Japanese researchers have developed a way to measure heartbeats remotely in real time with as much accuracy as electrocardiographs. (credit: Kyoto University)
The results were published in an open-access paper in the journal IEEE Transactions on Biomedical Engineering.
The researchers say this new approach will allow for developing long-term monitoring and “casual sensing” — taking measurements as people go about their daily activities, without having to attach uncomfortable electrodes or sensors to the patient’s body. People will also be able to monitor their cardio health status themselves.
The remote sensing system transmits and receives radar signals in the 24 GHz band* using “ultra-wideband” (UWB) modulation, which is known for its ability to detect specific signals in a noisy radio-frequency environment. A unique signal analysis algorithm extracts data from radar signals reflected from the body to detect heart rate and heart-rate variability (time derivative). Future use for detection of breathing, body movement, and other data from the body is also possible, the researchers suggest.
* The 24 GHz radar band is also used for new automotive radar sensors in the U.S. and Europe for collision detection, obstacle detection, blind-spot monitoring, and automatic cruise control for cars, including self-driving cars. Speculation: it may be possible to use the new UWB-based technology on semi-automated and fully automated vehicles for detecting and tracking humans and pets in the road in real time, based on heartbeat and other characteristics, and compensating for a subject’s movement. The remote feature also suggests possible future covert use in remote polygraph, airport screening, espionage, and other applications. The authors have been asked to technically comment on these uses.
Abstract of Feature-based Correlation and Topological Similarity for Interbeat Interval Estimation using Ultra-Wideband Radar
The objectives of this paper are to propose a method that can accurately estimate the human heart rate using an ultra-wideband radar system, and to determine the performance of the proposed method through measurements. The proposed method uses the feature points of a radar signal to estimate the heart rate efficiently and accurately. Fourier- and periodicity-based methods are inappropriate for estimation of instantaneous heart rates in real time because heartbeat waveforms are highly variable, even within the beat-to-beat interval. We define six radar waveform features that enable correlation processing to be performed quickly and accurately. In addition, we propose a feature topology signal that is generated from a feature sequence without using amplitude information. This feature topology signal is used to find unreliable feature points, and thus to suppress inaccurate heart rate estimates. Measurements were taken using ultra-wideband radar, while simultaneously performing electro-cardiography measurements in an experiment that was conducted on nine participants. The proposed method achieved an average root-mean-square error in the interbeat interval of 7.17 ms for the nine participants. The results demonstrate the effectiveness and accuracy of the proposed method. The significance of this work for biomedical research is that the proposed method will be useful in the realization of a remote vital signs monitoring system that enables accurate estimation of heart-rate variability, which has been used in various clinical settings for the treatment of conditions such as diabetes and arterial hypertension.
Despite the “Gaian Bottleneck” hypothesis, CSIRO’s Parkes radio telescope will search for alien civilizations as part of the $100 Million Breakthrough Listen project (credit: Wayne England)
The famous Fermi paradox raises the question: why haven’t we detected signs of alien life, despite high estimates of probability, such as observations of planets in the “habitable zone” around a Sun-like star by the Kepler telescope and calculations of hundreds of billions of Earth-like planets in our galaxy that might support life.
“The universe is probably filled with habitable planets, so many scientists think it should be teeming with aliens,” said Aditya Chopra, PhD., lead author on a paper published in Astrobiology. In fact, “early life is fragile, so we believe it rarely evolves quickly enough to survive. Most early planetary environments are unstable. To produce a habitable planet, life forms need to regulate greenhouse gases such as water and carbon dioxide to keep surface temperatures stable.”
The Gaian Bottleneck
For example, about four billion years ago Earth, Venus and Mars may have all been habitable. However, a billion years or so after formation, Venus turned into a hothouse and Mars froze into an icebox, the authors explain. Early microbial life on Venus and Mars, if there was any, failed to stabilize the rapidly changing environment, while life on Earth probably played a leading role in stabilizing the planet’s climate.
The authors name this near-universal early extinction the “Gaian Bottleneck,” which also leads to the prediction that the vast majority of fossils in the universe (found in future meteorites, for example) will be from extinct microbial life, not from multicellular species such as dinosaurs or humanoids that take billions of years to evolve. So far, that’s the case.
Abstract of The Case for a Gaian Bottleneck: The Biology of Habitability
The prerequisites and ingredients for life seem to be abundantly available in the Universe. However, the Universe does not seem to be teeming with life. The most common explanation for this is a low probability for the emergence of life (an emergence bottleneck), notionally due to the intricacies of the molecular recipe. Here, we present an alternative Gaian bottleneck explanation: If life emerges on a planet, it only rarely evolves quickly enough to regulate greenhouse gases and albedo, thereby maintaining surface temperatures compatible with liquid water and habitability. Such a Gaian bottleneck suggests that (i) extinction is the cosmic default for most life that has ever emerged on the surfaces of wet rocky planets in the Universe and (ii) rocky planets need to be inhabited to remain habitable. In the Gaian bottleneck model, the maintenance of planetary habitability is a property more associated with an unusually rapid evolution of biological regulation of surface volatiles than with the luminosity and distance to the host star. Key Words: Life—Habitability—Gaia—Abiogenesis habitable zone (AHZ)—Circumstellar habitable zone (CHZ). Astrobiology 16, 7–22.
The fruit fly’s eye is an intricate pattern of many different specialized cells, and scientists use it as a workhorse to study what goes wrong in human cancer. In a new study of the fly’s eye, Northwestern University researchers have gained insight into how developing cells normally switch to a restricted, or specialized, state and how that process might go wrong in cancer. (credit: Northwestern University)
In a study involving the fruit fly equivalent of an oncogene implicated in many human leukemias, Northwestern University researchers have gained insight into how developing cells normally switch to a restricted, or specialized, state and how that process might go wrong in cancer.
