingly accurate and precise. Take radioisotope dating, which scientists do by measuring the relative abundance of certain forms of elements (like potassium-40) called isotopes and then using the known decay rates of those elements to calculate the age of the minerals in which they are found. In the 1970s, scientists using radioisotope dating could pinpoint the age of a 100 million-year-old rock to within a few million years. Today Bowring and others have whittled the uncertainty down to less than 100,000 years.
But a few glitches are preventing scientists from making the most of these improvements. First, separate labs using the same dating techniques employ slightly different materials and methods, leading to different results. This didn’t matter when measurements of deep time were rough. Now that the science is more exact, though, small inconsistencies due to experimental error can spark big disagreements. “It’s when we sharpen our tools that these discrepancies turn up more glaringly,” Renne says.