Disconnectomics of the Rich Club Impacts Motor Recovery After Stroke

Background and Purpose: Structural brain networks possess a few hubs, which are not only highly connected to the rest of the brain but are also highly connected to each other. These hubs, which form a rich-club, play a central role in global brain organization. To investigate whether the concept of rich-club sheds new light on poststroke recovery, we applied a novel network-theoretical quantification of lesions to patients with stroke and compared the outcomes with what lesion size alone would indicate. Methods: Whole-brain structural networks of 73 patients with ischemic stroke were reconstructed using diffusion-weighted imaging data. Disconnectomes, a new type of network analyses, were constructed using only those fibers that pass through the lesion. Fugl-Meyer upper extremity scores and their changes were used to determine whether the patients show natural recovery or not. Results: Cluster analysis revealed 3 patient clusters: small-lesion-good-recovery, midsized-lesion-poor-recovery (MLPR), and large-lesion-poor-recovery (LLPR). The small-lesion-good-recovery consisted of subjects whose lesions were small, and whose prospects for recovery were relatively good. To explain the nondifference in recovery between the MLPR and LLPR clusters despite the difference (LLPR>MLPR) in lesion volume, we defined the metric to be the sum of the entries in the disconnectome and, more importantly, the to be the sum of all entries in the disconnectome corresponding to edges with at least one node in the rich-club. Unlike lesion volume and corticospinal tract damage (MLPR<LLPR), for , this relationship was reversed (MLPR>LLPR) or showed no difference for . Conclusions: Smaller lesions that focus on the rich-club can be just as devastating as much larger lesions that do not focus on the rich-club, pointing to the role of the rich-club as a backbone for functional communication within brain networks and for recovery from stroke.

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Unifying the Notions of Modularity and Core–Periphery Structure in Functional Brain Networks during Youth

Cerebral Cortex ◽

10.1093/cercor/bhz150 ◽

2019 ◽

Vol 30 (3) ◽

pp. 1087-1102

Author(s):

Shi Gu ◽

Cedric Huchuan Xia ◽

Rastko Ciric ◽

Tyler M Moore ◽

Ruben C Gur ◽

...

Keyword(s):

Individual Differences ◽

Brain Function ◽

Brain Networks ◽

Brain Regions ◽

Imaging Data ◽

Modular Architecture ◽

Functional Brain ◽

Rich Club ◽

Functional Brain Networks ◽

Integrative Processing

AbstractAt rest, human brain functional networks display striking modular architecture in which coherent clusters of brain regions are activated. The modular account of brain function is pervasive, reliable, and reproducible. Yet, a complementary perspective posits a core–periphery or rich-club account of brain function, where hubs are densely interconnected with one another, allowing for integrative processing. Unifying these two perspectives has remained difficult due to the fact that the methodological tools to identify modules are entirely distinct from the methodological tools to identify core–periphery structure. Here, we leverage a recently-developed model-based approach—the weighted stochastic block model—that simultaneously uncovers modular and core–periphery structure, and we apply it to functional magnetic resonance imaging data acquired at rest in 872 youth of the Philadelphia Neurodevelopmental Cohort. We demonstrate that functional brain networks display rich mesoscale organization beyond that sought by modularity maximization techniques. Moreover, we show that this mesoscale organization changes appreciably over the course of neurodevelopment, and that individual differences in this organization predict individual differences in cognition more accurately than module organization alone. Broadly, our study provides a unified assessment of modular and core–periphery structure in functional brain networks, offering novel insights into their development and implications for behavior.

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Structure and function of complex brain networks

Dialogues in Clinical Neuroscience ◽

10.31887/dcns.2013.15.3/osporns ◽

2013 ◽

Vol 15 (3) ◽

pp. 247-262 ◽

Cited By ~ 137

Keyword(s):

Empirical Studies ◽

Brain Networks ◽

Neural Substrates ◽

Cognitive Domains ◽

Rich Club ◽

Network Analyses ◽

Communication Processes ◽

Network Communities ◽

Functional Brain Networks ◽

And Function

An increasing number of theoretical and empirical studies approach the function of the human brain from a network perspective. The analysis of brain networks is made feasible by the development of new imaging acquisition methods as well as new tools from graph theory and dynamical systems. This review surveys some of these methodological advances and summarizes recent findings on the architecture of structural and functional brain networks. Studies of the structural connectome reveal several modules or network communities that are interlinked by hub regions mediating communication processes between modules. Recent network analyses have shown that network hubs form a densely linked collective called a "rich club," centrally positioned for attracting and dispersing signal traffic. In parallel, recordings of resting and task-evoked neural activity have revealed distinct resting-state networks that contribute to functions in distinct cognitive domains. Network methods are increasingly applied in a clinical context, and their promise for elucidating neural substrates of brain and mental disorders is discussed.

