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Topologically Reorganized Connectivity Architecture of Default-Mode, Executive-Control, and Salience Networks across Working Memory Task Loads
Open accessAbstract
The human brain is topologically organized into a set of spatially distributed, functionally specific networks. Of these networks, the default-mode network (DMN), executive-control network (ECN), and salience network (SN) have received the most attention recently for their vital roles in cognitive functions. However, very little is known about whether and how the interactions within and between these 3 networks would be modulated by cognitive demands. Here, we employed graph-based modularity analysis to identify the DMN, ECN, and SN during an N-back working memory (WM) task and further investigated the modulation of intra- and inter-network interactions at different cognitive loads. As the task load elevated, functional connectivity decreased within the DMN while increased within the ECN, and the SN connected more with both the DMN and ECN. Within-network connectivity of the ventral and dorsal posterior cingulate cortex was differentially modulated by cognitive load. Further, the superior parietal regions in the ECN showed increased internetwork connections at higher WM loads, and these increases correlated positively with WM task performance. Together, these findings advance our understanding of dynamic integrations of specialized brain systems in response to cognitive demands and may serve as a baseline for assessing potential disruptions of these interactions in pathological conditions.
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“The CEN, anchored in the dorsolateral prefrontal cortex (dlPFC) and posterior parietal cortices (PPC), is associated with executive functioning [36–42].”
From Infraslow closed-loop brain training for anxiety and depression (ISAD): a protocol for a randomized, double-blind, sham-controlled pilot trial in adult females with internalizing disorders (2022) · cites this paper as [40]
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Cites
Fast unfolding of communities in large networks
Blondel, V. D., Guillaume, J.-L., Lambiotte, R., & Lefebvre, E. (2008) · Journal of Statistical Mechanics: Theory and Experiment · doi:10.1088/1742-5468/2008/10/p10008 · Cited by 21,424
Finding and evaluating community structure in networks
Newman, M. E. J., & Girvan, M. (2004) · Physical Review E · doi:10.1103/physreve.69.026113 · Cited by 13,931
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
AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages
Cox, R. W. (1996) · Computers and Biomedical Research · doi:10.1006/cbmr.1996.0014 · Cited by 10,913
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
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
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
Fast algorithm for detecting community structure in networks
Newman, M. E. J. (2004) · Physical Review E · doi:10.1103/physreve.69.066133 · Cited by 5,415
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
Friston, K. J., Harrison, L., & Penny, W. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00202-7 · Cited by 4,583
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The Segregation and Integration of Distinct Brain Networks and Their Relationship to Cognition
Cohen, J. R., & D’Esposito, M. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.2965-15.2016 · Cited by 816
Farahani, F. V., Karwowski, W., & Lighthall, N. R. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00585 · Cited by 765
The role of PFC networks in cognitive control and executive function
Menon, V., & D’Esposito, M. (2022) · Neuropsychopharmacology · doi:10.1038/s41386-021-01152-w · Cited by 654
Small-world human brain networks: Perspectives and challenges
Liao, X., Vasilakos, A. V., & Yong He, A. (2017) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2017.03.018 · Cited by 443
Complex network analysis of time series
Gao, Z., SMALL, M. P., & Kurths, J. (2016) · Europhysics Letters (EPL) · doi:10.1209/0295-5075/116/50001 · Cited by 302
Ng, K. K., Lo, J. C.-Y., Lim, J. K. W., Chee, M. W. L., & Zhou, J. H. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.03.029 · Cited by 239
Disrupted structural and functional brain networks in Alzheimer's disease
Dai, Z., Lin, Q., Li, T., Wang, X., Yuan, H., Yu, X., Yong He, A., & Wang, H. (2018) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2018.11.005 · Cited by 222
Liu, J., Liao, X., Xia, M., & Yong He, A. (2017) · Human Brain Mapping · doi:10.1002/hbm.23890 · Cited by 212
Gratton, C., Sun, H., & Petersen, S. E. (2017) · Psychophysiology · doi:10.1111/psyp.13032 · Cited by 218
Wu, X., Zou, Q., Hu, J., Tang, W., Mao, Y. Q., Gao, L., Zhu, J., Jin, Y., Wu, X., Lu, L., et al. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.0415-15.2015 · Cited by 177
Self-citationIntegration and segregation of large-scale brain networks during short-term task automatization
Mohr, H., Wolfensteller, U., Betzel, R. F., Mišić, B., Sporns, O., Richiardi, J., & Ruge, H. (2016) · Nature Communications · doi:10.1038/ncomms13217 · Cited by 170
Hasson, U., Egidi, G., Marelli, M., & Willems, R. M. (2018) · Cognition · doi:10.1016/j.cognition.2018.06.018 · Cited by 157
Wang, P., Zhou, B., Yao, H., Zhan, Y., Zhang, Z., Cui, Y. J., Xu, K., Ma, J., Wang, L., An, N., et al. (2015) · Scientific Reports · doi:10.1038/srep14824 · Cited by 148
Sun, J., Liu, Z., Rolls, E. T., Chen, Q., Yao, Y., Yang, W., Wei, D., Zhang, Q., Zhang, J., Feng, J., et al. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy010 · Cited by 138
Intelligence is associated with the modular structure of intrinsic brain networks
Hilger, K., Ekman, M., Fiebach, C. J., & Basten, U. (2017) · Scientific Reports · doi:10.1038/s41598-017-15795-7 · Cited by 144
Large‐scale brain networks are distinctly affected in right and left mesial temporal lobe epilepsy
de Campos, B. M., Coan, A. C., Yasuda, C. L., Casseb, R. F., & Cendes, F. (2016) · Human Brain Mapping · doi:10.1002/hbm.23231 · Cited by 130
Esposito, R., Cieri, F., Chiacchiaretta, P., Cera, N., Lauriola, M., Giannantonio, M. D., Tartaro, A., & Ferretti, A. (2017) · Brain Imaging and Behavior · doi:10.1007/s11682-017-9686-y · Cited by 133
Modular Brain Network Organization Predicts Response to Cognitive Training in Older Adults
Gallen, C. L., Baniqued, P. L., Chapman, S. B., Aslan, S., Keebler, M. W., Didehbani, N., & D’Esposito, M. (2016) · PLoS ONE · doi:10.1371/journal.pone.0169015 · Cited by 122
Individual differences and time-varying features of modular brain architecture
Liao, X., Cao, M., Xia, M., & Yong He, A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.02.066 · Cited by 113
Episodic Memory Retrieval Benefits from a Less Modular Brain Network Organization
Westphal, A. J., Wang, S., & Rissman, J. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.2509-16.2017 · Cited by 95
Yu, Q., Du, Y., Chen, J., Jing Sui (Beijing Normal University), my correct affiliation is beijing normal university, N. Q. U. O. S. A. T., Adalı, T., Pearlson, G. D., & Calhoun, V. D. (2018) · Proceedings of the IEEE · doi:10.1109/jproc.2018.2825200 · Cited by 96
Brain network functional connectivity and cognitive performance in major depressive disorder
Albert, K. M., Potter, G. G., Boyd, B. D., Kang, H., & Taylor, W. D. (2018) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2018.11.020 · Cited by 87
