1. Lee, S, Zhao, X, Hatch, M, Chun, S, Chang, E. Central neuropathic pain in spinal cord injury. Crit Rev Phys Rehabil Med. 2013;25(3-4):159‐172.
Google Scholar | Crossref | Medline2. Hagen, EM, Rekand, T. Management of neuropathic pain associated with spinal cord injury. Pain Ther. 2015;4(1):51‐65.
Google Scholar | Crossref | Medline3. Athanasiou, A, Terzopoulos, N, Pandria, N, et al. Functional brain connectivity during multiple motor imagery tasks in spinal cord injury. Neural Plast. 2018;2018:16‐21.
Google Scholar | Crossref4. Vuckovic, A, Hasan, MA, Fraser, M, Conway, BA, Nasseroleslami, B, Allan, DB. Dynamic oscillatory signatures of central neuropathic pain in spinal cord injury. J Pain. 2014;15(6):645‐655.
Google Scholar | Crossref | Medline5. Freund, P, Curt, A, Friston, K, Thompson, A. Tracking changes following spinal cord injury: Insights from neuroimaging. Neuroscientist. 2013;19(2):116‐128.
Google Scholar | SAGE Journals | ISI6. Freund, P, Weiskopf, N, Ashburner, J, et al. MRI investigation of the sensorimotor cortex and the corticospinal tract after acute spinal cord injury: A prospective longitudinal study. Lancet Neurol. 2013;12(9):873‐881.
Google Scholar | Crossref | Medline7. Flodin, P, Martinsen, S, Altawil, R, et al. Intrinsic brain connectivity in chronic pain: A resting-state fMRI study in patients with rheumatoid arthritis. Front Hum Neurosci. 2016;10(MAR2016).
Google Scholar | Medline8. Lee, MJ, Park, BY, Cho, S, Kim, ST, Park, H, Chung, CS. Increased connectivity of pain matrix in chronic migraine: A resting-state functional MRI study. J Headache Pain. 2019;20(1).
Google Scholar | Crossref9. Mutso, AA, Petre, B, Huang, L, et al. Reorganization of hippocampal functional connectivity with transition to chronic back pain. J Neurophysiol. 2014;111(5):1065‐1076.
Google Scholar | Crossref | Medline10. Hawasli, AH, Rutlin, J, Roland, JL, et al. Spinal cord injury disrupts resting-state networks in the human brain. J Neurotrauma. 2018;35(6):864‐873.
Google Scholar | Crossref | Medline11. Oni-Orisan, A, Kaushal, M, Li, W, et al. Alterations in cortical sensorimotor connectivity following complete cervical spinal cord injury: A prospective resting-state fMRI study. PLoS One. 2016;11(3):1‐13.
Google Scholar | Crossref12. Hou, J, Xiang, Z, Yan, R, et al. Motor recovery at 6 months after admission is related to structural and functional reorganization of the spine and brain in patients with spinal cord injury. Hum Brain Mapp. 2016;37(6):2195‐2209.
Google Scholar | Crossref | Medline13. Min, Y-S, Chang, Y, Park, JW, et al. Change of brain functional connectivity in patients with spinal cord injury: graph theory based approach. Ann Rehabil Med. 2015;39(3):374‐383.
Google Scholar | Crossref | Medline14. Nickel, MM, Ta Dinh, S, May, ES, et al. Neural oscillations and connectivity characterizing the state of tonic experimental pain in humans. Hum Brain Mapp. 2019(May):1‐13.
Google Scholar15. Ye, Q, Yan, D, Yao, M, Lou, W, Peng, W. Hyperexcitability of cortical oscillations in patients with somatoform pain disorder: resting-state EEG study. Neural Plast. 2019;2019:2687150.
Google Scholar | Crossref | Medline16. De Vico Fallani, F, Astolfi, L, Cincotti, F, et al. Cortical functional connectivity networks in normal and spinal cord injured patients: Evaluation by graph analysis. Hum Brain Mapp. 2007;28(12):1334‐1346.
