Emergence of canonical functional networks from the structural connectome.
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ABSTRACT:
SUBMITTER: Xie X
PROVIDER: S-EPMC8451304 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:IntroductionConnectome analysis of the human brain's structural and functional architecture provides a unique opportunity to understand the organization of the brain's functional architecture. In previous studies, connectome fingerprinting using brain functional connectivity profiles as an individualized trait was able to predict an individual's neurocognitive performance from the Human Connectome Project (HCP) neurocognitive datasets.Materials and methodsIn the present study, we extend connectome fingerprinting from functional connectivity (FC) to structural connectivity (SC), identifying multiple relationships between behavioral traits and brain connectivity. Higher-order neurocognitive tasks were found to have a weaker association with structural connectivity than its functional connectivity counterparts.ResultsNeurocognitive tasks with a higher sensory footprint were, however, found to have a stronger association with structural connectivity than their functional connectivity counterparts. Language behavioral measurements had a particularly stronger correlation, especially between performance on the picture language test (Pic Vocab) and both FC (r = .28, p < .003) and SC (r = 0.27, p < .00077).ConclusionsAt the neural level, we found that the pattern of structural brain connectivity related to high-level language performance is consistent with the language white matter regions identified in presurgical mapping. We illustrate how this approach can be used to generalize the connectome fingerprinting framework to structural connectivity and how this can help understand the connections between cognitive behavior and the white matter connectome of the brain.
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Project description:Interaction networks are central elements of ecological systems and have very complex structures. Historically, much effort has focused on niche-mediated processes to explain these structures, while an emerging consensus posits that both niche and neutral mechanisms simultaneously shape many features of ecological communities. However, the study of interaction networks still lacks a comprehensive neutral theory. Here we present a neutral model of predator-prey interactions and analyze the structural characteristics of the simulated networks. We find that connectance values (complexity) and complexity-diversity relationships of neutral networks are close to those observed in empirical bipartite networks. High nestedness and low modularity values observed in neutral networks fall in the range of those from empirical antagonist bipartite networks. Our results suggest that, as an alternative to niche-mediated processes that induce incompatibility between species ("niche forbidden links"), neutral processes create "neutral forbidden links" due to uneven species abundance distributions and the low probability of interaction between rare species. Neutral trophic networks must be seen as the missing endpoint of a continuum from niche to purely stochastic approaches of community organization.
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Project description:One of the crucial questions in neuroscience is how a rich functional repertoire of brain states relates to its underlying structural organization. How to study the associations between these structural and functional layers is an open problem that involves novel conceptual ways of tackling this question. We here propose an extension of the Connectivity Independent Component Analysis (connICA) framework, to identify joint structural-functional connectivity traits. Here, we extend connICA to integrate structural and functional connectomes by merging them into common "hybrid" connectivity patterns that represent the connectivity fingerprint of a subject. We test this extended approach on the 100 unrelated subjects from the Human Connectome Project. The method is able to extract main independent structural-functional connectivity patterns from the entire cohort that are sensitive to the realization of different tasks. The hybrid connICA extracted two main task-sensitive hybrid traits. The first, encompassing the within and between connections of dorsal attentional and visual areas, as well as fronto-parietal circuits. The second, mainly encompassing the connectivity between visual, attentional, DMN and subcortical networks. Overall, these findings confirms the potential of the hybrid connICA for the compression of structural/functional connectomes into integrated patterns from a set of individual brain networks.
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Project description:Introduction:In neuroimaging studies, long-term unilateral hearing loss (UHL) is associated with functional changes in specific brain regions and connections; however, little is known regarding alterations in the topological organization of whole-brain functional networks and whether these alterations are related to hearing behavior in UHL patients. Methods:We acquired resting-state fMRI data from 21 patients with UHL caused by acoustic neuromas and 21 matched healthy controls. Whole-brain functional networks were constructed by measuring interregional temporal correlations of 278 brain regions. Alterations in interregional functional connectivity and topological properties (e.g., small-world, efficiency, and nodal centrality) were identified using graph-theory analysis. The subjects also completed a battery of hearing behavior measures. Results:Both UHL patients and controls exhibited efficient small-world properties in their functional networks. Compared with controls, UHL patients showed increased and decreased nodal centrality in distributed brain regions. Furthermore, the brain regions with significantly increased and decreased functional connections associated with UHL were components of the following important networks: (1) visual network; (2) higher-order functional networks, including the default-mode and attention networks; and (3) subcortical network and cerebellum. Intriguingly, the changes in intranetwork connections in UHL were significantly correlated with disease duration and hearing level. Conclusions:This study revealed connectome-level alterations involved in multiple large-scale networks related to sensory and higher-level cognitive functions in long-term UHL patients. These reorganizations of the brain in UHL patients may depend on the stage of deafness and hearing level. Together, our findings provided empirical evidence for understanding the neuroplastic mechanisms underlying hearing impairment, establishing potential biomarkers for monitoring the progression and further treatment effects for UHL patients.
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