The DOI matches its Crossref record; 71 of the 71 references it cites were found in a registry or an index.
Default network activity, coupled with the frontoparietal control network, supports goal-directed cognition
Open accessAbstract
Tasks that demand externalized attention reliably suppress default network activity while activating the dorsal attention network. These networks have an intrinsic competitive relationship; activation of one suppresses activity of the other. Consequently, many assume that default network activity is suppressed during goal-directed cognition. We challenge this assumption in an fMRI study of planning. Recent studies link default network activity with internally focused cognition, such as imagining personal future events, suggesting a role in autobiographical planning. However, it is unclear how goal-directed cognition with an internal focus is mediated by these opposing networks. A third anatomically interposed 'frontoparietal control network' might mediate planning across domains, flexibly coupling with either the default or dorsal attention network in support of internally versus externally focused goal-directed cognition, respectively. We tested this hypothesis by analyzing brain activity during autobiographical versus visuospatial planning. Autobiographical planning engaged the default network, whereas visuospatial planning engaged the dorsal attention network, consistent with the anti-correlated domains of internalized and externalized cognition. Critically, both planning tasks engaged the frontoparietal control network. Task-related activation of these three networks was anatomically consistent with independently defined resting-state functional connectivity MRI maps. Task-related functional connectivity analyses demonstrate that the default network can be involved in goal-directed cognition when its activity is coupled with the frontoparietal control network. Additionally, the frontoparietal control network may flexibly couple with the default and dorsal attention networks according to task domain, serving as a cortical mediator linking the two networks in support of goal-directed cognitive processes.
Overview
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
Verification
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?
The cited source says what the claim attributes to it.
In the citing paper
“For example, the default and control networks show cooperation during autobiographical future planning—constructing a detailed and sequential mental representation about a future goal state [10, 19, 24].”
From Creative Cognition and Brain Network Dynamics (2016) · cites this paper as [10]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“We propose that creative thought involves similar cognitive and neural mechanisms as other forms of goal-directed, self-generated cognition (e.g., autobiographical future planning; [10, 19, 24]).”
From Creative Cognition and Brain Network Dynamics (2016) · cites this paper as [10]
The cited source says what the claim attributes to it.
In the citing paper
“In this context, the control network may modify and direct self-generated thoughts to meet the demands of task-specific goals [10–11, 20].”
From Creative Cognition and Brain Network Dynamics (2016) · cites this paper as [10]
In the citing paper
“The FPCN (as well as the salience network; Box 3) may in turn, mediate internally and externally directed cognition by maintaining a dynamic balance between the default and attention networks.15,155,160,162,163”
From The default network and self-generated thought: component processes, dynamic control, and clinical relevance (2014) · cites this paper as [162]
In the citing paper
“However, the FPCN has also been shown to play an important role in regulating self-generated mnemonic, social, and emotional information, and does so by varying its functional connectivity with the DAN or the DN, respectively.”
From The default network and self-generated thought: component processes, dynamic control, and clinical relevance (2014) · cites this paper as [162]
In the citing paper
“Although spatially distinct, the FPCN is anatomically interposed between the default and dorsal attention networks,51,160,162 suggesting it may play an important modulatory role in the activation and suppression of these other networks based on switching goal states.”
From The default network and self-generated thought: component processes, dynamic control, and clinical relevance (2014) · cites this paper as [162]
In the citing paper
“Visuospatial planning engaged the DAN, whereas autobiographical planning engaged the DN. Both engaged the FPCN and, critically, task-related functional connectivity analyses indicated that this network was coupled with the DN during autobiographical planning and with the dorsal attention network during visuospatial planning.”
From The default network and self-generated thought: component processes, dynamic control, and clinical relevance (2014) · cites this paper as [162]
In the citing paper
“Such findings fit with the notion that brain networks functionally couple and uncouple as required by task demands, and a number of studies report connectivity between DMN and frontoparietal control network as the need for flexible or creative thinking increases (e.g., Beaty, Benedek, Barry Kaufman, & Silvia, 2015;Roberts & Addis, 2018;Spreng, Stevens, Chamberlain, Gilmore, & Schacter, 2010).”
