Static and dynamic posterior cingulate cortex nodal topology of default mode network predicts attention task performance
详细信息    查看全文
  • 作者:Pan Lin ; Yong Yang ; Jorge Jovicich ; Nicola De Pisapia…
  • 关键词:Default mode network (DMN) ; Functional connectivity (FC) ; Task performance ; Posterior cingulate cortex (PCC) ; Degree
  • 刊名:Brain Imaging and Behavior
  • 出版年:2016
  • 出版时间:March 2016
  • 年:2016
  • 卷:10
  • 期:1
  • 页码:212-225
  • 全文大小:4,923 KB
  • 参考文献:Achard, S., Delon-Martin, C., Vertes, P. E., Renard, F., Schenck, M., Schneider, F., Heinrich, C., Kremer, S., & Bullmore, E. T. (2012). Hubs of brain functional networks are radically reorganized in comatose patients. Proceedings of the National Academy of Sciences of the United States of America, 109(50), 20608–20613.CrossRef PubMed PubMedCentral
    Allen, E. A., Damaraju, E., Plis, S. M., Erhardt, E. B., Eichele, T., & Calhoun, V. D. (2014). Tracking whole
    ain connectivity dynamics in the resting state. Cerebral Cortex, 24(3), 663–676.CrossRef PubMed PubMedCentral
    Andrews-Hanna, J. R., Snyder, A. Z., Vincent, J. L., Lustig, C., Head, D., Raichle, M. E., & Buckner, R. L. (2007). Disruption of large-scale brain systems in advanced aging. Neuron, 56(5), 924–935.CrossRef PubMed PubMedCentral
    Arenivas, A., Diaz-Arrastia, R., Spence, J., Cullum, C. M., Krishnan, K., Bosworth, C., Culver, C., Kennard, B., & Marquez de la Plata, C. (2014). Three approaches to investigating functional compromise to the default mode network after traumatic axonal injury. Brain Imaging and Behavior, 8(3), 407–419.CrossRef PubMed
    Bassett, D. S., Bullmore, E. T., Meyer-Lindenberg, A., Apud, J. A., Weinberger, D. R., & Coppola, R. (2009). Cognitive fitness of cost-efficient brain functional networks. Proceedings of the National Academy of Sciences of the United States of America, 106(28), 11747–11752.CrossRef PubMed PubMedCentral
    Bonnelle, V., Ham, T. E., Leech, R., Kinnunen, K. M., Mehta, M. A., Greenwood, R. J., & Sharp, D. J. (2012). Salience network integrity predicts default mode network function after traumatic brain injury. Proceedings of the National Academy of Sciences of the United States of America, 109(12), 4690–4695.CrossRef PubMed PubMedCentral
    Buckner, R. L., Andrews-Hanna, J. R., & Schacter, D. L. (2008). The brain’s default network: anatomy, function, and relevance to disease. Annals of the New York Academy of Sciences, 1124, 1–38.CrossRef PubMed
    Buckner, R. L., Sepulcre, J., Talukdar, T., Krienen, F. M., Liu, H. S., Hedden, T., Andrews-Hanna, J. R., Sperling, R. A., & Johnson, K. A. (2009). Cortical hubs revealed by intrinsic functional connectivity: mapping, assessment of stability, and relation to Alzheimer’s disease. Journal of Neuroscience, 29(6), 1860–1873.CrossRef PubMed PubMedCentral
    Calhoun, V. D., Miller, R., Pearlson, G., & Adali, T. (2014). The chronnectome: time-varying connectivity networks as the next frontier in fMRI Data discovery. Neuron, 84(2), 262–274.CrossRef PubMed PubMedCentral
    Castellanos, N. P., Paul, N., Ordonez, V. E., Demuynck, O., Bajo, R., Campo, P., Bilbao, A., Ortiz, T., Del-Pozo, F., & Maestu, F. (2010). Reorganization of functional connectivity as a correlate of cognitive recovery in acquired brain injury. Brain: A Journal of Neurology, 133(Pt 8), 2365–2381.CrossRef
    Chang, C., & Glover, G. H. (2010). Time-frequency dynamics of resting-state brain connectivity measured with fMRI. NeuroImage, 50(1), 81–98.CrossRef PubMed PubMedCentral
    Chen, J. L., Ros, T., & Gruzelier, J. H. (2013). Dynamic changes of ICA-derived EEG functional connectivity in the resting state. Human Brain Mapping, 34(4), 852–868.CrossRef PubMed
    Chikazoe, J., Konishi, S., Asari, T., Jimura, K., & Miyashita, Y. (2007). Activation of right inferior frontal gyrus during response inhibition across response modalities. Journal of Cognitive Neuroscience, 19(1), 69–80.CrossRef PubMed
    Cocchi, L., Zalesky, A., Toepel, U., Whitford, T. J., De-Lucia, M., Murray, M. M., & Carter, O. (2011). Dynamic changes in brain functional connectivity during concurrent dual-task performance. PLoS One, 6(11), e28301.CrossRef PubMed PubMedCentral
    Corbetta, M., & Shulman, G. L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews Neuroscience, 3(3), 201–215.CrossRef PubMed
    Crossley, N. A., Mechelli, A., Vertes, P. E., Winton-Brown, T. T., Patel, A. X., Ginestet, C. E., McGuire, P., & Bullmore, E. T. (2013). Cognitive relevance of the community structure of the human brain functional coactivation network. Proceedings of the National Academy of Sciences of the United States of America, 110(28), 11583–11588.CrossRef PubMed PubMedCentral
    De Pisapia, N., Turatto, M., Lin, P., Jovicich, J., & Caramazza, A. (2012). Unconscious priming instructions modulate activity in default and executive networks of the human brain. Cerebral Cortex, 22(3), 639–649.CrossRef PubMed
    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). Distinct brain networks for adaptive and stable task control in humans. Proceedings of the National Academy of Sciences of the United States of America, 104(26), 11073–11078.CrossRef PubMed PubMedCentral
    Fair, D. A., Cohen, A. L., Dosenbach, N. U. F., Church, J. A., Miezin, F. M., Barch, D. M., Raichle, M. E., Petersen, S. E., & Schlaggar, B. L. (2008). The maturing architecture of the brain’s default network. Proceedings of the National Academy of Sciences of the United States of America, 105(10), 4028–4032.CrossRef PubMed PubMedCentral
    Fornito, A., Harrison, B. J., Zalesky, A., & Simons, J. S. (2012). Competitive and cooperative dynamics of large-scale brain functional networks supporting recollection. Proceedings of the National Academy of Sciences of the United States of America, 109(31), 12788–12793.CrossRef PubMed PubMedCentral
    Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005). The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences of the United States of America, 102(27), 9673–9678.CrossRef PubMed PubMedCentral
    Garrett, D. D., Kovacevic, N., McIntosh, A. R., & Grady, C. L. (2011). The importance of being variable. Journal of Neuroscience, 31(12), 4496–4503.CrossRef PubMed PubMedCentral
    Gong, G., He, Y., Concha, L., Lebel, C., Gross, D. W., Evans, A. C., & Beaulieu, C. (2009). Mapping anatomical connectivity patterns of human cerebral cortex using in vivo diffusion tensor imaging tractography. Cerebral Cortex (New York, N Y : 1991), 19(3), 524–536.CrossRef
    Greicius, M. D., Krasnow, B., Reiss, A. L., & Menon, V. (2003). Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proceedings of the National Academy of Sciences of the United States of America, 100(1), 253–258.CrossRef PubMed PubMedCentral
    Greicius, M. D., Supekar, K., Menon, V., & Dougherty, R. F. (2009). Resting-state functional connectivity reflects structural connectivity in the default mode network. Cerebral Cortex (New York, N Y : 1991), 19(1), 72–78.CrossRef
    Hagmann, P., Sporns, O., Madan, N., Cammoun, L., Pienaar, R., Wedeen, V. J., Meuli, R., Thiran, J. P., & Grant, P. E. (2010). White matter maturation reshapes structural connectivity in the late developing human brain. Proceedings of the National Academy of Sciences of the United States of America, 107(44), 19067–19072.CrossRef PubMed PubMedCentral
    Handwerker, D. A., Roopchansingh, V., Gonzalez-Castillo, J., & Bandettini, P. A. (2012). Periodic changes in fMRI connectivity. NeuroImage, 63(3), 1712–1719.CrossRef PubMed PubMedCentral
    Hellyer, P. J., Shanahan, M., Scott, G., Wise, R. J., Sharp, D. J., & Leech, R. (2014). The control of global brain dynamics: opposing actions of frontoparietal control and default mode networks on attention. Journal of Neuroscience, 34(2), 451–461.CrossRef PubMed PubMedCentral
    Hutchison, R. M., Womelsdorf, T., Allen, E. A., Bandettini, P. A., Calhoun, V. D., Corbetta, M., Penna, S., Duyn, J. H., Glover, G. H., Gonzalez-Castillo, J., et al. (2013a). Dynamic functional connectivity: promise, issues, and interpretations. NeuroImage, 80, 360–378.CrossRef PubMed
    Hutchison, R. M., Womelsdorf, T., Gati, J. S., Everling, S., & Menon, R. S. (2013b). Resting-state networks show dynamic functional connectivity in awake humans and anesthetized macaques. Human Brain Mapping, 34(9), 2154–2177.CrossRef PubMed
    Kelly, A. M. C., Uddin, L. Q., Biswal, B. B., Castellanos, F. X., & Milham, M. P. (2008). Competition between functional brain networks mediates behavioral variability. NeuroImage, 39(1), 527–537.CrossRef PubMed
    Konishi, S., Hayashi, T., Uchida, I., Kikyo, H., Takahashi, E., & Miyashita, Y. (2002). Hemispheric asymmetry in human lateral prefrontal cortex during cognitive set shifting. Proceedings of the National Academy of Sciences of the United States of America, 99(11), 7803–7808.CrossRef PubMed PubMedCentral
    Kucyi, A., & Davis, K. D. (2014). Dynamic functional connectivity of the default mode network tracks daydreaming. NeuroImage, 100, 471–480.CrossRef PubMed
    Kucyi, A., & Davis, K. D. (2015). The dynamic pain connectome. Trends in Neurosciences, 38(2), 86–95.CrossRef PubMed
    Kucyi, A., Salomons, T. V., & Davis, K. D. (2013). Mind wandering away from pain dynamically engages antinociceptive and default mode brain networks. Proceedings of the National Academy of Sciences of the United States of America, 110(46), 18692–18697.CrossRef PubMed PubMedCentral
    Lee, H. L., Zahneisen, B., Hugger, T., Levan, P., & Hennig, J. (2013). Tracking dynamic resting-state networks at higher frequencies using MR-encephalography. NeuroImage, 65, 216–222.CrossRef PubMed
    Leech, R., Kamourieh, S., Beckmann, C. F., & Sharp, D. J. (2011). Fractionating the default mode network: distinct contributions of the ventral and dorsal posterior cingulate cortex to cognitive control. Journal of Neuroscience, 31(9), 3217–3224.CrossRef PubMed
    Leech, R., Sharp, DJ. (2013). The role of the posterior cingulate cortex in cognition and disease. Brain.
