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Tuesday, August 6th, 2019
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| 11:00a |
How brain cells pick which connections to keep
Brain cells, or neurons, constantly tinker with their circuit connections, a crucial feature that allows the brain to store and process information. While neurons frequently test out new potential partners through transient contacts, only a fraction of fledging junctions, called synapses, are selected to become permanent.
The major criterion for excitatory synapse selection is based on how well they engage in response to experience-driven neural activity, but how such selection is implemented at the molecular level has been unclear. In a new study, MIT neuroscientists have identified the gene and protein, CPG15, that allows experience to tap a synapse as a keeper.
In a series of novel experiments described in Cell Reports, the team at MIT’s Picower Institute for Learning and Memory used multi-spectral, high-resolution two-photon microscopy to literally watch potential synapses come and go in the visual cortex of mice — both in the light, or normal visual experience, and in the darkness, where there is no visual input. By comparing observations made in normal mice and ones engineered to lack CPG15, they were able to show that the protein is required in order for visual experience to facilitate the transition of nascent excitatory synapses to permanence.
Mice engineered to lack CPG15 only exhibit one behavioral deficiency: They learn much more slowly than normal mice, says senior author Elly Nedivi, the William R. (1964) and Linda R. Young Professor of Neuroscience in the Picower Institute and a professor of brain and cognitive sciences at MIT. They need more trials and repetitions to learn associations that other mice can learn quickly. The new study suggests that’s because without CPG15, they must rely on circuits where synapses simply happened to take hold, rather than on a circuit architecture that has been refined by experience for optimal efficiency.
“Learning and memory are really specific manifestations of our brain’s ability in general to constantly adapt and change in response to our environment,” Nedivi says. “It’s not that the circuits aren’t there in mice lacking CPG15, they just don’t have that feature — which is really important — of being optimized through use.”
Watching in light and darkness
The first experiment reported in the paper, led by former MIT postdoc Jaichandar Subramanian, who is now an assistant professor at the University of Kansas, is a contribution to neuroscience in and of itself, Nedivi says. The novel labeling and imaging technologies implemented in the study, she says, allowed tracking key events in synapse formation with unprecedented spatial and temporal resolution. The study resolved the emergence of “dendritic spines,” which are the structural protrusions on which excitatory synapses are formed, and the recruitment of the synaptic scaffold, PSD95, that signals that a synapse is there to stay.
The team tracked specially labeled neurons in the visual cortex of mice after normal visual experience, and after two weeks in darkness. To their surprise, they saw that spines would routinely arise and then typically disappear again at the same rate regardless of whether the mice were in light or darkness. This careful scrutiny of spines confirmed that experience doesn’t matter for spine formation, Nedivi said. That upends a common assumption in the field, which held that experience was necessary for spines to even emerge.
By keeping track of the presence of PSD95 they could confirm that the synapses that became stabilized during normal visual experience were the ones that had accumulated that protein. But the question remained: How does experience drive PSD95 to the synapse? The team hypothesized that CPG15, which is activity dependent and associated with synapse stabilization, does that job.
CPG15 represents experience
To investigate that, they repeated the same light-versus-dark experiences, but this time in mice engineered to lack CPG15. In the normal mice, there was much more PSD95 recruitment during the light phase than during the dark, but in the mice without CPG15, the experience of seeing in the light never made a difference. It was as if CPG15-less mice in the light were like normal mice in the dark.
Later they tried another experiment testing whether the low PSD95 recruitment seen when normal mice were in the dark could be rescued by exogenous expression of CPG15. Indeed, PSD95 recruitment shot up, as if the animals were exposed to visual experience. This showed that CPG15 not only carries the message of experience in the light, it can actually substitute for it in the dark, essentially “tricking” PSD95 into acting as if experience had called upon it.
“This is a very exciting result, because it shows that CPG15 is not just required for experience-dependent synapse selection, but it’s also sufficient,” says Nedivi, “That’s unique in relation to all other molecules that are involved in synaptic plasticity.”