Functional connectomics from a “big data” perspective
Xia, M., & Yong He, A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.02.031 · Cited by 85
Sha, Z., Xia, M., Lin, Q., Cao, M., Tang, Y., Xu, K., Song, H., Wang, Z., Wang, F., Fox, P. T., et al. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx273 · Cited by 88
Mindfulness Improves Emotion Regulation and Executive Control on Bereaved Individuals: An fMRI Study
Huang, F., Hsu, A., Hsu, L.-M., Tsai, J., Huang, C., Chao, Y., Hwang, T., & Wu, C. W. (2019) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2018.00541 · Cited by 84
Zhan, Y., Initiative, A. D. N., Ma, J., Alexander‐Bloch, A. F., Xu, K., Cui, Y. J., Feng, Q., Jiang, T., & Liu, Y. (2016) · Journal of Alzheimer s Disease · doi:10.3233/jad-160008 · Cited by 78
Reconfiguration of brain network architecture to support executive control in aging
Gallen, C. L., Turner, G. R., Adnan, A., & D’Esposito, M. (2016) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2016.04.003 · Cited by 72
Lois, G., & Wessa, M. (2016) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsw085 · Cited by 66
Dynamic network coding of working-memory domains and working-memory processes
Soreq, E., Leech, R., & Hampshire, A. (2019) · Nature Communications · doi:10.1038/s41467-019-08840-8 · Cited by 64
Altered Functional Connectivity of Insular Subregions in Alzheimer’s Disease
Liu, X., Chen, X., Zheng, W., Xia, M., Han, Y., Song, H., Li, K., Yong He, A., & Wang, Z. (2018) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2018.00107 · Cited by 61
EEG microstates are correlated with brain functional networks during slow-wave sleep
Xu, J., Pan, Y., Zhou, S., Zou, G., Liu, J., Su, Z., Zou, Q., & Gao, J. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116786 · Cited by 65
Self-citationHearne, L. J., Cocchi, L., Zalesky, A., & Mattingley, J. B. (2015) · Human Brain Mapping · doi:10.1002/hbm.22802 · Cited by 67
Intrinsic Brain Hub Connectivity Underlies Individual Differences in Spatial Working Memory
Liu, J., Xia, M., Dai, Z., Wang, X., Liao, X., Bi, Y., & Yong He, A. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw317 · Cited by 59
Differences between child and adult large‐scale functional brain networks for reading tasks
Liu, X., Gao, Y., Di, Q., Hu, J., Lu, C., Nan, Y., Booth, J. R., & Liu, L. (2017) · Human Brain Mapping · doi:10.1002/hbm.23871 · Cited by 58
Gu, H., Hu, Y., Chen, X., Yong He, A., & Yang, Y. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.10.055 · Cited by 59
Self-citationWang, C., Hu, Y., Weng, J., Chen, F., & Liu, H. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116334 · Cited by 60
Differences in atypical resting-state effective connectivity distinguish autism from schizophrenia
Mastrovito, D., Hanson, C., & Hanson, S. J. (2018) · NeuroImage Clinical · doi:10.1016/j.nicl.2018.01.014 · Cited by 54
Yun, J., Jang, J. H., Kim, S. N., Jung, W. H., & Kwon, J. S. (2015) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2015.06.009 · Cited by 55
Wu, X., Li, Q., Yu, X., Chen, K., Fleisher, A., Guo, X., Zhang, J., Reiman, E. M., Li, Y., & Li, R. (2016) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2016.00231 · Cited by 47
Building an EEG-fMRI Multi-Modal Brain Graph: A Concurrent EEG-fMRI Study
Yu, Q., Wu, L., Bridwell, D. A., Erhardt, E. B., Du, Y., He, H., Chen, J., Liu, P., Jing Sui (Beijing Normal University), my correct affiliation is beijing normal university, N. Q. U. O. S. A. T., Pearlson, G. D., et al. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00476 · Cited by 49
Liang, X., Hsu, L., Lu, H., Sumiyoshi, A., Yong He, A., & Yang, Y. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw416 · Cited by 51
