Heterogeneity within the frontoparietal control network and its relationship to the default and dorsal attention networks
Open accessPublished version of a preprint
Abstract
Significance: The frontoparietal control network (FPCN) contributes to executive control, the ability to deliberately guide action based on goals. While the FPCN is often viewed as a unitary domain general system, it is possible that the FPCN contains a fine-grained internal organization, with separate zones involved in different types of executive control. Here, we use graph theory and meta-analytic functional profiling to demonstrate that the FPCN is composed of two separate subsystems: FPCN A is connected to the default network and is involved in the regulation of introspective processes, whereas FPCN B is connected to the dorsal attention network and is involved in the regulation of perceptual attention. These findings offer a distinct perspective on the systems-level circuitry underlying cognitive control.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Exteroceptive and interoceptive stimuli can activate lateral and medial frontoparietal networks in the brain that overlap with regions involved in the dorsal attentional network and the default mode network, respectively.
“Moreover, in addition to the prefrontal cortex, Dixon et al. (2018) suggests that exteroceptive and interoceptive stimuli can activate lateral and medial frontoparietal networks in the brain that overlap with regions involved in the dorsal attentional network and the default mode network, respectively.”
From How Processing of Sensory Information From the Internal and External Worlds Shape the Perception and Engagement With the World in the Aftermath of Trauma: Implications for PTSD (2021) · cites this paper as Dixon et al. (2018)
The paper reports that FPCN B is more strongly connected with the dorsal attention network, while FPCN A is more strongly connected with the default network; its Discussion also links them to perceptual attention and introspective thought, respectively. But the Differential Coupling Patterns section describes these networks as spatially segregated, not overlapping, and the paper does not establish that exteroceptive and interoceptive stimuli activate lateral and medial frontoparietal networks as claimed. Page numbers were not available in our copy. (LLM, conf=0.87)
Experimental — accuracy not yet measuredDixon et al. found in a meta-analysis that FPCN-A is more involved in mentalizing, emotional processing, and complex social reasoning than other FPCN regions.
“Moreover, Dixon et al. found in a meta-analysis that FPCN-A is more involved in mentalizing, emotional processing, and complex social reasoning than other regions of the FPCN, which is consistent with a role for SMG and DLPFC in representing idiosyncratic interpretations of an animated shapes movie.”
From Shared understanding of narratives is correlated with shared neural responses (2019) · cites this paper as Dixon et al., 2018
SMG and DLPFC belong to a proposed FPCN subnetwork, FPCN-A, which has been shown to be more highly correlated with the DMN across various tasks.
“In particular, both SMG and DLPFC are part of a proposed FPCN subnetwork, FPCN-A, that has been shown to be more highly correlated with DMN in a variety of tasks ranging from classic cognitive control tasks, resting state, social-cognitive tasks, and movie watching (Dixon et al., 2018).”
From Shared understanding of narratives is correlated with shared neural responses (2019) · cites this paper as Dixon et al., 2018
Although schema-reliance and associative strength vary across the spectrum of simulation tasks, neither process is unique to past or future simulation, and both remembering and imagining involve coupling of the DMN and frontoparietal control network.
“although schema-reliance and associative strength vary across this spectrum of simulation tasks, from past events through to novel or implausible future events, neither process is unique to the simulation of past or future events, and both remembering and imagining is associated with coupling of the DMN and frontoparietal control network (Dixon et al., 2018).”
