4.7 Article

On co-activation pattern analysis and non-stationarity of resting brain activity

Related references

Note: Only part of the references are listed.
Article Multidisciplinary Sciences

A mathematical perspective on edge-centric brain functional connectivity

Leonardo Novelli et al.

Summary: This study presents a mathematical framework for an edge-centric analysis of neuroimaging time series and re-examines previous findings in the field. The authors discuss the use of edge time series in studying node functional connectivity dynamics and highlight the importance of dynamic measures over static null models. Analyzing functional MRI data confirms that node functional connectivity can explain most variations in edge functional connectivity matrix, edge communities, large co-fluctuations, and corresponding spatial patterns. The study encourages the future use of dynamic measures in research.

NATURE COMMUNICATIONS (2022)

Article Neurosciences

Interpreting null models of resting-state functional MRI dynamics: not throwing the model out with the hypothesis

Raphael Liegeois et al.

Summary: Null models are useful for assessing non-trivial properties in datasets, but their interpretation in neuroimaging may not always be straightforward. While they can help characterize the statistical properties of fMRI time series and metrics, null-model testing should not be considered a mandatory validation step for assessing their relevance in representing brain functional dynamics.

NEUROIMAGE (2021)

Article Neurosciences

Reproducible coactivation patterns of functional brain networks reveal the aberrant dynamic state transition in schizophrenia

Hang Yang et al.

Summary: Recent studies have shown that there is significant dynamic information in resting-state fMRI and have identified recurring states dominated by similar coactivation patterns (CAPs). The reproducibility and generalizability of CAP analysis were investigated in this study, revealing six reliable CAP states and their dynamic characteristics. Additionally, aberrant CAP states in schizophrenia were found to be associated with symptom severity.

NEUROIMAGE (2021)

Article Neurosciences

Dynamics of amygdala connectivity in bipolar disorders: a longitudinal study across mood states

Gwladys Rey et al.

Summary: The study explores alterations in brain circuits related to emotion processing and regulation in different mood states of bipolar disorder (BD) patients, using a novel co-activation pattern (CAP) analysis to reveal dynamic changes in amygdala connectivity. Distinct interactions between amygdala and distributed brain networks in different mood states were identified, highlighting the importance of further research on interoception and default-mode systems.

NEUROPSYCHOPHARMACOLOGY (2021)

Article Multidisciplinary Sciences

High-amplitude cofluctuations in cortical activity drive functional connectivity

Farnaz Zamani Esfahlani et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2020)

Article Multidisciplinary Sciences

Resting brain dynamics at different timescales capture distinct aspects of human behavior

Raphael Liegeois et al.

NATURE COMMUNICATIONS (2019)

Review Neurosciences

Co-activation patterns in resting-state fMRI signals

Xiao Liu et al.

NEUROIMAGE (2018)

Article Neurosciences

On the Stability of BOLD fMRI Correlations

Timothy O. Laumann et al.

CEREBRAL CORTEX (2017)

Article Multidisciplinary Sciences

Temporal metastates are associated with differential patterns of time-resolved connectivity, network topology, and attention

James M. Shine et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2016)

Editorial Material Neurosciences

Towards a statistical test for functional connectivity dynamics

Andrew Zalesky et al.

NEUROIMAGE (2015)

Article Multidisciplinary Sciences

Transient brain activity disentangles fMRI resting-state dynamics in terms of spatially and temporally overlapping networks

Fikret Isik Karahanoglu et al.

NATURE COMMUNICATIONS (2015)

Article Neurosciences

Tracking Whole-Brain Connectivity Dynamics in the Resting State

Elena A. Allen et al.

CEREBRAL CORTEX (2014)

Review Neurosciences

Computational Psychiatry

Xiao-Jing Wang et al.

NEURON (2014)

Review Statistics & Probability

Energy statistics: A class of statistics based on distances

Gabor J. Szekely et al.

JOURNAL OF STATISTICAL PLANNING AND INFERENCE (2013)

Article Neurosciences

The WU-Minn Human Connectome Project: An overview

David C. Van Essen et al.

NEUROIMAGE (2013)

Article Neurosciences

Dynamic functional connectivity: Promise, issues, and interpretations

R. Matthew Hutchison et al.

NEUROIMAGE (2013)

Article Neurosciences

The minimal preprocessing pipelines for the Human Connectome Project

Matthew F. Glasser et al.

NEUROIMAGE (2013)

Article Multidisciplinary Sciences

Time-varying functional network information extracted from brief instances of spontaneous brain activity

Xiao Liu et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2013)

Article Neurosciences

Decomposition of spontaneous brain activity into distinct fMRI co-activation patterns

Xiao Liu et al.

FRONTIERS IN SYSTEMS NEUROSCIENCE (2013)

Article Neurosciences

Periodic changes in fMRI connectivity

Daniel A. Handwerker et al.

NEUROIMAGE (2012)

Article Neurosciences

Functional Network Organization of the Human Brain

Jonathan D. Power et al.

NEURON (2011)

Article Multidisciplinary Sciences

The human brain is intrinsically organized into dynamic, anticorrelated functional networks

MD Fox et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2005)