The extrinsic and intrinsic functional architectures of the human brain are not equivalent.

The brain's intrinsic functional architecture, revealed in correlated spontaneous activity, appears to constitute a faithful representation of its repertoire of evoked, extrinsic functional interactions. Here, using broad task contrasts to probe evoked patterns of coactivation, we demonstrate tight coupling between the brain's intrinsic and extrinsic functional architectures for default and task-positive regions, but not for subcortical and limbic regions or for primary sensory and motor cortices. While strong correspondence likely reflects persistent or recurrent patterns of evoked coactivation, weak correspondence may exist for regions whose patterns of evoked functional interactions are more adaptive and context dependent. These findings were independent of task. For tight task contrasts (e.g., incongruent vs. congruent trials), evoked patterns of coactivation were unrelated to the intrinsic functional architecture, suggesting that high-level task demands are accommodated by context-specific modulations of functional interactions. We conclude that intrinsic approaches provide only a partial understanding of the brain's functional architecture. Appreciating the full repertoire of dynamic neural responses will continue to require task-based functional magnetic resonance imaging approaches.

[1]  G. E. Alexander,et al.  Basal ganglia-thalamocortical circuits: parallel substrates for motor, oculomotor, "prefrontal" and "limbic" functions. , 1990, Progress in brain research.

[2]  G. Shulman,et al.  Medial prefrontal cortex and self-referential mental activity: Relation to a default mode of brain function , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[3]  S. Haber The primate basal ganglia: parallel and integrative networks , 2003, Journal of Chemical Neuroanatomy.

[4]  A. Grinvald,et al.  Spontaneously emerging cortical representations of visual attributes , 2003, Nature.

[5]  Adam Gazzaley,et al.  Measuring functional connectivity during distinct stages of a cognitive task , 2004, NeuroImage.

[6]  J. Doyon,et al.  Reorganization and plasticity in the adult brain during learning of motor skills , 2005, Current Opinion in Neurobiology.

[7]  Maurizio Corbetta,et al.  The human brain is intrinsically organized into dynamic, anticorrelated functional networks. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[8]  David J. Foster,et al.  Reverse replay of behavioural sequences in hippocampal place cells during the awake state , 2006, Nature.

[9]  Jeffrey M. Zacks,et al.  Coherent spontaneous activity accounts for trial-to-trial variability in human evoked brain responses , 2006, Nature Neuroscience.

[10]  Kenji Doya,et al.  fMRI investigation of cortical and subcortical networks in the learning of abstract and effector-specific representations of motor sequences , 2006, NeuroImage.

[11]  R. Passingham,et al.  Reading Hidden Intentions in the Human Brain , 2007, Current Biology.

[12]  M. Fox,et al.  Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging , 2007, Nature Reviews Neuroscience.

[13]  Scott T. Grafton,et al.  BOLD coherence reveals segregated functional neural interactions when adapting to distinct torque perturbations. , 2007, Journal of neurophysiology.

[14]  Olaf Sporns,et al.  Network structure of cerebral cortex shapes functional connectivity on multiple time scales , 2007, Proceedings of the National Academy of Sciences.

[15]  T. Paus,et al.  Functional coactivation map of the human brain. , 2008, Cerebral cortex.

[16]  V. Menon,et al.  A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks , 2008, Proceedings of the National Academy of Sciences.

[17]  Bharat B. Biswal,et al.  Competition between functional brain networks mediates behavioral variability , 2008, NeuroImage.

[18]  Yihong Yang,et al.  Static and dynamic characteristics of cerebral blood flow during the resting state , 2009, NeuroImage.

[19]  Stephen M Smith,et al.  Correspondence of the brain's functional architecture during activation and rest , 2009, Proceedings of the National Academy of Sciences.

[20]  Kevin Murphy,et al.  The impact of global signal regression on resting state correlations: Are anti-correlated networks introduced? , 2009, NeuroImage.

[21]  B. Biswal,et al.  The resting brain: unconstrained yet reliable. , 2009, Cerebral cortex.

[22]  Kaustubh Supekar,et al.  Development of Large-Scale Functional Brain Networks in Children , 2009, NeuroImage.

[23]  Bharat B. Biswal,et al.  The oscillating brain: Complex and reliable , 2010, NeuroImage.

[24]  M. Raichle Two views of brain function , 2010, Trends in Cognitive Sciences.

[25]  Xi-Nian Zuo,et al.  Reliable intrinsic connectivity networks: Test–retest evaluation using ICA and dual regression approach , 2010, NeuroImage.

[26]  Peter Stiers,et al.  Distributed task coding throughout the multiple demand network of the human frontal–insular cortex , 2010, NeuroImage.

[27]  G. Deco,et al.  Emerging concepts for the dynamical organization of resting-state activity in the brain , 2010, Nature Reviews Neuroscience.

[28]  J. Gold,et al.  Caudate Encodes Multiple Computations for Perceptual Decisions , 2010, The Journal of Neuroscience.

[29]  John X. Morris,et al.  Spatial correlation between brain aerobic glycolysis and amyloid-β (Aβ) deposition , 2010, Proceedings of the National Academy of Sciences.

[30]  Andrei G. Vlassenko,et al.  Regional aerobic glycolysis in the human brain , 2010, Proceedings of the National Academy of Sciences.

[31]  Bharat B. Biswal,et al.  Inter-individual differences in resting-state functional connectivity predict task-induced BOLD activity , 2010, NeuroImage.

[32]  M. Corbetta,et al.  The Dynamical Balance of the Brain at Rest , 2011, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[33]  Jeffrey S Anderson,et al.  Network anticorrelations, global regression, and phase‐shifted soft tissue correction , 2011, Human brain mapping.

[34]  Soyoung Q. Park,et al.  Decoding the Formation of Reward Predictions across Learning , 2011, The Journal of Neuroscience.

[35]  N. Volkow,et al.  Association between functional connectivity hubs and brain networks. , 2011, Cerebral cortex.

[36]  Timothy O. Laumann,et al.  Functional Network Organization of the Human Brain , 2011, Neuron.

[37]  Thomas T. Liu,et al.  A geometric view of global signal confounds in resting-state functional MRI , 2012, NeuroImage.

[38]  Evan M Gordon,et al.  Using spatial multiple regression to identify intrinsic connectivity networks involved in working memory performance , 2012, Human brain mapping.