Self-citationFunctional disruption of cerebello-thalamo-cortical networks in obsessive-compulsive disorder
Sha, Z., Edmiston, E. K., Versace, A., Fournier, J. C., Graur, S., Greenberg, T., Lima Santos, J. P., Chase, H. W., Stiffler, R. S., Bonar, L., et al. (2020) · Biological Psychiatry: Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2019.12.002 · Cited by 48
Lynch, C. J., Breeden, A. L., Gordon, E. M., Cherry, J. B. C., Turkeltaub, P. E., & Vaidya, C. J. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy270 · Cited by 47
Zanchi, D., Montandon, M., Sinanaj, I., Rodriguez, C. K., Depoorter, A., Herrmann, F. R., Borgwardt, S., Giannakopoulos, P., & Haller, S. (2017) · Neurosignals · doi:10.1159/000486152 · Cited by 47
Pu, W., Luo, Q., Palaniyappan, L. K., Xue, Z., Yao, S., Feng, J., & Liu, Z. (2016) · Psychological Medicine · doi:10.1017/s0033291715002755 · Cited by 48
Decreased Alertness Reconfigures Cognitive Control Networks
Canales‐Johnson, A., Beerendonk, L., Blain, S., Kitaoka, S., Ezquerro‐Nassar, A., Nuiten, S. A., Fahrenfort, J. J., van Gaal, S., & Bekinschtein, T. A. (2020) · Journal of Neuroscience · doi:10.1523/jneurosci.0343-20.2020 · Cited by 47
Neurocognitive Profiles of Older Adults with Working-Memory Dysfunction
Salami, A., Rieckmann, A., Karalija, N., Avelar‐Pereira, B., Andersson, M., Wåhlin, A., Papenberg, G., Garrett, D. D., Riklund, K., Lövdén, M., et al. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy062 · Cited by 50
Brain network modularity predicts cognitive training-related gains in young adults
Baniqued, P. L., Gallen, C. L., Kranz, M. B., Kramer, A. F., & D’Esposito, M. (2019) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2019.05.021 · Cited by 44
Involvement of the default mode network under varying levels of cognitive effort
Weber, S., Aleman, A., & Hugdahl, K. (2022) · Scientific Reports · doi:10.1038/s41598-022-10289-7 · Cited by 48
Functional Connectome Analyses Reveal the Human Olfactory Network Organization
Arnold, T. C., You, Y., Ding, M., Zuo, X., de Araújo, I., & Li, W. (2020) · eNeuro · doi:10.1523/eneuro.0551-19.2020 · Cited by 42
Lois, G., Gerchen, M. F., Kirsch, P., Kanske, P., Schönfelder, S., & Wessa, M. (2017) · Bipolar Disorders · doi:10.1111/bdi.12512 · Cited by 40
Lynch, C. J., Breeden, A. L., You, X., Ludlum, R. S., Gaillard, W. D., Kenworthy, L. E., & Vaidya, C. J. (2017) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2017.03.008 · Cited by 46
Core networks and their reconfiguration patterns across cognitive loads
Zuo, N., Yang, Z., Liu, Y., Li, J., & Jiang, T. (2018) · Human Brain Mapping · doi:10.1002/hbm.24193 · Cited by 39
Li, R., Zhang, S., Yin, S., Ren, W., He, R., & Li, J. (2018) · Human Brain Mapping · doi:10.1002/hbm.24247 · Cited by 39
Xue, C., Qi, W., Yuan, Q., Hu, G., Ge, H., Rao, J., Xiao, C., & Chen, J. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.711009 · Cited by 39
Lei, Y., Li, Y., Guo, Q., Liu, X., Liu, Z., Ni, W., Su, J., Yang, H., Jiang, H., Xu, B., et al. (2016) · Journal of neurosurgery · doi:10.3171/2015.12.jns151499 · Cited by 39
Rest but busy: Aberrant resting‐state functional connectivity of triple network model in insomnia
Dong, X., Qin, H., Wu, T., Hu, H., Liao, K., Cheng, F., Gao, D., & Lei, X. (2018) · Brain and Behavior · doi:10.1002/brb3.876 · Cited by 38
Takeuchi, H., Taki, Y., Nouchi, R., Sekiguchi, A., Kotozaki, Y., Nakagawa, S., Makoto Miyauchi, C., Sassa, Y., & Kawashima, R. (2017) · Scientific Reports · doi:10.1038/s41598-017-01460-6 · Cited by 36
Steardo, L., D’Angelo, M., Monaco, F., Stefano, V. D., & Steardo, L. (2025) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2025.106030 · Cited by 42
