The human connectome is an intricate system of interconnected elements, providing the basis for integrative brain function. An essential step in the macroscopic mapping and examination of this ...network of structural and functional interactions is the subdivision of the brain into large-scale regions. Parcellation approaches used for the formation of macroscopic brain networks include application of predefined anatomical templates, randomly generated templates and voxel-based divisions. In this review, we discuss the use of such parcellation approaches for the examination of connectome characteristics. We specifically address the impact of the choice of parcellation scheme and resolution on the estimation of the brain's topological and spatial network features. Although organizational principles of functional and structural brain networks appear to be largely independent of the adopted parcellation approach, quantitative measures of these principles may be significantly modulated. Future parcellation-based connectome studies might benefit from the adoption of novel network tools and promising advances in connectivity-based parcellation approaches.
•Parcellation schemes may be used to examine the macroscopic connectome.•The choice of parcellation scheme has an effect on topological characteristics.•Qualitative descriptions are robust, but precise numerical values fluctuate.•Results from different studies are therefore not directly comparable.•Advances in parcellation techniques and network tools may improve comparability.
The dynamics of spontaneous fluctuations in neural activity are shaped by underlying patterns of anatomical connectivity. While numerous studies have demonstrated edge-wise correspondence between ...structural and functional connections, much less is known about how large-scale coherent functional network patterns emerge from the topology of structural networks. In the present study, we deploy a multivariate statistical technique, partial least squares, to investigate the association between spatially extended structural networks and functional networks. We find multiple statistically robust patterns, reflecting reliable combinations of structural and functional subnetworks that are optimally associated with one another. Importantly, these patterns generally do not show a one-to-one correspondence between structural and functional edges, but are instead distributed and heterogeneous, with many functional relationships arising from nonoverlapping sets of anatomical connections. We also find that structural connections between high-degree hubs are disproportionately represented, suggesting that these connections are particularly important in establishing coherent functional networks. Altogether, these results demonstrate that the network organization of the cerebral cortex supports the emergence of diverse functional network configurations that often diverge from the underlying anatomical substrate.
Background
Attention deficit/hyperactivity disorder (ADHD) has frequently been associated with changes in resting‐state functional connectivity, and decreased white matter (WM) integrity. In the ...current study, we investigated functional connectivity within Default Mode and frontal control resting‐state networks (RSNs) in children with and without ADHD. We hypothesized the RSNs of interest would show a pattern of impaired functional integration and segregation and corresponding changes in WM structure.
Methods
Resting‐state fMRI and diffusion‐weighted imaging data were acquired from 35 participants with ADHD and 36 matched typically developing peers, aged 6 through 18 years. Functional connectivity was assessed using independent component analysis. Network topology and WM connectivity were further investigated using graph theoretical measures and tract‐based spatial statistics (TBSS).
Results
Resting‐state fMRI analyses showed increased functional connectivity in right inferior frontal gyrus (IFG), and bilateral medial prefrontal cortex (mPFC) within the Default Mode and frontal control networks. Furthermore, a more diffuse spatial pattern of functional connectivity was found in children with ADHD. We found no group differences in structural connectivity as assessed with TBSS or graph theoretical measures.
Conclusions
Resting‐state networks show a more diffuse pattern of connectivity in children with ADHD. The increases in functional connectivity in right IFG and bilateral mPFC in children with ADHD may reflect reduced or delayed functional segregation of prefrontal brain regions. As these functional changes were not accompanied by changes in WM, they may precede the development of the frequently reported changes in WM structure.
The human connectome is the result of an elaborate developmental trajectory. Acquiring diffusion-weighted imaging and resting-state fMRI, we studied connectome formation during the preterm phase of ...macroscopic connectome genesis. In total, 27 neonates were scanned at week 30 and/or week 40 gestational age (GA). Examining the architecture of the neonatal anatomical brain network revealed a clear presence of a small-world modular organization before term birth. Analysis of neonatal functional connectivity (FC) showed the early formation of resting-state networks, suggesting that functional networks are present in the preterm brain, albeit being in an immature state. Moreover, structural and FC patterns of the neonatal brain network showed strong overlap with connectome architecture of the adult brain (85 and 81%, respectively). Analysis of brain development between week 30 and week 40 GA revealed clear developmental effects in neonatal connectome architecture, including a significant increase in white matter microstructure (P < 0.01), small-world topology (P < 0.01) and interhemispheric FC (P < 0.01). Computational analysis further showed that developmental changes involved an increase in integration capacity of the connectivity network as a whole. Taken together, we conclude that hallmark organizational structures of the human connectome are present before term birth and subject to early development.
Brain function relies on the flexible integration of a diverse set of segregated cortical modules, with the structural connectivity of the brain being a fundamentally important factor in shaping the ...brain's functional dynamics. Following up on macroscopic studies showing the existence of centrally connected nodes in the mammalian brain, combined with the notion that these putative brain hubs may form a dense interconnected ‘rich club’ collective, we hypothesized that brain connectivity might involve a rich club type of architecture to promote a repertoire of different and flexibly accessible brain functions. With the rich club suggested to play an important role in global brain communication, examining the effects of a rich club organization on the functional repertoire of physical systems in general, and the brain in particular, is of keen interest. Here we elucidate these effects using a spin glass model of neural networks for simulating stable configurations of cortical activity. Using simulations, we show that the presence of a rich club increases the set of attractors and hence the diversity of the functional repertoire over and above the effects produced by scale free type topology alone. Within the networks' overall functional repertoire rich nodes are shown to be important for enabling a high level of dynamic integrations of low-degree nodes to form functional networks. This suggests that the rich club serves as an important backbone for numerous co-activation patterns among peripheral nodes of the network. In addition, applying the spin glass model to empirical anatomical data of the human brain, we show that the positive effects on the functional repertoire attributed to the rich club phenomenon can be observed for the brain as well. We conclude that a rich club organization in network architectures may be crucial for the facilitation and integration of a diverse number of segregated functions.
