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A hypothesis on improving foreign accents by optimizing variability in vocal learning brain circuits

View Article: PubMed Central

ABSTRACT

Rapid vocal motor learning is observed when acquiring a language in early childhood, or learning to speak another language later in life. Accurate pronunciation is one of the hardest things for late learners to master and they are almost always left with a non-native accent. Here, I propose a novel hypothesis that this accent could be improved by optimizing variability in vocal learning brain circuits during learning. Much of the neurobiology of human vocal motor learning has been inferred from studies on songbirds. Jarvis (2004) proposed the hypothesis that as in songbirds there are two pathways in humans: one for learning speech (the striatal vocal learning pathway), and one for production of previously learnt speech (the motor pathway). Learning new motor sequences necessary for accurate non-native pronunciation is challenging and I argue that in late learners of a foreign language the vocal learning pathway becomes inactive prematurely. The motor pathway is engaged once again and learners maintain their original native motor patterns for producing speech, resulting in speaking with a foreign accent. Further, I argue that variability in neural activity within vocal motor circuitry generates vocal variability that supports accurate non-native pronunciation. Recent theoretical and experimental work on motor learning suggests that variability in the motor movement is necessary for the development of expertise. I propose that there is little trial-by-trial variability when using the motor pathway. When using the vocal learning pathway variability gradually increases, reflecting an exploratory phase in which learners try out different ways of pronouncing words, before decreasing and stabilizing once the “best” performance has been identified. The hypothesis proposed here could be tested using behavioral interventions that optimize variability and engage the vocal learning pathway for longer, with the prediction that this would allow learners to develop new motor patterns that result in more native-like pronunciation.

No MeSH data available.


Motor and vocal learning pathways in songbirds and humans and the role of variability. (A) simplified diagram of the pathways involved in vocal learning and production in songbirds and humans. (i) In songbirds, the vocal motor pathway used for production of established song [shown in red: HVC, RA (robust nucleus of the arcopallium) and brainstem nucleus for vocal output] is used to produce the song. The vocal learning pathway [AFP: anterior forebrain pathway, shown in blue: Area X, dorsolateral nucleus of the medial thalamus (DLM) and LMAN (lateral magnocellular nucleus of the anterior nidopallium)] is used in songbirds during the acquisition of the pattern in song learning. (ii) In humans, the motor pathway (shown in red: laryngeal motor cortex and brainstem nucleus for vocal output), and the vocal learning pathway (shown in blue: anterior striatum, thalamus and premotor cortex). (B) Suggested levels of vocal variability when using the two pathways. I suggest that when using the motor pathway (i), production is stable, with little trial-by-trial variability. When using the vocal learning pathway (ii), trial-by-trial variability gradually increases, reflecting an exploratory phase in which the learners try out different ways of pronouncing the words (‘motor exploration’), before decreasing and stabilizing once the ‘best’ performance has been identified (‘motor exploitation’).
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Figure 2: Motor and vocal learning pathways in songbirds and humans and the role of variability. (A) simplified diagram of the pathways involved in vocal learning and production in songbirds and humans. (i) In songbirds, the vocal motor pathway used for production of established song [shown in red: HVC, RA (robust nucleus of the arcopallium) and brainstem nucleus for vocal output] is used to produce the song. The vocal learning pathway [AFP: anterior forebrain pathway, shown in blue: Area X, dorsolateral nucleus of the medial thalamus (DLM) and LMAN (lateral magnocellular nucleus of the anterior nidopallium)] is used in songbirds during the acquisition of the pattern in song learning. (ii) In humans, the motor pathway (shown in red: laryngeal motor cortex and brainstem nucleus for vocal output), and the vocal learning pathway (shown in blue: anterior striatum, thalamus and premotor cortex). (B) Suggested levels of vocal variability when using the two pathways. I suggest that when using the motor pathway (i), production is stable, with little trial-by-trial variability. When using the vocal learning pathway (ii), trial-by-trial variability gradually increases, reflecting an exploratory phase in which the learners try out different ways of pronouncing the words (‘motor exploration’), before decreasing and stabilizing once the ‘best’ performance has been identified (‘motor exploitation’).

Mentions: In this article I present a hypothesis on how foreign accents could be improved by optimizing variability in vocal learning brain circuits, followed by support for the hypothesis, drawing on the literature on variability in songbird vocal learning and variability in motor learning. The article concludes with approaches for testing the hypothesis.


