Spying on Thousands of Neurons in the Brain’s Vision Center Simultaneously

Scientists tracked how individual neurons (white dots)
across the mouse visual center responded when the
animals saw an image on a screen.
That let the team trace the sequence
of events triggered when the eyes detect an important sight.
Credit: S. Ebrahimi et al./Nature 2022

Using a custom-built microscope to peer into the mouse brain, scientists have tracked the activity of single neurons across the entire visual cortex.

These recordings, made in the tenths of seconds after the animals saw a cue on a screen, expose the complex dynamics involved in making sense of what the eyes see. In an unprecedented combination of breadth and detail, the results describe the behavior of more than 21,000 total neurons in six mice over five days, Howard Hughes Medical Institute Investigator Mark Schnitzer’s team reports in the journal Nature on May 18, 2022.

His team is the first to get a glimpse of individual cells’ activity occurring at the same time throughout eight parts of the brain involved in vision. “People have studied these brain areas before, but prior imaging studies did not have cellular resolution across the entire visual cortex,” says Schnitzer, a neuroscientist at Stanford University.

The work highlights the dramatic sequence of events that unfolds in the brain from the instant it receives messages from the eyes until it decides how to respond to that sight. The researchers’ far-reaching but fine-grained imaging approach made it possible for them to collect an “incredible” set of data, says Tatiana Engel, a computational neuroscientist at Cold Spring Harbor Laboratory who was not involved in the study.

A component for brain-inspired computing

Scientists aim to perform machine-learning tasks more efficiently with processors that emulate the working principles of the human brain.
Image: Unsplash

Researchers from ETH Zurich, Empa and the University of Zurich have developed a new material for an electronic component that can be used in a wider range of applications than its predecessors. Such components will help create electronic circuits that emulate the human brain and that are more efficient than conventional computers at performing machine-learning tasks.

Compared with computers, the human brain is incredibly energy-efficient. Scientists are therefore drawing on how the brain and its interconnected neurons function for inspiration in designing innovative computing technologies. They foresee that these brain-inspired computing systems will be more energy-efficient than conventional ones, as well as better at performing machine-learning tasks.

Much like neurons, which are responsible for both data storage and data processing in the brain, scientists want to combine storage and processing in a single type of electronic component, known as a memristor. Their hope is that this will help to achieve greater efficiency because moving data between the processor and the storage, as conventional computers do, is the main reason for the high energy consumption in machine-learning applications.

At-Risk Sea Life in the Atlantic Needs Better Protection from an Increase in Shipping

Researchers at the University of Portsmouth have discovered that rates of shipping in the North East Atlantic area rose by 34 per cent in a five-year period.

Even more noticeable, and of major concern to scientists, is the rate of shipping growth in Marine Protected Areas. Analysis of vessel movements in these delicate environments shows an increase of 73 per cent in the same time period.

The report, which was published in Marine Pollution Bulletin, is the first detailed survey of shipping activity in the North East Atlantic. Researchers used data from over 530 million vessel positions recorded by Automatic identification Systems (AIS). They looked at the change in shipping between 2013 and 2017 across ten distinct vessel types.

In total the study area covered 1.1 million km2, including waters off Belgium, Denmark, France, Germany, Iceland, Ireland, The Netherlands, Norway, Portugal, Spain, and the UK.

Renewed monitoring effort is needed to ensure that protective measures are adequate to conserve species under threat in a changing environment.

For Plant-based Proteins, Soy is a Smart Choice

Tofu, flour, milk, and sauce are just some of the products that can be made from the versatile plant protein soy

Soy – the versatile protein source that comes from the species of legumes known as soybeans – is becoming a popular alternative to meat and dairy products, and for good reason. Whether you are trying to eat healthier, eat more sustainably, or both, College of Agriculture, Health and Natural Resources Department of Nutritional Sciences researcher Yangchao Luo and his research group recently published an article in the Journal of Agriculture and Food Research exploring qualities that make soy a versatile and nutritious choice.

What makes soy such a popular source of plant-based meat (and dairy) alternatives?

