Neural Network Modeling of Psychoanalytic Concepts

Daniel Saul Levine^1*Ana Maria C Aleksandrowicz²Ana Luiza Verissimo Lopes³

• ¹Psychology, University of Texas at Arlington, Arlington, Texas, United States
• ²Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, Rio de Janeiro, Brazil
• ³Federal University of Rio de Janeiro, Rio de Janeiro, Rio de Janeiro, Brazil

Techniques used over decades in brain-based neural network modeling are applied to understanding processes involved in psychoanalysis. Behavioral change is interpreted as a transition, using simulated annealing, from a less to a more optimal attractor in a competitive-cooperative dynamical system that includes analogs of the amygdala, prefrontal cortex, and hypothalamus, and the neurotransmitter norepinephrine. The article explores how psychoanalysis can facilitate the quest for the life that is as meaningful as possible.The resulting network theory allows for new understanding of several traditional Freudian concepts. The theory provides insights about the life and death drives. It also helps us understand object and narcissistic libido, and the contrast of healthy forms of libido based on autonomy versus unhealthy forms based on dependence. This inquiry relates to the balance between self-interest and empathy, mediated by various areas of the limbic system. It illuminates transference, which involves both an emotional and intellectual relationship between the analyst and analysand, mediated by cognitiveemotional interactions in amygdala and orbitofrontal cortex. Sublimation, or redirection of socially inappropriate urges toward more appropriate behaviors, is interpreted via lateral inhibition between representations of similar complex behaviors.