The fruit fly’s eye is an intricate pattern of many different specialized cells, such as light-sensing neurons and cone cells. Because flies share with humans many of the same cancer-causing genes, scientists use the precisely made compound eye of Drosophila melanogaster (the common fruit fly) as a workhorse to study what goes wrong in human cancer.
A multidisciplinary team co-led by biologist Richard W. Carthew and engineer Luís A.N. Amaral studied normal cell behavior in the developing eye. The researchers were surprised to discover that the levels of an important protein called Yan start fluctuating wildly when the cell is switching from a more primitive, stem-like state to a more specialized state. If the levels don’t or can’t fluctuate, the cell doesn’t switch and move forward.
“This mad fluctuation, or noise, happens at the time of cell transition,” said Carthew, professor of molecular biosciences in Northwestern’s Weinberg College of Arts and Sciences. “For the first time, we see there is a brief time period as the developing cell goes from point A to point B. The noise is a state of ‘in between’ and is important for cells to switch to a more specialized state. This limbo might be where normal cells take a cancerous path.”
When the noise “off” switch doesn’t work
The researchers also found that a molecular signal received by a cell receptor called EGFR is important for turning the noise off. If that signal is not received, the cell remains in an uncontrolled state.
By pinpointing this noise and its “off” switch as important points in the normal process of cell differentiation, the Northwestern researchers provide targets for scientists studying how cells can go out of control and transform into cancer cells.
The study was published in an open-access paper and cover story Jan. 14 by the online life sciences and biomedicine journal eLife.
The “noisy” protein the Northwestern researchers studied is called Yan in the fly and Tel-1 in humans. (The protein is a transcription factor.) The Tel-1 protein instructs cells to turn into white blood cells; the gene that produces the protein, oncogene Tel-1, is frequently mutated in leukemia.
The EGFR protein that turns off the noise in flies is called Her-2 in humans. Her-2 is an oncogene that plays an important role in human breast cancer.
“On the surface, flies and humans are very different, but we share a remarkable amount of infrastructure,” said Carthew, a member of the Robert H. Lurie Comprehensive Cancer Center of Northwestern University. “We can use fruit fly genetics to understand how humans work and how things go wrong in cancer and other diseases.”
Fruit fly cells are small and closely packed together, making study of them challenging. Carthew and Amaral’s team of biologists, chemical and biological engineers, computer scientists and chemists together figured out how to identify and analyze thousands and thousands of individual cells in the flies’ eyes.
“In the past, people have built models of regulatory networks that control cell differentiation mostly by genetically perturbing one or two components of the network at a time and then compiling those results into models,” said Amaral, professor of chemical and biological engineering at the McCormick School of Engineering. “We instead measured the retina as it developed and found the unexpected behavior of the key regulatory factors Yan and EGFR.”
Nicolás Peláez, first author of the study and a Ph.D. candidate in interdisciplinary biological sciences working with Amaral and Carthew, built new tools to study this strange feature of noise in developing flies. His methods enabled the researchers to easily measure both the concentration of the Yan protein and its fluctuation (noise).
It takes 15 to 20 hours for a fruit fly cell to go from being an unrestricted cell to a restricted cell, Carthew said. Peláez determined the Yan protein is noisy, or fluctuating, for six to eight of those hours.
“Studying the dynamics of molecules regulating fly-eye patterning can inform us about human disease,” Peláez said. “Using model organisms such as fruit flies will help us understand quantitatively the basic biological principles governing differentiation in complex animals.”
Abstract of Dynamics and heterogeneity of a fate determinant during transition towards cell differentiation
Yan is an ETS-domain transcription factor responsible for maintaining Drosophila eye cells in a multipotent state. Yan is at the core of a regulatory network that determines the time and place in which cells transit from multipotency to one of several differentiated lineages. Using a fluorescent reporter for Yan expression, we observed a biphasic distribution of Yan in multipotent cells, with a rapid inductive phase and slow decay phase. Transitions to various differentiated states occurred over the course of this dynamic process, suggesting that Yan expression level does not strongly determine cell potential. Consistent with this conclusion, perturbing Yan expression by varying gene dosage had no effect on cell fate transitions. However, we observed that as cells transited to differentiation, Yan expression became highly heterogeneous and this heterogeneity was transient. Signals received via the EGF Receptor were necessary for the transience in Yan noise since genetic loss caused sustained noise. Since these signals are essential for eye cells to differentiate, we suggest that dynamic heterogeneity of Yan is a necessary element of the transition process, and cell states are stabilized through noise reduction.
Non-gray circles and their connections represent 80, 70 and 60 percent (from top to bottom) respectively of all outgoing traffic within the sampled section of a cortical region (credit: Indiana University)
A new study, reported in an open-access paper in the journal Neuroscience, shows that 70 percent of all information within cortical regions in the brain passes through only 20 percent of these regions’ neurons.
“The discovery of this small but information-rich subset of neurons within cortical regions suggests this sub-network might play a vital role in communication, learning and memory,” said Sunny Nigam, a Ph.D. candidate in the Indiana University Bloomington College of Arts and Sciences’ Department of Physics, the lead author on the study.
The scientists also report these high-traffic “hub neurons” could play a role in understanding brain health since this sort of highly efficient network — in which a small number of neurons are more essential to brain function — is also more vulnerable to disruption. That’s because relatively small breakages can cause the whole system to “go down.”
“The brain seems to favor efficiency over vulnerability,” said John M. Beggs, associate professor of biophysics in the IU Bloomington Department of Physics, who is senior author on the paper. “In addition to helping us understand how the cortex processes information, this work could shed light on how the brain responds to neurodegenerative diseases that affect the ‘network.’”
If the higher metabolic rates of hub neurons make them more vulnerable, for example, the resulting damage could be particularly harmful in conditions in which neurons are known to die, such as Alzheimer’s disease.
