Situating the default-mode network along a principal gradient of macroscale cortical organization
By Daniel S. Margulies, Satrajit S. Ghosh, Sulagna Dia Ghosh, Satrajit S. Ghosh, A. Goulas, M. Falkiewicz, Julia M. Huntenburg, Georg Langs, Gleb Bezgin, Simon B. Eickhoff and 4 more. Proceedings of the National Academy of Sciences of the United States of America, 2016
2,174 citations recorded by the source corpus.
Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging
View Paper: https://www.semanticscholar.org/paper/d51701868e12ecc1f8c68b4a6c3e7e07c8e3d918
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cognitive Neuroscience
- Olaf Sporns
- Stephen M. Smith
- Michael P. Milham
- Mark William Woolrich
- Vinod Menon
- Karl J. Friston
- D. Bassett
- Matthew F. Glasser
In Radiology, Nuclear Medicine and Imaging
- Stephen M. Smith
- Olaf Sporns
- Matthew F. Glasser
- Mark William Woolrich
- Michael P. Milham
- Vinod Menon
- Karl J. Friston
- Bratislav Misic
Citations in the corpus
- neuromaps: structural and functional interpretation of brain maps (2022, methodology): “[46] and allometric scaling from Reardon et al.”
- Linking Structure and Function in Macroscale Brain Networks. (2020, neutral): “relationships are organized around a hierarchical gradient spanning unimodal to transmodal cortex [78,111].”
- Hierarchical Heterogeneity across Human Cortex Shapes Large-Scale Neural Dynamics (2018, positive): “Cortical myelin content, measured by quantitative T1 mapping, has been observed to correlate with a prominent sensory–association gradient in rs-FC variation (Margulies et al., 2016; Huntenburg et al., 2017).”
- Brain network dynamics are hierarchically organized in time (2017, background): “(32), which is based on a mathematical decomposition of the structural connectivity elicited from the same 820 subjects used in this study.”
- BrainSpace: a toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets (2019, methodology): “…on identifying discrete regions and modules and their speci fi c functional roles 10 , recent conceptual and methodological developments have provided the data and methods that allow macroscale brain features mapped to low dimensional manifold representations, also described as gradients 11 .”
- Comparing spatial null models for brain maps (2021, neutral): “…et al., 2020; Zilles and Amunts, 2009; Zilles et al., 2004 ), intracortical myelin ( Burt et al., 2018; Whitaker et al., 2016 ), and functional organization ( Bellec et al., 2010; Damoi-seaux et al., 2006; Margulies et al., 2016; Murray et al., 2014; Shafiei et al., 2020; Yeo et al., 2011 ).”
- REBUS and the Anarchic Brain: Toward a Unified Model of the Brain Action of Psychedelics (2019, background): “, 2008), 3) extreme heteromodality (Margulies et al., 2016), and 4) association with functionally high-level behaviors—falling broadly under the constructs of perspective taking and metacognition (Soto et al.”
- Sex differences in the adult human brain: Evidence from 5,216 UK Biobank participants (2017, background): “The observed pattern of sex differences in functional connectome organization observed here appears to recapitulate the two main poles of that principal connectivity gradient (Margulies et al. 2016).”
- Gradients of structure–function tethering across neocortex (2019, positive): “Recent evidence points to a fundamental organizing principle for macroscale functional interactions (18).”