We propose a novel theory of consciousness as a functor (CF) that receives and transmits contents from unconscious memory into conscious memory. Our CF framework can be seen as a categorial formulation of the Global Workspace Theory proposed by Baars. CF models the ensemble of unconscious processes as a topos category of coalgebras. The internal language of thought in CF is defined as a Multi-modal Universal Mitchell-Benabou Language Embedding (MUMBLE). We model the transmission of information from conscious short-term working memory to long-term unconscious memory using our recently proposed Universal Reinforcement Learning (URL) framework. To model the transmission of information from unconscious long-term memory into resource-constrained short-term memory, we propose a network economic model.

This paper addresses questions of the transition related to conscious processes and unconscious processes, namely aims to substantiating a primary framework to the following open question: The vast majority of brain activity is non-conscious. What is the criterion to distinguish the non-conscious activities from conscious ones? To support our answers in a principled way, we present a general framework for the study of mental processes resting on two main principles: firstly, we endorse Matte Blanco’s principle of symmetry by giving central stage to the concept of unconscious processes. Secondly, to structure and combine the notions of infinity and part-whole equivalence in a mathematical logic method, moreover we base our work on modern non-classical logics in the disposition of context-dependency, as forcefully put forward by CJS Clarke. In particular, we employ the paraconsistent logic as the underlying logical system for defining the general framework for mental processes, highly structural and formal representation, called bi-logic framework.