Differential activation of a frontoparietal network explains population-level differences in statistical learning from speech.

ABSTRACT: People of all ages display the ability to detect and learn from patterns in seemingly random stimuli. Referred to as statistical learning (SL), this process is particularly critical when learning a spoken language, helping in the identification of discrete words within a spoken phrase. Here, by considering individual differences in speech auditory-motor synchronization, we demonstrate that recruitment of a specific neural network supports behavioral differences in SL from speech. While independent component analysis (ICA) of fMRI data revealed that a network of auditory and superior pre/motor regions is universally activated in the process of learning, a frontoparietal network is additionally and selectively engaged by only some individuals (high auditory-motor synchronizers). Importantly,

SUBMITTER: Orpella J 

PROVIDER: S-EPMC9292101 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature