Presentation
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Language network lateralization is reflected throughout the macroscale functional organization of cortex
Poster A95 in Poster Session A, Tuesday, October 24, 10:15 am - 12:00 pm CEST, Espace Vieux-Port
Loic Labache1, Tian Ge2,3, B.T. Thomas Yeo2,4, Avram J. Holmes1,5; 1Yale University, 2Massachusetts General Hospital, 3Broad Institute, Cambridge, US-MA, 4National University of Singapore, 5Rutgers University, Piscataway, US-NJ
A fundamental property of brain organization is the presence of asymmetries between hemispheres and the lateralization of brain functions. This architectural feature is thought to support human language development, potentially providing an axis for the specialization of large-scale cortical networks. Individuals exhibiting atypical language organization have been identified, suggesting the presence of considerable variability in the degree of brain asymmetry. To date, this literature has primarily focused on the hemispheric specialization of language without consideration for the extent to which this property of brain organization may reflect a common motif extending across the cortical sheet. Accordingly, the relations linking the atypical lateralization of the language network with the broader macroscale organization of cortex remain an open question. We investigated the impact of language network atypicality on the macroscale functional gradients that underpin complex cognition in humans. The study sample was part of the HCP database. For each participant, a connectivity matrix was calculated using the AICHA atlas. We computed the average strength asymmetry and sum for the language network and its average inter-hemispheric connectivity. Based on the listening-math contrast, we established the BOLD average asymmetry of the language network. Diffusion map embedding was implemented to decompose participants resting state connectivity matrices into three gradients. The first gradient (G1) was anchored in somato/motor and auditory cortex, with the regions at the other end encompassing broad swaths of the association cortex. The second gradient (G2) primarily differentiated the somato/motor and auditory cortex from the visual system. The third gradient (G3) reflected a network architecture contrasting frontoparietal and somato/motor systems. HCP participants with atypical lateralization were identified using a hierarchical clustering technique. Next, using ANCOVA, we examined the impact of language lateralization (typicality) on the average values of each gradient for 7 large-scale networks. Replicating previous results, we identified 3 groups of individuals. The strong and mild typical groups reflect leftward dominant individuals; these participants were then further grouped as typical. Conversely, the atypical participants were rightward dominant. Analyses revealed a typicality effect through the 3 gradients for the Default, Control, and Salience networks. However, the effects were different across gradients. For G1, the Default and Salience networks shifted in asymmetry, with typical being leftward lateralized and atypical rightward. The Control network being rightward asymmetrical in both cases, but stronger in atypical. For G2, no shift in asymmetry was present between the groups, but atypical were stronger rightward asymmetrical for the Default and Control networks. An opposite effect was found for the Salience network. For G3, the Default and Control networks underwent a reversed shift in asymmetry, with atypical being leftward lateralized and typical rightward. The Salience network being rightward asymmetrical in both cases, but stronger in typical. The presence of language network atypicality parallels the macroscale organization of cortex, spreading from the 1st gradient (association-sensory integration) to the 3rd (frontoparietal and somato/motor anchored). The canonical language network appears to be one component in the broader hemispheric organization of the human brain, reflecting the specialization of distributed large-scale networks across the cortical sheet.
Topic Areas: Computational Approaches, Multisensory or Sensorimotor Integration