Diffusion magnetic resonance imaging connectome featuresare predictive of functional lateralization of semanticprocessing in the anterior temporal lobes

Diffusion magnetic resonance imaging connectome featuresare predictive of functional lateralization of semanticprocessing in the anterior temporal lobes

Assessment of regional language lateralization is crucial in many scenarios, but not allpopulations are suited for its evaluation via task-functional magnetic resonance imag-ing (fMRI). In this study, the utility of structural connectome features for the classifi-cation of language lateralization in...

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Autoren: Zahnert, Felix, Kräling, Gunter, Melms, Leander, Belke, Marcus, Kleinholdermann, Urs, Timmermann, Lars, Hirsch, Martin, Jansen, Andreas, Mross, Peter, Menzler, Katja, Habermehl, Lena, Knake, Susanne
Format: Artikel
Sprache:Englisch
Veröffentlicht: Philipps-Universität Marburg 2022
Schlagworte:
graph theory
language dominance
machine learning
semantic processing
Medizin
structuralconnectome
Medical sciences Medicine
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Zusammenfassung:Assessment of regional language lateralization is crucial in many scenarios, but not allpopulations are suited for its evaluation via task-functional magnetic resonance imag-ing (fMRI). In this study, the utility of structural connectome features for the classifi-cation of language lateralization in the anterior temporal lobes (ATLs) wasinvestigated. Laterality indices for semantic processing in the ATL were computedfrom task-fMRI in 1038 subjects from the Human Connectome Project who werelabeled as stronger rightward lateralized (RL) or stronger leftward to bilaterally latera-lized (LL) in a data-driven approach. Data of unrelated subjects (n=432) were usedfor further analyses. Structural connectomes were generated from diffusion-MRItractography, and graph theoretical metrics (node degree, betweenness centrality)were computed. A neural network (NN) and a random forest (RF) classifier weretrained on these metrics to classify subjects as RL or LL. After classification, compari-sons of network measures were conducted via permutation testing. Degree-basedclassifiers produced significant above-chance predictions both during cross-validation(NN: AUC–ROC[CI]=0.68[0.64–0.73], accuracy[CI]=68.34%[63–73.2%]; RF:AUC–ROC[CI]=0.7[0.66–0.73], accuracy[CI]=64.81%[60.9–68.5]) and testing(NN: AUC–ROC[CI]=0.69[0.53–0.84], accuracy[CI]=68.09[53.2–80.9]; RF: AUC–ROC[CI]=0.68[0.53–0.84], accuracy[CI]=68.09[55.3–80.9]). Comparison of net-work metrics revealed small effects of increased node degree within the right poste-rior middle temporal gyrus (pMTG) in subjects with RL, while degree was decreasedin the right posterior cingulate cortex (PCC). Above-chance predictions of functionallanguage lateralization in the ATL are possible based on diffusion-MRI connectomesalone. Increased degree within the right pMTG as a right-sided homologue of aknown semantic hub, and decreased hubness of the right PCC may form a structuralbasis for rightward-lateralized semantic processing.
Beschreibung:Gefördert durch den Open-Access-Publikationsfonds der UB Marburg.
DOI:10.1002/hbm.26074

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