Disrupted brain connectivity networks in acute ischemic stroke patients

Brain Imaging and Behavior

Volumn 11, Issue 2, 2017, Pages 444-453

  Zhu, Yifei ^a   Bai, Lin ^a   Liang, Panpan ^a   Kang, Shan ^a   Gao, Hengbo ^a   Yang, Haiqing ^a  

^a HEBEI MEDICAL UNIVERSITY   (China)

Author keywords

Acute ischemic stroke; Brain connectome; Cognitive performance

Indexed keywords

ADULT; AGED; ANGULAR GYRUS; ARTICLE; BRAIN ISCHEMIA; CLINICAL ARTICLE; COGNITION; CONNECTOME; CONTROLLED STUDY; FEMALE; FUNCTIONAL CONNECTIVITY; FUNCTIONAL MAGNETIC RESONANCE IMAGING; FUNCTIONAL NEUROIMAGING; HEAD MOVEMENT; HIPPOCAMPUS; HUMAN; INFERIOR FRONTAL GYRUS; INSULA; MALE; MIDDLE FRONTAL GYRUS; MINI MENTAL STATE EXAMINATION; NATIONAL INSTITUTES OF HEALTH STROKE SCALE; NEUROANATOMY; NUCLEAR MAGNETIC RESONANCE SCANNER; PARIETAL GYRUS; PRECUNEUS; PREFRONTAL CORTEX; PRIORITY JOURNAL; STROKE PATIENT; SUPERIOR FRONTAL GYRUS; SUPERIOR TEMPORAL GYRUS; WESTERN APHASIA BATTERY; ADAPTATION; BIOLOGICAL MODEL; BRAIN; BRAIN CORTEX; CEREBROVASCULAR ACCIDENT; MIDDLE AGED; NERVE CELL NETWORK; NERVE TRACT; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOPHYSIOLOGY; PROCEDURES;

ADAPTATION, PHYSIOLOGICAL; BRAIN; CEREBRAL CORTEX; CONNECTOME; FEMALE; HUMANS; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; MODELS, NEUROLOGICAL; NERVE NET; NEURAL PATHWAYS; STROKE;

EID: 84958745224     PISSN: 19317557     EISSN: 19317565     Source Type: Journal    
DOI: 10.1007/s11682-016-9525-6     Document Type: Article

References (42)