From Mental Time Travel? A Neurocognitive Model of Event Simulation. (2020) · cites this paper as Spreng, Stevens, Chamberlain, Gilmore, & Schacter, 2010
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Baltosser, W. H., & Zar, J. H. (1996) · Ecology · doi:10.2307/2265725 · Cited by 35,166
A default mode of brain function
Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.2.676 · Cited by 12,190
Functional connectivity in the motor cortex of resting human brain using echo‐planar mri
Biswal, B., Zerrin Yetkin, F., Haughton, V. M., & Hyde, J. S. (1995) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910340409 · Cited by 9,812
The Brain's Default Network: Anatomy, Function, and Relevance to Disease
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
Self-citationThe 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
Higgins, E. T. (1997) · American Psychologist · doi:10.1037/0003-066x.52.12.1280 · Cited by 6,775
Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging
Fox, M. D., & Raichle, M. E. (2007) · Nature Reviews Neuroscience · doi:10.1038/nrn2201 · Cited by 6,700
Saliency, switching, attention and control: a network model of insula function
Menon, V., & Uddin, L. Q. (2010) · Brain Structure and Function · doi:10.1007/s00429-010-0262-0 · Cited by 5,592
Correspondence of the brain's functional architecture during activation and rest
Smith, S. M., Fox, P. T., Miller, K. L., Glahn, D. C., Fox, P. M., Mackay, C. E., Filippini, N., Watkins, K. E., Toro, R., Laird, A. R., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0905267106 · Cited by 5,150
Consistent resting-state networks across healthy subjects
Damoiseaux, J. S., Rombouts, S. A. R. B., Barkhof, F., Scheltens, P., Stam, C. J., Smith, S. M., & Beckmann, C. F. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601417103 · Cited by 4,326
Cited by
Sorted by citations
Items 701–800 of 1,000
Evolutionary Specializations of the Human Prefrontal Cortex
Passingham, R. E., Smaers, J. B., & Sherwood, C. C. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-804042-3.00114-7 · Cited by 14
Qi, S., Gao, Q., Shen, J., Teng, Y., Xie, X., Sun, Y., & Wu, J. (2018) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2018.00064 · Cited by 14
Correlation Guided Graph Learning to Estimate Functional Connectivity Patterns From fMRI Data
Xiao, L., Zhang, A., Cai, B., Stephen, J. M., Wilson, T. W., Calhoun, V. D., & Wang, Y. (2020) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2020.3022335 · Cited by 14
Sheng, W., Cui, Q., Jiang, K., Chen, Y., Tang, Q., Wang, C., Fan, Y., Guo, J., Lu, F., He, Z., et al. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac015 · Cited by 14
Neural Representations of Conceptual Fixation during Creative Imagination
Frith, E., Gerver, C. R., Benedek, M., Christensen, A. P., & Beaty, R. E. (2022) · Creativity Research Journal · doi:10.1080/10400419.2021.2008699 · Cited by 16
Coulborn, S., & Fernández‐Espejo, D. (2022) · Scientific Reports · doi:10.1038/s41598-022-22893-8 · Cited by 15
What Are the Neurological Foundations of Identities and Identity-Related Processes?