In comparison to other plant-based proteins, soy protein provides the most complete nutrients in terms of amino acids, compared to animal sources. Soy contains almost every amino acid, with only one minor exception, methionine, which is an essential amino acid, and what we call a limiting amino acid. Other plant-based proteins may miss two, three, or even four different essential amino acids. You can easily get all essential amino acids in a meal by mixing plant-based proteins or by pairing soy-based proteins with grains.

Upon extrusion process, soy-based proteins undergo a series of physicochemical changes to form fibrous anisotropic structure, the texture of which becomes very similar to meat products. When modified chemically or enzymatically, soy protein can further develop sensory characteristics that can mimic real meat. This is very easy to do for soy protein, but more challenging for many other plant proteins. A lot of food companies nowadays are trying to develop meat alternatives, and soy-based protein is just the top choice for the food industries.

Ultrahigh piezoelectric performance demonstrated in ceramic materials

The ability of piezoelectric materials to convert mechanical energy into electrical energy and vice versa makes them useful for various applications from robotics to communication to sensors. A new design strategy for creating ultrahigh-performing piezoelectric ceramics opens the door to even more beneficial uses for these materials, according to a team of researchers from Penn State and Michigan Technological University.

“For a long time, piezoelectric polycrystalline ceramics have shown limited piezoelectric response in comparison to single crystals,” said Shashank Priya, associate vice president for research and professor of materials science and engineering at Penn State and co-author of the study published in the journal Advanced Science. “There are many mechanisms that limit the magnitude of piezoelectricity in polycrystalline ceramic materials. In this paper, we demonstrate a novel mechanism that allows us to enhance the magnitude of the piezoelectric coefficient several times higher than is normally expected for a ceramic.”

The piezoelectric coefficient, which describes the level of a material's piezoelectric response, is measured in picocoulombs per Newton.

“We achieved close to 2,000 picocoulombs per Newton, which is a significant advance, because in polycrystalline ceramics, this magnitude has always been limited to around 1,000 picocoulombs per Newton,” Priya said. "2,000 was considered an unreachable target in the ceramics community, so achieving that number is very dramatic.”

Rice chemists skew the odds to prevent cancer

A new paper by a Rice University lab shows how to increase the odds of identifying cancer-causing mutations before tumors take hold. Authors are, from left, Cade Spaulding, Anatoly Kolomeisky and Hamid Teimouri.
Credit: Rice University

The path to cancer prevention is long and arduous for legions of researchers, but new work by Rice University scientists shows that there may be shortcuts.

Rice chemist Anatoly Kolomeisky, lead author and postdoctoral researcher Hamid Teimouri and research assistant Cade Spaulding are developing a theoretical framework to explain how cancers caused by more than one genetic mutation can be more easily identified and perhaps stopped.

Essentially, it does so by identifying and ignoring transition pathways that don’t contribute much to the fixation of mutations in a cell that goes on to establish a tumor.

A study in the Biophysical Journal describes their analysis of the effective energy landscapes of cellular transformation pathways implicated in a variety of cancers. The ability to limit the number of pathways to the few most likely to kick-start cancer could help to find ways to halt the process before it ever really starts.

“In some sense, cancer is a bad-luck story,” said Kolomeisky, a professor of chemistry and of chemical and biomolecular engineering. “We think we can decrease the probability of this bad luck by looking for low-probability collections of mutations that typically lead to cancer. Depending on the type of cancer, this can range between two mutations and 10.”

Technology allows amputees to control a robotic arm with their mind

University of Minnesota Department of Biomedical Engineering Associate Professor Zhi Yang shakes hands with research participant Cameron Slavens, who tested out the researchers' robotic arm system. With the help of industry collaborators, the researchers have developed a way to tap into a patient’s brain signals through a neural chip implanted in the arm, effectively reading the patient’s mind and opening the door for less invasive alternatives to brain surgeries.
Credit: Neuroelectronics Lab, University of Minnesota

University of Minnesota Twin Cities researchers have developed a more accurate, less invasive technology that allows amputees to move a robotic arm using their brain signals instead of their muscles.