A new model and method
In all, the paper’s data allowed Nedivi to propose a new model of experience-dependent synapse stabilization: Regardless of neural activity or experience, spines emerge with fledgling excitatory synapses and the receptors needed for further development. If activity and experience send CPG15 their way, that draws in PSD95 and the synapse stabilizes. If experience doesn’t involve the synapse, it gets no CPG15, very likely no PSD95, and the spine withers away.
The paper potentially has significance beyond the findings about experience-dependent synapse stabilization, Nedivi says. The method it describes of closely monitoring the growth or withering of spines and synapses amid a manipulation (like knocking out or modifying a gene) allows for a whole raft of studies in which examining how a gene, or a drug, or other factors affect synapses.
“You can apply this to any disease model and use this very sensitive tool for seeing what might be wrong at the synapse,” she says.
In addition to Nedivi and Subramanian, the paper’s other authors are Katrin Michel and Marc Benoit.
The National Institutes of Health and the JPB Foundation provided support for the research. | | 11:35a |
Computer-aided knitting The oldest known knitting item dates back to Egypt in the Middle Ages, by way of a pair of carefully handcrafted socks. Although handmade clothes have occupied our closets for centuries, a recent influx of high-tech knitting machines have changed how we now create our favorite pieces.
These systems, which have made anything from Prada sweaters to Nike shirts, are still far from seamless. Programming machines for designs can be a tedious and complicated ordeal: When you have to specify every single stitch, one mistake can throw off the entire garment.
In a new pair of papers, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have come up with a new approach to streamline the process: a new system and design tool for automating knitted garments.
In one paper, a team created a system called “InverseKnit”, that translates photos of knitted patterns into instructions that are then used with machines to make clothing. An approach like this could let casual users create designs without a memory bank of coding knowledge, and even reconcile issues of efficiency and waste in manufacturing.
“As far as machines and knitting go, this type of system could change accessibility for people looking to be the designers of their own items,'' says Alexandre Kaspar, CSAIL PhD student and lead author on a new paper about the system. “We want to let casual users get access to machines without needed programming expertise, so they can reap the benefits of customization by making use of machine learning for design and manufacturing.”
In another paper, researchers came up with a computer-aided design tool for customizing knitted items. The tool lets non-experts use templates for adjusting patterns and shapes, like adding a triangular pattern to a beanie, or vertical stripes to a sock. You can image users making items customized to their own bodies, while also personalizing for preferred aesthetics.
InverseKnit
Automation has already reshaped the fashion industry as we know it, with potential positive residuals of changing our manufacturing footprint as well.
To get InverseKnit up and running, the team first created a dataset of knitting instructions, and the matching images of those patterns. They then trained their deep neural network on that data to interpret the 2-D knitting instructions from images.
This might look something like giving the system a photo of a glove, and then letting the model produce a set of instructions, where the machine then follows those commands to output the design.
When testing InverseKnit, the team found that it produced accurate instructions 94% of the time.
“Current state-of-the-art computer vision techniques are data-hungry, and they need many examples to model the world effectively,” says Jim McCann, assistant professor in the Carnegie Mellon Robotics Institute. “With InverseKnit, the team collected an immense dataset of knit samples that, for the first time, enables modern computer vision techniques to be used to recognize and parse knitting patterns.”
While the system currently works with a small sample size, the team hopes to expand the sample pool to employ InverseKnit on a larger scale. Currently, the team only used a specific type of acrylic yarn, but they hope to test different materials to make the system more flexible.
A tool for knitting
While there’s been plenty of developments in the field — such as Carnegie Mellon’s automated knitting processes for 3-D meshes — these methods can often be complex and ambiguous. The distortions inherent in 3-D shapes hamper how we understand the positions of the items, and this can be a burden on the designers.
To address this design issue, Kaspar and his colleagues developed a tool called “CADKnit”, which uses 2-D images, CAD software, and photo editing techniques to let casual users customize templates for knitted designs.