    Leonardi, N., Richiardi, J., Gschwind, M., Simioni, S., Annoni, J. M., Schluep, M., Vuilleumier, P., & Van De Ville, D. (2013). Principal components of functional connectivity: a new approach to study dynamic brain connectivity during rest. NeuroImage, 83, 937–950.CrossRef PubMed
    Liang, X., Zou, Q. H., He, Y., & Yang, Y. H. (2013). Coupling of functional connectivity and regional cerebral blood flow reveals a physiological basis for network hubs of the human brain. Proceedings of the National Academy of Sciences of the United States of America, 110(5), 1929–1934.CrossRef PubMed PubMedCentral
    Lin, P., Hasson, U., Jovicich, J., & Robinson, S. (2011). A neuronal basis for task-negative responses in the human brain. Cerebral Cortex (New York, N Y : 1991), 21(4), 821–830.CrossRef
    Lin, P., Sun, J. B., Yu, G., Wu, Y., Yang, Y., Liang, M. L., & Liu, X. (2014). Global and local brain network reorganization in attention-deficit/hyperactivity disorder. Brain Imaging and Behavior, 8(4), 558–569.CrossRef PubMed
    Ma, S., Calhoun, V. D., Phlypo, R., & Adali, T. (2014). Dynamic changes of spatial functional network connectivity in healthy individuals and schizophrenia patients using independent vector analysis. NeuroImage, 90, 196–206.CrossRef PubMed
    Mantini, D., & Vanduffel, W. (2013). Emerging roles of the brain’s default network. The Neuroscientist, 19(1), 76–87.CrossRef PubMed
    Marchant, J. L., & Driver, J. (2013). Visual and audiovisual effects of isochronous timing on visual perception and brain activity. Cerebral Cortex, 23(6), 1290–1298.CrossRef PubMed PubMedCentral
    Mayhew, S. D., Hylands-White, N., Porcaro, C., Derbyshire, S. W. G., & Bagshaw, A. P. (2013). Intrinsic variability in the human response to pain is assembled from multiple, dynamic brain processes. NeuroImage, 75, 68–78.CrossRef PubMed
    McKiernan, K. A., Kaufman, J. N., Kucera-Thompson, J., & Binder, J. R. (2003). A parametric manipulation of factors affecting task-induced deactivation in functional neuroimaging. Journal of Cognitive Neuroscience, 15(3), 394–408.CrossRef PubMed
    Murphy, K., Birn, R. M., Handwerker, D. A., Jones, T. B., & Bandettini, P. A. (2009). The impact of global signal regression on resting state correlations: are anti-correlated networks introduced? NeuroImage, 44(3), 893–905.CrossRef PubMed PubMedCentral
    Park, H. J., & Friston, K. (2013). Structural and functional brain networks: from connections to cognition. Science, 342(6158), 1238411.CrossRef PubMed
    Patel, K. T., Stevens, M. C., Pearlson, G. D., Winkler, A. M., Hawkins, K. A., Skudlarski, P., & Bauer, L. O. (2013). Default mode network activity and white matter integrity in healthy middle-aged ApoE4 carriers. Brain Imaging and Behavior, 7(1), 60–67.CrossRef PubMed
    Pfefferbaum, A., Chanraud, S., Pitel, A. L., Muller-Oehring, E., Shankaranarayanan, A., Alsop, D. C., Rohlfing, T., & Sullivan, E. V. (2011). Cerebral blood flow in posterior cortical nodes of the default mode network decreases with task engagement but remains higher than in most brain regions. Cerebral Cortex, 21(1), 233–244.CrossRef PubMed PubMedCentral
    Philip, N. S., Sweet, L. H., Tyrka, A. R., Price, L. H., Carpenter, L. L., Kuras, Y. I., Clark, U. S., & Niaura, R. S. (2013). Early life stress is associated with greater default network deactivation during working memory in healthy controls: a preliminary report. Brain Imaging and Behavior, 7(2), 204–212.CrossRef PubMed PubMedCentral
    Power, J. D., Schlaggar, B. L., Lessov-Schlaggar, C. N., & Petersen, S. E. (2013). Evidence for hubs in human functional brain networks. Neuron, 79(4), 798–813.CrossRef PubMed