From Mental Time Travel? A Neurocognitive Model of Event Simulation. (2020) · cites this paper as Dixon et al., 2018
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Control of goal-directed and stimulus-driven attention in the brain
Corbetta, M., & Shulman, G. L. (2002) · Nature Reviews Neuroscience · doi:10.1038/nrn755 · Cited by 12,881 · see citing works
An Integrative Theory of Prefrontal Cortex Function
Miller, E. K., & Cohen, J. D. (2001) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.24.1.167 · Cited by 12,803 · see citing works
Complex network measures of brain connectivity: Uses and interpretations
Rubinov, M., & Sporns, O. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.10.003 · Cited by 11,522 · see citing works
<i>The Brain's Default Network</i>: <i>Anatomy, Function, and Relevance to Disease</i>
Buckner, R. L., Andrews‐Hanna, J. R., & Schacter, D. L. (2008) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1440.011 · Cited by 9,761 · see citing works
Self-citationThe organization of the human cerebral cortex estimated by intrinsic functional connectivity
Thomas Yeo, B. T., Krienen, F. M., Sepulcre, J., Sabuncu, M. R., Lashkari, D., Hollinshead, M., Roffman, J. L., Smoller, J. W., Zöllei, L., Polimeni, J. R., et al. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00338.2011 · Cited by 9,182 · see citing works
The human brain is intrinsically organized into dynamic, anticorrelated functional networks
Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0504136102 · Cited by 8,553 · see citing works
Dissociable intrinsic connectivity networks for salience processing and executive control
Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., Reiss, A. L., & Greicius, M. D. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.5587-06.2007 · Cited by 7,426 · see citing works
The organization of the human cerebellum estimated by intrinsic functional connectivity
Buckner, R. L., Krienen, F. M., Castellanos, A., Diaz, J. C., & Yeo, B. T. T. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00339.2011 · Cited by 7,304 · see citing works
<i>Conn</i> : A Functional Connectivity Toolbox for Correlated and Anticorrelated Brain Networks
Whitfield-Gabrieli, S., & Nieto-Castanon, A. (2012) · Brain Connectivity · doi:10.1089/brain.2012.0073 · Cited by 4,885 · see citing works
Functional Network Organization of the Human Brain
Power, J. D., Cohen, A. L., Nelson, S. M., Wig, G. S., Barnes, K. A., Church, J. A., Vogel, A. C., Laumann, T. O., Miezin, F. M., Schlaggar, B. L., et al. (2011) · Neuron · doi:10.1016/j.neuron.2011.09.006 · Cited by 4,124 · see citing works
The brain's default mode network
Raichle, M. E. (2015) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-071013-014030 · Cited by 3,904 · see citing works
Large-scale automated synthesis of human functional neuroimaging data.
Yarkoni, T., Poldrack, R. A., Nichols, T. E., Van Essen, D. C., & Wager, T. D. (2011) · Nature Methods · doi:10.1038/nmeth.1635 · Cited by 3,686 · see citing works
Mesulam, M. (1998) · Brain · doi:10.1093/brain/121.6.1013 · Cited by 3,072 · see citing works
Dynamic functional connectivity: Promise, issues, and interpretations
Hutchison, R. M., Womelsdorf, T., Allen, E. A., Bandettini, P. A., Calhoun, V. D., Corbetta, M., Della Penna, S., Duyn, J. H., Glover, G. H., Gonzalez-Castillo, J., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.079 · Cited by 2,962 · see citing works
Sridharan, D., Levitin, D. J., & Menon, V. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0800005105 · Cited by 2,892 · see citing works
Functional-anatomic fractionation of the brain’s default network
Andrews-Hanna, J. R., Reidler, J. S., Sepulcre, J., Poulin, R., & Buckner, R. L. (2010) · Neuron · doi:10.1016/j.neuron.2010.02.005 · Cited by 2,767 · see citing works
Self-citationAn algorithm for drawing general undirected graphs
Kamada, T., & Kawai, S. (1989) · Information Processing Letters · doi:10.1016/0020-0190(89)90102-6 · Cited by 2,670 · see citing works
Distinct brain networks for adaptive and stable task control in humans
Dosenbach, N. U. F., Fair, D. A., Miezin, F. M., Cohen, A. L., Wenger, K. K., Dosenbach, R. A. T., Fox, M. D., Snyder, A. Z., Vincent, J. L., Raichle, M. E., et al. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0704320104 · Cited by 2,632 · see citing works
Murphy, K., Birn, R. M., Handwerker, D. A., Jones, T. B., & Bandettini, P. A. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.09.036 · Cited by 2,387 · see citing works
Top-Down Versus Bottom-Up Control of Attention in the Prefrontal and Posterior Parietal Cortices
