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. 2022:33:102910.
doi: 10.1016/j.nicl.2021.102910. Epub 2021 Dec 6.

Multimodal MRI cerebral correlates of verbal fluency switching and its impairment in women with depression

L Domain  1 , M Guillery  1 , N Linz  2 , A König  3 , J M Batail  1 , R David  4 , I Corouge  5 , E Bannier  5 , J C Ferré  5 , T Dondaine  6 , D Drapier  1 , G H Robert  7
Affiliations

Multimodal MRI cerebral correlates of verbal fluency switching and its impairment in women with depression

L Domain et al. Neuroimage Clin. 2022.

Abstract

Background: The search of biomarkers in the field of depression requires easy implementable tests that are biologically rooted. Qualitative analysis of verbal fluency tests (VFT) are good candidates, but its cerebral correlates are unknown.

Methods: We collected qualitative semantic and phonemic VFT scores along with grey and white matter anatomical MRI of depressed (n = 26) and healthy controls (HC, n = 25) women. Qualitative VFT variables are the "clustering score" (i.e. the ability to produce words within subcategories) and the "switching score" (i.e. the ability to switch between clusters). The clustering and switching scores were automatically calculated using a data-driven approach. Brain measures were cortical thickness (CT) and fractional anisotropy (FA). We tested for associations between CT, FA and qualitative VFT variables within each group.

Results: Patients had reduced switching VFT scores compared to HC. Thicker cortex was associated with better switching score in semantic VFT bilaterally in the frontal (superior, rostral middle and inferior gyri), parietal (inferior parietal lobule including the supramarginal gyri), temporal (transverse and fusiform gyri) and occipital (lingual gyri) lobes in the depressed group. Positive association between FA and the switching score in semantic VFT was retrieved in depressed patients within the corpus callosum, right inferior fronto-occipital fasciculus, right superior longitudinal fasciculus extending to the anterior thalamic radiation (all p < 0.05, corrected).

Conclusion: Together, these results suggest that automatic qualitative VFT scores are associated with brain anatomy and reinforce its potential use as a surrogate for depression cerebral bases.

Keywords: Automatic speech analysis; Cortical Thickness; Fractional Anisotropy; Major depressive disorder; Switching; Verbal fluency.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Scatter dot plots of the switching and clustering scores stratified by groups and phonemic and semantic VFT.
Fig. 2
Fig. 2
Regions showing significant positive correlations between switching score during the semantic VFT and CT within the MDD group (age considered as covariate). FDR corrected group by CT interaction plots are also displayed for the left lingual gyrus and the right cuneus (left and right panel, respectively). Color bar depicts the p-value. L: left, R: right. Regions displayed are bilateral lingual gyrus, bilateral superior frontal gyrus, middle frontal gyrus, inferior parietal lobule, transverse and superior temporal and left posterior cingulate.
Fig. 3
Fig. 3
Fasciculi showing positive correlation between semantic switching score and FA in MDD group (5000 permutations), along with the significant (FDR corrected) group by FA interaction plots (accounting for age) for the cluster including the right SLF, the right IFOF and the body of the CC (5706 voxels, left panel); the right SLF (134 voxels, middle panel) and the right anterior part of the CC extending to the anterior corona radiata (74 voxels, right panel). Clusters are overlaid on a canonical template provided by FSLeyes (https://git.fmrib.ox.ac.uk/fsl/fsleyes/fsleyes/) (1 mm resolution).
See this image and copyright information in PMC

References

    1. James S.L., Abate D., Abate K.H., Abay S.M., Abbafati C., Abbasi N., et al. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392(10159):1789–1858. - PMC - PubMed
    1. Desai, R., Liebenthal, E., Possing, E.T., Waldron, E., Binder, J.R. 2005. Volumetric vs. surface-based alignment for localization of auditory cortex activation. Neuroimage 26(4), 1019–1029. - PubMed
    1. Greve D.N., Fischl B. False positive rates in surface-based anatomical analysis. Neuroimage. 2018;1(171):6–14. - PMC - PubMed
    1. Lerch J.P., Evans A.C. Cortical thickness analysis examined through power analysis and a population simulation. Neuroimage. 2005;24(1):163–173. - PubMed
    1. Lerch J.P., Carroll J.B., Dorr A., Spring S., Evans A.C., Hayden M.R., Sled J.G., Henkelman R.M. Cortical thickness measured from MRI in the YAC128 mouse model of Huntington’s disease. NeuroImage. 2008;41(2):243–251. - PubMed

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