Intrinsic and task-evoked network architectures of the human brain.

By Michael W. Cole, D. Bassett, Jonathan D. Power, Todd S. Braver, Steven E. Petersen. Neuron, 2014

1,550 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/114ee0eaf93b97a2c32cd9c65fba7c47e0f8988e

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In Cognitive Neuroscience

Citations in the corpus

Building a Science of Individual Differences from fMRI. (2016, methodology): “Functional connectivity can also be estimated from task fMRI data, usually following the removal of stimulus-evoked activity [72], and shares about half its variance with the functional connectivity estimated from RS-fMRI data [167].”
Modular Brain Networks (2015, background): “A number of studies have begun to investigate multislice representations of brain networks (Bassett et al. 2011, 2013, 2015; Cole et al. 2014) in which multiple instances of a single network (a slice) form a multislice stack.”
The Segregation and Integration of Distinct Brain Networks and Their Relationship to Cognition (2016, background): “…approach have found that while there are many similarities in network structure during rest and during the performance of different cognitive tasks (Cole et al., 2014; Krienen et al., 2014), there are also meaningful task-specific differences (Cole et al., 2013; Krienen et al., 2014; Davison et…”
Robust prediction of individual creative ability from brain functional connectivity (2018, background): “Given past work showing a correspondence between resting-state and task-induced network architecture (23), we hypothesized that strength of functional connectivity within the high- and low-creative networks at rest would predict creative ability, albeit to a lesser extent than with task-state connec”
GroupINN: Grouping-based Interpretable Neural Network for Classification of Limited, Noisy Brain Data (2019, background): “Many studies of task-specific functional activation have also shown strong integration of memory subnetworks with other subnetworks in cognitively demanding tasks [5, 6, 8], such as those represented by the GenExec measure.”
An evaluation of the efficacy, reliability, and sensitivity of motion correction strategies for resting-state functional MRI (2017, methodology): “These spontaneous dynamics predict task-evoked activation and behaviour (Cole et al., 2014; Fox and Raichle, 2007; Fox et al., 2007), can be used to accurately identify individuals across repeated scans (Finn et al., 2015), and are under significant genetic control (Fornito et al., 2011; Glahn et…”
Linking Structure and Function in Macroscale Brain Networks. (2020, positive): “Given the prominent relationship between functional configurations in task and rest [25], it seems likely they would display a similar relationship with structure.”
Questions and controversies in the study of time-varying functional connectivity in resting fMRI (2020, positive): “There is robust evidence that static BOLD FC patterns ﬂexibly reconﬁgure across a range of cognitive and behavioral states (Cohen & D’Esposito, 2016; Cole, Bassett, Power, Braver, & Petersen, 2014; Cole et al., 2013; Gratton et al., 2018; Mattar, Cole, Thompson-Schill, & Bassett, 2015; Shirer,…”
Functional brain networks are dominated by stable group and individual factors, not cognitive or daily variation (2018, methodology): “, 2013a), and respond to different cognitive demands (Betti et al., 2013; Cole et al., 2014; Gratton et al., 2016; Krienen et al., 2014; Shine et al., 2016; Shirer et al., 2012).”
Spatial Topography of Individual-Specific Cortical Networks Predicts Human Cognition, Personality and Emotion (2017, background): “RSFC brain networks correspond well to taskevoked activation patterns (Seeley et al. 2007; Smith et al., 2009; Cole et al., 2014; Yeo et al., 2015a).”