16 research outputs found
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
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
Parent Language Input Prior to School Forecasts Change in Children's Language-Related Cortical Structures During Mid-Adolescence.
Children differ widely in their early language development, and this variability has important implications for later life outcomes. Parent language input is a strong experiential factor predicting the variability in children's early language skills. However, little is known about the brain or cognitive mechanisms that underlie the relationship. In addressing this gap, we used longitudinal data spanning 15 years to examine the role of early parental language input that children receive during preschool years in the development of brain structures that support language processing during school years. Using naturalistic parent-child interactions, we measured parental language input (amount and complexity) to children between the ages of 18 and 42 months (n = 23). We then assessed longitudinal changes in children's cortical thickness measured at five time points between 9 and 16 years of age. We focused on specific regions of interest (ROIs) that have been shown to play a role in language processing. Our results support the view that, even after accounting for important covariates such as parental intelligence quotient (IQ) and education, the amount and complexity of language input to a young child prior to school forecasts the rate of change in cortical thickness during the 7-year period from 5½ to 12½ years later. Examining the proximal correlates of change in brain and cognitive differences has the potential to inform targets for effective prevention and intervention strategies