The existence of neurons that carry the majority of information between cortical regions in the brain has been previously reported by Olaf Sporns, Distinguished Professor and Robert H. Shaffer Chair in the IU Bloomington Department of Psychological and Brain Sciences, who is a co-author on the paper. But the new study is the first to show that a similar dynamic exists in communication within cortical regions (or “micro-structures”) of the brain.
It is also the first to measure activity across a particularly large number of neurons in these regions.
To conduct the study, IU scientists recorded small electrical impulses from up to 500 neurons from the somatosensory cortex — the part of the brain responsible for the sense of touch — measuring a surprisingly large volume of traffic across a relatively small area.
As a collaboration across the fields of physics, informatics, neuroscience, and psychological and brain sciences, the IU scientists were able to reveal the flow of both outgoing and incoming information within the living neural network by combining data from extremely high-resolution imaging technology with complex biophysical computer simulations of the brain.
“This is the first study to combine such a large number of neurons with such high temporal resolution,” Nigam said. “As a result, we can actually detect the direction of the communication flowing between neurons, creating a ‘transportation map’ from the connections within the cortex.”
The experiments, conducted in live and tissue samples, were based in rodents. But similar high-traffic zones in the cortex have been shown to exist in more advanced mammals, including primates and adult humans. The IU study is the first to explore the behavior of this region in mammals at the level of individual neurons. The only previous similar experiment was conducted in worms.
Nigam added that understanding how the brain maintains good “air traffic control” between information-rich and information-poor neurons will be the next step in unraveling the mystery of hub neurons. “If we ever want to understand how these types of neurons keep information in our heads flowing smoothly,” he said, “we really need to learn a lot more about how they work together.”
Other authors on the paper are researchers at University of California, Santa Cruz; University of California, Los Angeles; AGH University of Science and Technology, Poland; and Duke-NUS Graduate Medical School, Singapore.
This research was supported by the National Science Foundation; the National Institutes of Health; the Ministry of Education, Culture, Sports, Science and Technology of Japan; and Indiana University.
Abstract of Rich-Club Organization in Effective Connectivity among Cortical Neurons
The performance of complex networks, like the brain, depends on how effectively their elements communicate. Despite the importance of communication, it is virtually unknown how information is transferred in local cortical networks, consisting of hundreds of closely spaced neurons. To address this, it is important to record simultaneously from hundreds of neurons at a spacing that matches typical axonal connection distances, and at a temporal resolution that matches synaptic delays. We used a 512-electrode array (60 μm spacing) to record spontaneous activity at 20 kHz from up to 500 neurons simultaneously in slice cultures of mouse somatosensory cortex for 1 h at a time. We applied a previously validated version of transfer entropy to quantify information transfer. Similar to in vivo reports, we found an approximately lognormal distribution of firing rates. Pairwise information transfer strengths also were nearly lognormally distributed, similar to reports of synaptic strengths. Some neurons transferred and received much more information than others, which is consistent with previous predictions. Neurons with the highest outgoing and incoming information transfer were more strongly connected to each other than chance, thus forming a “rich club.” We found similar results in networks recorded in vivo from rodent cortex, suggesting the generality of these findings. A rich-club structure has been found previously in large-scale human brain networks and is thought to facilitate communication between cortical regions. The discovery of a small, but information-rich, subset of neurons within cortical regions suggests that this population will play a vital role in communication, learning, and memory.
SIGNIFICANCE STATEMENT Many studies have focused on communication networks between cortical brain regions. In contrast, very few studies have examined communication networks within a cortical region. This is the first study to combine such a large number of neurons (several hundred at a time) with such high temporal resolution (so we can know the direction of communication between neurons) for mapping networks within cortex. We found that information was not transferred equally through all neurons. Instead, ∼70% of the information passed through only 20% of the neurons. Network models suggest that this highly concentrated pattern of information transfer would be both efficient and robust to damage. Therefore, this work may help in understanding how the cortex processes information and responds to neurodegenerative diseases.
Conceptual schematic of “micro-tissue engineered neural network” (micro-TENN, left) with neurons (red, bottom end) that extend axons (red lines). The new Micro-TENNs (red vertical lines in the middle of the diagram) soften immediately following insertion to better match the mechanical properties of the native brain tissue (purple). The Micro-TENN constructs emulate long axonal pathways with neuronal clusters at the end(s) to allow for integration with native neurons at superficial and deep targets (right, circle insets). (credit: J P Harris et al./Journal of Neural Engineering)
Penn State scientists have grown improved artificial transplantable artificial axons (brain pathways) in the lab. The new “micro-tissue engineered neural networks” (micro-TENNS) replace broken axon pathways when implanted in the brains of rats.
(Neurons are connected by long fibrous projections known as axons. When these connections are damaged, they have very limited capacity to regenerate — unlike many other cells in the body — thus permanently disrupting the body’s signal transmission and communication structure.)
The new lab-grown axons could one day replace damaged axons in the brains of patients with severe head injuries, strokes, or neurodegenerative diseases and could be safely delivered with minimal disruption to brain tissue, according to new research from Penn Medicine’s department of Neurosurgical Research. Their (literally) pathfinding work is published in an open-access paper in the Journal of Neural Engineering.
Senior author D. Kacy Cullen, PhD, an assistant professor of Neurosurgery and his team, previously reported in a 2015 publication in Tissue Engineering that micro-TENNS could be delivered into the brains of rats. The research team has now developed a new, less-invasive delivery method to minimize the body’s reaction and improve the survival and integration of the neural networks.
Micro-TENN axon fabrication process (credit: J P Harris et al./Journal of Neural Engineering)
The team replaced needles with a molded cylinder of agarose (a sugar) filled with an extracellular matrix (ECM) supporting structure through which axons — and associated neurons — could grow in the cerebral cortex and the thalamus. The new axons maintained their architecture for several weeks and successfully integrated into existing brain structures, softening immediately following insertion to better match the mechanical properties of the native brain tissue.