The tool lets users design both patterns and shapes in the same interface. With other software systems, you’d likely lose some work on either end when customizing both.
“Whether it’s for the everyday user who wants to mimic a friend’s beanie hat, or a subset of the public who might benefit from using this tool in a manufacturing setting, we’re aiming to make the process more accessible for personal customization,'' says Kaspar.
The team tested the usability of CADKnit by having non-expert users create patterns for their garments and adjust the size and shape. In post-test surveys, the users said they found it easy to manipulate and customize their socks or beanies, successfully fabricating multiple knitted samples. They noted that lace patterns were tricky to design correctly and would benefit from fast realistic simulation.
However the system is only a first step towards full garment customization. The authors found that garments with complicated interfaces between different parts — such as sweaters — didn’t work well with the design tool. The trunk of sweaters and sleeves can be connected in various ways, and the software didn’t yet have a way of describing the whole design space for that.
Furthermore, the current system can only use one yarn for a shape, but the team hopes to improve this by introducing a stack of yarn at each stitch. To enable work with more complex patterns and larger shapes, the researchers plan to use hierarchical data structures that don’t incorporate all stitches, just the necessary ones.
“The impact of 3-D knitting has the potential to be even bigger than that of 3-D printing. Right now, design tools are holding the technology back, which is why this research is so important to the future,” says McCann.
A paper on InverseKnit was presented by Kaspar alongside MIT postdocs Tae-Hyun Oh and Petr Kellnhofer, PhD student Liane Makatura, MIT undergraduate Jacqueline Aslarus, and MIT Professor Wojciech Matusik. It was presented at the International Conference on Machine Learning this past June in Long Beach, California.
A paper on the design tool was led by Kaspar alongside Makatura and Matusik. | | 3:40p |
New insights into bismuth’s character The search for better materials for computers and other electronic devices has focused on a group of materials known as “topological insulators” that have a special property of conducting electricity on the edge of their surfaces like traffic lanes on a highway. This can increase energy efficiency and reduce heat output.
The first experimentally demonstrated topological insulator in 2009 was bismuth-antimony, but only recently did researchers identify pure bismuth as a new type of topological insulator. A group of researchers in Europe and the U.S. provided both experimental evidence and theoretical analysis in a 2018 Nature Physics report.
Now, researchers at MIT along with colleagues in Boston, Singapore, and Taiwan have conducted a theoretical analysis to reveal several more previously unidentified topological properties of bismuth. The team was led by senior authors MIT Associate Professor Liang Fu, MIT Professor Nuh Gedik, Northeastern University Distinguished Professor Arun Bansil, and Research Fellow Hsin Lin at Academica Sinica in Taiwan.
“It’s kind of a hidden topology where people did not know that it can be that way,” says MIT postdoc Su-Yang Xu, a coauthor of the paper published recently in PNAS.
Topology is a mathematical tool that physicists use to study electronic properties by analyzing electrons’ quantum wave functions. The “topological” properties give rise to a high degree of stability in the material and make its electronic structure very robust against minor imperfections in the crystal, such as impurities, or minor distortions of its shape, such as stretching or squeezing.
“Let’s say I have a crystal that has imperfections. Those imperfections, as long as they are not so dramatic, then my electrical property will not change,” Xu explains. “If there is such topology and if the electronic properties are uniquely tied to the topology rather than the shape, then it will be very robust.”
“In this particular compound, unless you somehow apply pressure or something to distort the crystal structure, otherwise this conduction will always be protected,” Xu says.
Since the electrons carrying a certain spin can only move in one direction in these topological materials, they cannot bounce backwards or scatter, which is the behavior that makes silicon- and copper-based electronic devices heat up.
While materials scientists seek to identify materials with fast electrical conduction and low heat output for advanced computers, physicists want to classify the types of topological and other properties that underlie these better-performing materials.
