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.

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

2021 ◽  
Author(s):  
Taylor Bolt ◽  
Jason Nomi ◽  
Danilo Bzdok ◽  
Catie Chang ◽  
B.T. Yeo ◽  
...  
Keyword(s):  
Large Scale ◽  
Functional Neuroimaging ◽  
Time Lag ◽  
Low Frequency ◽  
Resting State Fmri ◽  
Spatiotemporal Patterns ◽  
Brain Organization ◽  
Functional Brain ◽  
Global Signal ◽  
Functional Brain Organization

Abstract The past decade of functional neuroimaging research has seen the application of increasingly sophisticated advanced methods to characterize intrinsic functional brain organization. Accompanying these techniques are a patchwork of empirical findings highlighting novel properties of intrinsic functional brain organization. To date, there has been little attempt to understand whether there is an underlying unity across this patchwork of empirical findings. Our study conducted a systematic survey of popular analytic techniques and their output on a large sample of resting-state fMRI data. We found that the apparent complexity of intrinsic functional brain organization can be seamlessly reduced to three fundamental low-frequency spatiotemporal patterns. Our study demonstrates that a long list of previously observed phenomena, including functional connectivity gradients, the task-positive/task-negative pattern, the global signal, time-lag propagation patterns, the quasiperiodic pattern and the network structure of the functional connectome are simply manifestations of these three spatiotemporal patterns. An in-depth characterization of these three spatiotemporal patterns using a novel time-varying complex pattern analysis revealed that these three patterns may arise from a single hemodynamic mechanism.

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 Timescales of spontaneous fMRI fluctuations relate to structural connectivity in the brain

2019 ◽  
Author(s):  
John Fallon ◽  
Phil Ward ◽  
Linden Parkes ◽  
Stuart Oldham ◽  
Aurina Arnatkevic̆iūtė ◽  
...  
Keyword(s):  
Resting State ◽  
Structural Connectivity ◽  
Resting State Fmri ◽  
Information Storage ◽  
Brain Organization ◽  
Temporal Properties ◽  
Temporal Features ◽  
Human Connectome Project ◽  
The Brain ◽  
Connectivity Strength

AbstractIntrinsic timescales of activity fluctuations vary hierarchically across the brain. This variation reflects a broad gradient of functional specialization in information storage and processing, with integrative association areas displaying slower timescales that are thought to reflect longer temporal processing windows. The organization of timescales is associated with cognitive function, distinctive between individuals, and disrupted in disease, but we do not yet understand how the temporal properties of activity dynamics are shaped by the brain’s underlying structural-connectivity network. Using resting-state fMRI and diffusion MRI data from 100 healthy individuals from the Human Connectome Project, here we show that the timescale of resting-state fMRI dynamics increases with structural-connectivity strength, matching recent results in the mouse brain. Our results hold at the level of individuals, are robust to parcellation schemes, and are conserved across a range of different timescale-related statistics. We establish a comprehensive BOLD dynamical signature of structural connectivity strength by comparing over 6000 time-series features, highlighting a range of new temporal features for characterizing BOLD dynamics, including measures of stationarity and symbolic motif frequencies. Our findings indicate a conserved property of mouse and human brain organization in which a brain region’s spontaneous activity fluctuations are closely related to their surrounding structural scaffold.

scholarly journals Timescales of spontaneous fMRI fluctuations relate to structural connectivity in the brain

2020 ◽  
Vol 4 (3) ◽  
pp. 788-806 ◽  
Author(s):  
John Fallon ◽  
Phillip G. D. Ward ◽  
Linden Parkes ◽  
Stuart Oldham ◽  
Aurina Arnatkevičiūtė ◽  
...  
Keyword(s):  
Resting State ◽  
Structural Connectivity ◽  
Resting State Fmri ◽  
Information Storage ◽  
Brain Organization ◽  
Temporal Properties ◽  
Temporal Features ◽  
Human Connectome Project ◽  
The Brain ◽  
Connectivity Strength

Intrinsic timescales of activity fluctuations vary hierarchically across the brain. This variation reflects a broad gradient of functional specialization in information storage and processing, with integrative association areas displaying slower timescales that are thought to reflect longer temporal processing windows. The organization of timescales is associated with cognitive function, distinctive between individuals, and disrupted in disease, but we do not yet understand how the temporal properties of activity dynamics are shaped by the brain’s underlying structural connectivity network. Using resting-state fMRI and diffusion MRI data from 100 healthy individuals from the Human Connectome Project, here we show that the timescale of resting-state fMRI dynamics increases with structural connectivity strength, matching recent results in the mouse brain. Our results hold at the level of individuals, are robust to parcellation schemes, and are conserved across a range of different timescale- related statistics. We establish a comprehensive BOLD dynamical signature of structural connectivity strength by comparing over 6,000 time series features, highlighting a range of new temporal features for characterizing BOLD dynamics, including measures of stationarity and symbolic motif frequencies. Our findings indicate a conserved property of mouse and human brain organization in which a brain region’s spontaneous activity fluctuations are closely related to their surrounding structural scaffold.

scholarly journals Sex classification by resting state brain connectivity

2019 ◽  
Author(s):  
Susanne Weis ◽  
Kaustubh 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 ◽  
Two Samples ◽  
Imaging Research ◽  
Functional Brain Organization

