Have you ever wondered what happens inside your brain when you listen to music or a steady rhythm? A groundbreaking study from Aarhus University and the University of Oxford has revealed that your brain doesn’t just hear it – it reorganizes itself in real time. The research, led by Dr. Mattia Rosso and Associate Professor Leonardo Bonetti, introduces a novel neuroimaging method called FREQ-NESS, which maps the brain’s internal organization with high spectral and spatial precision.

Using advanced algorithms, FREQ-NESS disentangles overlapping brain networks based on their dominant frequency, allowing scientists to track how each frequency propagates in space across the brain. This development represents a major advance in neuroscience, enabling researchers to study the brain’s large-scale dynamics more accurately.

The traditional view of brainwaves as fixed stations – alpha, beta, gamma – is being challenged by this research. FREQ-NESS reveals that brain activity is organized through frequency-tuned networks, both internally and externally. This understanding opens new possibilities for basic neuroscience, brain-computer interfaces, and clinical diagnostics.

This study contributes to a growing body of research exploring how the brain’s rhythmic structure shapes perception, attention, and consciousness. Professor Leonardo Bonetti notes, “The brain doesn’t just react – it reconfigures. And now we can see it.” This breakthrough could revolutionize how scientists study brain responses to music and beyond.

A large-scale research program is underway to build on this methodology, supported by an international network of neuroscientists. FREQ-NESS may also pave the way for individualized brain mapping, offering new insights into the intricate harmony of the human brain.

The human visual system has long been a source of inspiration for computer vision researchers, who aim to develop machines that can see and understand the world around them with the same level of efficiency and accuracy as humans. While machine vision systems have made significant progress in recent years, they still face major challenges when it comes to processing vast amounts of visual data while consuming minimal power.

One approach to overcoming these hurdles is through neuromorphic computing, which mimics the structure and function of biological neural systems. However, two major challenges persist: achieving color recognition comparable to human vision, and eliminating the need for external power sources to minimize energy consumption.

A recent breakthrough by a research team led by Associate Professor Takashi Ikuno from Tokyo University of Science has addressed these issues with a groundbreaking solution. Their self-powered artificial synapse is capable of distinguishing colors with remarkable precision, making it particularly suitable for edge computing applications where energy efficiency is crucial.

The device integrates two different dye-sensitized solar cells that respond differently to various wavelengths of light, generating its electricity via solar energy conversion. This self-powering capability makes it an attractive solution for industries such as autonomous vehicles, healthcare, and consumer electronics, where visual recognition capabilities are essential but power consumption is limited.

The researchers demonstrated the potential of their device in a physical reservoir computing framework, recognizing different human movements recorded in red, green, and blue with an impressive 82% accuracy. This achievement has significant implications for various industries, including autonomous vehicles, which could utilize these devices to efficiently recognize traffic lights, road signs, and obstacles.

In healthcare, self-powered artificial synapses could power wearable devices that monitor vital signs like blood oxygen levels with minimal battery drain. For consumer electronics, this technology could lead to smartphones and augmented/virtual reality headsets with dramatically improved battery life while maintaining sophisticated visual recognition capabilities.

The realization of low-power machine vision systems with color discrimination capabilities close to those of the human eye is within reach, thanks to this breakthrough research. The potential applications of self-powered artificial synapses are vast, and their impact will be felt across various industries in the years to come.

The discovery of a specific group of nerve cells in the brain stem has shed new light on how semaglutide affects appetite and weight loss. Researchers at the University of Gothenburg have made a groundbreaking find that could pave the way for better drugs to treat obesity.

Semaglutide, a GLP-1R agonist, is already well-established as part of the treatment for obesity and type 2 diabetes. However, it can cause side effects such as nausea and muscle loss. The researchers were able to distinguish the nerve cells in the brain that control the beneficial effects of semaglutide from those that contribute to side effects.

In a study published in Cell Metabolism, the researchers worked with mice and tracked which nerve cells were activated by semaglutide. They then stimulated these cells without administering the drug itself. The result was that the mice ate less and lost weight, just as they did when treated with semaglutide. When these nerve cells were killed, the drug’s effect on appetite and fat loss decreased significantly, but side effects such as nausea and muscle loss remained.

“This suggests that these nerve cells control the beneficial effects of semaglutide,” says Júlia Teixidor-Deulofeu, first author of the study. “We have therefore identified a specific group of nerve cells that is necessary for the effects that semaglutide has on weight and appetite, but which does not appear to contribute to any significant extent to side effects such as nausea.”

The identified nerve cells are located in an area of the brain called the dorsal vagal complex. The study provides new knowledge about how semaglutide works in the brain and deeper insight into how the brain stem regulates our energy balance.

“The better we understand this, the greater the opportunity we have to improve them,” says Linda Engström Ruud, researcher and supervisor to PhD students Júlia Teixidor-Deulofeu and Sebastian Blid Sköldheden, who both worked on the project.

This discovery has significant implications for the development of better drugs to treat obesity and could potentially lead to improved treatment options with fewer side effects.