Search Abstracts | Symposia | Slide Sessions | Poster Sessions
Grey matter volume is associated with language performance in children with diverse language development profiles
Poster Session B, Friday, October 25, 10:00 - 11:30 am, Great Hall 3 and 4
Elizaveta Dmitrova1, Tatyana Bolgina2, Militina Gomozova2, Tatyana Zhilyaeva3,4, Ulyana Nasonova3, Olesya Klekochko3, Evgenij Klyuev3, Olga Dragoy2,5; 1Higher School of Economics, Nizhny Novgorod, Russia, 2Higher School of Economics, Moscow, Russia, 3Privolzhsky Research Medical University, Nizhny Novgorod, Russia, 4V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology, St. Petersburg, Russia, 5Institute of Linguistics, Russian Academy of Sciences, Moscow, Russia
Introduction: Previous studies on neural correlates of language disorders, such as developmental language disorder (DLD) and speech sound disorder (SSD), assessed the brain structural differences between participants in groups according to the diagnosis (Badcock et al., 2012; Girbau-Massana et al., 2014; Pigdon et al., 2019). However, taking into consideration the variability of language and behavioural performance in these disorders and debates on the diagnostic criteria (Gomozova et al., 2024; Lancaster & Camarata, 2019; Stringer et al., 2023), we attempted to study language outcomes and their associations with grey matter alterations in a group of Russian-speaking children with diverse language development profiles. Methods: Fifty children participated in the study (18 females, M(age)=6.4, SD(age)=0.4): 25 typically developing children, nine children with DLD, and 16 children with SSD. Firstly, to measure language and speech abilities of each child a face-to-face assessment was performed with the Russian Child Language Assessment Battery (RuCLAB) (Arutiunian et al., 2022). This standardised battery consisted of 11 subtests on language comprehension and speech production, which allows for a complex analysis of language skills. Each subtest’s data were transcribed (for production subtests) and scored, resulting in 11 language scores (in percentage of correct answers) for a child. These data were further included into the voxel-based morphometry (VBM) analysis. Secondly, each participant underwent structural MRI scanning to obtain T1-weighted MRI image (1.5T Siemens Essenza scanner, with TR/TE, 1900/3.37 ms; 1 x 1 x 1 mm3 voxels, 256 x 256 mm field of view; 176 axial slices). The VBM analysis (Ashburner & Friston, 2000, 2003) was performed in the SPM12 toolbox (https://fil.ion.ucl.ac.uk/spm/software/spm12/) in MATLAB, R2023a (The MathWorks Inc., 2023). Age, gender and language scores of each subtest of the RuCLAB were added as covariates in multiple regression models. Results: The results of the VBM analysis revealed increased grey matter volume (GMV) (significant at the FWE-corrected level, p<.05, cluster-size threshold k=20 voxels) associated with higher language scores in the RuCLAB subtests assessing verb comprehension (cluster in the left putamen, peak-level p=.01, size=39 voxels), sentence comprehension (cluster in the left medial superior frontal gyrus, peak-level p=.02, size=33 voxels) and object naming (cluster in the right caudate, peak-level p=.02, size=21 voxels). Conclusion: Our analysis revealed increases in GMV in the putamen and caudate nucleus associated with better performance in the verb comprehension and object naming tasks in a group of children with diverse language development profiles. Structural and functional abnormalities in these regions were reported previously in children with DLD (Badcock et al., 2012) and were proposed to be associated with language learning difficulties due to their involvement in procedural learning processes (Krishnan, Watkins & Bishop, 2016; Ullman & Pierpont, 2005). Our results go in line with previous studies and highlight the involvement of the striatum in language development, however, more research is needed to better understand the findings.
Topic Areas: Disorders: Developmental, Language Development/Acquisition