Speech and music shape the listening brain: evidence for shared domain-general mechanisms

Are there bi-directional influences between speech perception and music perception? An answer to this question is essential for understanding the extent to which the speech and music that we hear are processed by domain-general auditory processes and/or by distinct neural auditory mechanisms. This review summarizes a large body of behavioral and neuroscientific findings which suggest that the musical experience of trained musicians does modulate speech processing, and a sparser set of data, largely on pitch processing, which suggest in addition that linguistic experience, in particular learning a tone language, modulates music processing. Although research has focused mostly on music on speech effects, we argue that both directions of influence need to be studied, and conclude that the picture which thus emerges is one of mutual interaction across domains. In particular, it is not simply that experience with spoken language has some effects on music perception, and vice versa, but that because of shared domain-general subcortical and cortical networks, experiences in both domains influence behavior in both domains

Neural basis of speech and language impairments in development: the case of developmental language disorder

Developmental Language Disorder (DLD) is characterized by difficulties in acquiring one’s native language for no apparent reason. While DLD is a common developmental disorder, its neural basis is poorly understood. In this chapter, the authors will provide an overview of neuroimaging studies that investigated brain function and structure of children with DLD using magnetic resonance imaging (MRI). Under-activation in the left fronto-temporal cortex during language processing, atypical grey matter structure in the basal ganglia, and microstructural differences in dorsal fronto-temporal white matter connections are among the more consistent literature findings, although the overall picture that emerges is far from complete. The authors conclude that, moving forward, the field needs a paradigm shift from studies attempting to find a one-to-one brain region-to-behavior mapping to large-scale studies and approaches that take into consideration the brain as a network as well as the dimensionality and complexity within the disorder

Mean group performance for Pitch Interval and Rhythm Pattern Identification.

<p>Error bars represent standard error of the mean.</p

Steady contour pitch sequence task depiction: the second sequence differs from the first in the 2nd tone which has a different frequency but does not violate the contour.

<p>Steady contour pitch sequence task depiction: the second sequence differs from the first in the 2nd tone which has a different frequency but does not violate the contour.</p

(A) RTs for the Melodic Interval Speeded Classification task and (B) RTs for the Phonological Speeded Classification task in the Redundant (Redun), Baseline (Base) and Orthogonal (Ortho) Conditions.

<p>Error bars represent standard error of the mean.</p

(A) Pitch-change detection and pitch-direction discrimination mean group accuracies. (B) Mean group performance for the steady-contour pitch sequence tasks (simple and transposed).

<p>Error bars represent standard error of the mean.</p

The pace of vocabulary growth during preschool predicts cortical structure at school age

Children vary greatly in their vocabulary development during preschool years. Importantly, the pace of this early vocabulary growth predicts vocabulary size at school entrance. Despite its importance for later academic success, not much is known about the relation between individual differences in early vocabulary development and later brain structure and function. Here we examined the association between vocabulary growth in children, as estimated from longitudinal measurements from 14 to 58 months, and individual differences in brain structure measured in 3rd and 4th grade (8-10 years old). Our results show that the pace of vocabulary growth uniquely predicts cortical thickness in the left supramarginal gyrus. Probabilistic tractography revealed that this region is directly connected to the inferior frontal gyrus (pars opercularis) and the ventral premotor cortex, via what is most probably the superior longitudinal fasciculus III. Our findings demonstrate, for the first time, the relation between the pace of vocabulary learning in children and a specific change in the structure of the cerebral cortex, specifically, cortical thickness in the left supramarginal gyrus. They also highlight the fact that differences in the pace of vocabulary growth are associated with the dorsal language stream, which is thought to support speech perception and articulation

(A) RTs for the Melodic Interval Speeded Classification task and (B) RTs for the Phonological Speeded Classification task in the Redundant (Redun), Baseline (Base) and Orthogonal (Ortho) Conditions.

<p>Error bars represent standard error of the mean.</p