a b s t r a c tWe investigated how the statistical learning of auditory sequences is reflected in neuromagnetic responses in implicit and explicit learning conditions. Complex tones with fundamental frequencies (F0s) in a five-tone equal temperament were generated by a formant synthesizer. The tones were subsequently ordered with the constraint that the probability of the forthcoming tone was statistically defined (80% for one tone; 5% for the other four) by the latest two successive tones (second-order Markov chains). The tone sequence consisted of 500 tones and 250 successive tones with a relative shift of F0s based on the same Markov transitional matrix. In explicit and implicit learning conditions, neuromagnetic responses to the tone sequence were recorded from fourteen right-handed participants. The temporal profiles of the N1m responses to the tones with higher and lower transitional probabilities were compared. In the explicit learning condition, the N1m responses to tones with higher transitional probability were significantly decreased compared with responses to tones with lower transitional probability in the latter half of the 500-tone sequence. Furthermore, this difference was retained even after the F0s were relatively shifted. In the implicit learning condition, N1m responses to tones with higher transitional probability were significantly decreased only for the 250 tones following the relative shift of F0s. The delayed detection of learning effects across the sound-spectral shift in the implicit condition may imply that learning may progress earlier in explicit learning conditions than in implicit learning conditions. The finding that the learning effects were retained across spectral shifts regardless of the learning modality indicates that relative pitch processing may be an essential ability for humans.

Statistical learning (SL) is a method of learning based on the transitional probabilities embedded in sequential phenomena such as music and language. It has been considered an implicit and domain-general mechanism that is innate in the human brain and that functions independently of intention to learn and awareness of what has been learned. SL is an interdisciplinary notion that incorporates information technology, artificial intelligence, musicology, and linguistics, as well as psychology and neuroscience. A body of recent study has suggested that SL can be reflected in neurophysiological responses based on the framework of information theory. This paper reviews a range of work on SL in adults and children that suggests overlapping and independent neural correlations in music and language, and that indicates disability of SL. Furthermore, this article discusses the relationships between the order of transitional probabilities (TPs) (i.e., hierarchy of local statistics) and entropy (i.e., global statistics) regarding SL strategies in human’s brains; claims importance of information-theoretical approaches to understand domain-general, higher-order, and global SL covering both real-world music and language; and proposes promising approaches for the application of therapy and pedagogy from various perspectives of psychology, neuroscience, computational studies, musicology, and linguistics.

a b s t r a c tIn our previous study (Daikoku, Yatomi, & Yumoto, 2014), we demonstrated that the N1m response could be a marker for the statistical learning process of pitch sequence, in which each tone was ordered by a Markov stochastic model. The aim of the present study was to investigate how the statistical learning of music-and language-like auditory sequences is reflected in the N1m responses based on the assumption that both language and music share domain generality. By using vowel sounds generated by a formant synthesizer, we devised music-and language-like auditory sequences in which higher-ordered transitional rules were embedded according to a Markov stochastic model by controlling fundamental (F0) and/or formant frequencies (F1-F2). In each sequence, F0 and/or F1-F2 were spectrally shifted in the last one-third of the tone sequence. Neuromagnetic responses to the tone sequences were recorded from 14 right-handed normal volunteers. In the music-and language-like sequences with pitch change, the N1m responses to the tones that appeared with higher transitional probability were significantly decreased compared with the responses to the tones that appeared with lower transitional probability within the first two-thirds of each sequence. Moreover, the amplitude difference was even retained within the last one-third of the sequence after the spectral shifts. However, in the language-like sequence without pitch change, no significant difference could be detected. The pitch change may facilitate the statistical learning in language and music. Statistically acquired knowledge may be appropriated to process altered auditory sequences with spectral shifts. The relative processing of spectral sequences may be a domain-general auditory mechanism that is innate to humans.

