Measuring interregional functional connectivity using coherence and partial coherence analyses of fMRI data

By Felice T. Sun, Lee M. Miller, Mark D'Esposito. NeuroImage, 2004

435 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/4f954927909fcb7be2d65195b3004145db6fce1e

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In Cognitive Neuroscience

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Citations in the corpus

Estimation of functional connectivity in fMRI data using stability selection-based sparse partial correlation with elastic net penalty (2011, neutral): “…and connectivity (Beckmann and Smith, 2004; Calhoun et al., 2001, 2003); (Bullmore and Sporns, 2009; Cole et al., 2010; Deco et al., 2011; Friston et al., 1997; Greicius et al., 2003; McIntosh, 2000; Rubinov and Sporns, 2010; Sun et al., 2004; Supekar et al., 2008; Tononi and Sporns, 2003).”
Measuring functional connectivity during distinct stages of a cognitive task (2004, methodology): “The specific details of the data collection methods and behavioral tasks were described in Sun et al. (2004), and are summarized below.”
Development of functional and structural connectivity within the default mode network in young children (2010, methodology): “Partial correlation measures the degree of association between two regions, controlling for the effect of other regions, and has been widely used in task- and resting-state fMRI (Liu et al., 2008; Salvador et al., 2005; Sun et al., 2004; van den Heuvel et al., 2008).”
Small-world and scale-free organization of voxel-based resting-state functional connectivity in the human brain (2008, neutral): “Regions that show such a synchronized behavior are suggested to form functional resting-state brain networks (Beckmann et al., 2005; Biswal et al., 1995, 1997; Cordes et al., 2001; Damoiseaux et al., 2006; Fox et al., 2005; Greicius et al., 2003; Gusnard et al., 2001; Horwitz et al., 2005; Kiviniemi”
The Segregation and Integration of Distinct Brain Networks and Their Relationship to Cognition (2016, methodology): “During one of the testing sessions, participants performed a sequence tapping task in the scanner (Sun et al., 2004).”
Normalized Cut Group Clustering of Resting-State fMRI Data (2008, background): “The use of partial correlation or partial coherence has been suggested to account for these third party influences [15,19,44,45].”
Review of methods for functional brain connectivity detection using fMRI (2008, neutral): “[30].”
A Baseline for the Multivariate Comparison of Resting-State Networks (2011, background): “Significant effects are found primarily between 0 and 0.15 Hz, consistent with the frequency range over which synchronous fluctuations between brain regions are detected (Cordes et al., 2000; Sun et al., 2004).”
Nonlinear multivariate analysis of neurophysiological signals. (2005, background): “, 1986), and functional magnetic-resonance image (fMRI) data (Sun et al., 2004).”
Task-Based Core-Periphery Organization of Human Brain Dynamics (2012, methodology): “In using the coherence, which has been demonstrated to be useful in the context of fMRI neuroimaging data [95], we were able to measure frequency-specific linear relationships between time series.”
Neural reuse: A fundamental organizational principle of the brain (2010, methodology): “2008); fMRI coherence analysis (Muller et al. 2001; 2003; Sun et al. 2004); Multi-Voxel Pattern Analysis (Periera et al.”
A component based noise correction method (CompCor) for BOLD and perfusion based fMRI (2007, methodology): “The cross-spectral and power-spectral densities are estimated using Welch's modified periodogram averaging method as previously outlined by Sun et al. (2004).”
Classification and Prediction of Brain Disorders Using Functional Connectivity: Promising but Challenging (2018, methodology): “Coherence estimates the linear relationship in the frequency domain (Sun et al., 2004), and connectivity within a specific frequency can be achieved by methods such as wavelet decomposition (Skidmore et al.”