Neural representation of association strength and prediction error during novel symbol-speech sounds learning

Abstract

Efficient learning of letters-speech sound associations leads to specialization of visual and audiovisual brain regions and is necessary to develop adequate reading skills. We still do not understand the brain dynamics of this learning process, and the involvement of learning and performance monitoring networks is still underexplored. Here we examined a feedback learning task with two mutually dependent parts in which novel symbol-speech sound associations were learned by 39 healthy adults. We used functional magnetic resonance (fMRI) and a reinforcement learning drift diffusion model that described learning across trials. The model-based analysis showed that posterior-occipital activations during stimulus processing were positively modulated by the trial-by-trial learning, described by the increase in association strength of each audiovisual pair. Prediction errors, describing the update mechanism to learn with feedback across trials, modulated activations in several mid-frontal, striatal and cingulate regions. The two task parts yielded a similar pattern of results although they varied in their relative difficulty. This study demonstrates which processes during audiovisual learning contribute to the rapid visual specialization within an experimental session and delineates a set of coactivated regions engaged in learning from feedback. Our paradigm provides a framework to advance our understanding of the neurobiology of learning and reading development.