Resting brains never rest: computational insights into potential cognitive architectures.

By Gustavo Deco, Viktor Jirsa, Anthony Randal McIntosh. Trends in Neurosciences, 2013

359 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/41f0fe32ec00738a2ae1705935e7893f08630196

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In Cognitive Neuroscience

Citations in the corpus

Higher order interactions in complex networks of phase oscillators promote abrupt synchronization switching (2019, background): “In the context of brain dynamics, incoherent and synchronized states correspond to resting and active states, with abrupt transitions facilitating efficient switching between cognitive tasks [27].”
Criticality in the brain: A synthesis of neurobiology, models and cognition. (2017, background): “est of scientists in many different fields. The list of advantages associated with criticality spans many systems and different measurable quantities (Assis and Copelli, 2008; Boedecker et al., 2012; Deco et al., 2013; Gollo et al., 2013; Haldeman and Beggs, 2005; Hidalgo et al., 2014; Kastner et al”
Functional connectivity dynamics: Modeling the switching behavior of the resting state (2015, methodology): “Finally, model-driven explorations could be used to investigate how modi ﬁ cations of SC or the working point of brain dynamics (Deco et al., 2013b) translate into aberrant FC non-stationarity patternsasin Schizo-phrenia (Sakoglu et al., 2010) and Alzheimer's disease (Jones et al., 2012).”
Signature of consciousness in the dynamics of resting-state brain activity (2015, background): “Indeed, mean-field simulations models of resting state brain activity provide a relatively good match to the observed static functional connectivity patterns by simply implementing a noisy reverberation within the known whole-brain connectivity matrix, without making any specific assumption about on”
Colloquium: Criticality and dynamical scaling in living systems (2017, background): “Thus, resting state networks reflect structured/critical fluctuations among a set of possible attractors suggestive of a state of alertness facilitating rapid task-dependent shifts (Deco and Jirsa, 2012; Deco et al., 2013b; Ghosh et al., 2008).”
Reconfigurable task-dependent functional coupling modes cluster around a core functional architecture (2014, background): “Our discussion of the implications of these observations is motivated by several recent papers that have also grappled with the observation of both stable and dynamic components of functional network configurations [48–53].”
Maturational changes in frontal EEG alpha and theta activity from infancy into early childhood and the relation with self-regulation in boys and girls (2024, background): “Baseline EEG captures brain activity (i.e., power) within a specific frequency rhythm while children are awake and not engaged in any specific task (Anderson and Perone, 2018; Deco et al., 2013).”