Niemeyer, R. E. (2012) · Handbooks of sociology and social research · doi:10.1007/978-94-007-4473-8_12 · Cited by 14
CHANGE DETECTION, MULTIPLE CONTROLLERS, AND DYNAMIC ENVIRONMENTS: INSIGHTS FROM THE BRAIN
Pearson, J. M., & Platt, M. L. (2012) · Journal of the Experimental Analysis of Behavior · doi:10.1002/jeab.5 · Cited by 14
Tommasin, S., Mascali, D., Moraschi, M., Gili, T., Hassan, I. E., Fratini, M., DiNuzzo, M., Wise, R. G., Mangia, S., Macaluso, E., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.06.006 · Cited by 15
How the human brain introspects about one's own episodes of cognitive control
Soto, D., Theodoraki, M., & Paz‐Alonso, P. M. (2017) · Cortex · doi:10.1016/j.cortex.2017.10.016 · Cited by 15
Neural Correlates of Autobiographical Memory
Jacques, P. L. S., & Brigard, F. D. (2015) · Wiley eBooks · doi:10.1002/9781118332634.ch13 · Cited by 14
Murphy, C., Jefferies, E., Rueschemeyer, S., Sormaz, M., Wang, H.-T., Margulies, D. S., & Smallwood, J. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/150466 · Cited by 14
Altered microstructural properties of superficial white matter in patients with Parkinson’s disease
Zhang, Y., Huang, B., Chen, Q., Wang, L., Zhang, L., Nie, K., Huang, Q., & Huang, R. (2021) · Brain Imaging and Behavior · doi:10.1007/s11682-021-00522-8 · Cited by 13
Karr, J. E., Hakun, J. G., Elbich, D., Pinheiro, C. N., Schmitt, F. A., & Segerstrom, S. C. (2023) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617723000607 · Cited by 13
Zhu, M., & Gong, Q. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1254423 · Cited by 13
Boyatzis, R. E. (2024) · doi:10.1093/9780197765142.001.0001 · Cited by 15
Kaiser, M., Wang, Y., ten Oever, S., Duecker, F., Sack, A. T., & van de Ven, V. G. (2025) · Communications Psychology · doi:10.1038/s44271-025-00202-z · Cited by 13
Cognitive approaches to the study of episodic future thinking
Szpunar, K. K., & Radvansky, G. A. (2015) · Quarterly Journal of Experimental Psychology · doi:10.1080/17470218.2015.1095213 · Cited by 14
Brain Networks With Modified Connectivity in Patients With Neuropathic Pain and Spinal Cord Injury
Hasan, M. A., Sattar, P., Qazi, S. A., Fraser, M., & Vučković, A. (2021) · Clinical EEG and Neuroscience · doi:10.1177/15500594211051485 · Cited by 13
Calzolari, S., Boneva, S., & Fernández‐Espejo, D. (2022) · Neuroscience of Consciousness · doi:10.1093/nc/niac016 · Cited by 17
Solé‐Padullés, C., Cattaneo, G., Marchant, N. L., Cabello‐Toscano, M. R., Mulet‐Pons, L., Sánchez, J. S., Bargalló, N., Tormos, J. M., Pascual‐Leone, Á., & Bartrés‐Faz, D. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.1062887 · Cited by 14
Minassian, A. T., Ricalens, E., Tich, S. N. T., Dinomais, M., Aubé, C., & Beydon, L. (2014) · Brain Connectivity · doi:10.1089/brain.2014.0263 · Cited by 13
Can Conscious Agency Be Saved?
Pacherie, É. (2013) · Topoi · doi:10.1007/s11245-013-9187-6 · Cited by 13
Contextual and Developmental Differences in the Neural Architecture of Cognitive Control
Petrican, R., & Grady, C. L. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.0667-17.2017 · Cited by 14
Low, I., Kuo, P., Liu, Y.-H., Tsai, C.-L., Chao, H., Hsieh, J., Chen, L., & Chen, Y. (2017) · Entropy · doi:10.3390/e19120680 · Cited by 13
Mapping of the Language Network With Deep Learning
Luckett, P. H., Lee, J. J., Park, K. Y., Dierker, D. L., Daniel, A. G. S., Seitzman, B. A., Hacker, C. D., Ances, B. M., Leuthardt, E. C., Snyder, A. Z., et al. (2020) · Frontiers in Neurology · doi:10.3389/fneur.2020.00819 · Cited by 14
Samanta, A., van Rongen, L. S., Rossato, J. I., Jacobse, J., Schoenfeld, R., & Genzel, L. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab135 · Cited by 17
Can We Exploit Cognitive Brain Networks to Treat Chronic Pain?
