Auditory Magnetoencephalographic Frequency-Tagged Responses Mirror the Ongoing Segmentation Processes Underlying Statistical Learning.

Humans are highly sensitive to statistical regularities in their environment. This phenomenon, usually referred as statistical learning, is most often assessed using post-learning behavioural measures that are limited by a lack of sensibility and do not monitor the temporal dynamics of learning. In the present study, we used magnetoencephalographic frequency-tagged responses to investigate the neural sources and temporal development of the ongoing brain activity that supports the detection of regularities embedded in auditory streams. Participants passively listened to statistical streams in which tones were grouped as triplets, and to random streams in which tones were randomly presented. Results show that during exposure to statistical (vs. random) streams, tritone frequency-related responses reflecting the learning of regularities embedded in the stream increased in the left supplementary motor area and left posterior superior temporal sulcus (pSTS), whereas tone frequency-related responses decreased in the right angular gyrus and right pSTS. Tritone frequency-related responses rapidly developed to reach significance after 3 min of exposure. These results suggest that the incidental extraction of novel regularities is subtended by a gradual shift from rhythmic activity reflecting individual tone succession toward rhythmic activity synchronised with triplet presentation, and that these rhythmic processes are subtended by distinct neural sources.

Implicit learning is better at subjectively defined non-optimal time of day.

Individual preferences in morningness-eveningness rhythms modulate temporal fluctuations of cognitive performance over a normal day. Besides enhanced cognitive performance at individual's peak time as derived from morningness-eveningness questionnaires, a few studies have shown increased implicit memory abilities at a non-optimal (NOP) time of day. Various subjective factors might also determine the clock time for high or low cognitive efficiency. Using an artificial grammar learning (AGL) task, we show enhanced implicit learning of high-order information at NOP [vs optimal (OP)] time of day as subjectively defined by participants, irrespective of morningness-eveningness scores. Our results suggest that subjectively defined efficiency periods are a modulating factor in the testing of cognitive functions.