A new study found that brain stimulation effectiveness is linked to individual learning abilities, not age. The study used atDCS on participants with optimal and suboptimal learning strategies, revealing accelerated accuracy improvement in suboptimal learners.
EPFL researchers developed detailed computational models of rat hippocampal and somatosensory cortex regions, simulating brain activity and studying the roles of each part. The models' three-dimensional geometry allows for testing with new experimental data and exploring a wide range of phenomena.
NeuroMechFly v2 simulates how a fruit fly navigates through its environment while reacting to sights, smells, and obstacles. The model can track moving objects visually or navigate towards an odor source, while avoiding obstacles in its path, enabling researchers to study brain-body coordination and animal intelligence.
Researchers at EPFL have created a unique experimental setup combining non-invasive deep-brain stimulation, virtual reality training, and fMRI imaging to improve spatial memory. The study shows that targeted electric impulses to the hippocampus can temporarily increase brain plasticity, leading to better navigation and recall.
EPFL researchers have developed correlated vibrational spectroscopy (CVS) to measure the behavior of water molecules participating in hydrogen bonds. The method allows for direct measurement of electronic charge sharing and H-bond strength, enabling precise characterization of molecular-level details in various materials.
The study found that P. aeruginosa adapts to the lung's mucus by relying on sugars and lactate, but also needs to synthesize essential nutrients through metabolic independence. Biofilm formation imposes a metabolic burden, slowing down the bacteria's ability to spread, while disrupting biofilms makes them more vulnerable to antibiotics.
A new benchmark, V-score, has been developed to tackle quantum many-body problems. The V-score combines energy and fluctuation data into a single number, making it easier to rank different methods based on accuracy.
Researchers at EPFL have developed the e-Flower, a flower-shaped 3D microelectrode array that enables real-time recording of neural activity from 3D neural spheroids. This breakthrough technology allows for more accurate and gentle monitoring of brain cells, paving the way for further research on brain organoids.
Researchers developed a rating system to evaluate climate model plausibility, finding that a third of models fail to reproduce sea surface temperature data. Carbon-sensitive models, which predict stronger heating than the IPCC estimate, are deemed plausible and warrant serious consideration.
Researchers found inhibiting ACMSD increases NAD+ levels, reducing inflammation and fibrosis in mouse models of MASLD/MASH. Boosting NAD+ production could protect against severe liver damage and cirrhosis.
Researchers developed an AI-driven approach to model complex hand movements, overcoming current limitations in neuroscience and biomedical engineering. The model achieved a 100% success rate in controlling virtual Baoding balls, showcasing its strength in various challenging situations.
A new study published in Nature has found that the type 2 immune response is positively correlated with long-term cancer remission, contradicting previous theories that it promotes tumor growth. The research used samples from pioneering clinical trials and revealed a statistically significant correlation between type 2 immune factors a...
Researchers discovered 'context-only' TFs that boost enhancer activity and contribute to regulatory factor clusters, which regulate genes effectively. This finding provides a new understanding of cooperative environments that TFs create to regulate genes in health and disease.
A deep-learning algorithm developed by astronomer David Harvey can untangle the complex signals of self-interacting dark matter and AGN feedback in galaxy cluster images. The Inception model achieved an accuracy of 80% under ideal conditions, showcasing its potential for analyzing vast amounts of space data.
A team of researchers created RENAISSANCE, an AI-based tool that simplifies the creation of kinetic models to accurately depict metabolic states. The tool successfully generated models that matched experimentally observed metabolic behaviors in Escherichia coli, simulating how the bacteria would adjust their metabolism over time.
Researchers at EPFL developed a next-generation miniaturized brain-machine interface capable of direct brain-to-text communication on tiny silicon chips. The MiBMI system can decode neural signals generated when a person imagines writing letters or words with high accuracy and low power consumption.
EPFL researchers have created an energy-efficient method for nonlinear computations using scattered light from low-power lasers. The new approach is scalable and up to 1,000 times more power-efficient than state-of-the-art digital networks, making it suitable for realizing optical neural networks.
Scientists have unveiled that beetles' hindwings are passively deployed and retracted, leveraging the elytra to deploy and retract while flapping forces unfold the wings. This finding has potential applications in designing new microrobots that can fly in confined spaces.
Researchers found that epigenetic state affects neurons' recruitment into memory trace formation. Open chromatin states enable more efficient learning. The study opens new avenues for understanding learning and may lead to medication for improving cognitive disorders.
Researchers have developed PrISMa, a novel platform that seamlessly connects materials science, process design, techno-economics, and life-cycle assessment to identify effective and sustainable carbon capture solutions. The platform has been tested on over 60 real-world case studies, providing valuable insights for stakeholders.
Researchers at EPFL's Laboratory of Nanoscale Electronics and Structures have fabricated a device that efficiently converts heat into electrical voltage at temperatures lower than outer space. The innovative device exploits the Nernst effect, a complex thermoelectric phenomenon, to achieve unprecedented performance.
Using wave momentum shaping, EPFL researchers guided a ping-pong ball along a pre-determined path in a tank of water, even with obstacles and dynamic environments. The method, inspired by optical tweezers, holds great promise for biomedical applications like noninvasive targeted drug delivery.
A new study developed an AI-based approach, DiffPALM, to predict protein interactions with high accuracy, outperforming traditional methods. This advancement has significant implications for drug development and disease treatment, and the researchers have made it freely available for further research.
Researchers investigated the efficiency of modern neural network-based generative models, comparing them to traditional sampling techniques. The study found that modern diffusion-based methods may face challenges due to a first-order phase transition, but also exhibit superior efficiency in certain cases.
