Polar Carno Neural Model for Tumor Localization

This paper introduces a comprehensive framework for modeling neural activity using a Karnaugh-map-inspired (Carno) representation, encoded in binary format for computational efficiency. The approach integrates an 8-state neuron model with polar coordinate mapping, vectorial synaptic aggregation interpreted as electromagnetic vector fields, and multimodal brain imaging data from magnetic resonance imaging (MRI), functional MRI (fMRI), and diffusion tensor imaging (DTI). The model incorporates probabilistic synaptic states, hyperbolic forced states arising from field instabilities, and multidimensional cortical visualizations. Designed for clinical applicability in neurosurgery, the framework facilitates integration with established software platforms such as 3D Slicer and Brainlab, supporting real-time tumor localization, three-dimensional cortical mapping, and AI-assisted simulations for functional-preserving surgical interventions.