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Retrospective web-based multicenter evaluation of 18F-FDG-PET and CT derived predictive factors

Nuklearmedizin ◽

10.3413/nukmed-0322-10-06 ◽

2011 ◽

Vol 50 (01) ◽

pp. 39-47 ◽

Cited By ~ 5

Author(s):

U. Nestle ◽

K. Scheidhauer ◽

C. Puskas ◽

E. Ballek ◽

K. Hohloch ◽

...

Keyword(s):

Predictive Factors ◽

Fdg Pet ◽

Standardized Uptake Value ◽

Multivariate Model ◽

Small Lesion ◽

Lesion Volume ◽

Imaging Data ◽

Web Based ◽

Before And After ◽

Web Based System

Summary Aim: Although predictive factors (PF) for conventional lymphoma therapy are established and frequently used in clinical practice and medical research, the PF for radioimmunotherapy (RIT) have not been fully defined until now. The aim of this multicenter evaluation is to prove the feasibility of the multicenter web-based data collection and to preliminary explore imaging findings and prediction of therapy response in patients with follicular lymphoma (FL) following radioimmuno therapy (RIT) with 90Y-ibritumomab tiuxetan. Patients, methods: We retrospectively analyzed and correlated clinical and imaging data (CT and FDG-PET) before and after RIT as documented by the RIT-Network. Evaluation of treatment response was done on both patient and lesion basis. Every measurable lesion was analyzed in terms of standardized uptake value (SUV), volume (CT and PET) and response. PF were identified using a uni- and multivariate model. A web-based system was used for the documentation and evaluation of clinical and imaging data. Results: 16 patients with at least one PET before and after RIT were eligible for analysis. Concerning response three months postRIT, 5 patients achieved a CR, 6 patients a PR and 4 patients remained with NC. A total of 159 lesions were measured (mean 10 ± 8). In the multivariate model the log lesion volume (p < 0.0001), the total (p = 0.03) and maximum lesion volume (p = 0.05) were predictors for response (CR + PR). Concerning the lesional CR initial small lesion volume (p = 0.009) and its high metabolic activity (p = 0.01) were identified as predictors. The web-based system showed no major disturbances allowing secure data transfer and central image interpretation in a reasonable time. Conclusion: The use of a web-based multicenter archiving system for clinical and imaging data is technically feasible in a multicenter setting and allows a central analysis. This preliminary analysis suggests that FDG-PET may predict the likelihood of response to RIT.

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Reduced rich-club connectivity is related to disability in primary progressive MS

Neurology Neuroimmunology & Neuroinflammation ◽

10.1212/nxi.0000000000000375 ◽

2017 ◽

Vol 4 (5) ◽

pp. e375 ◽

Cited By ~ 9

Author(s):

Jan-Patrick Stellmann ◽

Sibylle Hodecker ◽

Bastian Cheng ◽

Nadine Wanke ◽

Kim Lea Young ◽

...

Keyword(s):

Hand Function ◽

Structural Connectivity ◽

Rank Correlation ◽

Insular Cortex ◽

Healthy Controls ◽

Imaging Data ◽

Information Processing Speed ◽

Primary Progressive ◽

Rich Club ◽

The Rich

Objective:To investigate whether the structural connectivity of the brain's rich-club organization is altered in patients with primary progressive MS and whether such changes to this fundamental network feature are associated with disability measures.Methods:We recruited 37 patients with primary progressive MS and 21 healthy controls for an observational cohort study. Structural connectomes were reconstructed based on diffusion-weighted imaging data using probabilistic tractography and analyzed with graph theory.Results:We observed the same topological organization of brain networks in patients and controls. Consistent with the originally defined rich-club regions, we identified superior frontal, precuneus, superior parietal, and insular cortex in both hemispheres as rich-club nodes. Connectivity within the rich club was significantly reduced in patients with MS (p = 0.039). The extent of reduced rich-club connectivity correlated with clinical measurements of mobility (Kendall rank correlation coefficient τ = −0.20, p = 0.047), hand function (τ = −0.26, p = 0.014), and information processing speed (τ = −0.20, p = 0.049).Conclusions:In patients with primary progressive MS, the fundamental organization of the structural connectome in rich-club and peripheral nodes was preserved and did not differ from healthy controls. The proportion of rich-club connections was altered and correlated with disability measures. Thus, the rich-club organization of the brain may be a promising network phenotype for understanding the patterns and mechanisms of neurodegeneration in MS.