1. Achard, S., & Bullmore, E. (2007). Efficiency and cost of economical brain functional networks. PLoS Computational Biology, 3(2), e17.
2. Achard, S., Salvador, R., Whitcher, B., Suckling, J., & Bullmore, E. (2006). A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs. Journal of Neuroscience, 26(1), 63–72.
3. Barker-Collo, S. L., Feigin, V. L., Lawes, C. M., Parag, V., Senior, H., & Rodgers, A. (2009). Reducing attention deficits after stroke using attention process training a randomized controlled trial. Stroke, 40(10), 3293–3298.
4. Breier, J., Hasan, K., Zhang, W., Men, D., & Papanicolaou, A. (2008). Language dysfunction after stroke and damage to white matter tracts evaluated using diffusion tensor imaging. American Journal of Neuroradiology, 29(3), 483–487.
5. Bullmore, E. T., & Bassett, D. S. (2011). Brain graphs: graphical models of the human brain connectome. Annual Review of Clinical Psychology, 7, 113–140.
6. Bullmore, E., & Sporns, O. (2009). Complex brain networks: graph theoretical analysis of structural and functional systems. Nature Reviews Neuroscience, 10(3), 186–198.
7. Bullmore, E. T., Suckling, J., Overmeyer, S., Rabe-Hesketh, S., Taylor, E., & Brammer, M. J. (1999). Global, voxel, and cluster tests, by theory and permutation, for a difference between two groups of structural MR images of the brain. IEEE Transactions on Medical Imaging, 18(1), 32–42.
8. Cheng, H.-L., Lin, C.-J., Soong, B.-W., Wang, P.-N., Chang, F.-C., Wu, Y.-T., et al. (2012). Impairments in cognitive function and brain connectivity in severe asymptomatic carotid stenosis. Stroke, 43(10), 2567–2573.
9. Dacosta‐Aguayo, R., Grana, M., Iturria‐Medina, Y., Fernández‐Andújar, M., López‐Cancio, E., Caceres, C., et al. (2015). Impairment of functional integration of the default mode network correlates with cognitive outcome at three months after stroke. Human Brain Mapping, 36(2), 577–590.
10. Fair, D. A., Dosenbach, N. U., Church, J. A., Cohen, A. L., Brahmbhatt, S., Miezin, F. M., et al. (2007). Development of distinct control networks through segregation and integration. Proceedings of the National Academy Science of the United States of America, 104(33), 13507–13512.
11. Fair, D. A., Cohen, A. L., Dosenbach, N. U., Church, J. A., Miezin, F. M., Barch, D. M., et al. (2008). The maturing architecture of the brain’s default network. Proceedings of the National Academy Science of the United States of America, 105(10), 4028–4032.
12. Fair, D. A., Nigg, J. T., Iyer, S., Bathula, D., Mills, K. L., Dosenbach, N. U., et al. (2012). Distinct neural signatures detected for ADHD subtypes after controlling for micro-movements in resting state functional connectivity MRI data. Frontiers in Systems Neuroscience, 6, 80.
13. Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). “Mini-mental state”: a practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12(3), 189–198.
14. Greicius, M. D., Srivastava, G., Reiss, A. L., & Menon, V. (2004). Default-mode network activity distinguishes Alzheimer’s disease from healthy aging: evidence from functional MRI. Proceedings of the National Academy Science of the United States of America, 101(13), 4637–4642.
15. Hayasaka, S., & Laurienti, P. J. (2010). Comparison of characteristics between region-and voxel-based network analyses in resting-state fMRI data. NeuroImage, 50(2), 499–508.
16. He, Y., & Evans, A. (2010). Graph theoretical modeling of brain connectivity. Current Opinion in Neurology, 23(4), 341–350.
17. He, Y., Chen, Z., & Evans, A. (2008). Structural insights into aberrant topological patterns of large-scale cortical networks in Alzheimer’s disease. The Journal of Neuroscience, 28(18), 4756–4766.
18. Ilvonen, T.-M., Kujala, T., Tervaniemi, M., Salonen, O., Näätänen, R., & Pekkonen, E. (2001). The processing of sound duration after left hemisphere stroke: event-related potential and behavioral evidence. Psychophysiology, 38(04), 622–628.
19. Ilvonen, T.-M., Kujala, T., Kiesiläinen, A., Salonen, O., Kozou, H., Pekkonen, E., et al. (2003). Auditory discrimination after left-hemisphere stroke a mismatch negativity follow-up study. Stroke, 34(7), 1746–1751.
20. Ilvonen, T., Kujala, T., Kozou, H., Kiesiläinen, A., Salonen, O., Alku, P., et al. (2004). The processing of speech and non-speech sounds in aphasic patients as reflected by the mismatch negativity (MMN). Neuroscience Letters, 366(3), 235–240.
21. Lecumberri, M. G., & Cooke, M. (2006). Effect of masker type on native and non-native consonant perception in noise. Journal of the Acoustical Society of America, 119(4), 2445–2454.
22. Li, X., Liang, Y., Chen, Y., Zhang, J., Wei, D., Chen, K., et al. (2015). Disrupted frontoparietal network mediates white matter structure dysfunction associated with cognitive decline in hypertension patients. Journal of Neuroscience, 35(27), 10015–10024.
23. Lin, C.-J., Tu, P.-C., Chern, C.-M., Hsiao, F.-J., Chang, F.-C., Cheng, H.-L., et al. (2014). Connectivity features for identifying cognitive impairment in presymptomatic carotid stenosis. PloS One, 9, e85441.
24. Liu, J., Zhao, L., Li, G., Xiong, S., Nan, J., Li, J., et al. (2012). Hierarchical alteration of brain structural and functional networks in female migraine sufferers. PloS One, 7(12), e51250.
25. Liu, J., Zhao, L., Lei, F., Zhang, Y., Yuan, K., Gong, Q., et al. (2015). Disrupted resting‐state functional connectivity and its changing trend in migraine suffers. Human Brain Mapping, 36(5), 1892–1907.
26. Papma, J. M., de Groot, M., de Koning, I., Mattace‐Raso, F. U., van der Lugt, A., Vernooij, M. W., et al. (2014). Cerebral small vessel disease affects white matter microstructure in mild cognitive impairment. Human Brain Mapping, 35(6), 2836–2851.
27. Power, J. D., Fair, D. A., Schlaggar, B. L., & Petersen, S. E. (2010). The development of human functional brain networks. Neuron, 67(5), 735–748.
28. Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2012). Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. NeuroImage, 59(3), 2142–2154.
29. Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: uses and interpretations. NeuroImage, 52(3), 1059–1069.
30. Scott, S. K., & Johnsrude, I. S. (2003). The neuroanatomical and functional organization of speech perception. Trends in Neurosciences, 26(2), 100–107.
31. Sporns, O. (2013). Network attributes for segregation and integration in the human brain. Current Opinion in Neurobiology, 23(2), 162–171.
32. Sun, Y.-w., Zhou, Y., Xu, Q., Qian, L.-j., Tao, J., & Xu, J.-r. (2011). Abnormal functional connectivity in patients with vascular cognitive impairment, no dementia: a resting-state functional magnetic resonance imaging study. Behavioural Brain Research, 223(2), 388–394.
33. Tuladhar, A. M., Snaphaan, L., Shumskaya, E., Rijpkema, M., Fernandez, G., Norris, D. G., et al. (2013). Default mode network connectivity in stroke patients. PloS One, 8, e66556.
34. Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., et al. (2002). Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. NeuroImage, 15(1), 273–289.
35. van den Heuvel, M. P., & Sporns, O. (2011). Rich-club organization of the human connectome. Journal of Neuroscience, 31(44), 15775–15786.
36. Wang, L., Li, Y., Metzak, P., He, Y., & Woodward, T. S. (2010). Age-related changes in topological patterns of large-scale brain functional networks during memory encoding and recognition. NeuroImage, 50(3), 862–872.
37. Wang, J., Zuo, X., Dai, Z., Xia, M., Zhao, Z., Zhao, X., et al. (2013). Disrupted functional brain connectome in individuals at risk for Alzheimer’s disease. Biological Psychiatry, 73(5), 472–481.
38. Warren, J. E., Crinion, J. T., Ralph, M. A. L., & Wise, R. J. (2009). Anterior temporal lobe connectivity correlates with functional outcome after aphasic stroke. Brain, 132, 3428–3442.
39. Warrier, C., Wong, P., Penhune, V., Zatorre, R., Parrish, T., Abrams, D., et al. (2009). Relating structure to function: Heschl’s gyrus and acoustic processing. Journal of Neuroscience, 29(1), 61–69.
40. Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of ‘small-world’ networks. Nature, 393(6684), 440–442.
41. Yao, Z., Zhang, Y., Lin, L., Zhou, Y., Xu, C., & Jiang, T. (2010). Abnormal cortical networks in mild cognitive impairment and Alzheimer’s disease. PLoS Computational Biology, 6(11), e1001006.
42. Zalesky, A., Fornito, A., & Bullmore, E. T. (2010). Network-based statistic: identifying differences in brain networks. NeuroImage, 53(4), 1197–1207.