Seminowicz, D. A., & Čeko, M. (2015) · Pain Management · doi:10.2217/pmt.15.44 · Cited by 13
The Neural Basis of Motivational Influences on Cognitive ControlPreprint
Parro, C., Dixon, M. L., & Kalina Christoff, A. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/113126 · Cited by 15
Functions of the posterior cingulate cortex and default network
Foster, B. L., & Koslov, S. R. (2025) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2025.101560 · Cited by 12
Yao, W., Initiative, A. D. N., Zhang, X., Zhao, H., Xu, Y., & Bai, F. (2022) · Journal of Alzheimer s Disease · doi:10.3233/jad-220475 · Cited by 10
Shaw, D. J., Czekóová, K., Mareček, R., Špiláková, B., & Brázdil, M. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.119933 · Cited by 15
Abnormalities in electroencephalographic microstates among violent patients with schizophrenia
Lin, R., Li, Q., Liu, Z., Zhong, S., Sun, Q., Guo, H., Cao, H., Zhang, X., Hu, Y., Zhou, J., et al. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2023.1082481 · Cited by 13
Li, X., Chen, H., Hu, Y., Larsen, R. J., Sutton, B. P., McElwain, N. L., & Gao, W. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad117 · Cited by 14
Morphometric and Functional Brain Connectivity Differentiates Chess Masters From Amateur Players
RaviPrakash, H., Anwar, S. M., Biassou, N. M., & Bağcı, U. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.629478 · Cited by 13
Ahmed, R., Ucci, M., Mumovic, D., & Bagkeris, E. (2022) · Indoor Air · doi:10.1111/ina.13005 · Cited by 13
Anziano, M., Mouthon, M., Thoeny, H. C., Sperber, C., & Spierer, L. (2023) · Cortex · doi:10.1016/j.cortex.2023.04.007 · Cited by 12
Creativity, Self-Generated Thought, and the Brain’s Default Network
Beaty, R. E., & Schacter, D. L. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-809790-8.00010-8 · Cited by 13
Self-citationOberlin, B. G., Shen, Y. I., & Kareken, D. A. (2019) · Neurotherapeutics · doi:10.1007/s13311-019-00817-1 · Cited by 14
Saliasi, E., Geerligs, L., Lorist, M. M., & Maurits, N. M. (2016) · PLoS ONE · doi:10.1371/journal.pone.0151185 · Cited by 11
Assessing Autobiographical Memory
Sheldon, S., Diamond, N. B., Armson, M. J., Palombo, D. J., Selarka, D., Romero, K., Bacopulos, A., & Levine, B. (2018) · Wiley eBooks · doi:10.1002/9781119170174.epcn111 · Cited by 12
Classic psychedelics: the special role of the visual system
Császár-Nagy, N., Kapócs, G., & Bókkon, I. (2019) · Reviews in the Neurosciences · doi:10.1515/revneuro-2018-0092 · Cited by 12
Brain Network Modularity During a Sustained Working-Memory Task
Moraschi, M., Mascali, D., Tommasin, S., Gili, T., Hassan, I. E., Fratini, M., DiNuzzo, M., Wise, R. G., Mangia, S., Macaluso, E., et al. (2020) · Frontiers in Physiology · doi:10.3389/fphys.2020.00422 · Cited by 11
Han, Z., Liu, T., Shi, Z., Zhang, J., Suo, D., Wang, L., Chen, D., Wu, J., & Yan, T. (2023) · PNAS Nexus · doi:10.1093/pnasnexus/pgad276 · Cited by 14
Data-driven connectivity profiles relate to smoking cessation outcomes
Murray, L., Frederick, B. B., & Janes, A. C. (2024) · Neuropsychopharmacology · doi:10.1038/s41386-024-01802-9 · Cited by 12
Methylphenidate differentially alters corticostriatal connectivity after traumatic brain injury
Mallas, E., Simoni, S. D., Jenkins, P. O., David, M., Bourke, N., & Sharp, D. J. (2024) · Brain · doi:10.1093/brain/awae334 · Cited by 11
Cao, Y., Yang, H., Zhou, Z., Cheng, Z., & Zhao, X. (2021) · Frontiers in Neurology · doi:10.3389/fneur.2020.569806 · Cited by 11
Kuchinsky, S. E., Pandža, N. B., & Haarmann, H. J. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-39955-3_21 · Cited by 11