    Raichle, M. E., & Gusnard, D. A. (2002). Appraising the brain’s energy budget. Proceedings of the National Academy of Sciences of the United States of America, 99(16), 10237–10239.CrossRef PubMed PubMedCentral
    Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001). A default mode of brain function. Proceedings of the National Academy of Sciences of the United States of America, 98(2), 676–682.CrossRef PubMed PubMedCentral
    Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: uses and interpretations. NeuroImage, 52(3), 1059–1069.CrossRef PubMed
    Scholvinck, M. L., Maier, A., Ye, F. Q., Duyn, J. H., & Leopold, D. A. (2010). Neural basis of global resting-state fMRI activity. Proceedings of the National Academy of Sciences of the United States of America, 107(22), 10238–10243.CrossRef PubMed PubMedCentral
    Sharp, D. J., Beckmann, C. F., Greenwood, R., Kinnunen, K. M., Bonnelle, V., De Boissezon, X., Powell, J. H., Counsell, S. J., Patel, M. C., & Leech, R. (2011). Default mode network functional and structural connectivity after traumatic brain injury. Brain, 134(Pt 8), 2233–2247.CrossRef PubMed
    Sharp, D. J., Scott, G., & Leech, R. (2014). Network dysfunction after traumatic brain injury. Nature Reviews Neurology, 10(3), 156–166.CrossRef PubMed
    Sporns, O., Tononi, G., & Edelman, G. M. (2000). Theoretical neuroanatomy: relating anatomical and functional connectivity in graphs and cortical connection matrices. Cerebral Cortex, 10(2), 127–141.CrossRef PubMed
    Street, J. O., Carroll, R. J., & Ruppert, D. (1988). A note on computing robust regression estimates via iteratively reweighted least-squares. American Statistician, 42(2), 152–154.
    Supekar, K., Musen, M., & Menon, V. (2009). Development of large-scale functional brain networks in children. PLoS Biology, 7(7), e1000157.CrossRef PubMed PubMedCentral
    Supekar, K., Uddin, L. Q., Prater, K., Amin, H., Greicius, M. D., & Menon, V. (2010). Development of functional and structural connectivity within the default mode network in young children. NeuroImage, 52(1), 290–301.CrossRef PubMed PubMedCentral
    Tagliazucchi, E., & Laufs, H. (2014). Decoding wakefulness levels from typical fMRI resting-state data reveals reliable drifts between wakefulness and sleep. Neuron, 82(3), 695–708.CrossRef PubMed
    Tagliazucchi, E., von Wegner, F., Morzelewski, A., Brodbeck, V., & Laufs, H. (2012). Dynamic BOLD functional connectivity in humans and its electrophysiological correlates. Frontiers in Human Neuroscience, 6, 339.CrossRef PubMed PubMedCentral
    Tam, A., Luedke, AC., Walsh, JJ., Fernandez-Ruiz, J., Garcia, A. (2014). Effects of reaction time variability and age on brain activity during Stroop task performance. Brain Imaging and Behav
    Thompson, G. J., Merritt, M. D., Pan, W. J., Magnuson, M. E., Grooms, J. K., Jaeger, D., & Keilholz, S. D. (2013). Neural correlates of time-varying functional connectivity in the rat. NeuroImage, 83, 826–836.CrossRef PubMed
    Utevsky, A. V., Smith, D. V., & Huettel, S. A. (2014). Precuneus is a functional core of the default-mode network. Journal of Neuroscience, 34(3), 932–940.CrossRef PubMed PubMedCentral
    van den Bos, W., Talwar, A., & McClure, S. M. (2013). Neural correlates of reinforcement learning and social preferences in competitive bidding. Journal of Neuroscience, 33(5), 2137–2146.CrossRef PubMed
    van den Heuvel, M., Mandl, R., Luigjes, J., & Hulshoff, P. H. (2008). Microstructural organization of the cingulum tract and the level of default mode functional connectivity. Journal of Neuroscience, 28(43), 10844–10851.CrossRef PubMed
    van den Heuvel, M. P., Stam, C. J., Kahn, R. S., & Hulshoff Pol, H. E. (2009). Efficiency of functional brain networks and intellectual performance. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 29(23), 7619–7624.CrossRef
