Discovery, Interruption, and Updating of Auditory Regularities in Memory: Evidence from Low-Frequency Brain Dynamics in Human MEG

Abstract

During passive listening, the brain maintains a hierarchy of predictive models to monitor the statistics of its surroundings. The automatic discovery of regular patterns has been associated with a gradual increase in sustained tonic M/EEG activity, sourced in auditory, hippocampal, and frontal areas -- reflecting evidence accumulation and establishment of a regularity model. Conversely, when a regular pattern is interrupted, the sustained activity drops -- indicating disengagement from the model. However, how such models are established in and retrieved from memory as well as the conditions under which they are activated and interrupted remain underexplored. In this MEG experiment (N=26; both sexes), we examined how neural responses related to model establishment and interruption are influenced by (1) the rate of stimulus presentation (tone presentation rate 20 Hz vs. 40 Hz), and (2) the novelty of the experienced acoustic structure (novel vs resumed REG pattern). The results show that (1) the dynamics of model interruption and establishment are independent of stimulus presentation rate, and that (2) model establishment occurred much faster when an experienced vs novel pattern was presented after pattern interruption, suggesting re-activation of the stored original model facilitated by the hippocampus. (3) Finally, sustained response rises in response to pattern establishment and interruption were localized in auditory, hippocampal, and frontal sources, supporting top-down model information flow. These results unveil the temporal dynamics and neural network underlying the brains construction and selection of predictive models to monitor changes in sensory statistics. Significance statementSustained neural activity in response to statistical shifts in auditory sequences reflects how the brain integrates sensory information to build and update predictive models. The present magnetoencephalography (MEG) study aims to uncover the factors that affect this updating. Using tone-pip sequences as a controlled model system, we found that the brain tracks sequence information regardless of tempo and automatically retains a memory of previously encountered patterns, facilitating detection when they re-emerge. Source localization revealed activation in auditory, hippocampal, and frontal areas, highlighting a distributed network involved in top-down model updating and predictive processing. These findings provide new insights into the neural mechanisms of statistical learning and memory, revealing how the brain adapts perception in dynamic environments.