Cullen and team plan to perfect their processes and further integrate neuroscience and engineering to come up with unique ways to aid patients suffering from brain injury or common neurodegenerative diseases. “Additional research is required to directly test micro-TENN neuron survival and integration for each of these insertion methods,” Cullen said.
“We hope this regenerative medicine strategy will someday enable us to grow individualized neural networks that are tailored for each patient’s specific need,” he said, “ultimately, to replace lost neural circuits and improve brain function.”
Abstract of Advanced biomaterial strategies to transplant preformed micro-tissue engineered neural networks into the brain
Objective. Connectome disruption is a hallmark of many neurological diseases and trauma with no current strategies to restore lost long-distance axonal pathways in the brain. We are creating transplantable micro-tissue engineered neural networks (micro-TENNs), which are preformed constructs consisting of embedded neurons and long axonal tracts to integrate with the nervous system to physically reconstitute lost axonal pathways. Approach. We advanced micro-tissue engineering techniques to generate micro-TENNs consisting of discrete populations of mature primary cerebral cortical neurons spanned by long axonal fascicles encased in miniature hydrogel micro-columns. Further, we improved the biomaterial encasement scheme by adding a thin layer of low viscosity carboxymethylcellulose (CMC) to enable needle-less insertion and rapid softening for mechanical similarity with brain tissue. Main results. The engineered architecture of cortical micro-TENNs facilitated robust neuronal viability and axonal cytoarchitecture to at least 22 days in vitro. Micro-TENNs displayed discrete neuronal populations spanned by long axonal fasciculation throughout the core, thus mimicking the general systems-level anatomy of gray matter—white matter in the brain. Additionally, micro-columns with thin CMC-coating upon mild dehydration were able to withstand a force of 893 ± 457 mN before buckling, whereas a solid agarose cylinder of similar dimensions was predicted to withstand less than 150 μN of force. This thin CMC coating increased the stiffness by three orders of magnitude, enabling needle-less insertion into brain while significantly reducing the footprint of previous needle-based delivery methods to minimize insertion trauma. Significance. Our novel micro-TENNs are the first strategy designed for minimally invasive implantation to facilitate nervous system repair by simultaneously providing neuronal replacement and physical reconstruction of long-distance axon pathways in the brain. The micro-TENN approach may offer the ability to treat several disorders that disrupt the connectome, including Parkinson’s disease, traumatic brain injury, stroke, and brain tumor excision.
Abstract of Rebuilding Brain Circuitry with Living Micro-Tissue Engineered Neural Networks
Prominent neuropathology following trauma, stroke, and various neurodegenerative diseases includes neuronal degeneration as well as loss of long-distance axonal connections. While cell replacement and axonal pathfinding strategies are often explored independently, there is no strategy capable of simultaneously replacing lost neurons and re-establishing long-distance axonal connections in the central nervous system. Accordingly, we have created micro-tissue engineered neural networks (micro-TENNs), which are preformed constructs consisting of long integrated axonal tracts spanning discrete neuronal populations. These living micro-TENNs reconstitute the architecture of long-distance axonal tracts, and thus may serve as an effective substrate for targeted neurosurgical reconstruction of damaged pathways in the brain. Cerebral cortical neurons or dorsal root ganglia neurons were precisely delivered into the tubular constructs, and properties of the hydrogel exterior and extracellular matrix internal column (180–500 μm diameter) were optimized for robust neuronal survival and to promote axonal extensions across the 2.0 cm tube length. The very small diameter permits minimally invasive delivery into the brain. In this study, preformed micro-TENNs were stereotaxically injected into naive rats to bridge deep thalamic structures with the cerebral cortex to assess construct survival and integration. We found that micro-TENN neurons survived at least 1 month and maintained their long axonal architecture along the cortical–thalamic axis. Notably, we also found neurite penetration from micro-TENN neurons into the host cortex, with evidence of synapse formation. These micro-TENNs represent a new strategy to facilitate nervous system repair by recapitulating features of neural pathways to restore or modulate damaged brain circuitry.
Ultrasonic waves form microscopic glass fibers into a pattern of lines, collectively creating a reinforcing microstructure that gives the printed component increased strength. (credit: Tom Llewellyn-Jones, Bruce Drinkwater and Richard Trask)
University of Bristol engineers have developed a new type of 3-D printing that can print strong composite materials.
The new method is based on a modification of an off-the-shelf 3D printer: mounting a switchable, focused laser module and an ultrasonic alignment apparatus.
The method uses ultrasonic waves to position and align millions of microscopic glass fibers to form reinforcement fibers into a framework that gives the material strength. A focused laser beam carriage then cures (hardens) the epoxy resin for printing. The precise orientation of the fibers can be controlled by switching the ultrasonic standing-wave pattern mid-print. The engineers achieved a print speed of 20 millimeters per second, similar to conventional additive layer techniques.
Schematic representation of printer and ultrasonic manipulation rig. (a) Switchable laser module (red) is attached to the print head carriage (gray) and traces out the shape of the printed part. The laser can be deliberately defocused to cure large regions slowly by increasing the height of the laser module. (b) Focused laser beam (blue) cures resin within the cavity of the ultrasonic manipulation device (red). LD=laser diode, P=PMMA, W=Water, PZT=lead zirconate titanate transducers, R=resin. Cross sections of the bundles of glass fibers lying within traps are shown, separated by half a wavelength of the laser light. (credit: Thomas M. Llewellyn-Jones et al./Smart Materials and Structures)
Composite materials are widely used in many high-performance products such as tennis rackets, golf clubs, and airplanes. So this technology should soon enable a much greater range of strong composite materials to be 3-D printed at home and at low cost, the engineers suggest. The method is expected to be useful for a range of smart materials applications, such as printing resin-filled capsules for self-healing materials or piezoelectric particles for energy harvesting.
The study is described in an open-access paper in Smart Materials and Structures.
Matt Sutton, Tom Llewellyn-Jones, Bruce Drinkwater and Richard Trask | The new composite printing process.
