Musical Expertise Boosts Implicit Learning of Both Musical and Linguistic Structures

Clément, François; Schön, Daniele

doi:10.1093/cercor/bhr022

Cited by 128 publications

(114 citation statements)

References 60 publications

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“…This process is not complete until young adulthood, by which time N1 has become the largest component in the cortical response to sound (17,18,(21)(22)(23). In adults, music training amplifies the N1 response (53)(54)(55)(56). Here, we find an increase in N1 amplitude relative to P1 amplitude only in the music group.…”

Section: Discussionmentioning

confidence: 52%

Music training alters the course of adolescent auditory development

Tierney

Krizman

Kraus

2015

Proc. Natl. Acad. Sci. U.S.A.

131

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Fundamental changes in brain structure and function during adolescence are well-characterized, but the extent to which experience modulates adolescent neurodevelopment is not. Musical experience provides an ideal case for examining this question because the influence of music training begun early in life is wellknown. We investigated the effects of in-school music training, previously shown to enhance auditory skills, versus another inschool training program that did not focus on development of auditory skills (active control). We tested adolescents on neural responses to sound and language skills before they entered high school (pretraining) and again 3 y later. Here, we show that inschool music training begun in high school prolongs the stability of subcortical sound processing and accelerates maturation of cortical auditory responses. Although phonological processing improved in both the music training and active control groups, the enhancement was greater in adolescents who underwent music training. Thus, music training initiated as late as adolescence can enhance neural processing of sound and confer benefits for language skills. These results establish the potential for experience-driven brain plasticity during adolescence and demonstrate that in-school programs can engender these changes. music | training | auditory B y age six, the brain has reached 90% of its adult size (1).However, the years between childhood and young adulthood are marked by a host of subtler neural developments. Myelination and synaptic pruning (2-5) lead to a decrease in gray matter and an increase in white matter (6-13). Resting-state oscillations decline (14-16), and passive evoked responses to sound change in complex ways. Cortically, the P1, which is a positive deflection at around 50 ms generated within lateral Heschl's gyrus (17), declines whereas the N1, a negative deflection at around 100 ms generated within primary and secondary auditory cortices (18)(19)(20), increases (21-23). Subcortically, the trial-by-trial consistency of the response declines (24,25). An open question is how experience interacts with this developmental plasticity during adolescence. Is the transition from the plasticity of childhood to the stability of adulthood malleable by experience? And if so, what types of enrichment have the greatest impact on the development of the neural mechanisms contributing to auditory and language skills?Music training is an enrichment program commonly available to high school students, and its neural and behavioral consequences are well-understood (for a review, see ref. 26). Studies comparing nonmusicians with musicians who began training early in life have revealed a "signature" set of enhancements associated with musical experience (27,28). Relative to nonmusician peers, musicians tend to show enhanced speech-innoise perception (29-34), verbal memory (30-33, 35-38), phonological skills (39-45), and reading (46-50), although not without exception (51, 52). Music training has also been linked to enhancements in the enco...

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Section: Discussionmentioning

confidence: 52%

Music training alters the course of adolescent auditory development

Tierney

Krizman

Kraus

2015

Proc. Natl. Acad. Sci. U.S.A.

131

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“…Implicit learning plays an important role in the acquisition of complex structural knowledge, both in language (e.g., Saffran, Aslin, & Newport, 1996;see Kuhl, 2004, for a review) and in music (e.g., Ettlinger, Margulis, & Wong, 2011;Loui, Wu, Wessel, & Knight, 2009;Loui, Wessel, & Husdon Kam, 2010;Loui, 2012;Rohrmeier & Rebuschat, 2012). Support for shared reliance on implicit learning mechanisms comes from the finding that musical training (which presumably places additional demands on implicit learning mechanisms) leads to better implicit learning of both musical and linguistic structure (Francois & Schön, 2011). Working memory has also been linked to processing of syntax in language (e.g., Just & Carpenter, 1992;Lewis et al, 2006) and in music (Koelsch et al, 2009;Schulze et al, 2011;Williamson et al, 2010), and is associated with the inferior frontal regions that are implicated in both domains (Koelsch et al, 2009;Schulze, Zysset, Mueller, Friederici, & Koelsch, 2011; but see Fedorenko et al, 2011).…”

Section: Discussionmentioning

confidence: 99%

Processing structure in language and music: a case for shared reliance on cognitive control

Slevc

Okada

2014

Psychon Bull Rev

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The relationship between structural processing in music and language has received increasing interest in the last several years, spurred by the influential Shared Syntactic Integration Resource Hypothesis (SSIRH;Patel, 2003). According to this resource-sharing framework, music and language rely on separable syntactic representations but recruit shared cognitive resources to integrate these representations into evolving structures. The SSIRH is supported by findings of interactions between structural manipulations in music and language. However, other recent evidence suggests that such interactions can also arise with non-structural manipulations, and some recent neuroimaging studies report largely non-overlapping neural regions involved in processing musical and linguistic structure. These conflicting results raise the question of exactly what shared (and distinct) resources underlie musical and linguistic structural processing. This paper suggests that one shared resource is prefrontal cortical mechanisms of cognitive control, which are recruited to detect and resolve conflict that occurs when expectations are violated and interpretations must be revised. By this account, musical processing involves not just the incremental processing and integration of musical elements as they occur, but also the incremental generation of musical predictions and expectations, which must sometimes be overridden and revised in light of evolving musical input.

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“…While most studies suggested that explicit learning is more effective than implicit learning, these studies measured the learning effects using behavioral tests that may favor explicit learning such as short-term learning. Other studies suggested that the learning effects depend on the learner's prior knowledge (Francois & Schön, 2011;Gass, Svetics, & Lemelin, 2003). Thus, we cannot precisely determine which learning process is more effective (DeKeyser, 2003;Ellis, 2009).…”

Section: Implicit and Explicit Knowledgementioning

confidence: 90%

“…Thus, we cannot precisely determine which learning process is more effective (DeKeyser, 2003;Ellis, 2009). Interestingly, some earlier studies claimed that knowledge of music and language is acquired largely by implicit learning (Ettlinger, Margulis, & Wong, 2011;Francois & Schön, 2011;Krashen, 1982). Reber (1989) argued that implicit learning is the fundamental process that lies at the heart of the adaptive behavioral repertoire of every complex organism, while Dekeyser claimed that implicit learning is essential for adaptation to the environment (Reber, 1993).…”

Section: Implicit and Explicit Knowledgementioning

confidence: 99%

Implicit and explicit statistical learning of tone sequences across spectral shifts

2014

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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.

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Musical Expertise Boosts Implicit Learning of Both Musical and Linguistic Structures

Cited by 128 publications

References 60 publications

Music training alters the course of adolescent auditory development

Music training alters the course of adolescent auditory development

Processing structure in language and music: a case for shared reliance on cognitive control

Implicit and explicit statistical learning of tone sequences across spectral shifts

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