Wednesday, November 21st, 2012

Time	Event
5:00a	Ocean currents play a role in predicting extent of Arctic sea ice Each winter, wide swaths of the Arctic Ocean freeze to form sheets of sea ice that spread over millions of square miles. This ice acts as a massive sun visor for the Earth, reflecting solar radiation and shielding the planet from excessive warming. The Arctic ice cover reaches its peak each year in mid-March, before shrinking with warmer spring temperatures. But over the last three decades, this winter ice cap has shrunk: Its annual maximum reached record lows, according to satellite observations, in 2007 and again in 2011. Understanding the processes that drive sea-ice formation and advancement can help scientists predict the future extent of Arctic ice coverage — an essential factor in detecting climate fluctuations and change. But existing models vary in their predictions for how sea ice will evolve. Now researchers at MIT have developed a new method for optimally combining models and observations to accurately simulate the seasonal extent of Arctic sea ice and the ocean circulation beneath. The team applied its synthesis method to produce a simulation of the Labrador Sea, off the southern coast of Greenland, that matched actual satellite and ship-based observations in the area. Through their model, the researchers identified an interaction between sea ice and ocean currents that is important for determining what’s called “sea ice extent” — where, in winter, winds and ocean currents push newly formed ice into warmer waters, growing the ice sheet. Furthermore, springtime ice melt may form a “bath” of fresh seawater more conducive for ice to survive the following winter. Accounting for this feedback phenomenon is an important piece in the puzzle to precisely predict sea-ice extent, says Patrick Heimbach, a principal research scientist in MIT’s Department of Earth, Atmospheric and Planetary Sciences. “Until a few years ago, people thought we might have a seasonal ice-free Arctic by 2050,” Heimbach says. “But recent observations of sustained ice loss make scientists wonder whether this ice-free Arctic might occur much sooner than any models predict … and people want to understand what physical processes are implicated in sea-ice growth and decline.” Heimbach and former MIT graduate student Ian Fenty, now a postdoc at NASA’s Jet Propulsion Laboratory, will publish a paper, "Hydrographic Preconditioning for Seasonal Sea Ice Anomalies in the Labrador Sea," in the Journal of Physical Oceanography. An icy forecast As Arctic temperatures drop each winter, seawater turns to ice — starting as thin, snowflake-like crystals on the ocean surface that gradually accumulate to form larger, pancake-shaped sheets. These ice sheets eventually collide and fuse to create massive ice floes that can span hundreds of miles. When seawater freezes, it leaches salt, which mixes with deeper waters to create a dense, briny ocean layer. The overlying ice is fresh and light in comparison, with very little salt in its composition. As ice melts in the spring, it creates a freshwater layer on the ocean surface, setting up ideal conditions for sea ice to form the following winter. Heimbach and Fenty constructed a model to simulate ice cover, thickness and transport in response to atmospheric and ocean circulation. In a novel approach, they developed a method known in computational science and engineering as “optimal state and parameter estimation” to plug in a variety of observations to improve the simulations. A tight fit The researchers tested their approach on data originally taken in 1996 and 1997 in the Labrador Sea, an arm of the North Atlantic Ocean that lies between Greenland and Canada. They included satellite observations of ice cover, as well as local readings of wind speed, water and air temperature, and water salinity. The approach produced a tight fit between simulated and observed sea-ice and ocean conditions in the Labrador Sea — a large improvement over existing models. The optimal synthesis of model and observations revealed not just where ice forms, but also how ocean currents transport ice floes within and between seasons. From its simulations, the team found that, as new ice forms in northern regions of the Arctic, ocean currents push this ice to the south in a process called advection. The ice migrates further south, into unfrozen waters, where it melts, creating a fresh layer of ocean water that eventually insulates more incoming ice from warmer subsurface waters of subtropical Atlantic origin. Knowing that this model fits with observations suggests to Heimbach that researchers may use the method of model-data synthesis to predict sea-ice growth and transport in the future — a valuable tool for climate scientists, as well as oil and shipping industries. “The Northwest Passage has for centuries been considered a shortcut shipping route between Asia and North America — if it was navigable,” Heimbach says. “But it’s very difficult to predict. You can just change the wind pattern a bit and push ice, and suddenly it’s closed. So it’s a tricky business, and needs to be better understood.” Martin Losch, a research scientist at the Alfred Wegener Institute for Polar and Marine Research in Bremerhaven, Germany, says the feedback mechanism identified by the MIT group is important for predicting sea-ice extent on a regional scale. “The dynamics of climate are complicated and nonlinear, and are due to many different feedback processes,” says Losch, who was not involved with the research. “Identifying these feedbacks and their impact on the system is at the heart of climate research.” As part of the “Estimating the Circulation and Climate of the Ocean” (ECCO) project, Heimbach and his colleagues are now applying their model to larger regions in the Arctic. This research was supported in part by the National Science Foundation and NASA. (Comment on this)