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Dwelling quietly in the rich club: brain network determinants of slow cortical fluctuations

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.2014.0165 ◽

2015 ◽

Vol 370 (1668) ◽

pp. 20140165 ◽

Cited By ~ 87

Author(s):

Leonardo L. Gollo ◽

Andrew Zalesky ◽

R. Matthew Hutchison ◽

Martijn van den Heuvel ◽

Michael Breakspear

Keyword(s):

Spatial Scales ◽

Brain Regions ◽

Brain Network ◽

Morphological Properties ◽

Brain Organization ◽

Rich Club ◽

Guiding Principle ◽

The Rich ◽

Cortical Regions ◽

The Brain

For more than a century, cerebral cartography has been driven by investigations of structural and morphological properties of the brain across spatial scales and the temporal/functional phenomena that emerge from these underlying features. The next era of brain mapping will be driven by studies that consider both of these components of brain organization simultaneously—elucidating their interactions and dependencies. Using this guiding principle, we explored the origin of slowly fluctuating patterns of synchronization within the topological core of brain regions known as the rich club, implicated in the regulation of mood and introspection. We find that a constellation of densely interconnected regions that constitute the rich club (including the anterior insula, amygdala and precuneus) play a central role in promoting a stable, dynamical core of spontaneous activity in the primate cortex. The slow timescales are well matched to the regulation of internal visceral states, corresponding to the somatic correlates of mood and anxiety. In contrast, the topology of the surrounding ‘feeder’ cortical regions shows unstable, rapidly fluctuating dynamics likely to be crucial for fast perceptual processes. We discuss these findings in relation to psychiatric disorders and the future of connectomics.

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Functional Brain Networks and Alcohol Consumption: From the Naïve State to Chronic Heavy Drinking

10.1101/2020.09.14.296871 ◽

2020 ◽

Author(s):

Jared A. Rowland ◽

Jennifer R. Stapleton-Kotloski ◽

Greg E. Alberto ◽

April T. Davenport ◽

Phillip M. Epperly ◽

...

Keyword(s):

Alcohol Consumption ◽

Alcohol Use ◽

Brain Networks ◽

Alcohol Exposure ◽

Brain Network ◽

Free Access ◽

Functional Brain ◽

Rich Club ◽

Functional Brain Networks ◽

The Rich

AbstractA fundamental question for alcohol use disorder is how naïve brain networks are reorganized in response to the consumption of alcohol. The current study aimed to determine the progression of alcohol’s effect on functional brain networks during the transition from naïve, to early, to chronic consumption. Resting-state brain networks of six female monkeys were acquired using magnetoencephalography prior to alcohol exposure, after early exposure, and after free-access to alcohol using a well-established model of chronic heavy alcohol use. Functional brain network metrics were derived at each time point. Assortativity, average connection frequency, and number of gamma connections changed significantly over time. All metrics remained relatively stable from naïve to early drinking, and displayed significant changes following increased quantity of alcohol consumption. The assortativity coefficient was significantly less negative (p=.043), connection frequency increased (p=.03), and gamma connections increased (p=.034). Further, brain regions considered hubs (p=.037) and members of the Rich Club (p=.012) became less common across animals following the introduction of alcohol. The minimum degree of the Rich Club prior to alcohol exposure was significantly predictive of future free-access drinking (r=-.88, p<.001). Results suggest naïve brain network characteristics may be used to predict future alcohol consumption, and that alcohol consumption alters the topology of functional brain networks, shifting hubs and Rich Club membership away from previous regions in a non-systematic manner. Further work to refine these relationships may lead to the identification of a high-risk AUD phenotype.

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Breakdown of Whole-brain Dynamics in Preterm-born Children

Cerebral Cortex ◽

10.1093/cercor/bhz156 ◽

2019 ◽

Vol 30 (3) ◽

pp. 1159-1170 ◽

Cited By ~ 3

Author(s):

Nelly Padilla ◽

Victor M Saenger ◽

Tim J van Hartevelt ◽

Henrique M Fernandes ◽

Finn Lennartsson ◽

...