Paquola, C., Bennett, M. R., & Lagopoulos, J. (2018) · Brain Connectivity · doi:10.1089/brain.2018.0584 · Cited by 12
Visual search task immediate training effects on task-related functional connectivity
Bueichekú, E., Ávila, C., Miró‐Padilla, A., & Sepulcre, J. (2018) · Brain Imaging and Behavior · doi:10.1007/s11682-018-9993-y · Cited by 12
Bonn, G. B. (2013) · Frontiers in Psychology · doi:10.3389/fpsyg.2013.00920 · Cited by 10
Contributions of Episodic Memory to Imagining the Future
McLelland, V. C., Schacter, D. L., & Addis, D. R. (2015) · Wiley eBooks · doi:10.1002/9781118332634.ch14 · Cited by 11
Self-citationBrain Network Organization During Mindful Acceptance of EmotionsPreprint
Dixon, M. L., Girn, M., & Kalina Christoff, A. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.03.31.018697 · Cited by 12
Architecture of the Human Default Mode Network: Cytoarchitecture, Wiring and Signal FlowPreprint
Paquola, C., Garber, M., Frässle, S., Royer, J., Zhou, Y., Tavakol, S., Rodríguez‐Cruces, R., Cabalo, D. G., Valk, S. L., Eickhoff, S. B., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.11.22.469533 · Cited by 11
Speth, J., Schloerscheidt, A. M., & Speth, C. (2016) · Consciousness and Cognition · doi:10.1016/j.concog.2016.08.014 · Cited by 10
How AI is rewiring the human brain: the generational transformation of cognition and knowing
Westerbeek, H. M. (2026) · AI & Society · doi:10.1007/s00146-026-02912-2 · Cited by 14
Gondo, M., Kawai, K., Moriguchi, Y., Hiwatashi, A., Takakura, S., Yoshihara, K., Morita, C., Yamashita, M., Eto, S., & Sudo, N. (2023) · PLoS ONE · doi:10.1371/journal.pone.0283318 · Cited by 11
Plinio, S. D., Perrucci, M. G., Ferrara, G., Sergi, M. R., Tommasi, M., Martino, M., Saggino, A., & Ebisch, S. J. H. (2025) · NeuroImage · doi:10.1016/j.neuroimage.2025.121094 · Cited by 11
Jiang, Y., Guo, Z., Jiao, R., He, H., Jiang, N., & He, J. (2025) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2025.1640966 · Cited by 10
Hsu, L., Lane, T. J., Wu, C. W., Lin, C.-Y. E., Yeh, C.-B., Kao, H., & Lin, C. (2020) · Brain Imaging and Behavior · doi:10.1007/s11682-020-00364-w · Cited by 10
Roberts, S. D., Wilson, A. D., Rahimi, A., Gorbet, D. J., Sergio, L. E., Stevens, W. D., & Wojtowicz, M. A. (2022) · Brain Imaging and Behavior · doi:10.1007/s11682-022-00635-8 · Cited by 10
Self-citationWei, X., Shen, Q., Litvan, I., Huang, M., Lee, R. R., & Harrington, D. L. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.853029 · Cited by 10
Still Wanting to Win: Reward System Stability in Healthy Aging
Opitz, L., Wagner, F., Rogenz, J., Maas, J., Schmidt, A., Brodoehl, S., & Klingner, C. M. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.863580 · Cited by 11
Abraham, A. (2024) · The MIT Press eBooks · doi:10.7551/mitpress/14313.001.0001 · Cited by 10
P2–186: Resting state executive control network adaptations in amnestic mild cognitive impairment
Wu, L., Soder, R., Schoemaker, D., Carbonnell, F., Sziklas, V., Rowley, J., Mohades, S., Fonov, V., Bellec, P., Dagher, A., et al. (2013) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2013.05.831 · Cited by 10
Psychopathy, Mental Time Travel, and Legal Responsibility
Vierra, A. (2015) · Neuroethics · doi:10.1007/s12152-015-9243-6 · Cited by 10
Morgan, J., Clark, D. C., Tripodis, Y., Halloran, C. S., Minsky, A., Wildman, W. J., Durso, R., & McNamara, P. (2016) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2016.07.020 · Cited by 11
