Wedemann2025AMPCSM

Title

Associative Memory Models for Mental Processes: Connections with q-Statistical Mechanics
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Authors

Roseli S. Wedemann, Angel R. Plastino

Affiliations

Instituto de Matematica e Estatistica, Universidade do Estado do Rio de Janeiro (UERJ), Rio de Janeiro, Brazil; CeBio y Departamento de Ciencias Básicas, Universidad Nacional del Noroeste de la Provincia de Buenos Aires (UNNOBA), CONICET, Junin, Argentina.

Abstract

We present here a review of our modelling efforts in recent years based on associative memory, artificial neural networks, to illustrate the main basic mechanisms of neurotic mental behavior as described by Freud. We proposed, that neurotic behavior may be understood as an associative memory process in the brain, and that the symbolic associative process involved in psychoanalytic working-through can be mapped onto a corresponding process of reconfiguration of the neural network. The connection of symbolic processing to sensorial memory traces illustrates a phenomenological view of the mind, where consciousness is deeply rooted in sensorial experience with the environment and the association of symbols to meaning. These associative memory models for mental processes suggest that q-MaxEnt distributions may be relevant for the study of these neural models. We therefore also review our recent work regarding dynamical mechanisms leading to q-MaxEnt distributions in memory neural networks, when these are modeled by nonlinear Fokker-Planck equations.

KeyPhrases

Consciousness, unconsciousness, mental processes, meta-representations, self-organized associative-memory neural networks, entropic measures, generalized statistical mechanics, nonlinear Fokker--Planck equations.

Dates

Created 2025-05-01, presented 2025-06-03, updated 2025-11-11, published 2025-11-13.

Citation

Brainiacs Journal 2025 Volume 6 Issue 1 Edoc X41D74D73
DOI: 10.48085/X41D74D73
NPDS: LINKS/Brainiacs/Wedemann2025AMPCSM