Though the technology for brain-computer interfaces (or BCI’s) has existed for decades, recent strides have been made to create BCI devices which are safer, smaller, and more effective. Konrad Kording, Nathan Francis Mossell University Professor in Bioengineering, Neuroscience, and Computer and Information Science, helps to elucidate the potential future of this technology in a recent feature in Wired. In the article, he discusses the “invasive” aspects of previous BCI technology, in contrast to recent innovations, such as a new device by Synchron, which do not require surgery and are consequently much less risky:
“The device, called a Stentrode, has a mesh-like design and is about the length of a AAA battery. It is implanted endovascularly, meaning it’s placed into a blood vessel in the brain, in the region known as the motor cortex, which controls movement. Insertion involves cutting into the jugular vein in the neck, snaking a catheter in, and feeding the device through it all the way up into the brain, where, when the catheter is removed, it opens up like a flower and nestles itself into the blood vessel’s wall. Most neurosurgeons are already up to speed on the basic approach required to put it in, which reduces a high-risk surgery to a procedure that could send the patient home the very same day. ‘And that is the big innovation,” Kording says.
DNA Microscopy Gives a Better Look at Cell and Tissue Organization
A new technique that researchers from the Broad Institute of MIT and Harvard University are calling DNA microscopy could help map cells for better understanding of genetic and molecular complexities. Joshua Weinstein, Ph.D., a postdoctoral associate at the Broad Institute, who is also an alumnus of Penn’s Physics and Biophysics department and former student in Penn Bioengineering Professor Ravi Radhakrishnan’s lab, is the first author of this paper on optics-free imaging published in Cell.
The primary goal of the study was to find a way of improving analysis of the spatial organization of cells and tissues in terms of their molecules like DNA and RNA. The DNA microscopy method that Weinstein and his team designed involves first tagging DNA, and allowing the DNA to replicate with those tags, which eventually creates a cloud of sorts that diffuses throughout the cell. The DNA tags subsequent interactions with molecules throughout the cell allowed Weinstein and his team to calculate the locations of those molecules within the cell using basic lab equipment. While the researchers on this project focused their application of DNA microscopy on tracking human cancer cells through RNA tags, this new method opens the door to future study of any condition in which the organization of cells is important.
Penn Engineers Demonstrate Superstrong, Reversible Adhesive that Works like Snail Slime
If you’ve ever pressed a picture-hanging strip onto the wall only to realize it’s slightly off-center, you know the disappointment behind adhesion as we typically experience it: it may be strong, but it’s mostly irreversible. While you can un-stick the used strip from the wall, you can’t turn its stickiness back on to adjust its placement; you have to start over with a new strip or tolerate your mistake. Beyond its relevance to interior decorating, durable, reversible adhesion could allow for reusable envelopes, gravity-defying boots, and more heavy-duty industrial applications like car assembly.
Such adhesion has eluded scientists for years but is naturally found in snail slime. A snail’s epiphragm — a slimy layer of moisture that can harden to protect its body from dryness — allows the snail to cement itself in place for long periods of time, making it the ultimate model in adhesion that can be switched on and off as needed. In a new study, Penn Engineers demonstrate a strong, reversible adhesive that uses the same mechanisms that snails do.
Low-Dose Radiation CT Scans Could Be Improved by Machine Learning
Machine learning is a type of artificial intelligence growing more and more popular for applications in bioengineering and therapeutics. Based on learning from patterns in a way similar to the way we do as humans, machine learning is the study of statistical models that can perform specific tasks without explicit instructions. Now, researchers at Rensselaer Polytechnic Institute (RPI) want to use these kinds of models in computerized tomography (CT) scanning by lowering radiation dosage and improving imaging techniques.
A recent paper published in Nature Machine Intelligence details the use of modularized neural networks in low-dose CT scans by RPI bioengineering faculty member Ge Wang, Ph.D., and his lab. Since decreasing the amount of radiation used in a scan will also decrease the quality of the final image, Wang and his team focused on a more optimized approach of image reconstruction with machine learning, so that as little data as possible would be altered or lost in the reconstruction. When tested on CT scans from Massachusetts General Hospital and compared to current image reconstruction methods for the scans, Wang and his team’s method performed just as well if not better than scans performed without the use of machine learning, giving promise to future improvements in low-dose CT scans.
A Mind-Controlled Robotic Arm That Requires No Implants
A new mind-controlled robotic arm designed by researchers at Carnegie Mellon University is the first successful noninvasive brain-computer interface (BCI) of its kind. While BCIs have been around for a while now, this new design from the lab of Bin He, Ph.D., a Trustee Professor and the Department Head of Biomedical Engineering at CMU, hopes to eliminate the brain implant that most interfaces currently use. The key to doing this isn’t in trying to replace the implants with noninvasive sensors, but in improving noisy EEG signals through machine learning, neural decoding, and neural imaging. Paired with increased user engagement and training for the new device, He and his team demonstrated that their design enhanced continuous tracking of a target on a computer screen by 500% when compared to typical noninvasive BCIs. He and his team hope that their innovation will help make BCIs more accessible to the patients that need them by reducing the cost and risk of a surgical implant while also improving interface performance.
KIChE is an organization that aims “to promote constructive and mutually beneficial interactions among Korean Chemical Engineers in the U.S. and facilitate international collaboration between engineers in U.S. and Korea.”
We would also like to congratulate Natalia Trayanova, Ph.D., of the Department of Biomedical Engineering at Johns Hopkins University on being inducted into the Women in Tech International (WITI) Hall of Fame. Beginning in 1996, the Hall of Fame recognizes significant contributions to science and technology from women. Trayanova’s research specializes in computational cardiology with a focus on virtual heart models for the study of individualized heart irregularities in patients. Her research helps to improve treatment plans for patients with cardiac problems by creating virtual simulations that help reduce uncertainty in either diagnosis or courses of therapy.