Buschman, T. J., & Miller, E. K. (2007) · Science · doi:10.1126/science.1138071 · Cited by 2,380 · see citing works
Situating the default-mode network along a principal gradient of macroscale cortical organization
Margulies, D. S., Ghosh, S. S., Goulas, A., Falkiewicz, M., Huntenburg, J. M., Langs, G., Bezgin, G., Eickhoff, S. B., Castellanos, F. X., Petrides, M., et al. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1608282113 · Cited by 2,321 · see citing works
Spreng, R. N., Mar, R. A., & Kim, A. S. N. (2009) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2008.21029 · Cited by 2,143 · see citing works
Self-citationAndrews‐Hanna, J. R., Smallwood, J., & Spreng, R. N. (2014) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.12360 · Cited by 2,102 · see citing works
Self-citationThe multiple-demand (MD) system of the primate brain: mental programs for intelligent behaviour
Duncan, J. (2010) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2010.01.004 · Cited by 1,846 · see citing works
A Core System for the Implementation of Task Sets
Dosenbach, N. U. F., Visscher, K. M., Palmer, E. D., Miezin, F. M., Wenger, K. K., Kang, H. C., Burgund, E. D., Grimes, A. L., Schlaggar, B. L., & Petersen, S. E. (2006) · Neuron · doi:10.1016/j.neuron.2006.04.031 · Cited by 1,772 · see citing works
Christoff, K., Gordon, A. M., Smallwood, J., Smith, R., & Schooler, J. W. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0900234106 · Cited by 1,769 · see citing works
Self-citationThe Prefrontal Cortex—An Update
Fuster, J. M. (2001) · Neuron · doi:10.1016/s0896-6273(01)00285-9 · Cited by 1,760 · see citing works
Dynamic reconfiguration of human brain networks during learning
Bassett, D. S., Wymbs, N. F., Porter, M. A., Mucha, P. J., Carlson, J. M., & Grafton, S. T. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1018985108 · Cited by 1,705 · see citing works
Multi-task connectivity reveals flexible hubs for adaptive task control
Cole, M. W., Reynolds, J. R., Power, J. D., Repovs, G., Anticevic, A., & Braver, T. S. (2013) · Nature Neuroscience · doi:10.1038/nn.3470 · Cited by 1,704 · see citing works
Self-citationKastner, S., Pinsk, M. A., De Weerd, P., Desimone, R., & Ungerleider, L. G. (1999) · Neuron · doi:10.1016/s0896-6273(00)80734-5 · Cited by 1,622 · see citing works
A Common Network of Functional Areas for Attention and Eye Movements
Corbetta, M., Akbudak, E., Conturo, T. E., Snyder, A. Z., Ollinger, J. M., Drury, H. A., Linenweber, M. R., Petersen, S. E., Raichle, M. E., Essen, D. C. V., et al. (1998) · Neuron · doi:10.1016/s0896-6273(00)80593-0 · Cited by 1,590 · see citing works
Dunbar, R., & Shultz, S. (2007) · Science · doi:10.1126/science.1145463 · Cited by 1,580 · see citing works
Generation and evaluation of a cortical area parcellation from resting-state correlations
Gordon, E. M., Laumann, T. O., Adeyemo, B., Huckins, J. F., Kelley, W. M., & Petersen, S. E. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhu239 · Cited by 1,463 · see citing works
Mind-wandering as spontaneous thought: a dynamic framework
Christoff, K., Irving, Z. C., Fox, K. C. R., Spreng, R. N., & Andrews-Hanna, J. R. (2016) · Nature Reviews Neuroscience · doi:10.1038/nrn.2016.113 · Cited by 1,376 · see citing works
Self-citationCompetition between functional brain networks mediates behavioral variability
Kelly, A. M. C., Uddin, L. Q., Biswal, B. B., Castellanos, F. X., & Milham, M. P. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2007.08.008 · Cited by 1,287 · see citing works
Spreng, R. N., Stevens, W. D., Chamberlain, J. P., Gilmore, A. W., & Schacter, D. L. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.06.016 · Cited by 1,256 · see citing works
Self-citationAn information theoretical approach to prefrontal executive function
Koechlin, E., & Summerfield, C. (2007) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2007.04.005 · Cited by 1,183 · see citing works
Selective gating of visual signals by microstimulation of frontal cortex
Moore, T., & Armstrong, K. M. (2003) · Nature · doi:10.1038/nature01341 · Cited by 1,156 · see citing works
The representation of visual salience in monkey parietal cortex
Gottlieb, J. P., Kusunoki, M., & Goldberg, M. E. (1998) · Nature · doi:10.1038/35135 · Cited by 1,078 · see citing works
The role of the anterior prefrontal cortex in human cognition
Koechlin, É., Basso, G., Pietrini, P., Panzer, S., & Grafman, J. H. (1999) · Nature · doi:10.1038/20178 · Cited by 1,046 · see citing works
Is the rostro-caudal axis of the frontal lobe hierarchical?
Badre, D., & D'Esposito, M. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2667 · Cited by 946 · see citing works
Denny, B. T., Kober, H., Wager, T. D., & Ochsner, K. N. (2012) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00233 · Cited by 830 · see citing works
On spurious and real fluctuations of dynamic functional connectivity during rest
Leonardi, N., & Van De Ville, D. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.09.007 · Cited by 828 · see citing works
Neuronal Activity in the Lateral Intraparietal Area and Spatial Attention
Bisley, J. W., & Goldberg, M. E. (2003) · Science · doi:10.1126/science.1077395 · Cited by 821 · see citing works
Fundamentals of Brain Network Analysis
Fornito, A., Zalesky, A., & Bullmore, E. T. (2016) · Elsevier eBooks · doi:10.1016/c2012-0-06036-x · Cited by 820 · see citing works
Relating Introspective Accuracy to Individual Differences in Brain Structure
Fleming, S. M., Weil, R. S., Nagy, Z., Dolan, R. J., & Rees, G. (2010) · Science · doi:10.1126/science.1191883 · Cited by 809 · see citing works
Dynamic reconfiguration of frontal brain networks during executive cognition in humans
Braun, U., Schäfer, A., Walter, H., Erk, S., Romanczuk-Seiferth, N., Haddad, L., Schweiger, J. I., Grimm, O., Heinz, A., Tost, H., et al. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1422487112 · Cited by 791 · see citing works
Time-resolved resting-state brain networks
Zalesky, A., Fornito, A., Cocchi, L., Gollo, L. L., & Breakspear, M. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1400181111 · Cited by 753 · see citing works
The gateway hypothesis of rostral prefrontal cortex (area 10) function
Burgess, P. W., Dumontheil, I., & Gilbert, S. J. (2007) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2007.05.004 · Cited by 753 · see citing works
Emotion and the prefrontal cortex: an integrative review
Dixon, M. L., Thiruchselvam, R., Todd, R., & Christoff, K. (2017) · Psychological Bulletin · doi:10.1037/bul0000096 · Cited by 745 · cited 1× · see citing works
“Specifically, the DN is involved in mentalizing (36), autobiographical memory (37), spontaneous cognition (38–41), self-referential processing (42), and high-level aspects of emotion (34, 43, 44).”
BackgroundSelf-citationDynamic Coding for Cognitive Control in Prefrontal Cortex
Stokes, M. G., Kusunoki, M., Sigala, N., Nili, H., Gaffan, D., & Duncan, J. (2013) · Neuron · doi:10.1016/j.neuron.2013.01.039 · Cited by 711 · see citing works
Fox, K. C. R., Spreng, R. N., Ellamil, M., Andrews-Hanna, J. R., & Christoff, K. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.02.039 · Cited by 690 · see citing works
Self-citationKalina Christoff, A., & Gabrieli, J. D. E. (2000) · Psychobiology · doi:10.3758/bf03331976 · Cited by 684 · see citing works
Functional Specialization within Rostral Prefrontal Cortex (Area 10): A Meta-analysis
Gilbert, S. J., Spengler, S., Simons, J. S., Steele, J. D., Lawrie, S. M., Frith, C., & Burgess, P. W. (2006) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2006.18.6.932 · Cited by 681 · see citing works
Spreng, R. N., Sepulcre, J., Turner, G. R., Stevens, W. D., & Schacter, D. L. (2013) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00281 · Cited by 668 · see citing works
Self-citationRostrolateral Prefrontal Cortex Involvement in Relational Integration during Reasoning
Kalina Christoff, A., Prabhakaran, V., Dorfman, J., Zhao, Z., Kroger, J. K., Holyoak, K. J., & Gabrieli, J. D. E. (2001) · NeuroImage · doi:10.1006/nimg.2001.0922 · Cited by 645 · see citing works
Ptak, R. (2012) · The Neuroscientist · doi:10.1177/1073858411409051 · Cited by 597 · see citing works
Braga, R. M., & Buckner, R. L. (2017) · Neuron · doi:10.1016/j.neuron.2017.06.038 · Cited by 588 · see citing works
Fornito, A., Harrison, B. J., Zalesky, A., & Simons, J. S. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1204185109 · Cited by 538 · see citing works
Neural Mechanisms of Object-Based Attention
Baldauf, D., & Desimone, R. (2014) · Science · doi:10.1126/science.1247003 · Cited by 536 · see citing works
Understanding brain networks and brain organization
Pessoa, L. (2014) · Physics of Life Reviews · doi:10.1016/j.plrev.2014.03.005 · Cited by 464 · see citing works
The Frontoparietal Control System: A Central Role in Mental Health
Cole, M. W., Repovš, G., & Anticevic, A. (2014) · The Neuroscientist · doi:10.1177/1073858414525995 · Cited by 461 · see citing works
The role of the inferior frontal junction area in cognitive control.