Many current commercial prosthetic limbs use a cable and harness system that is controlled by the shoulders or chest, and more advanced limbs use sensors to pick up on subtle muscle movements in a patient’s existing limb above the device. But both options can be cumbersome, unintuitive, and take months of practice for amputees to learn how to move them.

Researchers in the University’s Department of Biomedical Engineering, with the help of industry collaborators, have created a small, implantable device that attaches to the peripheral nerve in a person’s arm. When combined with an artificial intelligence computer and a robotic arm, the device can read and interpret brain signals, allowing upper limb amputees to control the arm using only their thoughts.

Scent dogs detect coronavirus reliably from skin swabs

Scent dog Silja at the Helsinki-Vantaa airport.
Credit: Egil Björkman

The rapid and accurate identification and isolation of patients with coronavirus infection is an important part of global pandemic management. The current diagnosis of coronavirus infection is based on a PCR test that accurately and sensitively identifies coronavirus from other pathogens. However, PCR tests are ill-suited for screening large masses of people because of, among other things, their slow results and high cost.

Researchers from the Faculties of Veterinary Medicine and Medicine at the University of Helsinki and from Helsinki University Hospital jointly designed a triple-blind, randomized, controlled study set-up to test the accuracy of trained scent detection dogs where none of the trio – dog, dog handler or researcher – knew which of the sniffed skin swab samples were positive and which negative. The study also analyzed factors potentially interfering with the ability of the dogs to recognize a positive sample.

The three-faceted study has now been published in the journal BMJ Global Health. The study provides valuable information on the use of scent dogs in pandemic control.

Scientists Nail Down 'Destination' for Protein That Delivers Zinc

Brookhaven Lab biologist Crysten Blaby and postdoctoral fellow Nicolas Grosjean and colleagues ran genetic experiments, biochemical assays, and computational modeling studies that identified ZNG1 as a zinc chaperone protein.
Credit: Brookhaven National Laboratory

Most people don’t think much about zinc. But all living things need zinc for survival. This trace element helps many proteins fold into the right shapes to do their jobs. And in proteins known as enzymes, zinc helps catalyze chemical reactions—including many important for providing energy to cells. If zinc is absent, people, pets, and plants don’t thrive.

That’s one reason biologists at the U.S. Department of Energy’s Brookhaven National Laboratory are so interested in this element.

“We're looking for ways to grow bioenergy plants—either plants that produce biofuels or whose biomass can be converted into fuel—and doing it on land that is not suitable for growing food crops,” said Brookhaven Lab biologist Crysten Blaby, who also holds an adjunct appointment at Stony Brook University. “So, we’re interested in strategies nature uses to survive when zinc and other micronutrients are lacking.”

In a paper just published in the journal Cell Reports, Blaby and her colleagues describe one such strategy: a so-called “chaperone” protein that delivers zinc to where it’s needed, which could be especially important when access to zinc is limited. Though scientists, including Blaby, have long suspected the existence of a zinc chaperone, the new research provides the first definitive evidence by identifying a “destination” for its deliveries.

A new mathematical model of cellular movement

A new mathematical model describes how cells change their shape during movement and suggests that the movement is mainly driven by the contraction of the skeletal proteins, called “myosin.” The image shows the shape of cells at various speeds as predicted by the model. Non-moving cells are circular but become asymmetric as they begin to move. The colors indicate the concentration of myosin in the cell with red indicating a higher concentration.
Credit: C. Alex Safsten, Penn State

A mathematical model that describes how cells change their shape during movement suggests that the movement is mainly driven by the contraction of the skeletal proteins, called “myosin.” The new model developed at Penn State can help researchers to better understand the various biological processes where cellular movement plays a key role and also could inform the development of artificial systems that mimic biological processes.

“The focus of this work is on the development of minimal mathematical models that are simple enough to be amenable to rigorous analysis but still capture key biological phenomena,” said Leonid Berlyand, professor of mathematics at Penn State and the leader of this research team. “The point of our model is to capture the onset of cell motion driven by myosin contraction with focus on analyzing the stability of this motion observed in experiments.”