    Van Dijk, K. R. A., Hedden, T., Venkataraman, A., Evans, K. C., Lazar, S. W., & Buckner, R. L. (2010). Intrinsic functional connectivity as a tool for human connectomics: theory, properties, and optimization. Journal of Neurophysiology, 103(1), 297–321.CrossRef PubMed PubMedCentral
    van Veluw, S. J., & Chance, S. A. (2014). Differentiating between self and others: an ALE meta-analysis of fMRI studies of self-recognition and theory of mind. Brain Imaging and Behavior, 8(1), 24–38.CrossRef PubMed
    Weissman, D. H., Roberts, K. C., Visscher, K. M., & Woldorff, M. G. (2006). The neural bases of momentary lapses in attention. Nature Neuroscience, 9(7), 971–978.CrossRef PubMed
    Yan, Y., Rasch, M. J., Chen, M., Xiang, X., Huang, M., Wu, S., & Li, W. (2014). Perceptual training continuously refines neuronal population codes in primary visual cortex. Nature Neuroscience, 17(10), 1380–1387.CrossRef PubMed
    Zaitsev, M., Hennig, J., & Speck, O. (2004). Point spread function mapping with parallel imaging techniques and high acceleration factors: Fast, robust, and flexible method for echo-planar imaging distortion correction. Magnetic Resonance in Medicine, 52(5), 1156–1166.CrossRef PubMed
  • 作者单位:Pan Lin (1) (3) (6)
    Yong Yang (2)
    Jorge Jovicich (3) (4)
    Nicola De Pisapia (3)
    Xiang Wang (5)
    Chun S. Zuo (6)
    James Jonathan Levitt (7) (8)

    1. Key Laboratory of Biomedical Information Engineering of Education Ministry, Institute of Biomedical Engineering, Xi’an Jiaotong University, Xi’an, 710049, China
    3. Center for Mind/Brain Sciences, University of Trento, Mattarello, 38100, Italy
    6. Brain Imaging Center, McLean Hospital, Department of Psychiatry, Harvard Medical School, Belmont, MA, USA
    2. School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, People’s Republic of China
    4. Department of Cognitive and Education Sciences, University of Trento, Rovereto, 38068, Italy
    5. Medical Psychological Institute of Second Xiangya Hospital, Central South University, Changsha, China
    7. Clinical Neuroscience Division, Laboratory of Neuroscience, Department of Psychiatry, VA, Boston Healthcare System, Brockton Division, Harvard Medical School, Boston, MA, 02301, USA
    8. Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, 02215, USA
  • 刊物主题:Neurosciences; Neuroradiology; Neuropsychology; Psychiatry;
  • 出版者:Springer US
  • ISSN:1931-7565
文摘
Characterization of the default mode network (DMN) as a complex network of functionally interacting dynamic systems has received great interest for the study of DMN neural mechanisms. In particular, understanding the relationship of intrinsic resting-state DMN brain network with cognitive behaviors is an important issue in healthy cognition and mental disorders. However, it is still unclear how DMN functional connectivity links to cognitive behaviors during resting-state. In this study, we hypothesize that static and dynamic DMN nodal topology is associated with upcoming cognitive task performance. We used graph theory analysis in order to understand better the relationship between the DMN functional connectivity and cognitive behavior during resting-state and task performance. Nodal degree of the DMN was calculated as a metric of network topology. We found that the static and dynamic posterior cingulate cortex (PCC) nodal degree within the DMN was associated with task performance (Reaction Time). Our results show that the core node PCC nodal degree within the DMN was significantly correlated with reaction time, which suggests that the PCC plays a key role in supporting cognitive function.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700