InBrain Neuroelectronics: Next-gen neural interfaces with AI

Everyone is talking about Neuralink.Brain–computer interfaces promise to “think-to-type” by wiring neurons directly into silicon. But here’s the real question: Do we really need brain surgery to connect more deeply? At YINIQ, we believe the next trillion-dollar interface will not be invasive. It will be soft, emotional, and resonant. Our foundation is a rare living biosystem formed over 40,000 years—naturally rich in PQQ, nucleic acids, polysaccharides, and more than 8,000 microbial species in a self-renewing matrix. This isn’t sci-fi. It builds on decades of biofilm ecology and cognitive science showing how frequency and emotion shape resilience. What this teaches us is the future of soft interfaces: Emotion as the first operating system Water as the oldest memory field Frequency as the true protocol of connection If Neuralink is about controlling machines, YINIQ is about resonating with life and intelligence. This isn’t wellness. This isn’t skincare. It’s the Soft Singularity: turning emotion into the next interface layer for health, creativity, and human–AI collaboration. The next trillion-dollar platform won’t be hard tech. It will be soft resonance at scale. Engagement question (to drive comments): Do you believe the future of interfaces will be built on hard implants — or soft resonance? #Neuralink #BCI #SoftTech #PlatformShift #FutureOfInterface #YINIQ

Scientists have built a dopamine-sensitive artificial neuron from metal–organic frameworks that works in water, mimics brain-like learning, and even controlled a robotic hand—bringing us closer to brain-inspired AI and advanced prosthetics. https://lnkd.in/e6CzPTNc

The future of prosthetics just got more human. Scientists have discovered how to harness dopamine - our brain's reward chemical - to create prosthetics that don't just move, but *feel* right to the user. Here's why this matters: The Current Challenge: Most prosthetic users abandon their devices within 2 years. Why? Because current prosthetics feel foreign - they lack the neurochemical feedback that makes movement feel natural and rewarding. The Breakthrough: Researchers found that by incorporating dopamine-responsive feedback systems, prosthetics can trigger the same reward pathways that make natural movement satisfying. Users report feeling like the prosthetic is truly "part of them." What This Means for Tomorrow: Prosthetics that adapt and learn from user behavior Reduced phantom limb pain through proper neurochemical integration Higher adoption rates and improved quality of life A stepping stone toward artificial consciousness in medical devices My Vision: As someone deeply invested in the intersection of neuroscience and advanced prosthetics, I see this as more than just better devices. This is about creating technology that doesn't just replace function - it restores the human experience and this is specially one of my domain of interest and one of my startup project it's fascinating to see more researchers closely decode those biological feedback which I explored while ago. The line between biological and artificial intelligence continues to blur, and frankly, that's exactly where the most meaningful breakthroughs happen. What excites you most about the future of human-machine integration? Are you working on similar innovations? Let's connect if you're passionate about neurotechnology, prosthetics, or artificial consciousness. The future is collaborative. #Neuroscience #Prosthetics #ArtificialIntelligence #BioTech #Innovation #DisabilityTech #HumanAugmentation #FutureTech

🔷 Neuralink's announcement of a U.S. clinical trial to translate thoughts into text by October marks a significant milestone in neurotechnology. This endeavor, primarily targeting individuals with speech impairments, addresses a critical need for enhanced communication solutions. Beyond its immediate therapeutic applications, the long-term vision of enabling seamless human-AI interaction at the speed of thought presents a transformative, albeit complex, future for various industries. While the clinical advancements offer profound potential, the broader implications of consumer brain implants and the ethical considerations surrounding such pervasive technology warrant careful consideration. The industry must navigate these innovations responsibly, balancing groundbreaking progress with robust ethical frameworks to ensure societal benefit and mitigate potential risks. This trial's outcomes will undoubtedly influence future research and development in the brain-computer interface (BCI) sector. #Neuralink, #BCI, #Neurotechnology, #ThoughtToText

Elon Musk’s Neuralink is set to launch a new clinical trial in the US this October 🧠, aiming to help people with speech impairments communicate by converting their thoughts into text. The trial is part of an FDA-approved investigational device exemption, and Neuralink is exploring how thought translation can interact directly with AI and devices like AirPods .⚡ 🔑 Key Details: 🔸 Trial Start: October 2025 in the US. 🔸 Purpose: Convert patients’ thoughts into text, aiding those with speech impairments .🗣️ 🔸 Method: Implant reads activity in the speech cortex, bypassing keyboards or other intermediaries. 🔸 Existing Trials: Neuralink runs five other studies across the US, Canada, UK, and UAE .🌍 🔸 Future Plans: Company hints healthy individuals could use implants to communicate with AI at thought speed in 3–4 years .⚡ 🔸 Long-term Vision: Potential integration with AI models and AirPods for instant information exchange. 🔸 Cautions: Experts warn about the risks of consumer brain implants, with parallels to sci-fi scenarios like Neuromancer or Cyberpunk 2077. #Neuralink #BrainImplant #ElonMusk #AI #TechNews #Innovation #Science #Neuroscience #ClinicalTrial #Communication #MedicalTech #NetSnix

