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

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.

scholarly journals Between-module functional connectivity of the salient ventral attention network and dorsal attention network is associated with motor inhibition

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0242985
Author(s):  
Howard Muchen Hsu ◽  
Zai-Fu Yao ◽  
Kai Hwang ◽  
Shulan Hsieh
Keyword(s):  
Individual Differences ◽  
Brain Networks ◽  
Network Connectivity ◽  
Brain Regions ◽  
Motor Inhibition ◽  
Attention Network ◽  
Functional Brain ◽  
Graph Theoretic ◽  
Dorsal Attention Network ◽  
Functional Brain Networks

The ability to inhibit motor response is crucial for daily activities. However, whether brain networks connecting spatially distinct brain regions can explain individual differences in motor inhibition is not known. Therefore, we took a graph-theoretic perspective to examine the relationship between the properties of topological organization in functional brain networks and motor inhibition. We analyzed data from 141 healthy adults aged 20 to 78, who underwent resting-state functional magnetic resonance imaging and performed a stop-signal task along with neuropsychological assessments outside the scanner. The graph-theoretic properties of 17 functional brain networks were estimated, including within-network connectivity and between-network connectivity. We employed multiple linear regression to examine how these graph-theoretical properties were associated with motor inhibition. The results showed that between-network connectivity of the salient ventral attention network and dorsal attention network explained the highest and second highest variance of individual differences in motor inhibition. In addition, we also found those two networks span over brain regions in the frontal-cingulate-parietal network, suggesting that these network interactions are also important to motor inhibition.

scholarly journals Identifying reproducible individual differences in childhood functional brain networks: An ABCD study

2019 ◽  
Vol 40 ◽  
pp. 100706 ◽  
Author(s):  
Scott Marek ◽  
Brenden Tervo-Clemmens ◽  
Ashley N. Nielsen ◽  
Muriah D. Wheelock ◽  
Ryland L. Miller ◽  
...  
Keyword(s):  
Individual Differences ◽  
Brain Networks ◽  
Functional Brain ◽  
Functional Brain Networks

scholarly journals Individual differences in intrinsic brain connectivity predict decision strategy

2014 ◽  
Vol 112 (8) ◽  
pp. 1838-1848 ◽  
Author(s):  
Kelly Anne Barnes ◽  
Kevin M. Anderson ◽  
Mark Plitt ◽  
Alex Martin
Keyword(s):  
Decision Making ◽  
Individual Differences ◽  
Brain Activity ◽  
Brain Networks ◽  
Decision Strategy ◽  
Neural Basis ◽  
Motion Direction ◽  
Functional Brain ◽  
Spontaneous Brain Activity ◽  
Functional Brain Networks

When humans are provided with ample time to make a decision, individual differences in strategy emerge. Using an adaptation of a well-studied decision making paradigm, motion direction discrimination, we probed the neural basis of individual differences in strategy. We tested whether strategies emerged from moment-to-moment reconfiguration of functional brain networks involved in decision making with task-evoked functional MRI (fMRI) and whether intrinsic properties of functional brain networks, measured at rest with functional connectivity MRI (fcMRI), were associated with strategy use. We found that human participants reliably selected one of two strategies across 2 days of task performance, either continuously accumulating evidence or waiting for task difficulty to decrease. Individual differences in decision strategy were predicted both by the degree of task-evoked activation of decision-related brain regions and by the strength of pretask correlated spontaneous brain activity. These results suggest that spontaneous brain activity constrains strategy selection on perceptual decisions.

scholarly journals Vascular physiology drives functional brain networks

2018 ◽  
Author(s):  
Molly G. Bright ◽  
Joseph R. Whittaker ◽  
Ian D. Driver ◽  
Kevin Murphy
Keyword(s):  
Time Series ◽  
Vascular Function ◽  
Brain Networks ◽  
Memory Task ◽  
Imaging Data ◽  
Dual Nature ◽  
Functional Brain ◽  
Vascular Regulation ◽  
Functional Brain Networks ◽  
Dual Regression