BRASS, M., DERRFUSS, J., FORSTMANN, B., & CRAMON, D. (2005) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2005.05.001 · Cited by 437 · see citing works
Dynamic cooperation and competition between brain systems during cognitive control
Cocchi, L., Zalesky, A., Fornito, A., & Mattingley, J. B. (2013) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2013.08.006 · Cited by 429 · see citing works
The Role of Frontopolar Cortex in Subgoal Processing during Working Memory
Braver, T., & Bongiolatti, S. R. (2002) · NeuroImage · doi:10.1006/nimg.2001.1019 · Cited by 411 · see citing works
Task Set and Prefrontal Cortex
Sakai, K. (2008) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.31.060407.125642 · Cited by 390 · see citing works
Smallwood, J., Brown, K., Baird, B., & Schooler, J. W. (2012) · Brain Research · doi:10.1016/j.brainres.2011.03.072 · Cited by 379 · see citing works
Krienen, F. M., Yeo, B. T. T., & Buckner, R. L. (2014) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2013.0526 · Cited by 372 · see citing works
From Behavior to Neural Dynamics: An Integrated Theory of Attention
Buschman, T. J., & Kästner, S. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.017 · Cited by 363 · see citing works
Neural Circuits Subserving the Retrieval and Maintenance of Abstract Rules
Bunge, S. A., Kahn, I., Wallis, J. D., Miller, E. K., & Wagner, A. D. (2003) · Journal of Neurophysiology · doi:10.1152/jn.00910.2002 · Cited by 361 · see citing works
Teffer, K., & Semendeferi, K. (2012) · Progress in brain research · doi:10.1016/b978-0-444-53860-4.00009-x · Cited by 345 · see citing works
Golland, Y., Bentin, S., Gelbard, H., Benjamini, Y., Heller, R., Nir, Y., Hasson, U., & Malach, R. (2007) · Cerebral Cortex · doi:10.1093/cercor/bhk030 · Cited by 337 · see citing works
Baird, B., Smallwood, J., Gorgolewski, K. J., & Margulies, D. S. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.0786-13.2013 · Cited by 315 · see citing works
(2016) · Chapman & Hall/CRC eBooks · doi:10.1201/b16023 · Cited by 314 · see citing works
Andrews-Hanna, J. R., Saxe, R., & Yarkoni, T. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.01.032 · Cited by 313 · see citing works
Self-citationEvaluating Self-Generated Information: Anterior Prefrontal Contributions to Human Cognition.
Kalina Christoff, A., Ream, J. M., Geddes, L. P. T., & Gabrieli, J. D. E. (2003) · Behavioral Neuroscience · doi:10.1037/0735-7044.117.6.1161 · Cited by 306 · see citing works
Task-based dynamic functional connectivity: Recent findings and open questions
González-Castillo, J., & Bandettini, P. A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.08.006 · Cited by 293 · see citing works
A source for feature-based attention in the prefrontal cortex
Bichot, N. P., Heard, M. T., DeGennaro, E. M., & Desimone, R. (2015) · Neuron · doi:10.1016/j.neuron.2015.10.001 · Cited by 283 · see citing works
Betzel, R. F., Fukushima, M., He, Y., Zuo, X.-N., & Sporns, O. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.12.001 · Cited by 249 · see citing works
The hierarchical organization of the lateral prefrontal cortex
Nee, D. E., & D'Esposito, M. (2016) · eLife · doi:10.7554/elife.12112 · Cited by 233 · see citing works
Dixon, M. L., Andrews‐Hanna, J. R., Spreng, R. N., Irving, Z. C., Mills, C., Girn, M., & Kalina Christoff, A. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.12.073 · Cited by 228 · see citing works
Self-citationPrefrontal organization of cognitive control according to levels of abstraction.