Researchers at EPFL have created a deep learning pipeline to design soluble analogues of cell membrane proteins, making them easier to study and use in pharmaceutical development. The approach has shown remarkable success in producing functional proteins that maintain parts of their native functionality.
Scientists have discovered that specific light wavelengths can induce non-equilibrium transitions in magnetite, a well-studied material. This breakthrough enables the control of electronic properties at ultrafast timescales, opening up new avenues for advanced materials and device development.
Researchers have developed a new open-source tool, SuperAnimal, that can automatically recognize keypoints in various animal species without human supervision. This enables standardized labeling efforts and training large-scale datasets for behavioral phenotyping.
Researchers at EPFL have published an open-source project Tabulae Paralytica, providing a comprehensive understanding of spinal cord injury biology. The study identifies specific neurons and genes involved in recovery and proposes a successful gene therapy derived from its discoveries.
A new dataset from the VELOCE project has collected over 18,000 high-precision measurements of Cepheid radial velocities, providing insights into the structure and evolution of these stars. The data reveal complex patterns in pulsations that cannot be explained by traditional models, suggesting intricate processes within the stars.
Researchers developed a metabolic health score based on clinical parameters and used it to explore its genetic underpinnings in mice, validating findings in human data. The study identified two significant genetic regions linked to metabolic health and pinpointed candidate genes associated with metabolic traits.
Researchers developed a chip-scale erbium-doped waveguide laser that approaches fiber-based laser performance, featuring wide wavelength tunability and stable output. The breakthrough enables low-cost, portable systems for various applications including telecommunications, medical diagnostics, and consumer electronics.
Researchers discovered that command-like DNs in fruit flies recruit additional networks of neurons to orchestrate complex behaviors. The study shows that these networks work together to produce coordinated actions, transforming the way we understand brain signals and behavior.
Researchers at EPFL have developed a novel non-invasive technique to target deep brain regions involved in neurological disorders. By applying low-level electrical stimulation on the scalp, they can selectively stimulate key brain regions without invasive procedures.
Researchers developed a novel approach to block cancer cell growth by targeting specific proteins, reducing side effects and increasing treatment efficacy. The method uses antibody-peptide inhibitor conjugates, which deliver inhibitors specifically to cancer cells,
The study explores how different cell division strategies have evolved across organisms, finding a link between life cycle stages and mitotic strategies. Species with multinucleate stages tend to use closed mitosis, while those with mononucleate stages employ open mitosis.
Researchers have identified a population of mesothelial-like cells in omental adipose tissue that limit fat cell formation, offering new insights into the mechanisms underlying obesity. These cells secrete Insulin-like Growth Factor Binding Protein 2, which inhibits adipogenesis and regulates metabolic behavior.
A new, low-cost, high-efficiency photonic integrated circuit has been developed using lithium tantalate technology. The breakthrough platform offers scalable and cost-effective manufacturing of advanced electro-optical PICs, paving the way for volume manufacturing.
Researchers developed ChemCrow, an AI-powered tool that integrates expertly designed software tools to autonomously perform chemical synthesis tasks. The system enables plan-and-execute approach with reduced hallucinations and practical application, accelerating research and development in pharmaceuticals and materials science.
Researchers trained a quadruped robot using deep reinforcement learning to learn gait transitions on challenging terrain. The robot transitioned from walking to trotting and then to pronking to avoid falls, demonstrating the emergence of animal-like locomotion.
Scientists have recorded X-rays being produced at the beginning of upward positive lightning flashes, providing valuable insights into the origins of this rare and dangerous form of lightning. The observations, made possible by a unique setup in Switzerland, support the cold runaway electron model theory of lightning formation.
Scientists have developed mini-colon tissues that can simulate the complex process of tumorigenesis outside the body with high fidelity. These miniature organs mimic the physical structure and cellular diversity of colon tissue, allowing researchers to study colorectal cancer development and test potential therapies.
Researchers at EPFL have developed a comprehensive model of the quantum-mechanical effects behind photoluminescence in thin gold films, which could drive the development of solar fuels and batteries. The study reveals unexpected quantum effects emerging in films as thin as 40 nanometers.
EPFL researchers develop DNGEs, 3D-printable double network granular elastomers that can vary their mechanical properties. These inks enable the creation of flexible devices with locally changing properties, eliminating the need for cumbersome mechanical joints.
Researchers at EPFL have developed a genetic learning algorithm to identify optimal pitch profiles for VAWT blades, increasing turbine efficiency by 200% and reducing vibrations by 77%. This innovation addresses the engineering problem of air flow control and has the potential to bring efficient VAWT technology to maturity.
EPFL researchers have developed a novel approach to boost electrocatalysis using magnetic fields, enhancing the movement of reactants and improving reaction efficiency. This innovation has significant potential to revolutionize energy conversion technologies and increase sustainable fuel production, mitigating climate change.
Researchers at EPFL's EMSI lab discovered a positive correlation between crack complexity and material toughness, revealing that more energy is required to advance complex cracks than simple ones. This finding could improve materials testing and development for safe and cost-effective composite materials.
Researchers discovered that brains prioritize integrating muscle spindle input to understand body movement and position. Task-driven neural network models were found to be most effective in predicting limb position and velocity.
Researchers at EPFL have successfully connected two artificial synapses using ions to process data, paving the way for brain-inspired computing. The device stores information in a readily accessible way, reducing energy costs and mimicking the brain's own processing mechanism.
A pioneering approach produces high-performance polyamides from sugar cores derived from agricultural waste, with impressive atom efficiency and recyclability
Researchers found that people with Parkinson's disease who experience presence hallucinations overestimate the number of people in a room due to a perceptual disorder. The study used virtual reality and robotics to induce presence hallucinations and measure susceptibility, developing an online test for early detection.