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Relational Nets Over Attractors, A Primer: Part 1, Design for a Mind, Version 2

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2023-03-16 11:00:04

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Miriam Yevick’s 1975 holographic logic suggests we need both symbols and networks to model the mind. I explore that premise by adapting Sydney Lamb’s relational network notation to represent a logical structure over basins of attraction in a collection of attractor landscapes, each belonging to a different neurofunctional area (NFA) of the cortex. Peter Gärdenfors provides the idea of a conceptual space, a low dimensional projection of the high-dimensional phase space of a NFA. Vygotsky’s account of language acquisition and internalization is used to show how the mind is indexed. We then define a MIND as a relational network of logic gates over the attractor landscape of a neural network loosely partitioned into many NFAs. An INDEXED MIND consists of a GENERAL network and an INDEXING network adjacent to and recursively linked to it. A NATURAL MIND is one where the substrate is the nervous system of a living animal. An ARTIFICIAL MIND is one where the substrate is inanimate matter engineered by humans to be a mind; it becomes AUTONOMOUS when it is able to purchase its compute with services rendered.

Naturalist literary theory conceives of literature as an adaptive behavioral realm grounded in the capacities of the human brain. In the course of human history literature itself has undergone an evolution that has produced many kinds of literary work. In this article I propose nine propositions to characterize a treatment of literary form. These propositions concern neural and mental mechanisms, and literary evolution in history. Textual meaning is elastic - through not infinitely so - and constrained by form. Form indicates the computational structure of the act of reading and is the same for all readers. Over the long term, literary forms become more complex and sophisticated. Slightly revised, 6 August, 2016, with a new appendix about obtaining neural evidence about binary oppositions.