Venkatesan, U. M., & Hillary, F. G. (2019) · Neuropsychology · doi:10.1037/neu0000553 · Cited by 10
Regional Specialization and Coordination Within the Network for Perceiving and Knowing About Others
Aglinskas, A., & Fairhall, S. L. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz130 · Cited by 11
Yamashita, M., Shimokawa, T., Takahashi, S., Yamada, S., Terada, M., Ukai, S., & Tanemura, R. (2020) · Applied Neuropsychology Adult · doi:10.1080/23279095.2020.1852565 · Cited by 10
Wang, X., Li, Y., Li, X., Duan, H., Li, Y., & Hu, W. (2021) · Creativity Research Journal · doi:10.1080/10400419.2020.1856595 · Cited by 10
Xie, Y., Guan, M., Wang, Z., Ma, Z., Wang, H., & Fang, P. (2023) · Psychiatry Research · doi:10.1016/j.psychres.2023.115457 · Cited by 10
1142 The neural basis of impaired self-awareness after traumatic brain injury
Ham, T. E., Bonnelle, V., Barber, T., Leech, R., Kinnunen, K. M., Boissezon, X. D., Greenwood, R., & Sharp, D. J. (2012) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp-2011-301993.2 · Cited by 10
A cross-modal investigation of the neural substrates for ongoing cognition
Wang, M., & He, B. J. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.00945 · Cited by 10
Mattan, B. D., Kubota, J. T., Li, T., Dang, T. P., & Cloutier, J. (2018) · eNeuro · doi:10.1523/eneuro.0039-18.2018 · Cited by 10
Petrican, R., Graham, K. S., & Lawrence, A. D. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118177 · Cited by 11
Structural brain network topological alterations in stuttering adults
Gracco, V. L., Sares, A. G., & Koirala, N. (2022) · Brain Communications · doi:10.1093/braincomms/fcac058 · Cited by 9
Unveiling altered connectivity between cognitive networks and cerebellum in schizophrenia
Biondi, M., Marino, M., Mantini, D., & Spironelli, C. (2024) · Schizophrenia Research · doi:10.1016/j.schres.2024.06.044 · Cited by 11
Brain topology underlying executive functions across the lifespan: focus on the default mode network
Menardi, A., Spoa, M., & Vallesi, A. (2024) · Frontiers in Psychology · doi:10.3389/fpsyg.2024.1441584 · Cited by 10
Has, A. C., Chen, H., Sati, P., & Gao, W. (2024) · Communications Biology · doi:10.1038/s42003-024-07160-y · Cited by 11
Wen, G., Cao, P., Liu, L., Hao, M., Liu, S., Zheng, J., Yang, J., Zai͏̈ane, O. R., & Wang, F. (2024) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2024.3512603 · Cited by 9
Yao, Y., Ti, S. U., Wang, X., Hu, B., Zhang, R., Zhou, F., & Feng, T. (2025) · Cerebral Cortex · doi:10.1093/cercor/bhae503 · Cited by 10
Oscillatory brain dynamics underlying affective face processing
Petro, N. M., Livermore, C. L., Springer, S. D., Okelberry, H. J., John, J. A., Glesinger, R. J., Horne, L. K., Embury, C. M., Spooner, R. K., Taylor, B. K., et al. (2025) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsaf047 · Cited by 11
Reading and Calculation Neural Systems and Their Weighted Adaptive Use for Programming Skills
Castelhano, J., Duarte, I. C., Durães, J., Madeira, H., & Castelo-Branco, M. (2021) · Journal of Neural Transplantation and Plasticity · doi:10.1155/2021/5596145 · Cited by 8
Zhang, B., Wang, F., Zhang, Q., & Naya, Y. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119041 · Cited by 8
Yao, W., Zhou, H., Zhang, X., Chen, H., Bai, F., & Initiative, A. D. N. (2023) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.14391 · Cited by 9
Christou, A. I., Tsermentseli, S. K., & Drigas, A. S. (2023) · International Journal of Interactive Mobile Technologies (iJIM) · doi:10.3991/ijim.v17i18.42437 · Cited by 15
EEG microstates are associated with music training experience
