New Way to Gain a Clear View of the Brain (NYT 11/10/11)
A group of Japanese neuroscientists is trying to peer into the mind — literally. They have devised a way to turn the brain’s opaque gray matter into a glassy, see-through substance.
The group, based at the government-financed Riken Brain Science Institute in Wako, Japan, has created an inexpensive chemical cocktail that transforms dead biological tissue from a colored mass into what looks like translucent jelly. Soaking brain tissue in the solution makes it easier for neuroscientists to see what’s inside, a step they hope will uncover the physical basis of personality traits, memories and even consciousness.
“I’m very excited about the potential,” said Dr. Atsushi Miyawaki, a researcher on the team, which published its discovery in the journal Nature Neuroscience.
The chemical solution — patented under the name Scale, a phonetic approximation of the Japanese word for “transparent” — could help neuroscientists map the brain’s underlying architecture, though that goal is still a distant one. At the moment, researchers are working to build such a map, called a “connectome,” of mouse brains, which are far less complex than human ones.
Ultimately, this mapping could be conducted on brains of different ages, Dr. Miyawaki said, providing a glimpse into how the organ develops and even how genetic differences might affect that development.
Dr. Miyawaki and his team have yet to try Scale on a human brain — their lab works with mice — but they plan to as soon as the gated process of obtaining a specimen is completed. He expects that the transparency solution will work just as well as it does on mouse brains.
Dr. Jeff Lichtman, a neuroscientist at Harvard University who is involved with the Human Connectome Project — a multi-institution effort to map a mouse brain, and then a human one — thinks that Scale shows promise and plans to use it in his lab. It looks like a good method for “clearing the brain,” he said in a telephone interview. “Clear brains,” he said. “That’s the big thing.”
The neurons of the brain are “interconnected in a vast and deeply mysterious network of wires, so there’s a wiring diagram,” Dr. Lichtman said. Scientists have to figure that diagram out before they can understand how information flows through it, he continued. If the brain were clarified using a solution like Scale, researchers could trace big sections of the diagram “all in one sitting,” he said, “and that would be terrific.”
Currently, to see brain tissue under a microscope, neuroscientists have to slice it into slivers about the thickness of a human hair, so that light can pass through. To analyze an entire mouse brain this way — a process that Dr. Lichtman’s lab is attempting, but that is nowhere near finished — the organ needs to be divided into roughly a hundred slices, each of which must be passed under a microscope for a snapshot of its cells.
Not only is the process labor-intensive, but the slices of brain can get distorted, and small bits of tissue can get lost. These hard-to-avoid errors can turn the snapshots into deformed puzzle pieces that can’t easily be fitted together into a wiring diagram.
A mouse brain that has been clarified with Scale, on the other hand, is clear enough without thin-slicing, and could be imaged in three big chunks, avoiding these problems, according to Dr. Miyawaki. Because it clarifies tissue without removing water, the solution sustains genetically introduced cell labels — used to differentiate one neuron from the next — in a wet environment like the one in which they originally evolved. The labels are made of proteins that come from jellyfish and corals.
According to Dr. Miyawaki, Scale works much better on young brains than on older ones, which are filled with more hard connective tissue that doesn’t absorb the solution as readily.
So far, Dr. Miyawaki and his team have used the solution only on dead tissue. The next step, he said, is to come up with a formulation that works on living tissue, though for now that is a distant goal.
Scale is not difficult to make: It is a cheap mixture of urea (found in urine and fertilizer), glycerol and detergent. While he and a colleague hold the patent on it, Dr. Miyawaki included the complete recipe in his recently published article and hopes that labs around the world will start using it for brain mapping.
Neuroscientists can’t answer important questions about the brain until they have a map of the neuronal circuit, Dr. Miyawaki said, adding, “and there are many, many important questions.”
Government Aims to Build A “Data Eye in the Sky”(NYT 11/10/11)
More than 60 years ago, in his “Foundation” series, the science fiction novelist Isaac Asimov invented a new science — psychohistory — that combined mathematics and psychology to predict the future.
Now social scientists are trying to mine the vast resources of the Internet — Web searches and Twitter messages, Facebook and blog posts, the digital location trails generated by billions of cellphones — to do the same thing.
The most optimistic researchers believe that these storehouses of “big data” will for the first time reveal sociological laws of human behavior — enabling them to predict political crises, revolutions and other forms of social and economic instability, just as physicists and chemists can predict natural phenomena.
“This is a significant step forward,” said Thomas Malone, the director of the Center for Collective Intelligence at the Massachusetts Institute of Technology. “We have vastly more detailed and richer kinds of data available as well as predictive algorithms to use, and that makes possible a kind of prediction that would have never been possible before.”
The government is showing interest in the idea. This summer a little-known intelligence agency began seeking ideas from academic social scientists and corporations for ways to automatically scan the Internet in 21 Latin American countries for “big data,” according to a research proposal being circulated by the agency. The three-year experiment, to begin in April, is being financed by the Intelligence Advanced Research Projects Activity, or Iarpa (pronounced eye-AR-puh), part of the office of the director of national intelligence.
