Pre-stimulus beta-band activity is a signature of statistical learning

Abstract

Statistical learning (SL) is taken to be the main mechanism by which cognitive systems discover the underlying regularities of the environment. We document, in the context of a classical visual SL task, divergent rhythmic EEG activity during the anticipation of stimuli within patterns versus pattern transitions. Our findings reveal differential pre-stimulus oscillatory activity in the beta band ([~]20 Hz) 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 prediction. Significance StatementSL has become a major theoretical construct in cognitive science, providing the primary means by which organisms learn about regularities in the environment. As such it is a critical building block for basic and higher-order cognitive functions. Here we identify for the first time a spectral neural index in the time window prior to stimulus presentation, which evolves with increased pattern exposure, and is predictive of learning performance. The manifestation of learning that is revealed not in stimulus processing but in anticipatory moments of the learning episode, makes a direct link between the fields of statistical learning and predictive processing, and suggests a possible mechanistic account of visual SL.