On Brain as a Mathematical Manifold: Neural Manifolds, Sheaf Semantics, and Leibnizian Harmony
Takao Inoué
TL;DR
The paper addresses how to interpret the relation between local neural functions and global cognition within a precise semantic framework. It models local functions as sections of a neural sheaf over a brain-related space, with global coherence requiring a global section and obstructions captured by $H^1(\mathcal{B},\mathcal{F})$. The main contributions include a rigorous sheaf-theoretic interpretation of neural manifolds, a cohomological classification of brain pathology as global integration failures, and a Leibnizian philosophical framing that links monads, atlases, and pre-established harmony. This framework provides a mathematically principled language for discussing cognitive unity and its disruption, promoting interdisciplinary dialogue among neuroscience, mathematics, and philosophy of mind.
Abstract
We present a mathematical and philosophical framework in which brain function is modeled using sheaf theory over neural state spaces. Local neural or cognitive functions are represented as sections of a sheaf, while global coherence corresponds to the existence of global sections. Brain pathologies are interpreted as obstructions to such global integration and are classified using tools from sheaf cohomology. The framework builds on the neural manifold program in contemporary neuroscience and on standard results in sheaf theory, and is further interpreted through a Leibnizian lens \cite{Churchland2012, Leibniz1714, MacLaneMoerdijk, Perich2025}. This paper is intended as a conceptual and formal proposal rather than a complete empirical theory.
