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 Innate Organization of the Human Brain

2021 ◽  
Author(s):  
M. Fiona Molloy ◽  
Zeynep M. Saygin
Keyword(s):  
Individual Variability ◽  
Adult Brain ◽  
Brain Organization ◽  
Attention Networks ◽  
Functional Brain ◽  
Human Connectome Project ◽  
Differential Gene ◽  
Functional Brain Organization ◽  
High Level ◽  
Genetically Determined

The adult brain is organized into distinct functional networks, forming the basis of information processing and determining individual differences in behavior. Is this network organization genetically determined and present at birth? Here, we use unsupervised learning to uncover intrinsic functional brain organization using resting-state connectivity from a large cohort of neonates (Developing Human Connectome Project). We identified a set of symmetric, hierarchical, and replicable networks: sensorimotor, visual, default mode, ventral attention, and high-level vision. We also quantified neonate individual variability, finding low variability for sensorimotor, but high for ventral attention networks. These neonate networks resembled adult networks (Yeo et al., 2011), but frontoparietal and limbic networks found in adults were indiscernible in neonates. Finally, differential gene expression provided a potential explanation for the emergence of these distinct networks. Our results reveal the basic proto-organization of cortex at birth, but indicate a role for maturation and experience in developing adult-like functional brain organization.

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 Sex Classification by Resting State Brain Connectivity

2019 ◽  
Vol 30 (2) ◽  
pp. 824-835 ◽  
Author(s):  
Susanne Weis ◽  
Kaustubh R Patil ◽  
Felix Hoffstaedter ◽  
Alessandra Nostro ◽  
B T Thomas Yeo ◽  
...  
Keyword(s):  
Resting State ◽  
Brain Connectivity ◽  
Brain Regions ◽  
Brain Organization ◽  
Functional Brain ◽  
Clear Cut ◽  
Human Connectome Project ◽  
Machine Learning Approach ◽  
Imaging Research ◽  
Functional Brain Organization

Abstract A large amount of brain imaging research has focused on group studies delineating differences between males and females with respect to both cognitive performance as well as structural and functional brain organization. To supplement existing findings, the present study employed a machine learning approach to assess how accurately participants’ sex can be classified based on spatially specific resting state (RS) brain connectivity, using 2 samples from the Human Connectome Project (n1 = 434, n2 = 310) and 1 fully independent sample from the 1000BRAINS study (n = 941). The classifier, which was trained on 1 sample and tested on the other 2, was able to reliably classify sex, both within sample and across independent samples, differing both with respect to imaging parameters and sample characteristics. Brain regions displaying highest sex classification accuracies were mainly located along the cingulate cortex, medial and lateral frontal cortex, temporoparietal regions, insula, and precuneus. These areas were stable across samples and match well with previously described sex differences in functional brain organization. While our data show a clear link between sex and regionally specific brain connectivity, they do not support a clear-cut dimorphism in functional brain organization that is driven by sex alone.

scholarly journals Default network activity, coupled with the frontoparietal control network, supports goal-directed cognition

NeuroImage ◽  
2010 ◽  
Vol 53 (1) ◽  
pp. 303-317 ◽  
Author(s):  
R. Nathan Spreng ◽  
W. Dale Stevens ◽  
Jon P. Chamberlain ◽  
Adrian W. Gilmore ◽  
Daniel L. Schacter
Keyword(s):  
Network Activity ◽  
Default Network ◽  
Control Network ◽  
Frontoparietal Control Network

scholarly journals Influence of estradiol on functional brain organization for working memory

NeuroImage ◽  
2012 ◽  
Vol 59 (3) ◽  
pp. 2923-2931 ◽  
Author(s):  
Jane E. Joseph ◽  
Joshua E. Swearingen ◽  
Christine R. Corbly ◽  
Thomas E. Curry ◽  
Thomas H. Kelly
Keyword(s):  
Working Memory ◽  
Brain Organization ◽  
Functional Brain ◽  
Functional Brain Organization

scholarly journals Large-Scale Intrinsic Functional Brain Organization Emerges from Three Canonical Spatiotemporal Patterns

2021 ◽  
Author(s):  
Taylor S Bolt ◽  
Jason Nomi ◽  
Danilo Bzdok ◽  
Catie Chang ◽  
B.T. Thomas Yeo ◽  
...  
Keyword(s):  
Resting State ◽  
Large Scale ◽  
Low Frequency ◽  
Resting State Fmri ◽  
Spatiotemporal Patterns ◽  
Brain Organization ◽  
Functional Brain ◽  
Temporal Properties ◽  
Human Connectome Project ◽  
Functional Brain Organization

The characterization of intrinsic functional brain organization has been approached from a multitude of analytic techniques and methods. We are still at a loss of a unifying conceptual framework for capturing common insights across this patchwork of empirical findings. By analyzing resting-state fMRI data from the Human Connectome Project using a large number of popular analytic techniques, we find that all results can be seamlessly reconciled by three fundamental low-frequency spatiotemporal patterns that we have identified via a novel time-varying complex pattern analysis. Overall, these three spatiotemporal patterns account for a wide variety of previously observed phenomena in the resting-state fMRI literature including the task-positive/task-negative anticorrelation, the global signal, the primary functional connectivity gradient and the network community structure of the functional connectome. The shared spatial and temporal properties of these three canonical patterns suggest that they arise from a single hemodynamic mechanism.

Functional brain organization of working memory in adolescents varies in relation to family income and academic achievement

2016 ◽  
Vol 20 (5) ◽  
pp. e12450 ◽  
Author(s):  
Amy S. Finn ◽  
Jennifer E. Minas ◽  
Julia A. Leonard ◽  
Allyson P. Mackey ◽  
John Salvatore ◽  
...  
Keyword(s):  
Academic Achievement ◽  
Working Memory ◽  
Family Income ◽  
Brain Organization ◽  
Functional Brain ◽  
Functional Brain Organization
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