Beta-Band Activity Is a Signature of Statistical Learning

First published August 21, 2020.Through statistical learning (SL), cognitive systems may discover the underlying regularities in the environment. Testing human adults (n = 35, 21 females), we document, in the context of a classical visual SL task, divergent rhythmic EEG activity in the interstimulus delay periods within patterns versus between patterns (i.e., pattern transitions). Our findings reveal increased oscillatory activity in the beta band (;20 Hz) at triplet transitions that indexes learning: it emerges with increased pattern repetitions; and importantly, it is highly correlated with behavioral learning outcomes. These findings hold the promise of converging on an online measure of learning regularities and provide important theoretical insights regarding the mechanisms of SL and predictionThis work was supported by ERC Advanced Grant Project 692502-L2STAT to R.F., Marie Skłodowska-Curie Grant 743528 (IF-EF, European Union’s Horizon 2020 Research and Innovation Program) to L.B., the Basque Government BERC 2018-2021 program, and the Spanish State Research Agency BCBL Severo Ochoa excellence accreditation SEV-2015-0490