How do listeners respond to prediction errors within patterned sequence of sounds? To answer this question we carried out a statistical learning study using electroencephalography (EEG). In a continuous auditory stream of sound triplets the deviations were either (a) statistical, in terms of transitional probability, (b) physical, due to a change in sound location (left or right speaker) or (c) a double deviants, i.e. a combination of the two. Statistical and physical deviants elicited a statistical mismatch negativity and a physical MMN respectively. Most importantly, we found that effects of statistical and physical deviants interacted (the statistical MMN was smaller when co-occurring with a physical deviant). Results show, for the first time, that processing of prediction errors due to statistical learning is affected by prediction errors due to physical deviance. Our findings thus show that the statistical MMN interacts with the physical MMN, implying that prediction error processing due to physical sound attributes suppresses processing of learned statistical properties of sounds.

a b s t r a c tThe present study investigated whether neural responses could demonstrate the statistical learning of chord sequences and how the perception underlying a pitch class can affect the statistical learning of chord sequences. Neuromagnetic responses to two chord sequences of augmented triads that were presented every 0.5 s were recorded from fourteen right-handed participants. One sequence was a series of 360 chord triplets, each of which consisted of three chords in the same pitch class (clustered pitch-classes sequences). The other sequence was a series of 360 chord triplets, each of which consisted of three chords in different pitch classes (dispersed pitch-classes sequences). The order of the triplets was constrained by a first-order Markov stochastic model such that a forthcoming triplet was statistically defined by the most recent triplet (80% for one; 20% for the other two). We performed a repeated-measures ANOVA with the peak amplitude and latency of the P1m, N1m and P2m. In the clustered pitch-classes sequences, the P1m responses to the triplets that appeared with higher transitional probability were significantly reduced compared with those with lower transitional probability, whereas no significant result was detected in the dispersed pitch-classes sequences. Neuromagnetic significance was concordant with the results of familiarity interviews conducted after each learning session. The P1m response is a useful index for the statistical learning of chord sequences. Domain-specific perception based on the pitch class may facilitate the domain-general statistical learning of chord sequences.

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When we are exposed to a novel stimulus sequence, we can learn the sequence by extracting a statistical structure that is potentially embedded in the sequence. This mechanism is called statistical learning, and is considered a fundamental and domain-general process that is innate in humans. In the real-world environment, humans are inevitably exposed to auditory sequences that often overlap with one another, such as speech sound streams from multiple speakers or entangled melody lines generated by multiple instruments. The present study investigated how single and dual attention modulates brain activity, reflecting statistical learning when two auditory sequences were presented simultaneously. The results demonstrated that the effect of statistical learning had more pronounced neural activity when listeners paid attention to only one sequence and ignored the other, rather than paying attention to both sequences. Biased attention may thus be an essential strategy when learners are exposed to multiple information streams.

Human learning is supported by multiple neural mechanisms that maturate at different rates and interact in mostly cooperative but also sometimes competitive ways. We tested the hypothesis that mature cognitive mechanisms constrain implicit statistical learning mechanisms that contribute to early language acquisition. Specifically, we tested the prediction that depleting cognitive control mechanisms in adults enhances their implicit, auditory word-segmentation abilities. Young adults were exposed to continuous streams of syllables that repeated into hidden novel words while watching a silent film. Afterward, learning was measured in a forced-choice test that contrasted hidden words with nonwords. The participants also had to indicate whether they explicitly recalled the word or not in order to dissociate explicit versus implicit knowledge. We additionally measured electroencephalography during exposure to measure neural entrainment to the repeating words. Engagement of the cognitive mechanisms was manipulated by using two methods. In experiment 1 (n = 36), inhibitory theta-burst stimulation (TBS) was applied to the left dorsolateral prefrontal cortex or to a control region. In experiment 2 (n = 60), participants performed a dual working-memory task that induced high or low levels of cognitive fatigue. In both experiments, cognitive depletion enhanced word recognition, especially when participants reported low confidence in remembering the words (i.e., when their knowledge was implicit). TBS additionally modulated neural entrainment to the words and syllables. These findings suggest that cognitive depletion improves the acquisition of linguistic knowledge in adults by unlocking implicit statistical learning mechanisms and support the hypothesis that adult language learning is antagonized by higher cognitive mechanisms.