Abstract
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.
Highlights
The brain is a learning system that adapts to multiple external phenomena existing in its living environment, including various types of input such as auditory, visual, and somatosensory stimuli, and various learning domains such as music and language
Hasson et al [61] indicated that certain regions or networks perform specific computations of global or summary statistics, which are independent of local statistics (i.e., transitional probabilities (TPs))
Information-theoretical approaches based on higher-order Markov models can be used to understand statistical learning (SL) systems in a form closer to that used for natural language and music, from a perspective of linguistics, musicology, and a unified brain theory such as the free-energy principle [16], including optimisation of action, as well as perception and learning
Summary
The brain is a learning system that adapts to multiple external phenomena existing in its living environment, including various types of input such as auditory, visual, and somatosensory stimuli, and various learning domains such as music and language. The SL phenomenon can partially be supported by a unified brain theory [16] This theory tries to provide a unified account of action and perception, as well as learning under a free-energy principle [17,18], which views several keys of brain theories in the biological (e.g., neural Darwinism), physical (e.g., information theory), and neurophysiological (e.g., predictive coding) sciences. This suggests that several brain theories might be unified within a free-energy framework [19], its capacity to unify different perspectives has yet to be established This theory suggests that the brain models phenomena in its living environment as a hierarchy of dynamical systems that encode a causal chain structure in the sensorium to maintain low entropy [16], and predicts a future state based on the internalized model to minimize sensory reaction and optimize motor action. This article focuses on three themes in SL from the viewpoint of information theory, as well as neuroscience: (1) a mathematical interpretation of SL that can cover music and language and the experimental paradigms that have been used to verify SL; (2) the neural basis underlying SL in adults and children; and (3) the applicability of therapy and pedagogy for humans with learning disabilities and healthy humans
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