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The role of the Speech-Motor Network in implicit linguistic learning, an fMRI study

Poster Session E - Monday, March 31, 2025, 2:30 – 4:30 pm EDT, Back Bay Ballroom/Republic Ballroom

Anna Ciriello¹ (ciriello.a@northeastern.edu), Amanda O'Brien^2,3, Zhenghan Qi¹, John Gabrieli²; ¹Northeastern University, ²Massachusetts Institute of Technology, ³Harvard University

Recently in language learning literature, there has been an interest in the interactions between auditory language learning networks and speech-motor networks. Assaneo et al. (2018) designed the spontaneous synchronization to speech task (SSS) and found an intrinsic speech-motor rhythm that is related to implicit learning of embedded speech patterns. However, we still do not know how the speech production network is involved during different stages of language learning Thus, in the current fMRI study, we ask whether areas active during our speech production task are engaged during learning across synchronization profiles (e.g., high vs. low). Neurotypical adults’ (N=48) completed a novel speech production task and an implicit linguistic learning task in an fMRI scanner. We will first examine how the speech production network, defined individually, responds to the embedded linguistic patterns in speech in real time during the learning task. To do this, we will determine the regions of interest (ROIs) for each participant and examine learning-induced brain activation in these regions. Secondly, a subset of participants completed a web-based SSS task (N = 18), where we identified 11 high-synchronizers and 7 low-synchronizers. In an exploratory analysis, we will compare the magnitude of activation in the speech motor network between high and low synchronizers. Our findings will suggest that speech production networks, and their synchrony, play a specific and critical role in auditory statistical learning.

Topic Area: LANGUAGE: Other