Individual Variability in Functional Connectivity Architecture of the Human Brain

By S. Mueller, Danhong Wang, Michael D. Fox, B. T. T. Yeo, Jorge Sepulcre, Mert Rory Sabuncu, Rebecca Shafee, Jie Lu, Hesheng Liu. Neuron, 2013

1,148 citations recorded by the source corpus.

Summary The fact that people think or behave differently from one another is rooted in individual differences in brain anatomy and connectivity. Here we used repeated-measurement resting-state functional MRI to explore inter-subject variability in connectivity. Individual differences in functional connectivity were heterogeneous across the cortex, with significantly higher variability in heteromodal association cortex and lower variability in unimodal cortices. Inter-subject variability in connectivity was significantly correlated with the degree of evolutionary cortical expansion, suggesting a potential evolutionary root of functional variability. The connectivity variability was also related to variability in sulcal depth but not cortical thickness, positively correlated with the degree of long-range connectivity but negatively correlated with local connectivity. A meta-analysis further revealed that regions predicting individual differences in cognitive domains are predominantly located in regions of high connectivity variability. Our findings have potential implications for understanding brain evolution and development, guiding intervention, and interpreting statistical maps in neuroimaging.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/52ed210bef5a7d7db9ed5903d53e852b33224ecf

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Citations in the corpus

neuromaps: structural and functional interpretation of brain maps (2022, background): “Collectively, these maps represent more than a decade of human brain mapping research and encompass phenotypes including: the first principal component of gene expression [33], 36 neurotransmitter receptor PET tracer images [32], glucose and oxygen metabolism [72], cerebral blood flow and volume [72”
Hierarchical Heterogeneity across Human Cortex Shapes Large-Scale Neural Dynamics (2018, positive): “Compared to sensory cortex, association areas exhibit greater variation in rs-FC profiles across subjects, suggesting that cortical hierarchy plays a role in shaping single-subject specificity of FC patterns (Mueller et al., 2013; Finn et al., 2015).”
The dynamics of resting fluctuations in the brain: metastability and its dynamical cortical core (2016, neutral): “FC has become routinely used as a biomarker in various clinical applications, even though its predictive value holds only for group analyses, and not currently for the individual 43 .”
Functional system and areal organization of a highly sampled individual human brain (2015, result): “Between-subject variability was relatively higher in fronto-parietal, cingulo-opercular, attentional, and default mode regions than in visual, auditory, and somato-motor regions, as previously reported (Mueller et al., 2013).”
Generation and Evaluation of a Cortical Area Parcellation from Resting-State Correlations. (2016, background): “3)—correspond to regions previously reported to have particularly high intersubject variability in RSFC patterns (Mueller et al. 2013).”
Spatial Topography of Individual-Specific Cortical Networks Predicts Human Cognition, Personality and Emotion (2017, background): “Comparison with alternative approaches Having confirmed previous literature (Mueller et al., 2013; Laumann et al., 2015) that inter-subject and intra-subject functional connectivity variability were indeed different across cortical networks, we compared MS-HBM with four alternative approaches.”
Network hubs in the human brain. (2013, background): “Further observations have suggested that hub regions display distinct developmental trajectories [108], that they show high levels of variability across individuals [160], and that their level of cost-efficient wiring is under strong genetic control [98].”
Process Overlap Theory: A Unified Account of the General Factor of Intelligence (2016, background): “It is remarkable from an individual differences perspective that of all brain networks the frontoparietal network has the largest variability in functional connectivity, larger than any other network in the brain (Mueller et al., 2013).”
Human brain mapping: A systematic comparison of parcellation methods for the human cerebral cortex (2017, background): “Evidence suggests that the human connectome possesses connectional traits that are unique to each individual (Mueller et al., 2013; Barch et al., 2013; Wang et al., 2015; Gordon et al., 2017).”
Global Signal Regression Strengthens Association between Resting-State Functional Connectivity and Behavior (2019, positive): “Given significant interest in the relationship between behavior and functional brain architecture revealed by RSFC (Fox et al., 2012; Mueller et al., 2013; Smith et al., 2015; Finn et al., 2015; Rosenberg et al., 2016; Dubois et al., 2016; Bertolero et al., 2018; Kong et al., 2018), here we…”
Neurodevelopment of the association cortices: Patterns, mechanisms, and implications for psychopathology (2021, positive): “Accordingly, inter-individual neurobiological variability increases along the S-A axis as well, with most marked individual differences found in evolutionarily expanded heteromodal association cortices (Cui et al., 2020; Mueller et al., 2013; Reardon et al., 2018; Figure 6).”