Google Scholar | Crossref | Medline17. De Vico Fallani, F, Astolfi, L, Cincotti, F, et al. Brain connectivity structure in spinal cord injured: Evaluation by graph analysis. Annu Int Conf IEEE Eng Med Biol - Proc. Published online 2006:988‐991.
Google Scholar | Crossref18. Cramer, SC, Lastra, L, Lacourse, MG, Cohen, MJ. Brain motor system function after chronic, complete spinal cord injury. Brain. 2005;128(12):2941‐2950.
Google Scholar | Crossref | Medline19. Kaushal, M, Oni-orisan, A, Chen, G, et al. Large-scale network analysis of whole-brain resting-state functional connectivity in spinal cord injury: A comparative study. Brain Connect. 2017;7(7):413‐423.
Google Scholar | Crossref | Medline20. Wrigley, PJ, Gustin, SM, Macey, PM, et al. Anatomical changes in human motor cortex and motor pathways following complete thoracic spinal cord injury. Cereb Cortex. 2009;19(1):224‐232.
Google Scholar | Crossref | Medline | ISI21. Hou, QJ, Sun, T, Xiang, Z, Zhang, J, Zhang, Z. Alterations of resting-state regional and network-level neural function after acute spinal cord injury. Neuroscience. 2014;277:446‐454.
Google Scholar | Crossref | Medline22. Rao, JS, Liu, Z, Zhao, C, et al. Longitudinal evaluation of functional connectivity variation in the monkey sensorimotor network induced by spinal cord injury. Acta Physiol. 2016;217(2):164‐173.
Google Scholar | Crossref | Medline23. Kaushal, M, Oni-orisan, A, Chen, G, et al. Evaluation of whole-brain resting-state functional connectivity in spinal cord injury – a large-scale network analysis using network-based statistic. J Neurotrauma. 2016;34(6):1‐16.
Google Scholar | Medline24. Burns, S, Biering-Sørensen, F, Donovan, W, et al. International standards for neurological classification of spinal cord injury, revised 2011. Top Spinal Cord Inj Rehabil. 2012;18(1):85‐99.
Google Scholar | Crossref | Medline25. Lesser, R, Picton, TW. American Electroencephalographic Society Guidelines for Standard Electrode Position Nomenclature. J Clin Neurophysiol. 1991;8(2):200‐202.
Google Scholar | Crossref | Medline26. Frølich, L, Dowding, I. Removal of muscular artifacts in EEG signals: a comparison of linear decomposition methods. Brain Inform. 2018;5(1):13‐22.
Google Scholar | Crossref | Medline27. Dimigen, O . Optimizing the ICA-based removal of ocular EEG artifacts from free viewing experiments. Neuroimage. 2020;207(January 2019):116117.
Google Scholar | Crossref | Medline28. Chaumon, M, Bishop, DVM, Busch, NA. A practical guide to the selection of independent components of the electroencephalogram for artifact correction. J Neurosci Methods. 2015;250:47‐63.
Google Scholar | Crossref | Medline | ISI29. Daut, RL, Cleeland, CS, Flanery, RC. Development of the Wisconsin Brief Pain Questionnaire to assess pain in cancer and other diseases. Pain. 1983;17(2):197‐210.
Google Scholar | Crossref | Medline | ISI30. Lachaux, J, Rodriguez, E, Martinerie, J, Varela, FJ. Measuring phase synchrony in brain signals. 1999;208:1‐15.
Google Scholar31. Jian, W, Chen, M, McFarland, DJ. EEG based zero-phase phase-locking value (PLV) and effects of spatial filtering during actual movement. Brain Res Bull. 2017;130:156‐164.
Google Scholar | Crossref | Medline32. Hamner, B, Leeb, R, Tavella, M, Del, R, Millán, J. Phase-based features for motor imagery brain-computer interfaces. 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society; ; IEEE; 2578‐2581.
Google Scholar33. Bakhshayesh, H, Fitzgibbon, SP, Janani, AS, Grummett, TS, Pope, KJ. Detecting synchrony in EEG: A comparative study of functional connectivity measures. Comput Biol Med. 2019;105:1‐15.
Google Scholar | Crossref | Medline34. Fourier, BA . Hilbert- and wavelet-based signal analysis: are they really different approaches ? J Neurosci Methods. 2004;137:321‐332.
