Vision Scientists Demonstrate Innovative Learning Method

New research published today in the journal Science suggests it may be possible to use brain technology to learn to play a piano, reduce mental stress or hit a curve ball with little or no conscious effort. It's the kind of thing seen in Hollywood's "Matrix" franchise.

Experiments conducted at Boston University (BU) and ATR Computational Neuroscience Laboratories in Kyoto, Japan, recently demonstrated that through a person's visual cortex, researchers could use decoded functional magnetic resonance imaging (fMRI) to induce brain activity patterns to match a previously known target state and thereby improve performance on visual tasks.

Think of a person watching a computer screen and having his or her brain patterns modified to match those of a high-performing athlete or modified to recuperate from an accident or disease. Though preliminary, researchers say such possibilities may exist in the future.

"Adult early visual areas are sufficiently plastic to cause visual perceptual learning," said lead author and BU neuroscientist Takeo Watanabe of the part of the brain analyzed in the study.

Neuroscientists have found that pictures gradually build up inside a person's brain, appearing first as lines, edges, shapes, colors and motion in early visual areas. The brain then fills in greater detail to make a red ball appear as a red ball, for example.

Researchers studied the early visual areas for their ability to cause improvements in visual performance and learning.

"Some previous research confirmed a correlation between improving visual performance and changes in early visual areas, while other researchers found correlations in higher visual and decision areas," said Watanabe, director of BU's Visual Science Laboratory. "However, none of these studies directly addressed the question of whether early visual areas are sufficiently plastic to cause visual perceptual learning." Until now.

Boston University post-doctoral fellow Kazuhisa Shibata designed and implemented a method using decoded fMRI neurofeedback to induce a particular activation pattern in targeted early visual areas that corresponded to a pattern evoked by a specific visual feature in a brain region of interest. The researchers then tested whether repetitions of the activation pattern caused visual performance improvement on that visual feature.

The result, say researchers, is a novel learning approach sufficient to cause long-lasting improvement in tasks that require visual performance.

What's more, the approached worked even when test subjects were not aware of what they were learning.

"The most surprising thing in this study is that mere inductions of neural activation patterns corresponding to a specific visual feature led to visual performance improvement on the visual feature, without presenting the feature or subjects' awareness of what was to be learned," said Watanabe, who developed the idea for the research project along with Mitsuo Kawato, director of ATR lab and Yuka Sasaki, an assistant in neuroscience at Massachusetts General Hospital.

"We found that subjects were not aware of what was to be learned while behavioral data obtained before and after the neurofeedback training showed that subjects' visual performance improved specifically for the target orientation, which was used in the neurofeedback training," he said.

The finding brings up an inevitable question. Is hypnosis or a type of automated learning a potential outcome of the research?

"In theory, hypnosis or a type of automated learning is a potential outcome," said Kawato. "However, in this study we confirmed the validity of our method only in visual perceptual learning. So we have to test if the method works in other types of learning in the future. At the same time, we have to be careful so that this method is not used in an unethical way."

At present, the decoded neurofeedback method might be used for various types of learning, including memory, motor and rehabilitation.

The National Science Foundation, the National Institutes of Health and the Ministry of Education, Culture, Sports, Science and Technology in Japan supported the research.

-NSF-

NASA Satellites Detect Extensive Drought Impact On Amazon Forests

Steve Cole

Headquarters, Washington                              

 

Ruth Dasso Marlaire

Ames Research Center, Moffett Field, Calif.

 

WASHINGTON -- A new NASA-funded study has revealed widespread reductions in the greenness of Amazon forests caused by last year's record-breaking drought.

"The greenness levels of Amazonian vegetation -- a measure of its health -- decreased dramatically over an area more than three and one-half times the size of Texas," said Liang Xu, the study's lead author from Boston University. "It did not recover to normal levels, even after the drought ended in late October 2010."

The drought sensitivity of Amazon rainforests is a subject of intense study. Computer models predict a changing climate with warmer temperatures and altered rainfall patterns could cause moisture stress leading to rainforests being replaced by grasslands or woody savannas. This would release the carbon stored in rotting wood into the atmosphere, which could accelerate global warming. The United Nations' Intergovernmental Panel on Climate Change has warned similar droughts could be more frequent in the Amazon region in the future.

The comprehensive study was prepared by an international team of scientists using more than a decade's worth of satellite data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM). Analysis of these data produced detailed maps of vegetation greenness declines from the 2010 drought. The study has been accepted for publication in Geophysical Research Letters, a journal of the American Geophysical Union.

The authors first developed maps of drought-affected areas using thresholds of below-average rainfall as a guide. Next, they identified affected vegetation using two different greenness indexes as surrogates for green leaf area and physiological functioning.

The maps show the 2010 drought reduced the greenness of approximately 965,000 square miles of vegetation in the Amazon -- more than four times the area affected by the last severe drought in 2005.

"The MODIS vegetation greenness data suggest a more widespread, severe and long-lasting impact to Amazonian vegetation than what can be inferred based solely on rainfall data," said Arindam Samanta, a co-lead author from Atmospheric and Environmental Research Inc. in Lexington, Mass.

The severity of the 2010 drought also was seen in records of water levels in rivers across the Amazon basin, including the Rio Negro which represents rainfall levels over the entire western Amazon. Water levels started to fall in August 2010, reaching record low levels in late October. Water levels only began to rise with the arrival of rains later that winter.

"Last year was the driest year on record based on 109 years of Rio Negro water level data at the Manaus harbor," said Marcos Costa, co-author from the Federal University in Vicosa, Brazil. "For comparison, the lowest level during the so-called once-in-a-century drought in 2005 was only eighth lowest."

As anecdotal reports of a severe drought began to appear in the news media last summer, the authors started near-real time processing of massive amounts of satellite data. They used a new capability, the NASA Earth Exchange (NEX), built for the NASA Advanced Supercomputer facility at the agency's Ames Research Center in Moffett Field, Calif. NEX is a collaborative supercomputing environment that brings together data, models and computing resources.

With NEX, the study's authors quickly obtained a large-scale view of the impact of the drought on the Amazon forests and were able to complete the analysis by January 2011. Similar reports about the impact of the 2005 drought were published about two years after the fact.

"Timely monitoring of our planet's vegetation with satellites is critical, and with NEX it can be done efficiently to deliver near-real time information, as this study demonstrates," said study co-author Ramakrishna Nemani, a research scientist at Ames. An article about the NEX project appears in this week's issue of Eos, the weekly newspaper of the American Geophysical Union.

For more information about this study and the NEX project, visit https://c3.ndc.nasa.gov/nex/projects/1209/.

For more information about the MODIS sensor and data products, visit http://modis.gsfc.nasa.gov.

For information about the Tropical Rainfall Measuring Mission, visit http://trmm.gsfc.nasa.gov.

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