Traces of statistical learning in the brain's functional connectivity after artificial language exposure

Pallabi Sengupta*, Miguel Burgaleta, Gorka Zamora-López, Anna Basora Marimon, Ana Sanjuan, Gustavo Deco, Núria Sebastián-Gallés

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Our environment is full of statistical regularities, and we are attuned to learn about these regularities by employing Statistical Learning (SL), a domain-general ability that enables the implicit detection of probabilistic regularities in our surrounding environment. The role of brain connectivity on SL has been previously explored, highlighting the relevance of structural and functional connections between frontal, parietal, and temporal cortices. However, whether SL can induce changes in the functional connections of the resting state brain has yet to be investigated. To address this question, we applied a pre-post design where participants (n = 38) were submitted to resting-state fMRI acquisition before and after in-scanner exposure to either an artificial language stream (formed by 4 concatenated words) or a random audio stream. Our results showed that exposure to an artificial language stream significantly changed (corrected p < 0.05) the functional connectivity between Right Posterior Cingulum and Left Superior Parietal Lobule. This suggests that functional connectivity between brain networks supporting attentional and working memory processes may play an important role in statistical learning.

Original languageEnglish
Pages (from-to)246-253
Number of pages8
Publication statusPublished - 18 Feb 2019
Externally publishedYes

Bibliographical note

Funding Information:
This research was supported by grants from the European Community's Seventh Framework Programme (FP7/2007-2013): ERG grant agreement number 323961 (Under Control); the Spanish Ministerio de Economía y Competitividad ( PSI2015-66918-P ) and the Catalan Government (SGR 2014–1210 ). Miguel Burgaleta is funded by the Juan de la Cierva Incorporación grant ( IJCI-2015- 25056 ). GZL and GD are supported by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 720270 (HBP SGA1).

Publisher Copyright:
© 2018 Elsevier Ltd


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