Dataset Information

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 structures 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.

SUBMITTER: Ji JL

PROVIDER: S-EPMC6289683 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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

Ji Jie Lisa JL Spronk Marjolein M Kulkarni Kaustubh K Repovš Grega G Anticevic Alan A Cole Michael W MW

NeuroImage 20181003

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 leve ...[more]

PMID: 30291974

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Project description:Highlights • Overlap has been noted disorders which fall on the psychotic spectrum.• Univariate studies may miss joint brain features across diagnostic categories.• mCCA with jICA is paired with features across the psychotic spectrum to produce joint components.• One joint component displayed a significant relationship with cognitive scores.• The replicate trends of cortical-subcortical irregularity in psychotic spectrum disorders. Multiple authors have noted overlapping symptoms and alterations across clinical, anatomical, and functional brain features in schizophrenia (SZ), schizoaffective disorder (SZA), and bipolar disorder (BPI). However, regarding brain features, few studies have approached this line of inquiry using analytical techniques optimally designed to extract the shared features across anatomical and functional information in a simultaneous manner. Univariate studies of anatomical or functional alterations across these disorders can be limited and run the risk of omitting small but potentially crucial overlapping or joint neuroanatomical (e.g., structural images) and functional features (e.g., fMRI-based features) which may serve as informative clinical indicators of across multiple diagnostic categories. To address this limitation, we paired an unsupervised multimodal canonical correlation analysis (mCCA) together with joint independent component analysis (jICA) to identify linked spatial gray matter (GM), resting-state functional network connectivity (FNC), and white matter fractional anisotropy (FA) features across these diagnostic categories. We then calculated associations between the identified linked features and trans-diagnostic behavioral measures (MATRICs Consensus Cognitive Battery, MCCB). Component number 4 of the 13 identified displayed a statistically significant relationship with overall MCCB scores across GM, resting-state FNC, and FA. These linked modalities of component 4 consisted primarily of positive correlations within subcortical structures including the caudate and putamen in the GM maps with overall MCCB, sparse negative correlations within subcortical and cortical connection tracts (e.g., corticospinal tract, superior longitudinal fasciculus) in the FA maps with overall MCCB, and negative relationships with MCCB values and loading parameters with FNC matrices displaying increased FNC in subcortical-cortical regions with auditory, somatomotor, and visual regions.

Project description:Assessment of impaired/preserved cortical regions in brain tumours is typically performed via intraoperative direct brain stimulation of eloquent areas or task-based functional MRI. One main limitation is that they overlook distal brain regions or networks that could be functionally impaired by the tumour. This study aims (i) to investigate the impact of brain tumours on the cortical synchronization of brain networks measured with resting-state functional magnetic resonance imaging (resting-state networks) both near the lesion and remotely and (ii) to test whether potential changes in resting-state networks correlate with cognitive status. The sample included 24 glioma patients (mean age: 58.1 ± 16.4 years) with different pathological staging. We developed a new method for single subject localization of resting-state networks abnormalities. First, we derived the spatial pattern of the main resting-state networks by means of the group-guided independent component analysis. This was informed by a high-resolution resting-state networks template derived from an independent sample of healthy controls. Second, we developed a spatial similarity index to measure differences in network topography and strength between healthy controls and individual brain tumour patients. Next, we investigated the spatial relationship between altered networks and tumour location. Finally, multivariate analyses related cognitive scores across multiple cognitive domains (attention, language, memory, decision making) with patterns of multi-network abnormality. We found that brain gliomas cause broad alterations of resting-state networks topography that occurred mainly in structurally normal regions outside the tumour and oedema region. Cortical regions near the tumour often showed normal synchronization. Finally, multi-network abnormalities predicted attention deficits. Overall, we present a novel method for the functional localization of resting-state networks abnormalities in individual glioma patients. These abnormalities partially explain cognitive disabilities and shall be carefully navigated during surgery.

Dataset Information

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

Publications

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

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