scholarly journals Heterogeneity Within the Frontoparietal Control Network and its Relationship to the Default and Dorsal Attention Networks

2017 ◽  
Author(s):  
Matthew L Dixon ◽  
Alejandro De La Vega ◽  
Caitlin Mills ◽  
Jessica Andrews-Hanna ◽  
R. Nathan Spreng ◽  
...  
Keyword(s):  
General System ◽  
Task Demands ◽  
Control Network ◽  
Data Sets ◽  
Activation Patterns ◽  
Attention Networks ◽  
Machine Learning Classification ◽  
Co Activation ◽  
Flexible Adaptation ◽  
Frontoparietal Control Network

ABSTRACTThe frontoparietal control network (FPCN) plays a central role in executive control. It has been predominantly viewed as a unitary domain general system. Here, we examined patterns of FPCN functional connectivity (FC) across multiple conditions of varying cognitive demands, in order to test for FPCN heterogeneity. We identified two distinct subsystems within the FPCN based on hierarchical clustering and machine learning classification analyses of within-FPCN FC patterns. These two FPCN subsystems exhibited distinct patterns of FC the default network (DN) and the dorsal attentional network (DAN). This 2-fold FPCN differentiation was observed across four independent data sets, across 9 different conditions (rest and 8 tasks), as well as in meta-analytic co-activation patterns. The extent of FPCN differentiation varied across conditions, suggesting flexible adaptation to task demands. These findings reveal a flexible and heterogeneous FPCN organization that may in part emerge from separable DN and DAN processing streams.

scholarly journals Heterogeneity within the frontoparietal control network and its relationship to the default and dorsal attention networks

2018 ◽  
Vol 115 (7) ◽  
pp. E1598-E1607 ◽  
Author(s):  
Matthew L. Dixon ◽  
Alejandro De La Vega ◽  
Caitlin Mills ◽  
Jessica Andrews-Hanna ◽  
R. Nathan Spreng ◽  
...  
Keyword(s):  
General System ◽  
Task Demands ◽  
Control Network ◽  
Opposite Pattern ◽  
Attention Networks ◽  
Machine Learning Classification ◽  
Dorsal Attention Network ◽  
Individual Participant ◽  
Flexible Adaptation ◽  
Frontoparietal Control Network

The frontoparietal control network (FPCN) plays a central role in executive control. It has been predominantly viewed as a unitary domain general system. Here, we examined patterns of FPCN functional connectivity (FC) across multiple conditions of varying cognitive demands, to test for FPCN heterogeneity. We identified two distinct subsystems within the FPCN based on hierarchical clustering and machine learning classification analyses of within-FPCN FC patterns. These two FPCN subsystems exhibited distinct patterns of FC with the default network (DN) and the dorsal attention network (DAN). FPCNA exhibited stronger connectivity with the DN than the DAN, whereas FPCNB exhibited the opposite pattern. This twofold FPCN differentiation was observed across four independent datasets, across nine different conditions (rest and eight tasks), at the level of individual-participant data, as well as in meta-analytic coactivation patterns. Notably, the extent of FPCN differentiation varied across conditions, suggesting flexible adaptation to task demands. Finally, we used meta-analytic tools to identify several functional domains associated with the DN and DAN that differentially predict activation in the FPCN subsystems. These findings reveal a flexible and heterogeneous FPCN organization that may in part emerge from separable DN and DAN processing streams. We propose that FPCNA may be preferentially involved in the regulation of introspective processes, whereas FPCNB may be preferentially involved in the regulation of visuospatial perceptual attention.

scholarly journals Intrinsic Architecture Underlying the Relations among the Default, Dorsal Attention, and Frontoparietal Control Networks of the Human Brain

2013 ◽  
Vol 25 (1) ◽  
pp. 74-86 ◽  
Author(s):  
R. Nathan Spreng ◽  
Jorge Sepulcre ◽  
Gary R. Turner ◽  
W. Dale Stevens ◽  
Daniel L. Schacter
Keyword(s):  
Functional Connectivity ◽  
Large Scale ◽  
Dynamic Balance ◽  
Brain Regions ◽  
Human Cognition ◽  
Control Network ◽  
Resting State Functional Connectivity ◽  
Attention Networks ◽  
Large Scale Networks ◽  
Frontoparietal Control Network