In the new paper, “Topology on a new facet of bismuth,” the authors calculated that bismuth should show a state known as a “Dirac surface state,” which is considered a hallmark of these topological insulators. They found that the crystal is unchanged by a half-circle rotation (180 degrees). This is called a twofold rotational symmetry. Such a twofold rotational symmetry protects the Dirac surface states. If this twofold rotation symmetry of the crystal is disrupted, these surface states lose their topological protection.
Bismuth also features a topological state along certain edges of the crystal where two vertical and horizontal faces meet, called a “hinge” state. To fully realize the desired topological effects in this material, the hinge state and other surface states must be coupled to another electronic phenomenon known as “band inversion” that the theorists’ calculations show also is present in bismuth. They predict that these topological surface states could be confirmed by using an experimental technique known as photoemission spectroscopy.
If electrons flowing through copper are like a school of fish swimming through a lake in summer, electrons flowing across a topological surface are more like ice skaters crossing the lake’s frozen surface in winter. For bismuth, however, in the hinge state, their motion would be more akin to skating on the corner edge of an ice cube.
The researchers also found that in the hinge state, as the electrons move forward, their momentum and another property, called spin — which defines a clockwise or counterclockwise rotation of the electrons — is “locked.” “Their direction of spinning is locked with respect to their direction of motion,” Xu explains.
These additional topological states might help explain why bismuth lets electrons travel through it much farther than most other materials, and why it conducts electricity efficiently with many fewer electrons than materials such as copper.
“If we really want to make these things useful and significantly improve the performance of our transistors, we need to find good topological materials — good in terms of they are easy to make, they are not toxic, and also they are relatively abundant on earth,” Xu suggests. Bismuth, which is an element that is safe for human consumption in the form of remedies to treat heartburn, for example, meets all these requirements.
“This work is a culmination of a decade and a half’s worth of advancement in our understanding of symmetry-protected topological materials,” says David Hsieh, professor of physics at Caltech, who was not involved in this research.
“I think that these theoretical results are robust, and it is simply a matter of experimentally imaging them using techniques like angle-resolved photoemission spectroscopy, which Professor Gedik is an expert in,” Hsieh adds.
Northeastern University Professor Gregory Fiete notes that “Bismuth-based compounds have long played a starring role in topological materials, though bismuth itself was originally believed to be topologically trivial.”
“Now, this team has discovered that pure bismuth is multiply topological, with a pair of surface Dirac cones untethered to any particular momentum value,” says Fiete, who also was not involved in this research. “The possibility to move the Dirac cones through external parameter control may open the way to applications that exploit this feature."
Caltech's Hsieh notes that the new findings add to the number of ways that topologically protected metallic states can be stabilized in materials. “If bismuth can be turned from semimetal into insulator, then isolation of these surface states in electrical transport can be realized, which may be useful for low-power electronics applications,” Hsieh explains.
Also contributing to the bismuth topology paper were MIT postdoc Qiong Ma; Tay-Rong Chang of the Department of Physics, National Cheng Kung University, Taiwan, and the Center for Quantum Frontiers of Research and Technology, Taiwan; Xiaoting Zhou, Department of Physics, National Cheng Kung University, Taiwan; and Chuang-Han Hsu, Centre for Advanced 2D Materials and Graphene Research Centre, National University of Singapore.
This work was partly supported by the Center for Integrated Quantum Materials and the U.S. Department of Energy, Materials Sciences and Engineering division. | | 11:59p |
Astrophysical shock phenomena reproduced in the laboratory Vast interstellar events where clouds of charged matter hurtle into each other and spew out high-energy particles have now been reproduced in the lab with high fidelity. The work, by MIT researchers and an international team of colleagues, should help resolve longstanding disputes over exactly what takes place in these gigantic shocks.
Many of the largest-scale events, such as the expanding bubble of matter hurtling outward from a supernova, involve a phenomenon called collisionless shock. In these interactions, the clouds of gas or plasma are so rarefied that most of the particles involved actually miss each other, but they nevertheless interact electromagnetically or in other ways to produces visible shock waves and filaments. These high-energy events have so far been difficult to reproduce under laboratory conditions that mirror those in an astrophysical setting, leading to disagreements among physicists as to the mechanisms at work in these astrophysical phenomena.
