A study of the plastic kuramoto model and its capacity to simulate mental synthesis

Abstract

Mental synthesis is the human ability to purposefully form novel mental imagery by combining memories of different modalities. The neuronal mechanisms that facilitate this process remain poorly understood. Mental synthesis is hypothesised to occur when memory encoding neuronal ensembles are synchronised while retaining aspects of the memories they encode. Presently, there is no mathematical model of such a process. In this study, we develop such a model by extending a plastic Kuramoto model with coupling that evolves via Hebbian learning. We construct neuronal ensembles with sparse random coupling and investigate the synchronisation of two such ensembles. Numerical simulations show that random coupling extends the parameter space supporting memory-encoding patterns and allows ensembles to synchronise while retaining features of their representations. This result suggests that memory encoding ensembles can be synchronised while retaining features of the memories they encode, representing the first step toward a mathematical model of mental synthesis.