Inter-individual differences in human brain structure and morphology link to variation in demographics and behavior

Abstract

We perform a comprehensive integrative analysis of multiple structural MR-based brain features and find for the first-time strong evidence relating inter-individual brain structural variations to a wide range of demographic and behavioral variates across a large cohort of young healthy human volunteers. Our analyses reveal that a robust ‘positive-negative’ spectrum of behavioral and demographic variates, recently associated to covariation in brain function, can already be identified using only structural features, highlighting the importance of careful integration of structural features in any analysis of inter-individual differences in functional connectivity and downstream associations with behavioral/demographic variates.

Predicting cognitive abilities across individuals using sparse EEG connectivity

“…For example, previous work using fMRI functional connectivity has been criticized because it measures blood oxygenation, which is an indirect measure of neural activity. Due to this, critics have suggested that fMRI functional connectivity fingerprinting could be driven by individual differences in brain structure or vasculature, rather than meaningful differences in brain function (Dubois & Adolphs, 2016;Llera et al, 2019). They additionally suggest that identification and behavioral prediction could be driven by trait-like head motion, which is a challenging confound in fMRI (Nentwich et al, 2020;Siegel et al, 2017;Xifra-Porxas et al, 2020).…”

Combining local and global evolutionary trajectories of brain-behavior equilibrium through game theory

“…The transition across different phenotypes is a universal evolutionary mechanism ascribable to the progressive action of selection (Darwin, 1859). Still, the backlashes of brain-specific evolutionary paths on the links between brain reorganization (Deacon, 1997;Mesulam, 2000;Mayr, 2001;Gould, 2002;Laland et al, 2015;Miller, 2019), human socio-cultural traits (Wilson, 1978;Dunbar and Shultz, 2007a;Laland, 2015), and behavioral complexity (Dunbar and Shultz, 2007b;Reader et al, 2011) is still unanswered, mainly due to the problematic integration of many branches of knowledge in the same scheme (Bertossa, 2011;Striedter, 2019;Llera et al, 2019). In the present paper, we unify these two distinct evolutionary mechanisms in a single model taking advantage of neuroscientific evidence, graph theory, and game theory.…”

“…These include, on one hand, structural features, such as cortical thickness, myelinization, and structural connectivity and, on the other hand, functional features, such as task-evoked activity and functional connectivity. Given the complications in integrating evolutionary, structural, functional, and behavioral specializations within the same framework (Bertossa, 2011;Feldman-Barrett and Satpute, 2013;Striedter, 2019, Llera et al, 2019, questions such as "what are the evolutionary causes of cross-species and within-species heterogeneity in the brain shape and functional organization? ", "why is the within-species structural and functional variability inhomogeneous across brain's subunits and subsystems?…”

Multivariate associative patterns between the gut microbiota and large-scale brain network connectivity

“…One substantial methodological challenge is the multivariate and simultaneous integration of gut microbiome and brain data that enable capturing variance in both modalities simultaneously. To address this issue, we applied a linked independent component analysis ( (12,13), LICA) to microbiota and brain connectivity data (Figure 1). LICA enables data reduction in several modalities simultaneously and thereby is able to demonstrate joint inter-individual variation patterns in different modalities.…”