Christoff, K., Keramatian, K., Gordon, A., Smith, R., & Mädler, B. (2009) · Brain Research · doi:10.1016/j.brainres.2009.05.096 · Cited by 225 · see citing works
Self-citationThe Dorsal Frontoparietal Network: A Core System for Emulated Action
Ptak, R., Schnider, A., & Fellrath, J. (2017) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2017.05.002 · Cited by 204 · see citing works
Cole, M. W., Laurent, P. A., & Stocco, A. (2012) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/s13415-012-0125-7 · Cited by 195 · see citing works
Self-citationKonishi, M., McLaren, D. G., Engen, H., & Smallwood, J. (2015) · PLOS ONE · doi:10.1371/journal.pone.0132209 · Cited by 194 · see citing works
Recruitment of the default mode network during a demanding act of executive control
Crittenden, B. M., Mitchell, D. J., & Duncan, J. (2015) · eLife · doi:10.7554/elife.06481 · Cited by 176 · see citing works
Goal-congruent default network activity facilitates cognitive control
Spreng, R. N., DuPre, E., Selarka, D., Garcia, J., Gojkovic, S., Mildner, J., Luh, W.-M., & Turner, G. R. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.2815-14.2014 · Cited by 167 · see citing works
Self-citationNeural signatures of strategic types in a two-person bargaining game
Bhatt, M. A., Lohrenz, T. M., Camerer, C. F., & Montague, P. R. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1009625107 · Cited by 165 · see citing works
Sestieri, C., Shulman, G. L., & Corbetta, M. (2010) · Journal of Neuroscience · doi:10.1523/jneurosci.4719-09.2010 · Cited by 154 · see citing works
Vendetti, M. S., & Bunge, S. A. (2014) · Neuron · doi:10.1016/j.neuron.2014.09.035 · Cited by 152 · see citing works
Dixon, M. L., & Kalina Christoff, A. (2012) · PLoS ONE · doi:10.1371/journal.pone.0051637 · Cited by 140 · see citing works
Self-citationPrefrontal Dynamics Underlying Rapid Instructed Task Learning Reverse with Practice
Cole, M. W., Bagic, A. I., Kass, R. E., & Schneider, W. (2010) · Journal of Neuroscience · doi:10.1523/jneurosci.1662-10.2010 · Cited by 139 · see citing works
Self-citationRepovš, G., & Barch, D. M. (2012) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2012.00137 · Cited by 138 · see citing works
Ellamil, M., Fox, K. C. R., Dixon, M. L., Pritchard, S., Todd, R. M., Thompson, E. T., & Kalina Christoff, A. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.04.034 · Cited by 138 · see citing works
Self-citationMcCaig, R. G., Dixon, M. L., Keramatian, K., Liu, I., & Christoff, K. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.12.016 · Cited by 125 · see citing works
Self-citationTaylor, P., Hobbs, J. N., Burroni, J., & Siegelmann, H. T. (2015) · Scientific Reports · doi:10.1038/srep18112 · Cited by 122 · see citing works
The Necessity of Rostrolateral Prefrontal Cortex for Higher-Level Sequential Behavior
Desrochers, T. M., Chatham, C. H., & Badre, D. (2015) · Neuron · doi:10.1016/j.neuron.2015.08.026 · Cited by 106 · see citing works
Précis on <i>The Cognitive-Emotional Brain</i>
Pessoa, L. (2015) · Behavioral and Brain Sciences · doi:10.1017/s0140525x14000120 · Cited by 84 · see citing works
Encoding the future: Successful processing of intentions engages predictive brain networks
Poppenk, J., Moscovitch, M., McIntosh, A. R., Özçelik, E., & Craik, F. I. M. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.08.049 · Cited by 78 · see citing works
Cross-linked structure of network evolution