Abstract of 3D printed components with ultrasonically arranged microscale structure
This paper shows the first application of in situ manipulation of discontinuous fibrous structure mid-print, within a 3D printed polymeric composite architecture. Currently, rapid prototyping methods (fused filament fabrication, stereolithography) are gaining increasing popularity within the engineering community to build structural components. Unfortunately, the full potential of these components is limited by the mechanical properties of the materials used. The aim of this study is to create and demonstrate a novel method to instantaneously orient micro-scale glass fibres within a selectively cured photocurable resin system, using ultrasonic forces to align the fibres in the desired 3D architecture. To achieve this we have mounted a switchable, focused laser module on the carriage of a three-axis 3D printing stage, above an in-house ultrasonic alignment rig containing a mixture of photocurable resin and discontinuous 14 μm diameter glass fibre reinforcement (50 μm length). In our study, a suitable print speed of 20 mm s−1 was used, which is comparable to conventional additive layer techniques. We show the ability to construct in-plane orthogonally aligned sections printed side by side, where the precise orientation of the configurations is controlled by switching the ultrasonic standing wave profile mid-print. This approach permits the realisation of complex fibrous architectures within a 3D printed landscape. The versatile nature of the ultrasonic manipulation technique also permits a wide range of particle types (diameters, aspect ratios and functions) and architectures (in-plane, and out-plane) to be patterned, leading to the creation of a new generation of fibrous reinforced composites for 3D printing.
Binghamton University researchers have developed Nyami, a synthesizable graphics processor unit (GPU) architectural model for general-purpose and graphics-specific workloads, and have run a series of experiments on it to see how different hardware and software configurations would affect the circuit’s performance.
Binghamton University computer science assistant professor Timothy Miller said the results will help other scientists make their own GPUs and “push computing power to the next level.”
GPUs are typically found on commercial video or graphics cards inside of a computer or gaming console. The specialized circuits have computing power designed to make images appear smoother and more vibrant on a screen. There has recently been a movement to see if the chip can also be applied to non-graphical computations, such as algorithms processing large chunks of data.
GPU programming model “unfamiliar”
Maxwell, Nvidia’s most powerful GPU architecture (credit: Nvidia)
“In terms of performance per Watt and performance per cubic meter, GPUs can outperform CPUs by orders of magnitude on many important workloads,” the researchers note in an open-access paper by Miller and other authors in International Symposium on Performance Analysis of Systems and Software (Jeff Bush, the director of software engineering at Roku, was lead author).
“The adoption of GPUs into HPC [high-performance computing] has therefore been both a major boost in performance and a shift in how supercomputers are programmed. Unfortunately, this shift has suffered slow adoption because the GPU programming model is unfamiliar to those who are accustomed to writing software for traditional CPUs.”
This slow adoption was a result of GPU manufacturers’ decision to keep their chip specifications secret, said Miller. “That prevented open source developers from writing software that could utilize that hardware. Nyami makes it easier for other researchers to conduct experiments of their own, because they don’t have to reinvent the wheel. With contributions from the ‘open hardware’ community, we can incorporate more creative ideas and produce an increasingly better tool.
“The ramifications of the findings could make processors easier for researchers to work with and explore different design tradeoffs. We can also use [Nyami] as a platform for conducting research that isn’t GPU-specific, like energy efficiency and reliability,” he added.
Abstract of Nyami: a synthesizable GPU architectural model for general-purpose and graphics-specific workloads
Graphics processing units (GPUs) continue to grow in popularity for general-purpose, highly parallel, high-throughput systems. This has forced GPU vendors to increase their focus on general purpose workloads, sometimes at the expense of the graphics-specific workloads. Using GPUs for general-purpose computation is a departure from the driving forces behind programmable GPUs that were focused on a narrow subset of graphics rendering operations. Rather than focus on purely graphics-related or general-purpose use, we have designed and modeled an architecture that optimizes for both simultaneously to efficiently handle all GPU workloads. In this paper, we present Nyami, a co-optimized GPU architecture and simulation model with an open-source implementation written in Verilog. This approach allows us to more easily explore the GPU design space in a synthesizable, cycle-precise, modular environment. An instruction-precise functional simulator is provided for co-simulation and verification. Overall, we assume a GPU may be used as a general-purpose GPU (GPGPU) or a graphics engine and account for this in the architecture’s construction and in the options and modules selectable for synthesis and simulation. To demonstrate Nyami’s viability as a GPU research platform, we exploit its flexibility and modularity to explore the impact of a set of architectural decisions. These include sensitivity to cache size and associativity, barrel and switch-on-stall multithreaded instruction scheduling, and software vs. hardware implementations of rasterization. Through these experiments, we gain insight into commonly accepted GPU architecture decisions, adapt the architecture accordingly, and give examples of the intended use as a GPU research tool.
In a computational reconstruction of brain tissue in the hippocampus, Salk and UT-Austin scientists found the unusual occurrence of two synapses from the axon of one neuron (translucent black strip) forming onto two spines on the same dendrite of a second neuron (yellow). Separate terminals from one neuron’s axon are shown in synaptic contact with two spines (arrows) on the same dendrite of a second neuron in the hippocampus. The spine head volumes, synaptic contact areas (red), neck diameters (gray) and number of presynaptic vesicles (white spheres) of these two synapses are almost identical. (credit: Salk Institute)
Salk researchers and collaborators have achieved critical insight into the size of neural connections, putting the memory capacity of the brain far higher than common estimates. The new work also answers a longstanding question as to how the brain is so energy efficient, and could help engineers build computers that are incredibly powerful but also conserve energy.
“This is a real bombshell in the field of neuroscience,” says Terry Sejnowski, Salk professor and co-senior author of the paper, which was published in eLife. “We discovered the key to unlocking the design principle for how hippocampal neurons function with low energy but high computation power. Our new measurements of the brain’s memory capacity increase conservative estimates by a factor of 10 to at least a petabyte (1 quadrillion or 1015 bytes), in the same ballpark as the World Wide Web.”