5:00p	Brain waves encode rules for behavior One of the biggest puzzles in neuroscience is how our brains encode thoughts, such as perceptions and memories, at the cellular level. Some evidence suggests that ensembles of neurons represent each unique piece of information, but no one knows just what these ensembles look like, or how they form. A new study from researchers at MIT and Boston University (BU) sheds light on how neural ensembles form thoughts and support the flexibility to change one’s mind. The research team, led by Earl Miller, the Picower Professor of Neuroscience at MIT, identified groups of neurons that encode specific behavioral rules by oscillating in synchrony with each other. The results suggest that the nature of conscious thought may be rhythmic, according to the researchers, who published their findings in the Nov. 21 issue of Neuron. “As we talk, thoughts float in and out of our heads. Those are all ensembles forming and then reconfiguring to something else. It’s been a mystery how the brain does this,” says Miller, who is also a member of MIT’s Picower Institute for Learning and Memory. “That’s the fundamental problem that we’re talking about — the very nature of thought itself.” Rules for behavior The researchers identified two neural ensembles in the brains of monkeys trained to respond to objects based on either their color or orientation. This task requires cognitive flexibility — the ability to switch between two distinct sets of rules for behavior. “Effectively what they’re doing is focusing on some parts of information in the world and ignoring others. Which behavior they’re doing depends on the context,” says Tim Buschman, an MIT postdoc and one of the lead authors of the paper. As the animals switched between tasks, the researchers measured the brain waves produced in different locations throughout the prefrontal cortex, where most planning and thought takes place. Those waves are generated by rhythmic fluctuations of neurons’ electrical activity. When the animals responded to objects based on orientation, the researchers found that certain neurons oscillated at high frequencies that produce so-called beta waves. When color was the required rule, a different ensemble of neurons oscillated in the beta frequency. Some neurons overlapped, belonging to more than one group, but each ensemble had its own distinctive pattern. Interestingly, the researchers also saw oscillations in the low-frequency alpha range among neurons that make up the orientation rule ensemble, but only when the color rule was being applied. The researchers believe that the alpha waves, which have been associated with suppression of brain activity, help to quiet the neurons that trigger the orientation rule. “What this suggests is that orientation was dominant, and color was weaker. The brain was throwing this blast of alpha at the orientation ensemble to shut it up, so the animal could use the weaker ensemble,” Miller says. The findings could explain how the brain can create any appropriate behavioral response to the countless possible combinations of stimuli, rules and required actions, says Pascal Fries, director of the Ernst Strungmann Institute for Neuroscience in Frankfurt, Germany. “We likely compose the appropriate neuronal assembly on the fly through synchronization,” says Fries, who was not part of the research team. “The number of combinatorial possibilities is enormous, just like the number of possible 10-digit telephone numbers is.” Eric Denovellis, a graduate student at Boston University, is also a lead author of the paper. Other authors are Cinira Diogo, a former Picower Institute postdoc, and Daniel Bullock, a professor of cognitive and neural systems at BU. Oscillation as consciousness The researchers are now trying to figure out how these neural ensembles coordinate their activity as the brain switches back and forth between different rules, or thoughts. Some neuroscientists have theorized that deeper brain structures, such as the thalamus, handle this coordination, but no one knows for sure, Miller says. “It’s one of the biggest mysteries of cognition, what controls your thoughts,” he says. This work could also help unravel the neural basis of consciousness. “The most fundamental characteristic of consciousness is its limited capacity. You only can hold a very few thoughts in mind simultaneously,” Miller says. These oscillations may explain why that is: Previous studies have shown that when an animal is holding two thoughts in mind, two different ensembles oscillate in beta frequencies, out of phase with one another. “That immediately suggests why there’s a limited capacity to consciousness: Only so many balls can be kept in the air at the same time, only a limited amount of information can fit into one oscillatory cycle,” Miller says. Disruptions of these oscillations may be involved in neurological disorders such as schizophrenia; studies have shown that patients with schizophrenia have reduced beta oscillations. The research was funded by the National Science Foundation and the National Institute of Mental Health. (Comment on this)

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