Study: 70.7% of neuroscientists believe memories can be extracted from deceased brains

Researchers at Washington University in St. Louis have developed a computational method that predicts fetal conditions through the analysis of placental texture in prenatal ultrasound imagery. By leveraging algorithms to perform texture analysis, including but not limited to filter-based, spectral, structural, and deep-learning methods, this invention provides a more objective and quantifiable assessment of fetal health. Technology Inventors: Michelle Oyen, Yuyang Hu, Ulugbek Kamilov, Anthony Odibo, Adrienne Scott, Emily Sheehan, and Patrick Yang To learn more about this #WashU technology, visit https://lnkd.in/gJSWxr4E

As a solicitor inspired by the healthcare space working alongside medical experts, advancements in medical science interest me hugely. This one is quite literally mind blowing. In a space no larger than a pinhead, deep within the human brain, lies an entire universe — and for the first time ever, it's been mapped in extraordinary detail. Led by researcher Alexander Shapson-Coe, a team turned the power of electron microscopy onto just one cubic millimeter of the temporal cortex. What they uncovered is nothing short of mind-blowing: a nano-resolution map revealing neurons, synapses, blood vessels, and intricate connections never before visible to science. That tiny fragment of brain produced 1.4 petabytes of data — over a thousand times more than what’s stored in a typical library. Even more incredible? They didn’t keep it to themselves. They created a free tool that allows anyone—from neuroscientists to curious minds—to explore this vast microscopic world. Published in Science, this isn’t just a breakthrough in technology—it’s a gateway to deeper understanding of the human brain. A map not only of what we are, but of what we’ve yet to uncover. More Information 👉🏻 https://lnkd.in/dvmcFu44

#EurekaBlog Science Ticker: Stanford scientists have developed a brain-computer interface that can decode imagined speech with up to 74% accuracy, offering new hope for people with severe paralysis — and sparking privacy debates. https://okt.to/3wQ42h #sciencenews

🚀 Breakthrough in Neural Interface Technology: RWD Automated Stereotaxic Instrument Supports Groundbreaking Research in Advanced Functional Materials (IF 19) We’re thrilled to share that the RWD Automated Stereotaxic Instrument played a pivotal role in enabling researchers from the Korea Institute of Science and Technology (KIST) to achieve a major milestone in neural engineering! Their latest work, published in the prestigious journal Advanced Functional Materials, introduces an innovative carbon nanotube (CNT) microelectrode array that successfully integrates mechanical flexibility, high conductivity, and biocompatibility—a critical advancement for long-term neural signal recording. Key Contributions of RWD’s Technology: ✔ Precision & Stability: Ensured accurate targeting and gentle implantation (1 μm/s) of CNT arrays into the visual cortex and hippocampus of mouse models. ✔ Reliable Foundation: Enabled high-quality neural signal recording and biocompatibility validation, supporting the study’s success. This research opens new possibilities for next-generation neural interfaces, and we’re honored to contribute to such transformative science. 🔗 Curious about how automated stereotaxic systems can elevate your research? Let’s connect! #Neuroscience #Innovation #ResearchTools #NeuralEngineering #Biotechnology

📢 Paper Published! I'm delighted to share that my research article titled "SpectroNet-LSTM: An Interpretable Deep Learning Approach to Cardiac Anomaly Detection Through Heartbeat Sound Analysis" has been published in the Journal of Computers in Biology and Medicine at Elsevier (IF 6.3). This research addresses a critical healthcare challenge in the early detection of cardiac anomalies, which remain a leading cause of mortality worldwide. Utilizing Mel-Frequency Cepstral Coefficients (MFCCs) and spectrogram analysis, we propose SpectroNet-LSTM as an advanced deep learning fusion architecture that achieves superior detection in need and provides interpretability through SHAP and LIME algorithms. Our goal is to bridge the gap between automation and clinical trust, paving way for more accessible cardiovascular diagnostics. A heartfelt thank you to my faculty guide Dr Krithiga Rajeshwaran, my team of co-authors (Utkarsh Mishra, Krishna Priyadarshan Behara) and others at Vellore Institute of Technology for their support throughout this journey. You can access the full paper here: https://lnkd.in/gaYSg5fr #CardiacAnomalies #DeepLearning #ExplainableAI #Innovation #MedicalAI #SpectroNetLSTM #ResearchPublication #Elsevier #AIinHealthcare #Journal #VIT #VITChennai #Healthcare

Coolness hits different; now scientists know why University of Michigan College of Literature, Science, and the Arts researchers discover a complete skin-to-brain neural circuit for temperature sensing, a finding that could help spur medical innovations such as new treatments for temperature-associated pain. https://lnkd.in/ee_Ks43X

🤖 What if AI could accelerate the way science builds its theories? At the Wolfram Institute, in conversation with Dugan Hammock and Brian Mboya, Daniel Van Zant — a Computational Neuroscience PhD student and Student Fellow for the Center for the Future of AI, Mind & Society, and the Florida Atlantic University Stiles-Nicholson Brain Institute — presented a system he is developing for his dissertation. The system is designed to help neuroscientists build robust theories more efficiently, with the aim of accelerating discovery and, downstream, improving the success rate of clinical trials for treatments targeting neurodegenerative diseases. Daniel also demonstrated how the same system could be applied to “fundamental computation” research, a core focus of the Wolfram Institute. 👏 We commend Daniel for showcasing how AI can help reshape the future of science! Watch now: https://lnkd.in/et48wmBR #AI #Neuroscience #Computation #NeurodegenerativeDisease #WolframInstitute #Science #Innovation #StudentSpotlight

65LAB has awarded US$1.5 million to Prof Enrico Petretto from the Duke-NUS Centre for Computational Biology to advance Systems Genetics, a cutting-edge platform combining computational biology, AI algorithms, and emerging quantum computing. This project aims to pioneer first-in-class antifibrotic therapies for lung and kidney diseases—serious conditions that currently have no effective treatment. Read more about this breakthrough from the link in the comments. 📸: Chen Huimei #MedicalInnovation #DrugDiscovery #AI #QuantumComputing #HealthcareBreakthrough #DukeNUS

Scientists have developed a new brain-computer interface that can capture and decode the “inner monologue” taking place in a person’s mind. It is hoped that this advancement in brain-computer interface technology will make it easier for people who are unable to speak due to severe paralysis or other neurological conditions to communicate. Article ➡️ https://lnkd.in/dMRUev7X

🧠✨ Big news from Stanford! For the first time, scientists have decoded inner speech, the silent voice we all hear in our heads. Using a brain-computer interface (BCI) with tiny electrodes in the motor cortex, they helped patients with paralysis translate their thoughts into sentences. 📌 Key results: 74% accuracy in decoding imagined speech Vocabulary span of 125,000 words Tested on patients with ALS or brainstem stroke Built-in privacy trigger: system only works when users think a chosen password phrase This breakthrough could one day allow people who cannot speak to communicate fluently using only their mind. A life-changing step in neuroscience and technology. #BrainComputerInterface #NeuroTech #StanfordResearch #FutureOfCommunication #MedicalBreakthrough