“When we first reconstructed every dendrite, axon, glial process, and synapse* from a volume of hippocampus the size of a single red blood cell, we were somewhat bewildered by the complexity and diversity amongst the synapses,” says Kristen Harris, co-senior author of the work and professor of neuroscience at the University of Texas, Austin. “While I had hoped to learn fundamental principles about how the brain is organized from these detailed reconstructions, I have been truly amazed at the precision obtained in the analyses of this report.”
10 times more discrete sizes of synapses discovered
The Salk team, while building a 3D reconstruction of rat hippocampus tissue (the memory center of the brain), noticed something unusual. In some cases, a single axon from one neuron formed two synapses reaching out to a single dendrite of a second neuron, signifying that the first neuron seemed to be sending a duplicate message to the receiving neuron.
At first, the researchers didn’t think much of this duplicity, which occurs about 10 percent of the time in the hippocampus. But Tom Bartol, a Salk staff scientist, had an idea: if they could measure the difference between two very similar synapses such as these, they might glean insight into synaptic sizes, which so far had only been classified in the field as small, medium and large.
To do this, researchers used advanced microscopy and computational algorithms they had developed to image rat brains and reconstruct the connectivity, shapes, volumes and surface area of the brain tissue down to a nanomolecular level.
The scientists expected the synapses would be roughly similar in size, but were surprised to discover the synapses were nearly identical.
Salk scientists computationally reconstructed brain tissue in the hippocampus to study the sizes of connections (synapses). The larger the synapse, the more likely the neuron will send a signal to a neighboring neuron. The team found that there are actually 26 discrete sizes that can change over a span of a few minutes, meaning that the brain has a far great capacity at storing information than previously thought. Pictured here is a synapse between an axon (green) and dendrite (yellow). (credit: Salk Institute)
“We were amazed to find that the difference in the sizes of the pairs of synapses were very small, on average, only about eight percent different in size. No one thought it would be such a small difference. This was a curveball from nature,” says Bartol.
Because the memory capacity of neurons is dependent upon synapse size, this eight percent difference turned out to be a key number the team could then plug into their algorithmic models of the brain to measure how much information could potentially be stored in synaptic connections.
It was known before that the range in sizes between the smallest and largest synapses was a factor of 60 and that most are small.
But armed with the knowledge that synapses of all sizes could vary in increments as little as eight percent between sizes within a factor of 60, the team determined there could be about 26 categories of sizes of synapses, rather than just a few.
“Our data suggests there are 10 times more discrete sizes of synapses than previously thought,” says Bartol. In computer terms, 26 sizes of synapses correspond to about 4.7 “bits” of information. Previously, it was thought that the brain was capable of just one to two bits for short and long memory storage in the hippocampus.
“This is roughly an order of magnitude of precision more than anyone has ever imagined,” says Sejnowski.
What makes this precision puzzling is that hippocampal synapses are notoriously unreliable. When a signal travels from one neuron to another, it typically activates that second neuron only 10 to 20 percent of the time.
“We had often wondered how the remarkable precision of the brain can come out of such unreliable synapses,” says Bartol. One answer, it seems, is in the constant adjustment of synapses, averaging out their success and failure rates over time. The team used their new data and a statistical model to find out how many signals it would take a pair of synapses to get to that eight percent difference.
The researchers calculated that for the smallest synapses, about 1,500 events cause a change in their size/ability (20 minutes) and for the largest synapses, only a couple hundred signaling events (1 to 2 minutes) cause a change.
“This means that every 2 or 20 minutes, your synapses are going up or down to the next size. The synapses are adjusting themselves according to the signals they receive,” says Bartol.
“Our prior work had hinted at the possibility that spines and axons that synapse together would be similar in size, but the reality of the precision is truly remarkable and lays the foundation for whole new ways to think about brains and computers,” says Harris. “The work resulting from this collaboration has opened a new chapter in the search for learning and memory mechanisms.” Harris adds that the findings suggest more questions to explore, for example, if similar rules apply for synapses in other regions of the brain and how those rules differ during development and as synapses change during the initial stages of learning.
“The implications of what we found are far-reaching,” adds Sejnowski. “Hidden under the apparent chaos and messiness of the brain is an underlying precision to the size and shapes of synapses that was hidden from us.”
A model for energy-efficient computers
The findings also offer a valuable explanation for the brain’s surprising efficiency. The waking adult brain generates only about 20 watts of continuous power—as much as a very dim light bulb. The Salk discovery could help computer scientists build powerful and ultraprecise, but energy-efficient, computers, particularly ones that employ “deep learning” and artificial neural nets—techniques capable of sophisticated learning and analysis, such as speech, object recognition and translation.
“This trick of the brain absolutely points to a way to design better computers,” says Sejnowski. “Using probabilistic transmission turns out to be as accurate and require much less energy for both computers and brains.”
Other authors on the paper were Cailey Bromer of the Salk Institute; Justin Kinney of the McGovern Institute for Brain Research; and Michael A. Chirillo and Jennifer N. Bourne of the University of Texas, Austin.
* Our memories and thoughts are the result of patterns of electrical and chemical activity in the brain. A key part of the activity happens when branches of neurons, much like electrical wire, interact at certain junctions, known as synapses. An output ‘wire’ (an axon) from one neuron connects to an input ‘wire’ (a dendrite) of a second neuron. Signals travel across the synapse as chemicals called neurotransmitters to tell the receiving neuron whether to convey an electrical signal to other neurons. Each neuron can have thousands of these synapses with thousands of other neurons. Synapses are still a mystery, though their dysfunction can cause a range of neurological diseases. Larger synapses — with more surface area and vesicles of neurotransmitters — are stronger, making them more likely to activate their surrounding neurons than medium or small synapses.