Human cognition is increasingly characterized as an emergent property of interactions among distributed, functionally specialized brain networks. We recently demonstrated that the antagonistic “default” and “dorsal attention” networks—subserving internally and externally directed cognition, respectively—are modulated by a third “frontoparietal control” network that flexibly couples with either network depending on task domain. However, little is known about the intrinsic functional architecture underlying this relationship. We used graph theory to analyze network properties of intrinsic functional connectivity within and between these three large-scale networks. Task-based activation from three independent studies were used to identify reliable brain regions (“nodes”) of each network. We then examined pairwise connections (“edges”) between nodes, as defined by resting-state functional connectivity MRI. Importantly, we used a novel bootstrap resampling procedure to determine the reliability of graph edges. Furthermore, we examined both full and partial correlations. As predicted, there was a higher degree of integration within each network than between networks. Critically, whereas the default and dorsal attention networks shared little positive connectivity with one another, the frontoparietal control network showed a high degree of between-network interconnectivity with each of these networks. Furthermore, we identified nodes within the frontoparietal control network of three different types—default-aligned, dorsal attention-aligned, and dual-aligned—that we propose play dissociable roles in mediating internetwork communication. The results provide evidence consistent with the idea that the frontoparietal control network plays a pivotal gate-keeping role in goal-directed cognition, mediating the dynamic balance between default and dorsal attention networks.

scholarly journals Anticorrelation between default and dorsal attention networks varies across default subsystems and cognitive states

2016 ◽  
Author(s):  
Matthew L. Dixon ◽  
Jessica R. Andrews-Hanna ◽  
R. Nathan Spreng ◽  
Zachary C. Irving ◽  
Kalina Christoff
Keyword(s):  
Default Network ◽  
Control Network ◽  
Brain Organization ◽  
Attention Networks ◽  
Functional Brain ◽  
Cognitive States ◽  
Dorsal Attention Network ◽  
Functional Brain Organization ◽  
The Stability ◽  
Frontoparietal Control Network

SummaryAnticorrelation between the default network (DN) and dorsal attention network (DAN) is thought to be an intrinsic aspect of functional brain organization reflecting competing functions. However, the stability of anticorrelations across distinct DN subsystems, different contexts, and time, remains unexplored. Here we examine DN-DAN functional connectivity across six different cognitive states. We show that:(i) the DAN is anticorrelated with the DN core subsystem, but not with the two DN subsystems involved in mentalizing and mnemonic functions, respectively; (ii) DN-DAN interactions vary significantly across cognitive states; (iii) DN-DAN connectivity fluctuates across time between periods of anticorrelation and periods of positive correlation; and (iv) coupling between the frontoparietal control network (FPCN) and DAN predicts variation in the strength of DN-DAN anticorrelation across time. These findings reveal substantial variability in DN-DAN interactions, suggesting that these networks are not strictly competitive, and that the FPCN may act to modulate their anticorrelation strength.

scholarly journals How (not) to cross a boundary: Crosslinguistic influence in simultaneous bilingual children's event construal

2021 ◽  
pp. 1-13
Author(s):  
Helen Engemann
Keyword(s):  
Production Process ◽  
Age Groups ◽  
Boundary Crossing ◽  
Bilingual Children ◽  
Activation Patterns ◽  
Motion Event ◽  
Co Activation ◽  
Crosslinguistic Influence ◽  
Event Construal ◽  
Two Age Groups

Abstract Simultaneous bilingual children sometimes display crosslinguistic influence (CLI), widely attested in the domain of morphosyntax. It remains less clear whether CLI affects bilinguals’ event construal, what motivates its occurrence and directionality, and how developmentally persistent it is. The present study tested predictions generated by the structural overlap hypothesis and the co-activation account in the motion event domain. 96 English–French bilingual children of two age groups and 96 age-matched monolingual English and French controls were asked to describe animated videos displaying voluntary motion events. Semantic encoding in main verbs showed bidirectional CLI. Unidirectional CLI affected French path encoding in the verbal periphery and was predicted by the presence of boundary-crossing, despite the absence of structural overlap. Furthermore, CLI increased developmentally in the French data. It is argued that these findings reflect highly dynamic co-activation patterns sensitive to the requirements of the task and to language-specific challenges in the online production process.

scholarly journals Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation states

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Arian Ashourvan ◽  
Preya Shah ◽  
Adam Pines ◽  
Shi Gu ◽  
Christopher W. Lynn ◽  
...  
Keyword(s):  
White Matter ◽  
Maximum Entropy ◽  
Large Scale ◽  
Structural Connectivity ◽  
Quantitative Relationship ◽  
Brain Regions ◽  
Maximum Entropy Model ◽  
Entropy Model ◽  
Activation Patterns ◽  
Co Activation

AbstractA major challenge in neuroscience is determining a quantitative relationship between the brain’s white matter structural connectivity and emergent activity. We seek to uncover the intrinsic relationship among brain regions fundamental to their functional activity by constructing a pairwise maximum entropy model (MEM) of the inter-ictal activation patterns of five patients with medically refractory epilepsy over an average of ~14 hours of band-passed intracranial EEG (iEEG) recordings per patient. We find that the pairwise MEM accurately predicts iEEG electrodes’ activation patterns’ probability and their pairwise correlations. We demonstrate that the estimated pairwise MEM’s interaction weights predict structural connectivity and its strength over several frequencies significantly beyond what is expected based solely on sampled regions’ distance in most patients. Together, the pairwise MEM offers a framework for explaining iEEG functional connectivity and provides insight into how the brain’s structural connectome gives rise to large-scale activation patterns by promoting co-activation between connected structures.