Jiang, Y., & Zheng, M. (2024) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2024.1434110 · Cited by 9
Exploring Dynamic Brain Functional Networks Using Continuous “State-Related” Functional MRI
Li, X., Zang, Y., & Zhang, H. (2015) · BioMed Research International · doi:10.1155/2015/824710 · Cited by 9
Detloff, A. M., Hariri, A. R., & Strauman, T. J. (2020) · Personality Neuroscience · doi:10.1017/pen.2019.13 · Cited by 9
Functional network activity during errorless and trial‐and‐error color‐name association learning
Yamashita, M., Shimokawa, T., Peper, F., & Tanemura, R. (2020) · Brain and Behavior · doi:10.1002/brb3.1723 · Cited by 9
Zhang, M., McNab, F., Smallwood, J., & Jefferies, E. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhab459 · Cited by 8
Saarikivi, K., Chan, T. M. V., Huotilainen, M., Tervaniemi, M. H., & Putkinen, V. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad034 · Cited by 11
Exploring adolescent cognitive control in a combined interference switching task
Mennigen, E., Rodehacke, S., Müller, K. U., Ripke, S., Goschke, T., & Smolka, M. N. (2014) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2014.06.022 · Cited by 9
de Caso, I., Karapanagiotidis, T., Aggius-Vella, E., Konishi, M., Margulies, D. S., Jefferies, E., & Smallwood, J. (2017) · Brain and Cognition · doi:10.1016/j.bandc.2017.01.004 · Cited by 9
Jackson, K. T. (2018) · Humanistic Management Journal · doi:10.1007/s41463-018-0040-3 · Cited by 9
Goal-Directed Processing of Naturalistic Stimuli Modulates Large-Scale Functional Connectivity
Wen, Z., Yu, T., Yang, X., & Li, Y. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.01003 · Cited by 9
Literacy Affects Brain Structure – What Can We Learn for Language Assessment in Low Literates?
Rüsseler, J., Arendt, D., Münte, T. F., Mohammadi, B., & Boltzmann, M. (2021) · Language Assessment Quarterly · doi:10.1080/15434303.2021.1931231 · Cited by 10
Hallucinogenic mechanisms: pathological and pharmacological insights
Lewis, S. J. G., Shine, J. M., Brooks, D., & Halliday, G. M. (2014) · Wiley eBooks · doi:10.1002/9781118892794.ch6 · Cited by 9
Specifying the Self for Cognitive NeurosciencePreprint
Kalina Christoff, A., Cosmelli, D. J., Legrand, D., & Thompson, E. T. (2017) · doi:10.31231/osf.io/7xedg · Cited by 10
Metadata
- Authors
- Spreng, R. N., Stevens, W. D., Chamberlain, J. P., Gilmore, A. W., & Schacter, D. L.
- Affiliations
- Harvard University (US)
- Corresponding author
- Spreng, R. Nathan
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2010-10
- Volume
- 53
- Issue
- 1
- Pages
- 303-317
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC2914129
- OpenAlex
- W1998268694
- Cited by
- 1,256
- References
- 71
- Citations by year
- 2026: 75 · 2025: 99 · 2024: 75 · 2023: 74 · 2022: 79 · 2021: 87 · 2020: 93 · 2019: 87 · 2018: 98 · 2017: 82 · 2016: 85 · 2015: 86 · 2014: 87 · 2013: 57 · 2012: 47
- FWCI
- 27.74
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH (MH060941)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Mind wandering and attention
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Functions and Memory
- Keywords
- default mode network, dorsal attention network, frontoparietal network, goal-directed cognition, planning, resting-state functional connectivity, network coupling
- MeSH terms
- Adolescent, Adult, Attention, Cognition, Decision Making, Female, Frontal Lobe, Goals, Humans, Magnetic Resonance Imaging, Male, Nerve Net, Parietal Lobe, Feedback, Physiological, Young Adult
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