UPDATE 1/22/2016 “in the same ballpark as the World Wide Web” removed; appears to be inaccurate. The Internet Archive, a subset of the Web, currently stores 50 petabytes, for example.
Salk Institute | Salk scientists computationally reconstructed brain tissue in the hippocampus to study the sizes of connections (synapses). The larger the synapse, the more likely the neuron will send a signal to a neighboring neuron. The team found that there are actually 26 discrete sizes that can change over a span of a few minutes, meaning that the brain has a far great capacity at storing information than previous
Abstract of Nanoconnectomic upper bound on the variability of synaptic plasticity
Information in a computer is quantified by the number of bits that can be stored and recovered. An important question about the brain is how much information can be stored at a synapse through synaptic plasticity, which depends on the history of probabilistic synaptic activity. The strong correlation between size and efficacy of a synapse allowed us to estimate the variability of synaptic plasticity. In an EM reconstruction of hippocampal neuropil we found single axons making two or more synaptic contacts onto the same dendrites, having shared histories of presynaptic and postsynaptic activity. The spine heads and neck diameters, but not neck lengths, of these pairs were nearly identical in size. We found that there is a minimum of 26 distinguishable synaptic strengths, corresponding to storing 4.7 bits of information at each synapse. Because of stochastic variability of synaptic activation the observed precision requires averaging activity over several minutes.
NIST concept for DNA sequencing through a graphene nanopore (credit: Smolyanitsky/NIST)
Researchers at the National Institute of Standards and Technology (NIST) have simulated a new concept for rapid, accurate gene sequencing by pulling a DNA molecule through a tiny chemically activated hole in graphene—an ultrathin sheet of carbon atoms—and detecting changes in electrical current.
The NIST simulation study suggests the method could identify about 66 million bases per second with 90 percent accuracy and no false positives. If demonstrated experimentally, the NIST method might ultimately be faster and cheaper than conventional DNA sequencing, meeting a critical need for applications such as forensics.
Nanopore sequencing improved
Conventional sequencing, developed in the 1970s, involves separating, copying, labeling and reassembling pieces of DNA to read the genetic information. The new NIST proposal is a twist on the more recent “nanopore sequencing” idea of pulling DNA through a hole in specific materials, originally a protein (see “First full genome of a living organism sequenced and assembled using smartphone-size device“).
Oxford Nanopore | Nanopore DNA sequencing
This concept—pioneered 20 years ago at NIST—is based on the passage of electrically charged particles (ions) through the pore. The idea remains popular but poses challenges such as unwanted electrical noise, or interference, and inadequate selectivity.
The graphene advantage
By contrast, NIST’s new proposal is to create temporary chemical bonds and rely on graphene’s capability to convert the mechanical strains (rather than charged particles) from breaking those bonds into measurable blips in electrical current.
“This is essentially a tiny strain sensor,” says NIST theorist Alex Smolyanitsky, who came up with the idea and led the project. “We did not invent a complete technology. We outlined a new physical principle that can potentially be far superior to anything else out there.”
Graphene is popular in nanopore-sequencing proposals due to its electrical properties and miniaturized thin-film structure. In the new NIST method, a graphene nanoribbon (4.5 by 15.5 nanometers) has several copies of a base attached to the nanopore (2.5 nm wide). DNA’s genetic code is built from four kinds of bases, which bond in pairs as cytosine–guanine and thymine–adenine.
In simulations of how the sensor would perform at room temperature in water, cytosine is attached to the nanopore to detect guanine. A single-strand (unzipped) DNA molecule is pulled through the pore. When guanine passes by, hydrogen bonds form with the cytosine. As the DNA continues moving, the graphene is yanked and then slips back into position as the bonds break.
An atomistic model of a graphene nanoribbon with cytosine-functionalized nanopore (a), periodic single-strand DNA (b), and the complete simulated assembly immersed in water (c) (credit: Eugene Paulechka et al./Nanoscale)
The NIST study focused on how this strain affects graphene’s electronic properties and found that temporary changes in electrical current indeed indicate that a target base has just passed by. To detect all four bases, four graphene ribbons, each with a different base inserted in the pore, could be stacked vertically to create an integrated DNA sensor.
The researchers combined simulated data with theory to estimate levels of measurable signal variations. Signal strength was in the milliampere range, stronger than in the earlier ion-current nanopore methods. Based on the performance of 90 percent accuracy without any false positives (i.e., errors were due to missed bases rather than wrong ones), the researchers suggest that four independent measurements of the same DNA strand would produce 99.99 percent accuracy, as required for sequencing the human genome.
The study authors concluded that the proposed method shows “significant promise for realistic DNA sensing devices” without the need for advanced data processing, microscopes, or highly restricted operating conditions. Other than attaching bases to the nanopore, all sensor components have been demonstrated experimentally by other research groups. Theoretical analysis suggests that basic electronic filtering methods could isolate the useful electrical signals. The proposed method could also be used with other strain-sensitive membranes, such as molybdenum disulfide.
About half of the simulations were performed by a co-author at the University of Groningen in the Netherlands. The rest were done at NIST.
T.A. Wassenaar/Univ. Groningen; A.F. Kazakov and A. Smolyanitsky/NIST | Molecular dynamics simulation of DNA sequencing through a graphene nanopore. Cytosine molecules (white) linked to nanopore detect guanine (green) in vertical DNA strand. Inset shows graphene deflection over time.
Abstract of Nucleobase-functionalized graphene nanoribbons for accurate high-speed DNA sequencing
We propose a water-immersed nucleobase-functionalized suspended graphene nanoribbon as an intrinsically selective device for nucleotide detection. The proposed sensing method combines Watson–Crick selective base pairing with graphene’s capacity for converting anisotropic lattice strain to changes in an electrical current at the nanoscale. Using detailed atomistic molecular dynamics (MD) simulations, we study sensor operation at ambient conditions. We combine simulated data with theoretical arguments to estimate the levels of measurable electrical signal variation in response to strains and determine that the proposed sensing mechanism shows significant promise for realistic DNA sensing devices without the need for advanced data processing, or highly restrictive operational conditions.