A hypothesis on improving foreign accents by optimizing variability in vocal learning brain circuits
Motor and vocal learning pathways in songbirds and humans and the role of variability. (A) simplified diagram of the pathways involved in vocal learning and production in songbirds and humans. (i) In songbirds, the vocal motor pathway used for production of established song [shown in red: HVC, RA (robust nucleus of the arcopallium) and brainstem nucleus for vocal output] is used to produce the song. The vocal learning pathway [AFP: anterior forebrain pathway, shown in blue: Area X, dorsolateral nucleus of the medial thalamus (DLM) and LMAN (lateral magnocellular nucleus of the anterior nidopallium)] is used in songbirds during the acquisition of the pattern in song learning. (ii) In humans, the motor pathway (shown in red: laryngeal motor cortex and brainstem nucleus for vocal output), and the vocal learning pathway (shown in blue: anterior striatum, thalamus and premotor cortex). (B) Suggested levels of vocal variability when using the two pathways. I suggest that when using the motor pathway (i), production is stable, with little trial-by-trial variability. When using the vocal learning pathway (ii), trial-by-trial variability gradually increases, reflecting an exploratory phase in which the learners try out different ways of pronouncing the words (‘motor exploration’), before decreasing and stabilizing once the ‘best’ performance has been identified (‘motor exploitation’).
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Figure 2: Motor and vocal learning pathways in songbirds and humans and the role of variability. (A) simplified diagram of the pathways involved in vocal learning and production in songbirds and humans. (i) In songbirds, the vocal motor pathway used for production of established song [shown in red: HVC, RA (robust nucleus of the arcopallium) and brainstem nucleus for vocal output] is used to produce the song. The vocal learning pathway [AFP: anterior forebrain pathway, shown in blue: Area X, dorsolateral nucleus of the medial thalamus (DLM) and LMAN (lateral magnocellular nucleus of the anterior nidopallium)] is used in songbirds during the acquisition of the pattern in song learning. (ii) In humans, the motor pathway (shown in red: laryngeal motor cortex and brainstem nucleus for vocal output), and the vocal learning pathway (shown in blue: anterior striatum, thalamus and premotor cortex). (B) Suggested levels of vocal variability when using the two pathways. I suggest that when using the motor pathway (i), production is stable, with little trial-by-trial variability. When using the vocal learning pathway (ii), trial-by-trial variability gradually increases, reflecting an exploratory phase in which the learners try out different ways of pronouncing the words (‘motor exploration’), before decreasing and stabilizing once the ‘best’ performance has been identified (‘motor exploitation’).
Mentions: In this article I present a hypothesis on how foreign accents could be improved by optimizing variability in vocal learning brain circuits, followed by support for the hypothesis, drawing on the literature on variability in songbird vocal learning and variability in motor learning. The article concludes with approaches for testing the hypothesis.

View Article: PubMed Central

ABSTRACT

Rapid vocal motor learning is observed when acquiring a language in early childhood, or learning to speak another language later in life. Accurate pronunciation is one of the hardest things for late learners to master and they are almost always left with a non-native accent. Here, I propose a novel hypothesis that this accent could be improved by optimizing variability in vocal learning brain circuits during learning. Much of the neurobiology of human vocal motor learning has been inferred from studies on songbirds. Jarvis (2004) proposed the hypothesis that as in songbirds there are two pathways in humans: one for learning speech (the striatal vocal learning pathway), and one for production of previously learnt speech (the motor pathway). Learning new motor sequences necessary for accurate non-native pronunciation is challenging and I argue that in late learners of a foreign language the vocal learning pathway becomes inactive prematurely. The motor pathway is engaged once again and learners maintain their original native motor patterns for producing speech, resulting in speaking with a foreign accent. Further, I argue that variability in neural activity within vocal motor circuitry generates vocal variability that supports accurate non-native pronunciation. Recent theoretical and experimental work on motor learning suggests that variability in the motor movement is necessary for the development of expertise. I propose that there is little trial-by-trial variability when using the motor pathway. When using the vocal learning pathway variability gradually increases, reflecting an exploratory phase in which learners try out different ways of pronouncing words, before decreasing and stabilizing once the “best” performance has been identified. The hypothesis proposed here could be tested using behavioral interventions that optimize variability and engage the vocal learning pathway for longer, with the prediction that this would allow learners to develop new motor patterns that result in more native-like pronunciation.

No MeSH data available.