Keyword(s):

Activity Patterns ◽

Brain Magnetic Resonance Imaging ◽

Imaging Data ◽

Whole Brain ◽

Rich Club ◽

Extremely Preterm ◽

The Rich ◽

Preterm Born ◽

Brain Reorganization ◽

The Brain

Abstract The brain operates at a critical point that is balanced between order and disorder. Even during rest, unstable periods of random behavior are interspersed with stable periods of balanced activity patterns that support optimal information processing. Being born preterm may cause deviations from this normal pattern of development. We compared 33 extremely preterm (EPT) children born at < 27 weeks of gestation and 28 full-term controls. Two approaches were adopted in both groups, when they were 10 years of age, using structural and functional brain magnetic resonance imaging data. The first was using a novel intrinsic ignition analysis to study the ability of the areas of the brain to propagate neural activity. The second was a whole-brain Hopf model, to define the level of stability, desynchronization, or criticality of the brain. EPT-born children exhibited fewer intrinsic ignition events than controls; nodes were related to less sophisticated aspects of cognitive control, and there was a different hierarchy pattern in the propagation of information and suboptimal synchronicity and criticality. The largest differences were found in brain nodes belonging to the rich-club architecture. These results provide important insights into the neural substrates underlying brain reorganization and neurodevelopmental impairments related to prematurity.

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MERIT Study – “Multicenter Evaluation of Patient- and Lesion-Specific Prognostic Factors for RadioImmunoTherapy with 90yttrium-Labeled Anti-CD20 in Follicular Non-Hodgkin's lymphoma”.

Blood ◽

10.1182/blood.v114.22.4792.4792 ◽

2009 ◽

Vol 114 (22) ◽

pp. 4792-4792

Author(s):

Aleksandar Grgic ◽

Ursula Nestle ◽

Elena Ballek ◽

Klemens Scheidhauer ◽

Cornelia Puskas ◽

...

Keyword(s):

Prognostic Factors ◽

Prospective Study ◽

Conflicts Of Interest ◽

Standardized Uptake Value ◽

Image Data ◽

Small Lesion ◽

Lesion Volume ◽

Imaging Data ◽

Web Based ◽

Anti Cd20

Abstract Abstract 4792 Background / Aim Although prognostic factors (PF) for conventional lymphoma therapy are well known and used in clinical practice and medical research, the PF for radioimmunotherapy (RIT) have not been fully defined until now. The aim of this prospective multicenter trial is to identify patient- and lesion-specific PF for a standard RIT using 90Yttrium-labeled anti-CD20-antibodies in relapsed or refractory follicular lymphoma (FL) by means of clinical and image data including FDG-PET and CT. To prove the feasibility of the multicenter web-based data collection and to assess the imaging data we performed an analysis on retrospective data. Material and methods This retrospective analysis included clinical and image data of patients with FL from 3 German centers (UKS Homburg, TU Munich, SK Karlsruhe). Clinical data were documented using the ”International Registry on Radioimmunotherapy“ (RIT-Registry). PET and CT data were uploaded in pseudonymous form into an online archive designed for the purpose of this study (Hermes Medical Solutions®). Treatment response was evaluated both on patient and lesion basis. To do so, clinical parameters as well as the documented patient and image data were analysed for every measurable lesion in terms of location, standardized uptake value and volume. PF were evaluated using a uni- and multivariate generalized mixed linear model (MGMLM). Results Web-based data capture comprised a total of 32 patients (aged 44 up to 86 years) documented retrospectively in the RIT-Registry. From this group, 16 patients with at least 1 PET examination before and after RIT were further analysed. Altogether, 159 lesions were measured corresponding to 1 up to 25 lesions per patient. In regard to the patients response, 5/16 patients achieved a CR, 8/16 patients a PR and 3/16 patients remained with NC. 6 patients showed divergent findings (21/159 lesions). In the MGMLM evaluation, the number of lesions per patient (p=0.009), the maximum lesion volume (p=0.004), total volume of lesions per patient (p=0.001) and the FLIPI (p=0.01) were identified as prognostic factors for patient's response (CR, PR). Concerning the lesional response (CR, PR), initial small lesion volume (in PET and CT) and high metabolic activity (PET) were identified as prognostically relevant variables (both p=0.04). Only the maximum SUV (p<0.0001) in the preRIT scan showed a significant impact on lesional and patients CR. The data of 15 patients concerning the prospective study so far are currently being evaluated and will be presented during the meeting. Conclusion The web-based multicenter acquisition of patient and image data is technically feasible and allows a central evaluation. Based on the findings from the retrospective pilot study, the analysis of the ongoing prospective study will allow to the patient- and even lesion-specific PF for RIT in FL. The data of already available patients from the prospective study will also be presented during the meeting. Disclosures: No relevant conflicts of interest to declare.