Browndyke, J. N., Berger, M., Smith, P. J., Harshbarger, T. B., Monge, Z. A., Panchal, V., Bisanar, T. L., Glower, D. D., Alexander, J. H., Cabeza, R. E. L., et al. (2017) · Human Brain Mapping · doi:10.1002/hbm.23898 · Cited by 34
Qi, J., Li, B.-Z., Zhang, Y., Pan, B., Gao, Y., Zhan, H., Liu, Y., Shao, Y., & Zhang, X. (2021) · Sleep Medicine · doi:10.1016/j.sleep.2021.05.037 · Cited by 36
Altered topological patterns of brain functional networks in Crohn’s disease
Liu, P., Li, R., Bao, C., Wei, Y., Fan, Y., Liu, Y., Wang, G., Wu, H., & Qin, W. (2018) · Brain Imaging and Behavior · doi:10.1007/s11682-017-9814-8 · Cited by 35
Perera, M. P. N., Gotsis, E. S., Bailey, N. W., Fitzgibbon, B. M., & Fitzgerald, P. B. (2024) · Cerebral Cortex · doi:10.1093/cercor/bhae327 · Cited by 34
Nour, M. M., Dahoun, T., McCutcheon, R. A., Adams, R. A., Wall, M. B., & Howes, O. D. (2019) · eLife · doi:10.7554/elife.45045 · Cited by 35
Wang, Y., Wang, C., Wei, Y., Miao, P., Liu, J., Wu, L., Li, Z., Li, X., Wang, K., & Cheng, J. (2022) · Human Brain Mapping · doi:10.1002/hbm.25982 · Cited by 33
Dynamic reconfiguration of the functional brain network after musical training in young adults
Li, Q., Wang, X., Wang, S., Xie, Y., Li, X., Xie, Y., & Li, S. (2019) · Brain Structure and Function · doi:10.1007/s00429-019-01867-z · Cited by 32
Strategies and cognitive reserve to preserve lexical production in aging
Baciu, M., Banjac, S., Roger, É., Haldin, C., Perrone‐Bertolotti, M., Lœvenbruck, H., & Démonet, J. (2021) · GeroScience · doi:10.1007/s11357-021-00367-5 · Cited by 38
Chakladar, D. D., Roy, P. P., & Iwamura, M. (2021) · IEEE Transactions on Cognitive and Developmental Systems · doi:10.1109/tcds.2021.3116079 · Cited by 32
Hilger, K., & Fiebach, C. J. (2019) · Network Neuroscience · doi:10.1162/netn_a_00083 · Cited by 31
Liu, R., Chen, H., Qin, R., Gu, Y., Chen, X., Zou, J., Jiang, Y., Li, W., Bai, F., Zhang, B., et al. (2019) · Frontiers in Neurology · doi:10.3389/fneur.2019.00324 · Cited by 31
Li, X., Wang, L., Chen, Q., Hu, Y., Du, J., Chen, X., Zheng, W., Lu, J., & Chen, N. (2020) · Neural Plasticity · doi:10.1155/2020/2796571 · Cited by 30
Insula-cingulate structural and functional connectivity: an ultra-high field MRI study
Cormie, M. A., Kaya, B., Hadjis, G. E., Mouseli, P., & Moayedi, M. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad244 · Cited by 30
Wanke, N., & Schwabe, L. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhz298 · Cited by 28
Reconfigured functional network dynamics in adult moyamoya disease: a resting-state fMRI study
Lei, Y., Song, B., Chen, L., Su, J., Zhang, X., Ni, W., Yu, Y., Xu, B., Yu, L., Gu, Y., et al. (2018) · Brain Imaging and Behavior · doi:10.1007/s11682-018-0009-8 · Cited by 27
Otsuka, K., Cornélissen, G., Kubo, Y., Shibata, K., Hayashi, M., Mizuno, K., Ohshima, H., Furukawa, S., & Mukai, C. N. (2018) · Scientific Reports · doi:10.1038/s41598-018-28740-z · Cited by 30
Individualized video recommendation modulates functional connectivity between large scale networks
Su, C., Zhou, H., Wang, C., Geng, F., & Hu, Y. (2021) · Human Brain Mapping · doi:10.1002/hbm.25616 · Cited by 28
Brain Networks Reorganization During Maturation and Healthy Aging-Emphases for Resilience
González‐Escamilla, G., Muthuraman, M., Chirumamilla, V. C., Vogt, J., & Groppa, S. (2018) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2018.00601 · Cited by 28
Functional brain modules reconfigure at multiple scales across the human lifespanPreprint
Betzel, R. F., Mišić, B., He, Y., Rumschlag, J. A., Zuo, X., & Sporns, O. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1510.08045 · Cited by 35
Self-citationRegional Gray Matter Atrophy in Vascular Mild Cognitive Impairment
