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, Volume 77, Issue 3, pp 4065–4079 | Cite as

Aberrant functional connectivity in patients with obstructive sleep apnea-hypopnea syndrome: a resting-state functional MRI study

  • Yu -Ting Liu
  • Hui-Jun Li
  • Ting Chen
  • Ya-Qing Huang
  • Lian Zhang
  • Hui-Xin Zhang
  • Zhi-chun Huang
  • Bin LiuEmail author
  • Ming YangEmail author


The objective of this study was to investigate the change in the default mode network (DMN) in subjects with obstructive sleep apnea-hypopnea syndrome (OSAHS) using resting-state functional connectivity (rsFC). Functional magnetic resonance imaging (rs-fMRI) data were collected from twenty-nine subjects with OSAHS and twenty-six normal controls. The data were analyzed with the rsFC method and were compared between OSAHS subjects and controls. The Z-values of abnormal rsFC in different brain regions were correlated with clinical variables, including the apnea-hypopnea index (AHI), oxygen desaturation index (ODI), Epworth sleepiness scale (ESS), Rey-osterrieth complex figure test (CFT-immediately), CFT-delay, Logical memory test-immediately (LMT-immediately), LMT-delay and Minimum mental state examination (MMSE). The rsFC showed significant increases in the left temporal cortex, right midfrontal cortex, and left precuneus cortex as well as decreases in the bilateral inferior parietal lobule (IPL), left medial prefrontal cortex (MPFC), left superior frontal cortex and right cerebellum in patients with OSAHS. The FC strength in the left precuneus showed a remarkable positive correlation with ODI(p = .032, r = .399)and CFT-delay scores (p = .043, r = .378). We found that the FC strength in the right cerebellum was positively correlated with the CFT-delay scores (p = .017, r = .441). FC strength in the right cerebellum and left IPL demonstrated a remarkable positive correlation with LMT-delay scores (p = .037,r = .389;p = .043 and r = .379, respectively). However, there was a strong negative correlation between the left MPFC region and ESS scores (p = .032, r = −.398). The abnormal rsFC in subjects with OSAHS indicated the compensatory change of brain function, which possibly provides an innovative approach and perspective on understanding the neural mechanism alteration of OSAHS-related cognition.


Default mode network Magnetic resonance imaging Obstructive sleep apnea-hypopnea syndrome Functional connectivity 



This paper was supported by the Clinical Medical Science and Technology Special Project of Jiangsu,China(NO. BL2013029) and was partly supported by the Maternity and Child Care Project, Jiangsu Province,China(F201554), Science and Technology Development Project, Nanjing, China (2015sc511023) and Six Talent Peaks Project in Jiangsu Province (WSN-192),China.


  1. 1.
    (1992) EEG arousals: scoring rules and examples: a preliminary report from the Sleep Disorders Atlas Task Force of the American Sleep Disorders Association. Sleep. 15(2):173–184Google Scholar
  2. 2.
    Archbold KH, Borghesani PR, Mahurin RK, Kapur VK, Landis CA (2009) Neural activation patterns during working memory tasks and OSA disease severity: preliminary findings. J Clin Sleep Med 5(1):21–27Google Scholar
  3. 3.
    Ayalon L, Ancoli-Israel S, Drummond SP (2009) Altered brain activation during response inhibition in obstructive sleep apnea. J Sleep Res 18(2):L204–L208CrossRefGoogle Scholar
  4. 4.
    Ayalon L, Ancoli-lsrael S, Drummond SP (2009) Altered brain activation during response inhibition in obstructive sleep apnea. J Sleep Res 18(2):204–208CrossRefGoogle Scholar
  5. 5.
    Bagai K (2010) Obstructive sleep apnea, stroke, and cardiovascular diseases. Neurologist 16(6):329–339CrossRefGoogle Scholar
  6. 6.
    Buckner RL, Andrewa-Hanna JR, Schacter DL (2008) The brain's default network: anatomy, function, and relevance to disease. AnnNYAcad Sci 1124:1–38CrossRefGoogle Scholar
  7. 7.
    Cavanna AE, Trimble MR (2006) The precuneus: a review of its functional anatomy and behavioural correlates. Brain 129(pt3):564–583CrossRefGoogle Scholar
  8. 8.
    Chao-Gan Y, Yu-Feng Z (2010) DPARSF: a MATLAB toolbox for "pipeline" data analysis of resting-state MRI. Frontiers in systems neuroscience. 4:13Google Scholar
  9. 9.
    Chen T et al (2016) The resting-state functional connectivity of the default mode networks in patients with obstructive sleep apnea-hypopnea syndrome. CNS Neurol Disord Drug TargetsGoogle Scholar
  10. 10.
    Cross RL, Kumar R, Macey PM et al (2008) Neural alterations and depressive symptoms in obstructive sleep apnea patients. Sleep 31(8):1103–1109Google Scholar
  11. 11.
    Dong ZC (2015) Detection of Alzheimer's disease and mild cognitive impairment based on structural volumetric MR images using 3D-DWT and WTA-KSVM trained by PSOTVAC. Biomedical Signal Processing and Control 21:58–73CrossRefGoogle Scholar
  12. 12.
    Emin Akkoyunlu M, Kart L (2013) Brain diffusion changes in obstructive sleep Apnoea syndrome. Respiration 86(5):414–420CrossRefGoogle Scholar
  13. 13.
    Ferini-Strambi L, Baietto C, Di Gioia MR et al (2003) Cognitive dysfunction in patients with obstructive sleep apnea (OSA): partial reversibility after continuous positive airway pressure (CPAP). Brain Res Bull 61(1):87–92CrossRefGoogle Scholar
  14. 14.
    Fletcher PC, Dolan RJ, Shallice T, Frith CD, Frackowiak RS, Friston KJ (1996) Is multivariate analysis of PET data more revealing than the univariate approach? Evidence from a study of episodic memory retrieval. Neuroimage 3(3Pt1):209–215CrossRefGoogle Scholar
  15. 15.
    Fox MD, Raichle ME (2007) Spontaneous fluctuations in brain activity observed with functional magnetic resonance. Nat Rev Neurosci 8(9):700–711CrossRefGoogle Scholar
  16. 16.
    Fox MD, Snyder AZ, Vincent JL, Corbetta M, van Essen DC, Raichle ME (2005) The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci U S A 102(27):9673–9678CrossRefGoogle Scholar
  17. 17.
    Fox MD, Zhang D, Snyder AZ, Raichle ME (2009) The global signal and observed anticorrelated resting state brain networks. J Neurophysiol 101(6):3270–3283CrossRefGoogle Scholar
  18. 18.
    Fransson P (2005) Spontaneous low-frequency BOLD signal fluctuations: an fMRI investigation of the resting-state default mode of brain function hypothesis. Hum Brain Mapp 26(1):15–29CrossRefGoogle Scholar
  19. 19.
    Galea M, Woodward M (2005) Mini-mental state examination (MMSE). Aust J Physiother 51(3):198CrossRefGoogle Scholar
  20. 20.
    Greicius MD, Srivastava G, Reiss AL, Menon V (2004) Default-mode network activity distinguishes Alzheimer’s disease from healthy aging: evidence from functional MRI. Proc Natl Acad Sci U S A 101(13):4637–4642CrossRefGoogle Scholar
  21. 21.
    Gusnard DA, Raichle ME (2001) Searching for a baseline:functional imaging and the resting human brain. Nat Rev Neurosci 2(10):685–694CrossRefGoogle Scholar
  22. 22.
    Ip MS, Lam B, Ng MM, Lam WK, Tsang KW, Lam KS (2002) Obstructive sleep apnea is independently associated with insulin resistance. Am J Respir Crit Care Med 165(5):670–676CrossRefGoogle Scholar
  23. 23.
    Ji G (2016) Preliminary research on abnormal brain detection by wavelet-energy and quantum-behaved PSO. Technol Health Care 24(s2):S641–S649CrossRefGoogle Scholar
  24. 24.
    Johns MW (1991) A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep 14(6):540–545CrossRefGoogle Scholar
  25. 25.
    Joo EY, Jeon S, Kim.ST, Lee.JM, Hong.SB (2013) Localized cortical thinning in patients with obstructive sleep apnea syndrome. Sleep 36(8):1153–1162.CrossRefGoogle Scholar
  26. 26.
    Kim HC, Young T, Matthews CG, Weber SM, Woodward AR, Palta M (1997) Sleep-disordered breathing and neuropsychological deficits: a population-based study. Am J Respir Crit Care Med 156(6):1813–1819CrossRefGoogle Scholar
  27. 27.
    Kumar R, Chavez AS, Macey PM, Woo MA, Yan-Go FL, Harper RM (2012) Altered global and regional brain mean diffusivity in patients with obstructive sleep. J Neurosci Res 90(10):2043–2052CrossRefGoogle Scholar
  28. 28.
    Li HJ, Zhang W, Nie S, Peng DC (2016) Abnormal resting-state functional connectivity within the default mode network subregions in male patients with obstructive sleep apnea. Neuropsychiatr Dis Treat 12:203–212CrossRefGoogle Scholar
  29. 29.
    Liu G (2016) Detection of Alzheimer’s disease by three-dimensional displacement field estimation in structural magnetic resonance imaging. J Alzheimers Dis 50(1):233–248MathSciNetGoogle Scholar
  30. 30.
    Lu S, Yang M (2016) Dual-tree complex wavelet transform and twin support vector machine for pathological brain detection. Applied Science 6(6):169CrossRefGoogle Scholar
  31. 31.
    Lutherer LO, Williams JL (1986) Stimulating fastigial nucleus pressor region elicits patterned respiratory responses. Am J Physiol 250(3Pt2):R418–R426Google Scholar
  32. 32.
    Lutherer LO, Lutherer BC, Dormer KJ, Janssen HF, Barnes CD (1983) Bilateral lesions of the fastigial nucleus prevent the recovery of blood pressure following hypotension induced by hemorrhage or administration of endotoxin. Brain Res 269(2):251–257CrossRefGoogle Scholar
  33. 33.
    Macey PM, Henderson LA, Macey KE (2002) Brain morphology associated with obstructive sleep apnea. Am J Respir Crit Care Med 166(10):1382–1387CrossRefGoogle Scholar
  34. 34.
    Maddock R, Garrett A, Buonocore M (2001) Remembering familiar people: the posterior cingulate cortex and autobiographicalmemory retrieval. Neuroscience 104(3):667–676CrossRefGoogle Scholar
  35. 35.
    Naghavi HR, