Research Paper: Intracranial EEG Signals Disentangle Multi-Areal Neural Dynamics of Vicarious Pain Perception Authors: Huixin Tan, Xiaoyu Zeng, Jun Ni, Kun Liang, and colleagues Published: 2024 Journal: Nature Communications, Volume 15, Article 5203 DOI: https://doi.org/10.1038/s41467-024-49541-1 Introduction: How Does the Brain Experience Someone Else's Pain? Have you ever wondered why watching another person experience pain can generate an emotional response within your own brain? Why do we sometimes feel discomfort, sadness, or even pain when witnessing someone else's suffering? This phenomenon is known as empathy for pain , or vicarious pain perception. Empathy is one of the most sophisticated functions of the human nervous system. It involves the integration of sensory information, emotional processing, cognitive interpretation, and motivational responses. Although previous neuroimaging studies identified several brain regions associated with empathy, unders...
Energy Manifold Natural Gradient Descent: From Riemannian Optimization to Modern Neuroscience, NeuroAI and Quantum Physics
When Geometry, Energy, Artificial Intelligence and Neuroscience Converge Modern Artificial Intelligence is rapidly moving beyond the idea that learning simply means minimizing an error function. Increasingly, researchers are asking a deeper question: what is the structure of the space in which learning takes place? This question becomes particularly important when the system being modelled is constrained, nonlinear, dynamic, or governed by physical principles. A recent work titled “Energy Manifold Natural Gradient Descent: Riemannian Optimization for Neural PDE Solvers” , by Zhangyong Liang and Huanhuan Gao, introduces Energy Manifold Natural Gradient Descent (EMNGD) , a mathematical framework that extends energy-based natural-gradient optimization from unconstrained Euclidean parameter spaces to constrained Riemannian parameter manifolds . At its core, the framework proposes a simple but powerful principle: An optimization algorithm should not only determine how to reduce error; it sh...