2026-06-14T03:38:16Zhttps://repisalud.isciii.es/rest/oai/request

oai:repisalud.isciii.es:20.500.12105/187032024-09-21T22:05:57Zcom_20.500.12105_15322com_20.500.12105_2051col_20.500.12105_16927col_20.500.12105_16962

00925njm 22002777a 4500 dc Orpella, Joan author Assaneo, M Florencia author Ripollés, Pablo author Noejovich, Laura author López-Barroso, Diana author Diego-Balaguer, Ruth de author Poeppel, David author 2022-07-06 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, 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. 10.1371/journal.pbio.3001712 1545-7885 PLoS biology http://hdl.handle.net/10668/20411 35793349 http://hdl.handle.net/20.500.12105/18703 Differential activation of a frontoparietal network explains population-level differences in statistical learning from speech.