Orpella, JoanAssaneo, M FlorenciaRipollés, PabloNoejovich, LauraLópez-Barroso, DianaDiego-Balaguer, Ruth dePoeppel, David2024-02-272024-02-272022-07-06http://hdl.handle.net/10668/20411http://hdl.handle.net/20.500.12105/18703People 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, activation of this frontoparietal network is related to a boost in learning performance, and interference with this network via articulatory suppression (AS; i.e., producing irrelevant speech during learning) normalizes performance across the entire sample. Our work provides novel insights on SL from speech and reconciles previous contrasting findings. These findings also highlight a more general need to factor in fundamental individual differences for a precise characterization of cognitive phenomena.engVoRBrain MappingHumansMagnetic Resonance ImagingSpeechSpeech PerceptionAttribution 4.0 International35793349207e300171210.1371/journal.pbio.30017121545-7885PLoS biologyopen access