ABSTRACTWe present the first evidence for vascular regulation driving fMRI signals in specific functional brain networks. Using concurrent neuronal and vascular stimuli, we collected 30 BOLD fMRI datasets in 10 healthy individuals: a working memory task, flashing checkerboard stimulus, and CO2 inhalation challenge were delivered in concurrent but orthogonal paradigms. The resulting imaging data were averaged together and decomposed using independent component analysis, and three “neuronal networks” were identified as demonstrating maximum temporal correlation with the neuronal stimulus paradigms: Default Mode Network, Task Positive Network, and Visual Network. For each of these, we observed a second network component with high spatial overlap. Using dual regression in the original 30 datasets, we extracted the time-series associated with these network pairs and calculated the percent of variance explained by the neuronal or vascular stimuli using a normalized R2 parameter. In each pairing, one network was dominated by the appropriate neuronal stimulus, and the other was dominated by the vascular stimulus as represented by the end-tidal CO2 time-series recorded in each scan. We acquired a second dataset in 8 of the original participants, where no CO2 challenge was delivered and CO2 levels fluctuated naturally with breathing variations. Although splitting of functional networks was not robust in these data, performing dual regression with the network maps from the original analysis in this new dataset successfully replicated our observations. Thus, in addition to responding to localized metabolic changes, the brain’s vasculature may be regulated in a coordinated manner that mimics (and potentially supports) specific functional brain networks. Multi-modal imaging and advances in fMRI acquisition and analysis could facilitate further study of the dual nature of functional brain networks. It will be critical to understand network-specific vascular function, and the behavior of a coupled vascular-neural network, in future studies of brain pathology.

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

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.

scholarly journals Multiple Functional Brain Networks Related to Pain Perception Revealed by fMRI

2021 ◽  
Author(s):  
Matteo Damascelli ◽  
Todd S. Woodward ◽  
Nicole Sanford ◽  
Hafsa B. Zahid ◽  
Ryan Lim ◽  
...  
Keyword(s):  
Pain Perception ◽  
Brain Networks ◽  
Data Driven ◽  
Functional Networks ◽  
Brain State ◽  
Imaging Data ◽  
Whole Brain ◽  
Functional Brain ◽  
Network Activation ◽  
Functional Brain Networks

AbstractThe rise of functional magnetic resonance imaging (fMRI) has led to a deeper understanding of cortical processing of pain. Central to these advances has been the identification and analysis of “functional networks”, often derived from groups of pre-selected pain regions. In this study our main objective was to identify functional brain networks related to pain perception by examining whole-brain activation, avoiding the need for a priori selection of regions. We applied a data-driven technique—Constrained Principal Component Analysis for fMRI (fMRI-CPCA)—that identifies networks without assuming their anatomical or temporal properties. Open-source fMRI data collected during a thermal pain task (33 healthy participants) were subjected to fMRI-CPCA for network extraction, and networks were associated with pain perception by modelling subjective pain ratings as a function of network activation intensities. Three functional networks emerged: a sensorimotor response network, a salience-mediated attention network, and the default-mode network. Together, these networks constituted a brain state that explained variability in pain perception, both within and between individuals, demonstrating the potential of data-driven, whole-brain functional network techniques for the analysis of pain imaging data.

scholarly journals The role of norepinephrine in the pathophysiology of schizophrenia

2019 ◽  
Author(s):  
Verónica Expósito de Mäki-Marttunen ◽  
Ole A. Andreassen ◽  
Thomas Espeseth
Keyword(s):  
Locus Coeruleus ◽  
Structural Properties ◽  
Brain Function ◽  
Brain Networks ◽  
Pharmacological Interventions ◽  
Functional Brain ◽  
Functional Brain Networks ◽  
Experimental Approaches ◽  
Lines Of Evidence

Several lines of evidence suggest a role for norepinephrine (NE) in the pathophysiology of schizophrenia, and in pharmacological interventions. In the present paper, we review recent findings about the locus coeruleus-norepinephrine (LC-NE) system and its involvement in brain function and cognition to give a more integrated account of the possible role of NE in schizophrenia. First, we review the functional and structural properties of the LC-NE system and its impact on functional brain networks, cognition, stress, and neurodevelopment, with special emphasis on recent experimental and theoretical advances. Subsequently, we present an update about the role of these properties for the pathophysiology of schizophrenia, focusing on the cognitive and motivational deficits observed in schizophrenia. Finally, we suggest how recent development of experimental approaches can be used to characterize LC function in schizophrenia.

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