Now, the researchers have succeeded in reproducing critical conditions of these collisionless shocks in the laboratory, allowing for detailed study of the processes taking place within these giant cosmic smashups. The new findings are described in the journal Physical Review Letters, in a paper by MIT Plasma Science and Fusion Center Senior Research Scientist Chikang Li, five others at MIT, and 14 others around the world.
Virtually all visible matter in the universe is in the form of plasma, a kind of soup of subatomic particles where negatively charged electrons swim freely along with positively charged ions instead of being connected to each other in the form of atoms. The sun, the stars, and most clouds of interstellar material are made of plasma.
Most of these interstellar clouds are extremely tenuous, with such low density that true collisions between their constituent particles are rare even when one cloud slams into another at extreme velocities that can be much faster than 1,000 kilometers per second. Nevertheless, the result can be a spectacularly bright shock wave, sometimes showing a great deal of structural detail including long trailing filaments.
Astronomers have found that many changes take place at these shock boundaries, where physical parameters “jump,” Li says. But deciphering the mechanisms taking place in collisionless shocks has been difficult, since the combination of extremely high velocities and low densities has been hard to match on Earth.
While collisionless shocks had been predicted earlier, the first one that was directly identified, in the 1960s, was the bow shock formed by the solar wind, a tenuous stream of particles emanating from the sun, when it hits Earth’s magnetic field. Soon, many such shocks were recognized by astronomers in interstellar space. But in the decades since, “there has been a lot of simulations and theoretical modeling, but a lack of experiments” to understand how the processes work, Li says.
Li and his colleagues found a way to mimic the phenomena in the laboratory by generating a jet of low-density plasma using a set of six powerful laser beams, at the OMEGA laser facility at the University of Rochester, and aiming it at a thin-walled polyimide plastic bag filled with low-density hydrogen gas. The results reproduced many of the detailed instabilities observed in deep space, thus confirming that the conditions match closely enough to allow for detailed, close-up study of these elusive phenomena. A quantity called the mean free path of the plasma particles was measured as being much greater than the widths of the shock waves, Li says, thus meeting the formal definition of a collisionless shock.
At the boundary of the lab-generated collisionless shock, the density of the plasma spiked dramatically. The team was able to measure the detailed effects on both the upstream and downstream sides of the shock front, allowing them to begin to differentiate the mechanisms involved in the transfer of energy between the two clouds, something that physicists have spent years trying to figure out. The results are consistent with one set of predictions based on something called the Fermi mechanism, Li says, but further experiments will be needed to definitively rule out some other mechanisms that have been proposed.
“For the first time we were able to directly measure the structure” of important parts of the collisionless shock, Li says. “People have been pursuing this for several decades.”
The research also showed exactly how much energy is transferred to particles that pass through the shock boundary, which accelerates them to speeds that are a significant fraction of the speed of light, producing what are known as cosmic rays. A better understanding of this mechanism “was the goal of this experiment, and that’s what we measured” Li says, noting that they captured a full spectrum of the energies of the electrons accelerated by the shock.
"This report is the latest installment in a transformative series of experiments, annually reported since 2015, to emulate an actual astrophysical shock wave for comparison with space observations," says Mark Koepke, a professor of physics at West Virginia University and chair of the Omega Laser Facility User Group, who was not involved in the study. "Computer simulations, space observations, and these experiments reinforce the physics interpretations that are advancing our understanding of the particle acceleration mechanisms in play in high-energy-density cosmic events such as gamma-ray-burst-induced outflows of relativistic plasma."
The international team included researchers at the University of Bordeaux in France, the Czech Academy of Sciences, the National Research Nuclear University in Russia, the Russian Academy of Sciences, the University of Rome, the University of Rochester, the University of Paris, Osaka University in Japan, and the University of California at San Diego. It was supported by the U.S. Department of Energy and the French National Research Agency. |
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