Bassett, D. S., Wymbs, N. F., Porter, M. A., Mucha, P. J., & Grafton, S. T. (2014) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/1.4858457 · Cited by 63 · see citing works
Cross-linked structure of network evolution
Bassett, D. S., Wymbs, N. F., Porter, M. A., & Dawkins, M. S. (2014) · Oxford University Research Archive (ORA) (University of Oxford) · Cited by 60 · see citing works
Barrett, L. F., & Satpute, A. (2013) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2012.12.012 · Cited by 58 · see citing works
Dixon, M. L., de la Vega, A. I., Mills, C., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/178863 · Cited by 47 · see citing works
Self-citationLarge-scale Meta-analysis Suggests Low Regional Modularity in Lateral Frontal Cortex
de la Vega, A. I., Yarkoni, T., Wager, T. D., & Banich, M. T. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx204 · Cited by 40 · see citing works
Verstynen, T. (2014) · Journal of Neurophysiology · doi:10.1152/jn.00221.2014 · Cited by 32 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
The default mode network in cognition: a topographical perspective
Smallwood, J., Bernhardt, B. C., Leech, R., Bzdok, D., Jefferies, E., & Margulies, D. S. (2021) · Nature Reviews Neuroscience · doi:10.1038/s41583-021-00474-4 · Cited by 935 · see citing works
Towards a universal taxonomy of macro-scale functional human brain networks
Uddin, L. Q., Yeo, B. T. T., & Spreng, R. N. (2019) · Brain Topography · doi:10.1007/s10548-019-00744-6 · Cited by 683 · see citing works
Self-citationDevelopment of structure–function coupling in human brain networks during youth
Baum, G. L., Cui, Z., Roalf, D. R., Ciric, R., Betzel, R. F., Larsen, B., Cieslak, M., Cook, P. A., Xia, C. H., Moore, T. M., et al. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1912034117 · Cited by 544 · see citing works
Mindfulness and Behavior Change
Schuman-Olivier, Z., Trombka, M., Lovas, D. A., Brewer, J. A., Vago, D. R., Gawande, R., Dunne, J. P., Lazar, S. W., Loucks, E. B., & Fulwiler, C. (2020) · Harvard Review of Psychiatry · doi:10.1097/hrp.0000000000000277 · Cited by 435 · see citing works
Shared understanding of narratives is correlated with shared neural responses
Nguyen, M., Vanderwal, T., & Hasson, U. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2018.09.010 · Cited by 304 · see citing works
Paying attention to attention in depression
Keller, A. S., Leikauf, J. E., Holt-Gosselin, B., Staveland, B. R., & Williams, L. M. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0616-1 · Cited by 329 · see citing works
Cross-species functional alignment reveals evolutionary hierarchy within the connectome
Xu, T., Nenning, K.-H., Schwartz, E., Hong, S.-J., Vogelstein, J. T., Goulas, A., Fair, D. A., Schroeder, C. E., Margulies, D. S., Smallwood, J., et al. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117346 · Cited by 266 · see citing works
Mental Time Travel? A Neurocognitive Model of Event Simulation.
Addis, D. R. (2020) · Review of Philosophy and Psychology · doi:10.1007/s13164-020-00470-0 · Cited by 225 · see citing works
Sezer, I., Pizzagalli, D. A., & Sacchet, M. D. (2022) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2022.104583 · Cited by 214 · see citing works
“The dlPFC is commonly used as an a priori-defined seed region in rsFC analyses to quantify effects related to the FPN (Dixon et al., 2018).”
