A Brain Marker for Developmental Speech Disorders.
TL;DR: Atypical development of the left corticobulbar tract may be a neural marker for DSD, and changes for language disorders are likely more complex.
Abstract: Objective To characterize the organization of speech- and language-related white matter tracts in children with developmental speech and/or language disorders. Study design We collected magnetic resonance diffusion-weighted imaging data from 41 children, ages 9-11 years, with developmental speech and/or language disorders, and compared them with 45 typically developing controls with the same age range. We used probabilistic tractography of diffusion-weighted imaging to map language (3 segments of arcuate fasciculus, extreme capsule system) and speech motor (corticobulbar) tracts bilaterally. The corticospinal and callosal tracts were used as control regions. We compared the mean fractional anisotropy and diffusivity values between atypical and control groups, covarying for nonverbal IQ. We then examined differences between atypical subgroups: developmental speech disorder (DSD), developmental language disorder, and co-occurring developmental speech and language disorder. Results Fractional anisotropy in the left corticobulbar tract was lower in the DSD than in the control group. Radial and mean diffusivity were higher in the DSD than the developmental language disorder, co-occurring developmental speech and language disorder, or control groups. There were no group differences for any metrics in the language or control tracts. Conclusions Atypical development of the left corticobulbar tract may be a neural marker for DSD. This finding is in line with reports of speech disorder after left corticobulbar damage in children and adults with brain injury. By contrast, we found no association between diffusion metrics in language-related tracts in developmental language disorder, and changes for language disorders are likely more complex.
Summary (2 min read)
- Developmental speech and language disorders are common, seen in 1 in 20 preschool children, in the absence of neurological deficits, intellectual impairment or hearing loss.
- Most recently, diffusion weighted imaging and tractography have become promising tools as measures of white matter organization, allowing us to examine structural brain connectivity in these conditions.
- The dorsal pathway matures at a later stage of development and has been suggested to be involved in more complex language functions.
- Of note, the absence of such findings could be in part because existing studies include highly selected, cross-sectionally recruited, clinical samples (see 10-12 for review), with limited generalizability of findings to the broader DLD population.
- The authors hypothesized developmental speech and language disorders would be associated with atypical development of speech-motor and language (dorsal and ventral streams) tracts, respectively.
- Participants (N = 86, age range: 9.25-11.25 years) were recruited from the Early Language in Victoria Study (ELVS), a longitudinal community-based study of 1900 children.
- Age of scanning was carefully chosen to reflect a time when communication trajectories are relatively stable.
- Some attrition occurred across the 4 and 5 year old waves of the ELVS, hence expanding the DLD inclusion criteria across 2 data waves provided a larger pool for recruitment.
- Articulation disorder could also include an omission error where the phone was absent in the child’s inventory, but it appears in the phonetic inventory of >90% of peers in normative data.22-24 Phonological delay was use of a phonological process that occurs in typically developing speech, but is used beyond an age where it is typically resolved in >90% of peers.
- Exclusion criteria were a history of neurological, hearing, genetic or neurodevelopmental disorders (e.g., autistic spectrum disorder) and non-English speaking background.
- At the time of scanning, participants were assessed with the same speech, language and nonverbal IQ tests reported above for participant group selection (Table 1).
- Standardized scores were used for the CELF-IV26 and WASI.19 Clinical diagnosis of DSD was made based on phonetic transcription and phonological process analysis.
Preprocessing of MRI datasets
- DWI datasets were pre-processed using MRtrix.27 Fractional anisotropy (FA) and eigenvector maps were extracted.
- Constrained spherical deconvolution was used to estimate the distribution of fiber orientations.
- This is an optimal method relative to the diffusion tensor model, in areas with multiple crossing fibers.
- Conventional MRI scans were confirmed to be normal.
- Tractography delineated all tracts in all participants, with the exception of 8 instances in which no streamlines were generated for the posterior segment of the AF (TD=4, DLD=1, DSD=3, DSLD=3).
- Consistent with this finding, univariate analyses also revealed trends for a group difference and group by hemisphere effect for the CBT only.
- Post-hoc tests showed that FA in the left CBT was significantly different between DSD and TD groups only (Bonferroni corrected p=.045).
- The 4 groups were matched for demographic characteristics (Table 1).
- Non-verbal IQ scores, although within the typical range, were lower in DLD children than in children with DSD as commonly reported in this group.
- Children with DSLD had a more phonological presentation at age 4 but by age 9-11, at time of scanning, the majority of this group also had articulation errors.
- Slightly more participants in the DSD (72%) than DSLD (64%) group had articulation errors at time of scanning.
- The authors report the first association between developmental speech disorder and reduced FA of the left corticobulbar tract, suggesting atypical development of this tract may be a neural marker for DSD.
- Altered connectivity of the left CBT has previously been associated with speech disorder in different childhood populations and disease models including childhood stuttering14 and dysarthria after childhood traumatic brain injury.
- 10-12 Methodological approaches unique to this study represented important methodological strengths in the study of potential neural markers.
- These included longitudinally-informed selection of participants from a community cohort, within a narrow age range, and co-varying for NVIQ.
- The authors thank all participants and their families for their time and support.
- The authors also thank J.-D.T. for helpful input regarding MRTrix, Lauren Pigdon (Murdoch Children’s Research Institute, Melbourne; nil relevant funding sources and nil conflicts of interest) for data collection and Shawna Farquharson (Florey Institute of Neuroscience and Mental Health Melbourne; nil relevant funding sources and nil conflicts of interest) and her team of radiographers for scanning participants.
- AM, SR, and AC are grateful to the Operational Infrastructure Support Program of the State Government of Victoria for their support.
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Cites background from "A Brain Marker for Developmental Sp..."
...Note that some participants in this study were also included in structural MRI focused publications (Kurth et al., 2018; Luders et al., 2017; Morgan et al., 2018)....
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Q1. What contributions have the authors mentioned in the paper "A brain marker for developmental speech disorder short title: a brain marker for developmental speech disorder" ?
This paper examined white matter connectivity in children with DLD, DSD and typically developing controls, using diffusion weighted imaging and tractography to examine structural brain connectivity in these conditions.