1AbstractA 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 two samples from the Human Connectome Project (n1 = 434, n2 = 310) and one fully independent sample from the 1000BRAINS study (n=941). The classifier, which was trained on one sample and tested on the other two, 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, temporo-parietal 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 Organization of Propagated Intrinsic Brain Activity in Individual Humans

2019 ◽  
Vol 30 (3) ◽  
pp. 1716-1734 ◽  
Author(s):  
Ryan V Raut ◽  
Anish Mitra ◽  
Scott Marek ◽  
Mario Ortega ◽  
Abraham Z Snyder ◽  
...  
Keyword(s):  
Resting State ◽  
Large Scale ◽  
Cortical Excitability ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Brain Organization ◽  
Individual Level ◽  
Slow Activity ◽  
Lag Structure

Abstract Spontaneous infra-slow (<0.1 Hz) fluctuations in functional magnetic resonance imaging (fMRI) signals are temporally correlated within large-scale functional brain networks, motivating their use for mapping systems-level brain organization. However, recent electrophysiological and hemodynamic evidence suggest state-dependent propagation of infra-slow fluctuations, implying a functional role for ongoing infra-slow activity. Crucially, the study of infra-slow temporal lag structure has thus far been limited to large groups, as analyzing propagation delays requires extensive data averaging to overcome sampling variability. Here, we use resting-state fMRI data from 11 extensively-sampled individuals to characterize lag structure at the individual level. In addition to stable individual-specific features, we find spatiotemporal topographies in each subject similar to the group average. Notably, we find a set of early regions that are common to all individuals, are preferentially positioned proximal to multiple functional networks, and overlap with brain regions known to respond to diverse behavioral tasks—altogether consistent with a hypothesized ability to broadly influence cortical excitability. Our findings suggest that, like correlation structure, temporal lag structure is a fundamental organizational property of resting-state infra-slow activity.

scholarly journals Post-stroke fatigue is linked to resting state posterior hypoactivity and prefrontal hyperactivity

2021 ◽  
Author(s):  
Georgia Mary Cotter ◽  
Mohamed Salah Khlif ◽  
Laura Bird ◽  
Mark E Howard ◽  
Amy Brodtmann ◽  
...  
Keyword(s):  
Ischaemic Stroke ◽  
Resting State ◽  
Large Scale ◽  
Brain Activity ◽  
Low Frequency ◽  
Resting State Fmri ◽  
Stroke Severity ◽  
Stroke Survivors ◽  
Whole Brain ◽  
Post Stroke

Background and Purpose. Fatigue is associated with poor functional outcomes and increased mortality following stroke. Survivors identify fatigue as one of their key unmet needs. Despite the growing body of research into post-stroke fatigue, the specific neural mechanisms remain largely unknown. Methods. This observational study included 63 stroke survivors (22 women; age 30-89 years; mean 67.5 years) from the Cognition And Neocortical Volume After Stroke (CANVAS) study, a cohort study examining cognition, mood, and brain volume in stroke survivors following ischaemic stroke. Participants underwent brain imaging 3 months post-stroke, including a 7-minute resting state fMRI echoplanar sequence. We calculated the fractional amplitude of low-frequency fluctuations, a measure of resting state brain activity at the whole-brain level. Results. Forty-five participants reported experiencing post-stroke fatigue as measured by an item on the Patient Health Questionnaire-9. A generalised linear regression model analysis with age, sex, and stroke severity covariates was conducted to compare resting state brain activity in the 0.01-0.08 Hz range, as well as its subcomponents - slow-5 (0.01-0.027 Hz), and slow-4 (0.027-0.073 Hz) frequency bands between fatigued and non-fatigued participants. We found no significant associations between post-stroke fatigue and ischaemic stroke lesion location or stroke volume. However, in the overall 0.01-0.08 Hz band, participants with post-stroke fatigue demonstrated significantly lower resting-state activity in the calcarine cortex (p<0.001, cluster-corrected pFDR=0.009, k=63) and lingual gyrus (p<0.001, cluster-corrected pFDR=0.025, k=42) and significantly higher activity in the medial prefrontal cortex (p<0.001, cluster-corrected pFDR=0.03, k=45), attributed to slow-4 and slow-5 oscillations, respectively. Conclusions. Post-stroke fatigue is associated with posterior hypoactivity and prefrontal hyperactivity, reflecting dysfunction within large-scale brain systems such as fronto-striatal-thalamic and frontal-occipital networks. These systems in turn might reflect a relationship between post-stroke fatigue and abnormalities in executive and visual functioning. This first whole-brain resting-state study provides new targets for further investigation of post-stroke fatigue beyond the lesion approach.

scholarly journals Large-scale functional brain network changes in taxi drivers: Evidence from resting-state fMRI

2014 ◽  
Vol 36 (3) ◽  
pp. 862-871 ◽  
Author(s):  
Lubin Wang ◽  
Qiang Liu ◽  
Hui Shen ◽  
Hong Li ◽  
Dewen Hu
Keyword(s):  
Resting State ◽  
Large Scale ◽  
Resting State Fmri ◽  
Brain Network ◽  
Taxi Drivers ◽  
Functional Brain ◽  
Functional Brain Network

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.

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