Artist’s rendering of bioresorbable implanted brain sensor (top left) connected via biodegradable wires to external wireless transmitter (ring, top right) for monitoring a rat’s brain (red) (credit: Graphic by Julie McMahon)
Researchers at University of Illinois at Urbana-Champaign and Washington University School of Medicine in St. Louis have developed a new class of small, thin electronic sensors that can monitor temperature and pressure within the skull — crucial health parameters after a brain injury or surgery* — then melt away when they are no longer needed, eliminating the need for additional surgery to remove the monitors and reducing the risk of infection and hemorrhage.
Similar sensors could be adapted for postoperative monitoring in other body systems as well, the researchers say.
John A. Rogers, a professor of materials science and engineering at the at the U. of I. at Urbana-Champaign, and Wilson Ray, a professor of neurological surgery at Washington University, published their work in the journal Nature.
After a traumatic brain injury or brain surgery, it’s crucial to monitor the patient for swelling and pressure on the brain. Current monitoring technology is bulky and invasive, Rogers said, and the wires restrict the patent’s movement and hamper physical therapy as they recover. Because they require continuous, hard-wired access into the head, such implants also carry the risk of allergic reactions, infection and hemorrhage, and even could exacerbate the inflammation they are meant to monitor.
Bioresorbable materials
“If you simply could throw out all the conventional hardware and replace it with very tiny, fully implantable sensors capable of the same function, constructed out of bioresorbable materials in a way that also eliminates or greatly miniaturizes the wires, then you could remove a lot of the risk and achieve better patient outcomes,” Rogers said. ”We were able to demonstrate all of these key features in animal models, with a measurement precision that’s just as good as that of conventional devices.”
Schematic illustration of a biodegradable pressure sensor. The inset shows the location of the silicon-nanomembrane (Si-NM) strain gauge. (credit: Seung-Kyun Kang et al./Nature)
The new devices incorporate dissolvable silicon technology developed by Rogers’ group at the U. of I. The sensors, smaller than a grain of rice, are built on extremely thin sheets of nanoporous silicon — which are naturally biodegradable. The sheets are configured to function normally for a few weeks, then dissolve away, completely and harmlessly, in the body’s own fluids (via hydrolysis and/or metabolic action).
The silicon platforms are also sensitive to clinically relevant pressure levels in the intracranial fluid surrounding the brain.
The researchers added a tiny temperature sensor and connected it to a wireless transmitter roughly the size of a postage stamp, implanted under the skin but on top of the skull.
Tiny pressure and temperature sensor (bottom right) connects via bioresorbable molybdenum wires (2-micrometers in diameter) to a penny-size wireless transmitter externally mounted on top of the skull. (image credit: John A. Rogers)
The Illinois group worked with clinical experts in traumatic brain injury at Washington University to implant the sensors in rats, testing for performance and biocompatibility. They found that the temperature and pressure readings from the dissolvable sensors matched conventional monitoring devices for accuracy.
“The ultimate strategy is to have a device that you can place in the brain — or in other organs in the body — that is entirely implanted, intimately connected with the organ you want to monitor and can transmit signals wirelessly to provide information on the health of that organ, allowing doctors to intervene if necessary to prevent bigger problems,” said Rory Murphy, a neurosurgeon at Washington University and co-author of the paper.
“After the critical period that you actually want to monitor, it will dissolve away and disappear.”
Embedding drug-delivery and electrical-stimulator devices
The researchers are moving toward human trials for this technology, as well as extending its functionality for other biomedical applications.
“We have established a range of device variations, materials, and measurement capabilities for sensing in other clinical contexts,” Rogers said. “In the near future, we believe that it will be possible to embed therapeutic function, such as electrical stimulation or drug delivery, into the same systems while retaining the essential bioresorbable character.”
The National Institutes of Health, the Defense Advanced Research Projects Agency and the Howard Hughes Medical Institute supported this work. Rogers and Braun are affiliated with the Beckman Institute for Advanced Science and Technology at the U. of I.
* About 50,000 people die of traumatic brain injuries annually in the U.S. When patients with such injuries arrive in the hospital, doctors must be able to accurately measure intracranial pressure in the brain and inside the skull because an increase in pressure can lead to further brain injury, and there is no way to reliably estimate pressure levels from brain scans or clinical features in patients.
Abstract of Bioresorbable silicon electronic sensors for the brain
Many procedures in modern clinical medicine rely on the use of electronic implants in treating conditions that range from acute coronary events to traumatic injury. However, standard permanent electronic hardware acts as a nidus for infection: bacteria form biofilms along percutaneous wires, or seed haematogenously, with the potential to migrate within the body and to provoke immune-mediated pathological tissue reactions. The associated surgical retrieval procedures, meanwhile, subject patients to the distress associated with re-operation and expose them to additional complications. Here, we report materials, device architectures, integration strategies, and in vivo demonstrations in rats of implantable, multifunctional silicon sensors for the brain, for which all of the constituent materials naturally resorb via hydrolysis and/or metabolic action, eliminating the need for extraction. Continuous monitoring of intracranial pressure and temperature illustrates functionality essential to the treatment of traumatic brain injury; the measurement performance of our resorbable devices compares favourably with that of non-resorbable clinical standards. In our experiments, insulated percutaneous wires connect to an externally mounted, miniaturized wireless potentiostat for data transmission. In a separate set-up, we connect a sensor to an implanted (but only partially resorbable) data-communication system, proving the principle that there is no need for any percutaneous wiring. The devices can be adapted to sense fluid flow, motion, pH or thermal characteristics, in formats that are compatible with the body’s abdomen and extremities, as well as the deep brain, suggesting that the sensors might meet many needs in clinical medicine.