BackgroundMethodInfluentialThe cognitive neuroscience of lucid dreaming
Baird, B., Mota-Rolim, S. A., & Dresler, M. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.03.008 · Cited by 192 · see citing works
Integrative frontal-parietal dynamics supporting cognitive control
Nee, D. E. (2021) · eLife · doi:10.7554/elife.57244 · Cited by 112 · see citing works
Rubia, K., Criaud, M., Wulff, M., Alegria, A., Brinson, H., Barker, G., Stahl, D., & Giampietro, V. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2018.11.055 · Cited by 111 · see citing works
Harricharan, S., McKinnon, M. C., & Lanius, R. A. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.625490 · Cited by 110 · see citing works
Jamadar, S. D., Ward, P. G., Liang, E. X., Orchard, E. R., Chen, Z., & Egan, G. F. (2020) · doi:10.1101/2020.05.01.071662 · Cited by 98 · see citing works
Allostasis as a core feature of hierarchical gradients in the human brain
Katsumi, Y., Theriault, J. E., Quigley, K. S., & Barrett, L. F. (2022) · Network Neuroscience · doi:10.1162/netn_a_00240 · Cited by 88 · see citing works
Intrinsic functional connectivity is organized as three interdependent gradients
Zhang, J., Abiose, O., Katsumi, Y., Touroutoglou, A., Dickerson, B. C., & Barrett, L. F. (2019) · Scientific Reports · doi:10.1038/s41598-019-51793-7 · Cited by 47 · see citing works
Lesion network mapping demonstrates that mind-wandering is associated with the default mode network
Philippi, C. L., Bruss, J., Boes, A. D., Albazron, F. M., Deifelt Streese, C., Ciaramelli, E., Rudrauf, D., & Tranel, D. (2021) · Journal of Neuroscience Research · doi:10.1002/jnr.24648 · Cited by 45 · see citing works
Mills, C., Zamani, A., White, R., & Christoff, K. (2021) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2019.0692 · Cited by 27 · see citing works
Self-citationDajani, D. R., Odriozola, P., Winters, M., Voorhies, W., Marcano, S., Baez, A., Gates, K. M., Dick, A. S., & Uddin, L. Q. (2020) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01536 · Cited by 27 · see citing works
The Effects of Amyloid and Tau on Functional Network Connectivity in Older Populations
Wales, R. M., & Leung, H.-C. (2021) · Brain Connectivity · doi:10.1089/brain.2020.0902 · Cited by 26 · see citing works
Creative thinking and brain network development in schoolchildren
Duval, P. E., Fornari, E., Décaillet, M., Ledoux, J., Beaty, R. E., & Denervaud, S. (2023) · Developmental Science · doi:10.1111/desc.13389 · Cited by 15 · see citing works
An implementation of integrated information theory in resting-state fMRI
Nemirovsky, I. E., Popiel, N. J. M., Rudas, J., Caius, M., Naci, L., Schiff, N. D., Owen, A. M., & Soddu, A. (2023) · Communications Biology · doi:10.1038/s42003-023-05063-y · Cited by 15 · see citing works
- Authors
- Dixon, M. L., De La Vega, A., Mills, C., Andrews-Hanna, J., Spreng, R. N., Cole, M. W., & Christoff, K.
- Affiliations
- University of British Columbia (CA)
- Department of Psychology, University of Texas at Austin, Austin, TX 78712;
- Institute of Cognitive Science, University of Colorado at Boulder, Boulder, CO 80309-0345;
- Montreal Neurological Institute and Hospital (CA)
- Rutgers, The State University of New Jersey (US)
- Department of Psychology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada;
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2018-01-30
- Volume
- 115
- Issue
- 7
- Pages
- E1598-E1607
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC5816169
- OpenAlex
- W2951435914
- Cited by
- 595
- References
- 106
- Citations by year
- 2026: 79 · 2025: 84 · 2024: 70 · 2023: 73 · 2022: 77 · 2021: 86 · 2020: 69 · 2019: 34 · 2018: 19 · 2017: 1 · 2016: 2
- FWCI
- 30.97
- Type
- journal article
- Language
- en
- Update notices
- correction (2018-03-12)
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Gouvernement du Canada | Natural Sciences and Engineering Research Council of Canada (RGPIN 327317-11)
- Gouvernement du Canada | Canadian Institutes of Health Research (MOP-115197)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Keywords
- frontoparietal network, default mode network, dorsal attention network, executive function, cognitive control, network heterogeneity, perceptual attention, functional connectivity
- MeSH terms
- Adult, Attention, Brain Mapping, Female, Frontal Lobe, Humans, Magnetic Resonance Imaging, Male, Neural Networks, Computer, Young Adult, Executive Function
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review