Mapping the human brain's cortical-subcortical functional network organization

Abstract

Understanding complex systems such as the human brain requires characterization of the system's architecture across multiple levels of organization-from neurons, to local circuits, to brain regions, and ultimately large-scale brain networks. Here we focus on characterizing the human brain's large-scale network organization, as it provides an overall framework for the organization of all other levels. We developed a highly principled approach to identify cortical network communities at the level of functional systems, calibrating our community detection algorithm using extremely well-established sensory and motor systems as guides. Building on previous network partitions, we replicated and expanded upon well-known and recently-identified networks, including several higher-order cognitive networks such as a left-lateralized language network. We expanded these cortical networks to subcortex, revealing 358 highly-organized subcortical parcels that take part in forming whole-brain functional networks. Notably, the identified subcortical parcels are similar in number to a recent estimate of the number of cortical parcels (360). This whole-brain network atlas-released as an open resource for the neuroscience community-places all brain structure s across both cortex and subcortex into a single large-scale functional framework, with the potential to facilitate a variety of studies investigating large-scale functional networks in health and disease.

A set of functionally-defined brain regions with improved representation of the subcortex and cerebellum

“…However, in the secondary (HCP) dataset, there was approximately 0 correlation between subcortical ROIs and all other ROIs, including homotopic subcortical ROI pairs. The likely reason for this difference is due to poor temporal signal-to-noise ratio in the subcortex of HCP data (Ji et al, 2019), which we demonstrate here in SI Figure 4. Thus, we excluded the secondary dataset from all further analyses.…”

“…The one major discrepancy was that in the subcortical portion of the matrix from the secondary (HCP) dataset, we observed correlations near zero. The reason for this observation is likely poor temporal signal-tonoise ratio (tSNR) in the subcortex of HCP data (Ji et al, 2019). Several factors may contribute to this poor tSNR.…”

“…Most such studies have used restingstate functional connectivity MRI, which measures correlations in low-frequency bloodoxygen-level-dependent (BOLD) signals across the whole brain while subjects remain awake and alert without engaging in an explicit task (Biswal et al, 1995;Gusnard and Raichle, 2001;Snyder and Raichle, 2012). While many of these existing sets of ROIs sample the cortex quite well, most approaches have under-sampled or completely omitted the subcortex and cerebellum (but see Ji et al, 2019).…”

Determining the Hierarchical Architecture of the Human Brain Using Subject-Level Clustering of Functional Networks

“…2c, there is branching of a community that is mostly expressed in the left hemisphere and includes Broca's area and the superior temporal gyrus, and bears resemblance to areas of activation during language processing tasks (Ji et al, 2019;Langs et al, 2015;Glasser et al, 2016a,b). This community, which has traditionally evaded most Power et al, 2011) (but not all (Ji et al, 2019;Langs et al, 2015)) mesoscale investigations, may represent a language system (Ji et al, 2019;Langs et al, 2015). It is notable that this putative language community is substantially more in agreement with the one described in Langs et al (2015) than Ji et al (2019), despite the fact that the former used a markedly different analytic approach (voxel-based, clustering in embedding space, etc).…”

“…Here clusters refer to communities, whereas in Yeo et al (2011), clusters were identified based on connectivity profiles. A recent study by Ji et al (2019), that used data from the HCP and the MMP cortical parcellation, identified an "oribito-affective" community that corresponds to posterior orbitofrontal parts of the limbic network descibed in Yeo et al (2011), though the authors note that it had the lowest "confidence score" of community assignment among the identified networks. Much of the nodes in the described orbito-affective community (i.e., posterior orbitofrontal) are included in our central executive community (Fig.…”