Lei, Y., Su, J., Guo, Q., Yang, H., Gu, Y., & Mao, Y. Q. (2015) · Journal of Stroke and Cerebrovascular Diseases · doi:10.1016/j.jstrokecerebrovasdis.2015.08.041 · Cited by 26
Functional neural network configuration in late childhood varies by age and cognitive state
Le, T. M., Huang, A., O’Rawe, J. F., & Leung, H. (2020) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2020.100862 · Cited by 30
Ding, X., Yang, Y., Stein, E. A., & Ross, T. J. (2017) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2017.00362 · Cited by 23
Self-citationRosa, P. A. D., Canini, M., Marchetta, E., Cirillo, S., Pontesilli, S., Scotti, R., Sora, M. G. N., Poloniato, A., Barera, G., Falini, A., et al. (2020) · Brain and Cognition · doi:10.1016/j.bandc.2020.105669 · Cited by 26
Yun, J.-Y., Jang, J. H., Jung, W. H., Shin, N. Y., Kim, S. N., Hwang, J. Y., & Kwon, J. S. (2017) · Psychiatry Investigation · doi:10.4306/pi.2017.14.3.333 · Cited by 22
Ahmadi, M., Kazemi, K., Kuć, K., Cybulska-Kłosowicz, A., Helfroush, M. S., & Aarabi, A. (2021) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac16b3 · Cited by 25
Liang, X., Yuan, Q., Xue, C., Qi, W., Ge, H., Yan, Z., Chen, S., Song, Y., Wu, H., Xiao, C., et al. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.919859 · Cited by 24
Self-citationWorking memory load-dependent changes in cortical network connectivity estimated by machine learning
Eryilmaz, H., Dowling, K. F., Hughes, D., Rodriguez-Thompson, A., Tanner, A. S., Huntington, C., Coon, W. G., & Roffman, J. L. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116895 · Cited by 24
Age differences in functional network reconfiguration with working memory training
Iordan, A. D., Moored, K., Katz, B., Cooke, K. A., Buschkuehl, M., Jaeggi, S. M., Polk, T. A., Peltier, S., Jonides, J., & Reuter‐Lorenz, P. A. (2021) · Human Brain Mapping · doi:10.1002/hbm.25337 · Cited by 26
Zheng, H., Ford, B. N., Kuplicki, R., Burrows, K., Hunt, P. W., Bodurka, J., Teague, T. K., Irwin, M. R., Yolken, R. H., Paulus, M. P., et al. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01558-6 · Cited by 23
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Metadata
- Authors
- Liang, X., Zou, Q., He, Y., & Yang, Y.
- Affiliations
- National Institutes of Health (US)
- Peking University (CN)
- Corresponding author
- Liang, Xia
- Venue
- Cerebral Cortex
- Publisher
- Oxford University Press (OUP)
- Published
- 2015-01-16
- Volume
- 26
- Issue
- 4
- Pages
- 1501-1511
- ISSN
- 1047-3211 (ISSN-L)
- 1460-2199
- PMC
- PMC4785946
- OpenAlex
- W1968592137
- Cited by
- 261
- References
- 56
- Citations by year
- 2026: 11 · 2025: 31 · 2024: 26 · 2023: 22 · 2022: 19 · 2021: 31 · 2020: 17 · 2019: 24 · 2018: 28 · 2017: 21 · 2016: 25 · 2015: 6
- FWCI
- 16.05
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- public-domain
- Locations
- Cerebral Cortex (publishedVersion, public-domain)
- PubMed Central (publishedVersion, public-domain)
- PubMed (publishedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- National Natural Science Foundation of China (81201142, 81225012, 31221003, 81030028)
- National Institutes of Health
- National Science Fund for Distinguished Young Scholars (81225012)
- National Institute on Drug Abuse
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- default mode network, frontoparietal network, salience network, working memory, cognitive load, functional connectivity, network topology, posterior cingulate cortex, superior parietal cortex
- MeSH terms
- Adult, Attention, Brain, Brain Mapping, Cognition, Female, Humans, Magnetic Resonance Imaging, Male, Memory, Short-Term, Neural Pathways, Young Adult, Executive Function
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