The automated data collection system is to focus on patterns of communication, consumption and movement of populations. It will use publicly accessible data, including Web search queries, blog entries, Internet traffic flow, financial market indicators, traffic webcams and changes in Wikipedia entries.
It is intended to be an entirely automated system, a “data eye in the sky” without human intervention, according to the program proposal. The research would not be limited to political and economic events, but would also explore the ability to predict pandemics and other types of widespread contagion, something that has been pursued independently by civilian researchers and by companies like Google.
Some social scientists and advocates of privacy rights are deeply skeptical of the project, saying it evokes queasy memories of Total Information Awareness, a post-9/11 Pentagon program that proposed hunting for potential attackers by identifying patterns in vast collections of public and private data: telephone calling records, e-mail, travel data, visa and passport information, and credit card transactions.
“I have Total Information Awareness flashbacks when things like this happen,” said David Price, an anthropologist at St. Martin’s University in Lacey, Wash., who has written about cooperation between social scientists and intelligence agencies. “On the one hand it’s understandable for a nation-state to want to track things like the outbreak of a pandemic, but I have to wonder about the total automation of this and what productive will come of it.”
Iarpa officials declined to discuss the research program, saying they are prohibited from giving interviews until contract awards are made later this year.
A similar project by their military sister organization, the Defense Advanced Research Projects Agency, or Darpa, aims to automatically identify insurgent social networks in Afghanistan.
In its most recent budget proposal, the defense agency argues that its analysis can expose terrorist cells and other stateless groups by tracking their meetings, rehearsals and sharing of material and money transfers.
So far there have been only scattered examples of the potential of mining social media. Last year HP Labs researchers used Twitter data to accurately predict box office revenues of Hollywood movies. In August, the National Science Foundation approved funds for research in using social media like Twitter and Facebook to assess earthquake damage in real time.
The accessibility and computerization of huge databases has already begun to spur the development of new statistical techniques and new software to manage data sets with trillions of entries or more.
“Big data allows one to move beyond inference and statistical significance and move toward meaningful and accurate analyses,” said Norman Nie, a political scientist who was a pioneering developer of statistical tools for social scientists and who recently formed a new company, Revolution Analytics, to develop software for the analysis of immense data sets.
Some scientists are skeptical. They cite the Pentagon’s ill-fated Project Camelot in the 1960s, which also explored the possibility that social science could predict political and economic events, but was canceled in the face of widespread criticism by scholars.
The project focused on Chile, with the goal of developing methods for anticipating “violent changes” and offering ways of averting possible rebellions. It led to an uproar among social scientists, who argued that the study would compromise their professional ethics.
In recent years, however, academic opposition to military financing of research has faded. Since 2008, a Pentagon project called the Minerva Initiative has paid for an array of studies, including research at Arizona State University into political opponents of radical Muslims and a University of Texas study on the effects of climate change on African political stability.
Social scientists who cooperate with the research agencies contend that, on balance, the new technologies will have a positive effect.
“The result will be much better understanding of what is going on in the world, and how well local governments are handling the situation,” said Sandy Pentland, a computer scientist at the M.I.T. Media Laboratory. “I find this all very hopeful rather than scary, because this is perhaps the first real opportunity for all of humanity to have transparency in government.”
But advocates of privacy rights worry that public data and the related techniques developed in the new Iarpa project will be adapted for clandestine “total information” operations.
“These techniques are double-edged,” said Marc Rotenberg, president of the Electronic Privacy Information Center, a privacy rights group based in Washington. “They can be used as easily against political opponents in the United States as they can against threats from foreign countries.”
And some computer scientists expressed skepticism about efforts to predict political instability with indicators like Web searches.
“I’m hard pressed to say that we are witnessing a revolution,” said Prabhakar Raghavan, the director of Yahoo Labs, who is an information retrieval specialist. He noted that much had been written about predicting flu epidemics by looking at Web searches for “flu,” but noted that the predictions did not improve significantly on what could already be found in data from the Centers for Disease Control and Prevention.
“You can look at search queries and divine that flu is about to break out,” he said, “but what our research has highlighted is that many of these new methods don’t add a huge lift.”
Other researchers are far more optimistic. “There is a huge amount of predictive power in this data,” said Albert-Laszlo Barabasi, a physicist at Northeastern University who specializes in network science. “If I have hourly information about your location, with about 93 percent accuracy I can predict where you are going to be an hour or a day later.”
Still, the ease of acquiring and manipulating huge data sets charting Internet behavior causes many researchers to warn that the data mining technologies may be quickly outrunning the ability of scientists to think through questions of privacy and ethics.
There is also the deeper question of whether it will be possible to discern behavioral laws that match the laws of physical sciences. For Isaac Asimov, the predictive powers of psychohistory worked only when it was possible to measure the human population of an entire galaxy.
This article has been revised to reflect the following correction:
Correction: October 12, 2011
An earlier version of this article misstated the academic affiliation of Albert-Laszlo Barabasi. He is with Northeastern University, not Notre Dame.
ce399 | research archive: (electronic) mind control 
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