•A spin glass model links structural connectivity to functional configurations.•Both diversity and shape of these configurations depend on structural connectivity.•Rich club scale free structures support the largest set of configurations.•These configurations have been hypothesized to be the brain's functional repertoire.•Rich club organization enriches and modulates the repertoire of cognitive functions.
The human brain is a complex network of anatomically segregated regions interconnected by white matter pathways, known as the human connectome. Diffusion tensor imaging can be used to reconstruct ...this structural brain network in vivo and noninvasively. However, due to a wide variety of influences, both false positive and false negative connections may occur. By choosing a ‘group threshold’, brain networks of multiple subjects can be combined into a single reconstruction, affecting the occurrence of these false positives and negatives. In this case, only connections that are detected in a large enough percentage of the subjects, specified by the group threshold, are considered to be present. Although this group threshold has a substantial impact on the resulting reconstruction and subsequent analyses, it is often chosen intuitively. Here, we introduce a model to estimate how the choice of group threshold influences the presence of false positives and negatives. Based on our findings, group thresholds should preferably be chosen between 30% and 90%. Our results further suggest that a group threshold of circa 60% is a suitable setting, providing a good balance between the elimination of false positives and false negatives.
► The impact of the group threshold on false positives and negatives is modeled. ► The group threshold has a substantial impact on network metrics and errors. ► Group thresholds should preferably be chosen between 30% and 90%. ► A group threshold of circa 60% appears to be appropriate for most applications.
Over the past years, several reports on a number of different species (including human, macaque, cat and nematode) have consistently suggested that brain hubs and their rich club connections play an ...important role in enabling efficient neural communication and integration, constituting a central communication backbone that boosts the functional repertoire of the system (Zamora-López et al., 2010; Crossley et al., 2013; Towlson et al., 2013; de Reus and van den Heuvel, 2013a; van den Heuvel and Sporns, 2013a; Grayson et al., 2014; Mišić et al., 2014; Senden et al., 2014). Since brain hubs have been shown to be implicated in both neurological (Stam et al., 2007; Buckner et al., 2009) and psychiatric (Collin et al., 2013; van den Heuvel et al., 2013) diseases, it is the general hope that a better fundamental understanding of their role in connectome organization may eventually provide insight in the pathology and effects of brain disorders. After evaluating the effects across all edges of the connectome, the authors found a diverse scaffold of white matter connections with a significant combined effect on the examined global network metrics, presenting (somewhat surprisingly) only little overlap with hub-to-hub rich club connections. If the hypothesized disruption of a connection does eliminate some but not all shortest paths between two brain regions, the shortest path length between those regions does not change, while their mutual communication is still likely to be affected (Figure 1A). (A) A simple toy network shows that, due to the presence of parallel pathways, removal of the dashed connection does not alter the path length (i.e., minimum number of steps) between nodes in the green and blue zone.
The rich variation in cytoarchitectonics of the human cortex is well known to play an important role in the differentiation of cortical information processing, with functional multimodal areas noted ...to display more branched, more spinous, and an overall more complex cytoarchitecture. In parallel, connectome studies have suggested that also the macroscale wiring profile of brain areas may have an important contribution in shaping neural processes; for example, multimodal areas have been noted to display an elaborate macroscale connectivity profile. However, how these two scales of brain connectivity are related-and perhaps interact-remains poorly understood. In this communication, we combined data from the detailed mappings of early twentieth century cytoarchitectonic pioneers Von Economo and Koskinas (1925) on the microscale cellular structure of the human cortex with data on macroscale connectome wiring as derived from high-resolution diffusion imaging data from the Human Connectome Project. In a cross-scale examination, we show evidence of a significant association between cytoarchitectonic features of human cortical organization-in particular the size of layer 3 neurons-and whole-brain corticocortical connectivity. Our findings suggest that aspects of microscale cytoarchitectonics and macroscale connectomics are related.
One of the most widely known and perhaps most fundamental properties of the human cortex is its rich variation in cytoarchitectonics. At the same time, neuroimaging studies have also revealed cortical areas to vary in their level of macroscale connectivity. Here, we provide evidence that aspects of local cytoarchitecture are associated with aspects of global macroscale connectivity, providing insight into the question of how the scales of micro-organization and macro-organization of the human cortex are related.
Macroscopic brain networks have been shown to display several properties of an efficient communication architecture. In light of global communication, the formation of a densely connected neural ..."rich club" of hubs is of particular interest, because brain hubs have been suggested to play a key role in enabling short communication pathways within neural networks. Here, analyzing the cat connectome as reconstructed from tract tracing data (Scannell et al., 1995), we provide several lines of evidence of an important role of the structural rich club to interlink functional domains. First, rich club hub nodes were found to be mostly present at the boundaries between functional communities and well represented among intermodule hubs, displaying a diverse connectivity profile. Second, rich club connections, linking nodes of the rich club, and feeder connections, linking non-rich club nodes to rich club nodes, were found to comprise 86% of the intermodule connections, whereas local connections between peripheral nodes mostly spanned between nodes of the same functional community. Third, almost 90% of all intermodule communication paths were found to follow a sequence or "path motif" that involved rich club or feeder edges and thus traversed a rich club node. Together, our findings provide evidence of the structural rich club to form a central infrastructure for intermodule communication in the brain.
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