Google Scholar | Crossref | Medline35. Strogatz DJW&, SH . Collective dynamics of ‘small-world’ networks Duncan. Conserv Biol. 2018;32(2):287‐293.
Google Scholar | Medline36. Latora, V, Marchiori, M. Efficient behavior of small-world networks. Phys Rev Lett. 2001;87(19):198701-1–198701-4.
Google Scholar | Crossref | Medline37. Hedges L, V . Distribution Theory for Glass’s Estimator of Effect Size and Related Estimators Author (s): Larry V. Hedges Published by: American Educational Research Association and American Statistical Association Journal of Educational Statis6tiL Key Words: ME. 2014;6(2):107‐128.
Google Scholar38. Gustin, SM, Peck, CC, Cheney, LB, Macey, PM, Murray, GM, Henderson, LA. Pain and plasticity: Is chronic pain always associated with somatosensory cortex activity and reorganization? J Neurosci. 2012;32(43):14874‐14884.
Google Scholar | Crossref | Medline39. Henderson, LA, Gustin, SM, Macey, PM, Wrigley, PJ, Siddall, PJ. Functional reorganization of the brain in humans following spinal cord injury: Evidence for underlying changes in cortical anatomy. J Neurosci. 2011;31(7):2630‐2637.
Google Scholar | Crossref | Medline40. Hemington, KS, Wu, Q, Kucyi, A, Inman, RD, Davis, KD. Abnormal cross-network functional connectivity in chronic pain and its association with clinical symptoms. Brain Struct Funct. 2016;221(8):4203‐4219.
Google Scholar | Crossref | Medline41. Seeley, WW, Menon, V, Schatzberg, AF, et al. Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci. 2007;27(9):2349‐2356.
Google Scholar | Crossref | Medline | ISI42. Di, X, Biswal, BB. Dynamic brain functional connectivity modulated by resting-state networks. Brain Struct Funct. 2015;220(1):37‐46.
Google Scholar | Crossref | Medline43. Sridharan, D, Levitin, DJ, Menon, V. A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks. Pnas. 2008;105(34):12569‐12574.
Google Scholar | Crossref | Medline | ISI44. Sidlauskaite, J, Wiersema, JR, Roeyers, H, et al. Anticipatory processes in brain state switching—Evidence from a novel cued-switching task implicating default mode and salience networks. Neuroimage. Published online 2014.
Google Scholar | Crossref | Medline45. Marek, S, Dosenbach, NUF. Control networks of the frontal lobes. Front Lobes. 2019;163:333‐347.
Google Scholar | Crossref46. Gogolla, N . The insular cortex. Curr Biol. 2017;27(12):R580‐R586.
Google Scholar | Crossref | Medline47. Heilbronner, SR, Hayden, BY. Dorsal anterior cingulate cortex: A bottom-up view. Annu Rev Neurosci. 2016;39:149‐170.
Google Scholar | Crossref | Medline48. Ettinger- H, V, Södermark, M, Graven-nielsen, T, Sjörs, A, Engström, M, Gerdle, B. Chronic widespread pain patients show disrupted cortical connectivity in default mode and salience networks, modulated by pain sensitivity. J Pain Res. 2019;12:1743‐1755.
Google Scholar | Crossref | Medline49. Yi, W, Qiu, S, Wang, K, et al. Evaluation of EEG oscillatory patterns and cognitive process during simple and compound limb motor imagery. PLoS One. 2014;9(12):1‐19.
Google Scholar | Crossref50. Cole, MW, Pathak, S, Schneider, W. Identifying the brain’s most globally connected regions. Neuroimage. 2010;49(4):3132‐3148.
Google Scholar | Crossref | Medline51. Power, JD, Schlaggar, BL, Lessov-Schlaggar, CNPS. Evidence for hubs in human functional brain networks. Neuron. 2013;79(4):798‐813.
Google Scholar | Crossref | Medline52. Marek, S, Hwang, K, Foran, W, Hallquist, MN, Luna, B. The Contribution of Network Organization and Integration to the Development of Cognitive Control. PLoS Biol.