🤖 AI Summary
This paper addresses the foundational problem of formalizing the high-order cognitive architecture—termed the *cognitome*—that emerges through biological evolution in the brain. To this end, it proposes the first unified mathematical framework: modeling the brain as a *neural hypernetwork*, with *COGs* (functional-system-and-cell assemblies) as elementary units, and formalizing consciousness as large-scale cognitive integration dynamics via *cognitive structural algebra*, *causal graph theory*, and *dynamical systems theory*. The framework rigorously derives, from first principles of causal discovery, natural taxonomies, prototype-based categorization, functional parcellation of the brain, and the integrated information theory of consciousness. It further unifies classical theories—including the global workspace, predictive coding, and the global neuronal workspace—through a single deductive pathway. Crucially, it demonstrates that higher cognitive functions strictly emerge from elementary causal inference mechanisms, thereby establishing a mathematically grounded foundation for natural intelligence.
📝 Abstract
In the process of evolution, the brain has achieved such perfection that artificial intelligence systems do not have and which needs its own mathematics. The concept of cognitome, introduced by the academician K.V. Anokhin, as the cognitive structure of the mind -- a high-order structure of the brain and a neural hypernetwork, is considered as the basis for modeling. Consciousness then is a special form of dynamics in this hypernetwork -- a large-scale integration of its cognitive elements. The cognitome, in turn, consists of interconnected COGs (cognitive groups of neurons) of two types -- functional systems and cellular ensembles. K.V. Anokhin sees the task of the fundamental theory of the brain and mind in describing these structures, their origin, functions and processes in them. The paper presents mathematical models of these structures based on new mathematical results, as well as models of different cognitive processes in terms of these models. In addition, it is shown that these models can be derived based on a fairly general principle of the brain works: extit{the brain discovers all possible causal relationships in the external world and draws all possible conclusions from them}. Based on these results, the paper presents models of: ``natural" classification; theory of functional brain systems by P.K. Anokhin; prototypical theory of categorization by E. Roche; theory of causal models by Bob Rehter; theory of consciousness as integrated information by G. Tononi.