Generation and Evaluation of a Cortical Area Parcellation from Resting-State Correlations.

By Evan M. Gordon, Timothy O. Laumann, Babatunde Adeyemo, Jeremy F. Huckins, William M. Kelley, Steven E. Petersen. Cerebral Cortex, 2016

1,449 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/7455f012f983418c5449823301e9a002aad83b3f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Data Quality Influences Observed Links Between Functional Connectivity and Behavior (2017, methodology): “Time series were extracted from a 324-region cortical parcellation (Gordon et al. 2016) (Supplementary Fig.”
Sources and implications of whole-brain fMRI signals in humans (2016, background): “The modular organizations of the WU and RP data have been extensively characterized in (Gordon et al., 2016; Laumann et al., 2015; Power et al., 2011; Power et al., 2013).”
Image processing and analysis methods for the Adolescent Brain Cognitive Development Study (2018, methodology): “DTI and RSI measures are also sampled onto the FreeSurfer-derived cortical surface mesh to make maps of diffusion properties for cortical gray matter and white matter adjacent to the cortex (Govindan et al., 2013; Kang et al., 2012) and calculate surface-based ROI averages.”
Precision functional mapping of individual human brains (2017, unknown): “Session-level RSFC matrix similarity was examined both within and across subjects using an a priori group-level parcellation (Gordon et al., 2016).”
Global Signal Regression Strengthens Association between Resting-State Functional Connectivity and Behavior (2019, background): “Uncensored segments of data lasting fewer than five contiguous volumes were also labeled as censored frames (Gordon et al., 2016).”
Statistical harmonization corrects site effects in functional connectivity measurements from multi-site fMRI data (2018, background): “, 2011); and (3) 333 cortical and subcortical ROIs from the functional Gordon atlas (Gordon et al., 2016).”
The Dynamics of Functional Brain Networks: Integrated Network States during Cognitive Task Performance (2015, unknown): “The network membership of each of the parcels was defined according to a previous study (Gordon et al., 2016).”
The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture (2016, unknown): “…(Brodmann 1909; Von Economo and Koskinas 1925; Zilles and Amunts 2010), while whole-brain parcellation studies based on rfMRI or dMRImay be realized by either global border detection (Wig et al. 2014; Gordon et al. 2016) or global clustering (Craddock et al. 2012; Moreno-Dominguez et al. 2014).”
The modular and integrative functional architecture of the human brain (2015, methodology): “Gordon EM, et al. (2014) Generation and evaluation of a cortical area parcellation from resting-state correlations.”
Activity flow over resting-state networks shapes cognitive task activations (2016, result): “Overall these results support the conclusion that the choice of whether or not to use GSR does not substantially affect the outcome of activity flow mapping.”
Multi-scale brain networks (2016, unknown): “, spatial variation in functional connectivity, myelination, cytoarchitectonics, etc—for grouping voxels together into regions (Destrieux et al., 2010; Yeo et al., 2011; Gordon et al., 2014; Glasser et al., 2015; Hermundstad et al., 2013).”
Functional brain networks are dominated by stable group and individual factors, not cognitive or daily variation (2018, methodology): “This study examined functional connectivity among 333 cortical group parcels defined based on boundary-mapping techniques in a large group of independent subjects (Gordon et al., 2016); group ROIs were selected to allow for comparison across individuals.”
Comparing spatial null models for brain maps (2021, unknown): “…al., 2021; Shaﬁei et al., 2020; Vázquez-Rodríguez et al., 2019; Wang et al., 2019 ); however, standard methods for statistical inference fall short when making such comparisons ( Alexander-Bloch et al. 2013; 2018, Breakspear et al. 2004, Burt et al. 2020; Fulcher et al. 2020; Gordon et al. 2016 ).”
Human brain mapping: A systematic comparison of parcellation methods for the human cerebral cortex (2017, methodology): “Similarly, various methods include a spatial smoothing stage (such as a fine-resolution parcellation) or average sub-1080 ject-level connectivity data for improved SNR and stability in parcellations (Yeo et al., 2011; Blumensath et al., 2013; Arslan and Rueckert, 2015; Gordon et al., 2016b).”