Organisation of structure-function coupling in the brain with respect to language laterality
Poster No:
1011
Submission Type:
Abstract Submission
Authors:
Ieva Andrulyte1, Christophe de Bezenac1, Simon Keller1
Institutions:
1University of Liverpool, Liverpool, Merseyside
First Author:
Co-Author(s):
Introduction:
Language is one of the most studied lateralised cognitive functions in the human brain, which functionally relies on the left hemisphere in most people. Nevertheless, the precise mechanisms through which a relatively stable white matter architecture is established to directly underpin language function in each individual remain uncertain. Previous studies utilised structural connectivity (SC) and functional connectivity (FC) coupling for individual fingerprinting and task decoding (Griffa et al., 2022), implying that the variability in brain entropy could serve as a distinguishing characteristic for individual brain identification. In this study, we investigated a large cohort (n=1006) of young, healthy individuals (ages 22 to 35) to look at each subject's SC-FC coupling and identify potential markers that could help to distinguish between different language laterality groups, defined as bilateral, left-, and right-language dominant.
Methods:
Language laterality was predetermined using task fMRI for language comprehension via a story-math contrast (Binder et al., 2011). Functional connectivity was measured by extracting rsfMRI time-series data from 360 brain regions using HCP atlas parcellation (Glasser et al., 2016). Functional connections were defined as weighted direct edges, modelled using Pearson correlation coefficients, producing a correlation matrix representing interregional functional connectivity (Gu et al., 2022) (Fig. 1a). To enhance interpretability, negative values in each connectivity matrix were set to zero (Luppi and Stamatakis, 2021). Structural connectivity was determined using a whole-brain deterministic fibre tractography algorithm leveraging spin distribution functions (SDFs) (Yeh et al., 2010). Two types of structural connectivity matrices per subject were generated: using (1) the counts of connecting tracts (streamlines) and (2) quantitative anisotropy (QA) between each node (Panesar et al., 2018) (Fig. 1b). The HCP atlas was employed for brain parcellation, with two ROIs deemed connected only if a fibre originated from one ROI and terminated in the other. Structure-function coupling was defined as the Pearson correlation between non-zero elements of regional structural (number of fibres and QA) and functional (correlation coefficient of rsfMRI) connectivity profiles across the whole brain (Baum et al., 2020) (Fig. 1c). For each participant, regional connectivity profiles were represented as vectors of connectivity strength from a single network node to all other nodes (Zarkali et al., 2021). Statistical analyses of group differences used the permutation analysis of linear models (PALM) toolbox in FSL, with family-wise error correction of p<0.05 and inclusion of sex, age, and handedness as covariates of no interest (Winkler et al., 2014).
·Figure 1. Flowchart of the methods pipeline
Results:
The results revealed a significant positive correlation in SC-FC coupling in the left 8c (a part of the dorsolateral prefrontal cortex) and right ventral area 24d (a part of paracentral lobular and mid-cingulate) in individuals with left language dominance (LLD) and right language dominance (RLD) compared to bilateral individuals (pFDR<0.05) (Fig. 2). Notably, this effect was observed only at the microstructural diffusion level (QA). Individuals with RLD also exhibited a greater coupling in the right hippocampus compared to bilateral individuals, a pattern not observed in LLD individuals. Additionally, SC-FC coupling in the right middle and agranular insular area was significantly tighter in people with RLD compared to LLD (FDR<0.01; difference observed at the streamline count level).
·Figure 2. Cohen’s d maps of PALM results
Conclusions:
In summary, lateralised individuals exhibit greater SC-FC coupling, while bilateral individuals show no differences on the group level. This suggests a reliance on structure and less functional variability in lateralized individuals regarding language specialisation compared to their bilateral counterparts.
Higher Cognitive Functions:
Executive Function, Cognitive Control and Decision Making
Language:
Language Comprehension and Semantics 1
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 2
Task-Independent and Resting-State Analysis
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
White Matter Anatomy, Fiber Pathways and Connectivity
Keywords:
Cognition
Computational Neuroscience
Language
MRI
NORMAL HUMAN
Open Data
Statistical Methods
White Matter
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
1|2Indicates the priority used for review
Provide references using author date format
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Griffa, A. et al. (2022). Brain structure-function coupling provides signatures for task decoding and individual fingerprinting. NeuroImage, 250, 118970.
Luppi, A. I. & Stamatakis, E. A. (2021). Combining network topology and information theory to construct representative brain networks. Network Neuroscience, 5(1), 96-124.
Panesar, S. S. et al. (2018). A quantitative tractography study into the connectivity, segmentation, and laterality of the human inferior longitudinal fasciculus. Frontiers in neuroanatomy, 12, 47.
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