Altered Resting-State Frontoparietal Control Network in Children with Attention-Deficit/Hyperactivity Disorder

2015 ◽  
Vol 21 (4) ◽  
pp. 271-284 ◽  
Author(s):  
Hsiang-Yuan Lin ◽  
Wen-Yih Isaac Tseng ◽  
Meng-Chuan Lai ◽  
Kayako Matsuo ◽  
Susan Shur-Fen Gau
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Prefrontal Cortex ◽  
Functional Connectivity ◽  
Resting State ◽  
Control Network ◽  
Children With Adhd ◽  
Hyperactivity Disorder ◽  
Anterior Prefrontal Cortex ◽  
The Right ◽  
Frontoparietal Control Network

AbstractThe frontoparietal control network, anatomically and functionally interposed between the dorsal attention network and default mode network, underpins executive control functions. Individuals with attention-deficit/hyperactivity disorder (ADHD) commonly exhibit deficits in executive functions, which are mainly mediated by the frontoparietal control network. Involvement of the frontoparietal control network based on the anterior prefrontal cortex in neurobiological mechanisms of ADHD has yet to be tested. We used resting-state functional MRI and seed-based correlation analyses to investigate functional connectivity of the frontoparietal control network in a sample of 25 children with ADHD (7–14 years; mean 9.94±1.77 years; 20 males), and 25 age-, sex-, and performance IQ-matched typically developing (TD) children. All participants had limited in-scanner head motion. Spearman’s rank correlations were used to test the associations between altered patterns of functional connectivity with clinical symptoms and executive functions, measured by the Conners’ Continuous Performance Test and Spatial Span in the Cambridge Neuropsychological Test Automated Battery. Compared with TD children, children with ADHD demonstrated weaker connectivity between the right anterior prefrontal cortex (PFC) and the right ventrolateral PFC, and between the left anterior PFC and the right inferior parietal lobule. Furthermore, this aberrant connectivity of the frontoparietal control network in ADHD was associated with symptoms of impulsivity and opposition-defiance, as well as impaired response inhibition and attentional control. The findings support potential integration of the disconnection model and the executive dysfunction model for ADHD. Atypical frontoparietal control network may play a pivotal role in the pathophysiology of ADHD. (JINS, 2015, 21, 271–284)

scholarly journals Rest-task Modulation of fMRI-derived Global Signal Topography is Mediated by Transient Co-activation Patterns

2019 ◽  
Author(s):  
Jianfeng Zhang ◽  
Zirui Huang ◽  
Shankar Tumati ◽  
Georg Northoff
Keyword(s):  
Resting State ◽  
Resting State Fmri ◽  
Peak Period ◽  
Physiological Noise ◽  
Activation Patterns ◽  
Global Signal ◽  
Co Activation ◽  
Human Connectome Project ◽  
Partial Dissociation ◽  
Signal Correlation

AbstractRecent resting-state fMRI studies have revealed that the global signal (GS) exhibits a non-uniform spatial distribution across the gray matter. Whether this topography is informative remains largely unknown. We therefore tested rest-task modulation of global signal topography by analyzing static global signal correlation and dynamic co-activation patterns in a large sample of fMRI dataset (n=837) from the Human Connectome Project. The GS topography in the resting-state and in seven different tasks was first measured by correlating the global signal with the local timeseries (GSCORR). In the resting state, high GSCORR was observed mainly in the primary sensory and motor regions, while low GSCORR was seen in the association brain areas. This pattern changed during the seven tasks, with mainly decreased GSCORR in sensorimotor cortex. Importantly, this rest-task modulation of GSCORR could be traced to transient co-activation patterns at the peak period of global signal (GS-peak). By comparing the topography of GSCORR and respiration effects, we observed that the topography of respiration mimicked the topography of global signal in the resting-state whereas both differed during the task states; due to such partial dissociation, we assume that GSCORR could not be equated with a respiration effect. Finally, rest-task modulation of GS topography could not be exclusively explained by other sources of physiological noise. Together, we here demonstrate the informative nature of global signal topography by showing its rest-task modulation, the underlying dynamic co-activation patterns, and its partial dissociation from respiration effects during task states.

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