🧠✨ Artificial Neurons - showing synaptic plasticity ⚠️ Researchers (Fadelli et al., 2025) have developed an artificial neuron that integrates DRAM with MoS₂-based circuits — moving us one step closer to truly adaptive neuromorphic systems. Unlike conventional models that rely on static synaptic weights, this hybrid device shows memory retention, plasticity, and adaptability—hallmarks of real biological neurons. 🔋 Core innovation – DRAM stores charge that can be tuned like a neuron’s membrane potential, while the inverter circuit fires bursts similar to biological spikes. 🧩 Brain-like adaptability – The system captures both synaptic plasticity (changes at connections) and intrinsic plasticity (changes within the neuron), the two key drivers of human learning and memory. 👁 Real-world emulation – It can dynamically adapt, just like the human visual system adjusting to different lighting—and has already been tested in a 3×3 neuron grid for image recognition tasks. This is not just about computing faster or cheaper. It’s about building systems that can adapt, learn, and evolve like living brains This design bridges memory and computation within a single neuron-like unit—paving the way for neuromorphic hardware that can learn, adapt, and evolve instead of just following programmed rules. 🚀 A step closer to neuromorphic hardware that could transform AI into something far more human-like. The Question is : Do Mankind is ready to handle such intelligence ⁉️ ⚠️The future physicians going to deal with, the era of completly different set of conditions, they haven't prepared, yet. ✨Those who can see beyond textbooks - May Survive 👉 Do you think adaptability will be the defining feature that separates next-gen AI from today’s models? Wang, Y., Gou, S., Bao, W., et al. (2025). A biologically inspired artificial neuron with intrinsic plasticity based on monolayer molybdenum disulfide. Nature Electronics, 8, 680–688. doi:10.1038/s41928-025-01433-y https://lnkd.in/gwD-J4Mh #ArtificialIntelligence #Neuroscience #Research #neuroplasticity

Glad to share that our last paper titled "ErisNet: A Deep Learning Model for Noise Reduction in CT Images" is now available online on Bioengineering MDPI (https://lnkd.in/ehmv5Efu). This study depicts the use of ErisNet, a convolutional neural network for noise removal in CT images; 23 post-mortem CT scans, each scan both in high and low-dose, were essential for training the neural network, validating and testing the dataset, obtaining significant values in both quantitative and qualitative analysis. ErisNet has demonstrated its ability in substantial noise reduction while maintaining or even increasing diagnostic reliability, a significant step towards the adoption of neural networks in routine clinical practice for low-dose CT image reconstruction, potentially reducing the dose absorbed by patients. Thanks and congratulations to all the authors for the excellent work; a big thanks to my colleague Fabio Mattiussi for getting me involved in this beautiful project born from an idea between one PMCT-on-call shift and another. Andrea Cozzi, Gabrio Cadei, Chiara Martini, Svenja Leu, Alcide Alessandro Azzena, Marco Pileggi, Ermidio Rezzonico, Stefania Rizzo, Ente Ospedaliero Cantonale (EOC), MDPI #Radiology #DnCNN #PMCT

So glad to share other article published with my student and colleagues in Taibah University in Neuro-Oncology Advances one of OXFORD ACADEMIC (https://academic.oup.com/) journal entitled:Assessment of the emerging role of AI in diagnosing gliomas using MRI: Systematic review and meta-analysis https://lnkd.in/dwXvqg-p https://lnkd.in/dWp3YKSY

🚀 Just published a new project on GitHub! Brain Tumor MRI Classification 🧠📊 I built a deep learning model that classifies brain MRI scans into tumor vs. non-tumor, aiming to support early detection with AI. The notebook includes data preprocessing, CNN training, evaluation, and visualization. 🔗 Check it out here: https://lnkd.in/gunjkf3X #AI #DeepLearning #MedicalAI #MachineLearning #ComputerVision

The thalamus, being a crucial region for sensory processing and multi-sensory integration with both bottom-up and top-down connectivity, is in a powerful anatomical and functional position to guide cortical processes. While past thalamic research has focused mostly on pure sensory processing (i.e., their relay role), the importance of non-relay functions (e.g., cognition) has recently been emphasized, but much less understood. We are especially interested in the anterior thalamic nuclei (ATN) and its cell types, which have been implicated in long-term memory formation, attention, and spatial navigation. In this talk, I will describe our work aimed at developing tools to genetically access ATN cell types with high specificity, investigate their role in contextual learning and generalization, and how computational models along with in vivo calcium imaging is helping us uncover similarities vs. differences between the ATN and the broader cognitive network (i.e., cortex and hippocampus). We believe that these complementary approaches have the potential to reveal novel cell type- and functionally-distinct subnetworks within the ATN, which underlie cognitive functions.