Mediated learning: A computational rendering of ketamine-induced symptoms.
Behavioral neuroscience – June 01, 2024
Source: PubMed
Summary
Ketamine's effects on the brain may help explain how false associations form in conditions like schizophrenia. Using computer modeling, researchers demonstrated how memory retrieval and mental representations interact during learning. The simulations revealed that disrupted processing of indirect associations mirrors symptoms seen in ketamine studies, offering insights into how the brain forms and maintains unusual thought patterns.
Abstract
This article explores the contribution of the double error dynamic asymptote computational associative learning model to understanding the role of mediated learning mechanisms in the generation of spurious associations, as those postulated to characterize schizophrenia. Three sets of simulations for mediated conditioning, mediated extinction, and a mediated enhancement of latent inhibition, a unique model prediction, are presented. For each set of simulations, a parameter that modulates the impact of associative memory retrieval and the dissipation of nonperceptual activated representations through the network was manipulated. The effect of this operation is analyzed and compared to ketamine-induced effects on associative memories and mediated learning. The model's potential to predict these effects and present a plausible error-correction associative mechanism is discussed in the context of animal models of schizophrenia. (PsycInfo Database Record (c) 2024 APA, all rights reserved).