New technique for detecting causality in neural spike trains

Excited to showcase my latest work: a hybrid computational neuropharmacology prototype! In this demo, you can see how we can combine the best of classical and quantum computing to accelerate drug discovery. The process works in two key phases: Classical Analysis: The program uses methods like molecular docking and network analysis to identify potential drug candidates from a vast database of protein targets like the Dopamine D2 and Serotonin 5-HT2A receptors. Quantum Refinement: The top-scoring molecules are then passed to a quantum-inspired model, such as a Quantum Convolutional Neural Network (QCNN) or a Variational Quantum Autoencoder (QVAE), to precisely optimize their structure for maximum efficacy and minimal side effects. This prototype isn't about immediate drug discovery, but rather about exploring the powerful synergy between current computational techniques and future quantum technology. It's a glimpse into how we might one day design more targeted and effective treatments for neurological disorders. What are your thoughts on this fusion of classical and quantum methods in drug research? #Neuropharmacology #QuantumComputing #DrugDiscovery #ComputationalChemistry #HybridComputing #AIinMedicine #Biotechnology #FutureOfScience

Researchers have created a novel computational method to decipher the complex communication patterns between neurons. By analyzing their irregular electrical "spikes," the technique accurately identifies which neurons influence others, a key step in understanding brain function and neurological disorders.

Cracking the Wave–Particle Code of the Brain For over 100 years, neuroscience has been constrained by the “spike model”—reducing action potentials to digital blips. The ECEPJ Model redefines this: neurons are not switches. They are capacitor lattices, storing and releasing energy across 3D dielectric layers of myelin. • Waves = field patterns, analog, infinite, orchestrating thought like harmonics. • Particles = neurotransmitters, discrete messengers that translate the waves. • Code = the infinite combinations where energy configurations map to memory, emotion, and awareness. This is where wave–particle duality and quantum coherence converge. Why this matters: • PBM (light) restores mitochondrial energy → stabilizes field codes. • TMS (magnetic fields) modulates synchrony → strengthens coherence. • TUM (ultrasound) penetrates deep tissue → fine-tunes oscillations. Together, they demonstrate: the brain is an energy-driven code system, not a wiring diagram. The cure for neurological disease will not be found in plaques or tangles. It will be found in decoding and restoring the energy codes. The ECEPJ framework is the path toward a neural codebook—a map not only for treating Alzheimer’s and Parkinson’s, but for building AI that learns like the brain itself.

In a groundbreaking experiment, Dr. Miguel Nicolelis and teams at Duke University and Brazil’s International Institute for Neuroscience of Natal connected two rat brains using brain-to-brain interface (BBI) technology. The "encoder" rat, trained to perform tasks like lever-pressing or texture identification, had its neural activity recorded via cortical electrodes and sent digitally over the internet to the "decoder" rat, thousands of miles away. The decoder received this as brain stimulation and performed the tasks correctly at 60–70% accuracy, despite no direct exposure to stimuli. Feedback to the encoder improved performance, marking the first successful intercontinental brain-to-brain communication and hinting at future neural network applications.

Everyday Actions, Deep #Brain Connections: #NYCU Study Uncovers How #Chewing and #Swallowing Engage the Human #Mind What if every bite of rice or sip of water was more than just a reflex? Researchers from the National Yang Ming Chiao Tung University (NYCU) have discovered that these seemingly mundane actions—chewing and swallowing—are intricately linked to the brain’s complex neural networks. In two recently published studies in the Journal of Oral Rehabilitation, NYCU’s Department of Dentistry and Magnetic Resonance Imaging (MRI) Core Laboratory reveal that these everyday functions are not just mechanical—they reflect and rely on distinct neural pathways in the brain, particularly in relation to aging and cognitive adaptation. For continuous reading: https://lnkd.in/gqPazBEx

A new study shows that the brain activity behind decision-making is far more widespread across the organ than first thought. Researchers have completed the first-ever activity map of a mammalian brain in a groundbreaking duo of studies, and it has rewritten scientists' understanding of how decisions are made. The project, involving a dozen labs and data from over 600,000 individual mouse brain cells, covered areas representing over 95% of the brain. Findings from the research, published in two papers in the journal Nature, suggest that decision-making involves far more of the brain than previously thought. The mammoth project was led by the International Brain Laboratory (IBL), a collaboration of experimental and theoretical neuroscientists from across Europe and the U.S. These scientists were united by a familiar, nagging feeling. https://lnkd.in/gWKnpxrq

Neural activity is mostly electrical but also biochemical. The way we measure it isn’t always direct. Some imaging techniques don’t measure electrical activity itself, but secondary signals like blood flow. This adds delay, noise, and interpretation challenges when studying fast neural processes. Generally though, techniques that measure biochemical changes always have greater spatial resolution compared to techniques measuring electrical changes If you are interested in learning about neurotechnology and computational neuroscience read GL02 from GreyLattice https://lnkd.in/g3Sxvb8V

🧠 Towards a Brain-Wide Map of Neural Activity During Decision-Making This paper presents one of the most comprehensive efforts to map brain-wide activity during behavior in mice. Using Neuropixels probes across hundreds of brain regions, the study analyzed how neurons encode key decision-making variables such as stimulus, choice, and feedback at both single-cell and population levels. Main findings: • Neural signals related to decision-making are widely distributed across cortical and subcortical regions, not confined to localized “decision centers.” • Both single-neuron firing rates and population dynamics showed robust encoding of task variables. • Feedback-related activity emerged as one of the most dominant signals, shaping brain-wide computations. Future perspectives: • The open dataset (accessible via the International Brain Lab) provides a resource for global collaboration. • Future work could explore causal manipulations, temporal dynamics, and cross-species comparisons, bringing us closer to a unified understanding of distributed cognition. Personal perspective: I find this paper inspiring because it shifts the view from isolated brain areas to distributed neural systems. As someone interested in brain-inspired AI and biomedical engineering, I see this as a blueprint for how large-scale, high-resolution neural datasets can inform both neuroscience and intelligent systems design. #Neuroscience #BrainMapping #DecisionMaking #NeuralCoding #BigData #Neurotechnology

Going to the International Ultrasonics Symposium (IUS) next week 🇳🇱 + 📍? Check out our recent work on diffusion model–based ultrasound despeckling, developed in collaboration with my college professor, Geoffrey Luke. Our research explores how an IR-SDE–based diffusion model can enhance ultrasound image quality by reducing speckle while preserving fine anatomical details. The lecture presentation will be led by Prof. Luke on September 18 at 2:30 pm (Netherlands time), as part of session C4L-05: MIS: Deep Learning for Image Reconstruction. The talk is titled “Generalizable Ultrasound Despeckling via Image Restoration Diffusion Method” (paper ID 3405). Looking forward to hearing your thoughts on generative modeling and deep learning for ultrasound imaging!