Gaussian Mixture Modeling of Hemispheric Lateralization for Language in a Large Sample of Healthy Individuals Balanced for Handedness

Abstract

Hemispheric lateralization for language production and its relationships with manual preference and manual preference strength were studied in a sample of 297 subjects, including 153 left-handers (LH). A hemispheric functional lateralization index (HFLI) for language was derived from fMRI acquired during a covert sentence generation task as compared with a covert word list recitation. The multimodal HFLI distribution was optimally modeled using a mixture of 3 and 4 Gaussian functions in right-handers (RH) and LH, respectively. Gaussian function parameters helped to define 3 types of language hemispheric lateralization, namely “Typical” (left hemisphere dominance with clear positive HFLI values, 88% of RH, 78% of LH), “Ambilateral” (no dominant hemisphere with HFLI values close to 0, 12% of RH, 15% of LH) and “Strongly-atypical” (right-hemisphere dominance with clear negative HFLI values, 7% of LH). Concordance between dominant hemispheres for hand and for language did not exceed chance level, and most of the association between handedness and language lateralization was explained by the fact that all Strongly-atypical individuals were left-handed. Similarly, most of the relationship between language lateralization and manual preference strength was explained by the fact that Strongly-atypical individuals exhibited a strong preference for their left hand. These results indicate that concordance of hemispheric dominance for hand and for language occurs barely above the chance level, except in a group of rare individuals (less than 1% in the general population) who exhibit strong right hemisphere dominance for both language and their preferred hand. They call for a revisit of models hypothesizing common determinants for handedness and for language dominance.

Long-term proper name anomia after removal of the uncinate fasciculus

“…Although it is generally assumed that language lateralization was predictive of hand preference (Knecht 2000), recent findings have questioned this relationship when disregarding subjects who are strongly right language lateralized (Mazoyer et al 2014). Although our study was not specifically aimed at Fig.…”

Lateralization of gene expression in human language cortex

“…One prominently lateralized functional network underlies the human ability to speak and understand language, and critically involves the Superior Temporal Gyrus (STG) and the auditory cortex of Heschl's Gyrus (HG), both of which show anatomical asymmetry (Agcaoglu, Miller, Mayer, Hugdahl, & Calhoun, 2014;Dikker, Silbert, Hasson, & Zevin, 2014;Lyttelton et al, 2009;Mazoyer et al, 2014;Menenti, Gierhan, Segaert, & Hagoort, 2011;Willems, Van der Haegen, Fisher, & Francks, 2014). These regions have also shown microanatomical (Hutsler, 2003) and neurophysiological (Morillon et al, 2010) lateralization; left-sided neural oscillatory frequencies reportedly correspond to syllabic speech rhythms (Morillon et al, 2010).…”

CANDICE A1: Measuring language lateralisation with different language tasks: A systematic review

“…High mean LIs of between 0.74 and 0.89 have been reported for sentence generation, both when sentences are pre-learnt prior to scanning (e.g., Stippich et al, 2003), and when they are actively generated during the scan (e.g., Tzourio- Mazoyer et al, 2016). However, other studies have reported more modest laterality estimates of between 0.48 and 0.65, again with both variants of the task (Mazoyer et al, 2014;Partovi et al, 2012a;Partovi et al, 2012b). Thus, it does not appear to be the case that strength of laterality differs according to whether sentences are generated spontaneously during the scanning session, or learnt prior to scanning.…”