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Disrupted Functional Rich-Club Organization of the Brain Networks in Children with Attention-Deficit/Hyperactivity Disorder, a Resting-State EEG Study

Brain Sciences ◽

10.3390/brainsci11070938 ◽

2021 ◽

Vol 11 (7) ◽

pp. 938

Author(s):

Maliheh Ahmadi ◽

Kamran Kazemi ◽

Katarzyna Kuc ◽

Anita Cybulska-Klosowicz ◽

Mohammad Sadegh Helfroush ◽

...

Keyword(s):

Resting State ◽

Phase Synchronization ◽

Brain Networks ◽

Source Analysis ◽

Group Differences ◽

Rich Club ◽

Eyes Closed ◽

Eeg Source Analysis ◽

Functional Brain Networks ◽

The Rich

Growing evidence indicates that disruptions in the brain’s functional connectivity play an important role in the pathophysiology of ADHD. The present study investigates alterations in resting-state EEG source connectivity and rich-club organization in children with inattentive (ADHDI) and combined (ADHDC) ADHD compared with typically developing children (TD) under the eyes-closed condition. EEG source analysis was performed by eLORETA in different frequency bands. The lagged phase synchronization (LPS) and graph theoretical metrics were then used to examine group differences in the topological properties and rich-club organization of functional networks. Compared with the TD children, the ADHDI children were characterized by a widespread significant decrease in delta and beta LPS, as well as increased theta and alpha LPS in the left frontal and right occipital regions. The ADHDC children displayed significant increases in LPS in the central, temporal and posterior areas. Both ADHD groups showed small-worldness properties with significant increases and decreases in the network degree in the θ and β bands, respectively. Both subtypes also displayed reduced levels of network segregation. Group differences in rich-club distribution were found in the central and posterior areas. Our findings suggest that resting-state EEG source connectivity analysis can better characterize alterations in the rich-club organization of functional brain networks in ADHD patients.

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Graph Metrics of Structural Brain Networks in Individuals with Schizophrenia and Healthy Controls: Group Differences, Relationships with Intelligence, and Genetics

Journal of the International Neuropsychological Society ◽

10.1017/s1355617715000867 ◽

2016 ◽

Vol 22 (2) ◽

pp. 240-249 ◽

Cited By ~ 20

Author(s):

Ronald A. Yeo ◽

Sephira G. Ryman ◽

Martijn P. van den Heuvel ◽

Marcel A. de Reus ◽

Rex E. Jung ◽

...

Keyword(s):

Path Length ◽

Brain Networks ◽

Principal Component ◽

Group Differences ◽

Healthy Controls ◽

Characteristic Path Length ◽

Rich Club ◽

Graph Metrics ◽

The Rich ◽

Multi Center Study

AbstractObjectives: One of the most prominent features of schizophrenia is relatively lower general cognitive ability (GCA). An emerging approach to understanding the roots of variation in GCA relies on network properties of the brain. In this multi-center study, we determined global characteristics of brain networks using graph theory and related these to GCA in healthy controls and individuals with schizophrenia. Methods: Participants (N=116 controls, 80 patients with schizophrenia) were recruited from four sites. GCA was represented by the first principal component of a large battery of neurocognitive tests. Graph metrics were derived from diffusion-weighted imaging. Results: The global metrics of longer characteristic path length and reduced overall connectivity predicted lower GCA across groups, and group differences were noted for both variables. Measures of clustering, efficiency, and modularity did not differ across groups or predict GCA. Follow-up analyses investigated three topological types of connectivity—connections among high degree “rich club” nodes, “feeder” connections to these rich club nodes, and “local” connections not involving the rich club. Rich club and local connectivity predicted performance across groups. In a subsample (N=101 controls, 56 patients), a genetic measure reflecting mutation load, based on rare copy number deletions, was associated with longer characteristic path length. Conclusions: Results highlight the importance of characteristic path lengths and rich club connectivity for GCA and provide no evidence for group differences in the relationships between graph metrics and GCA. (JINS, 2016, 22, 240–249)

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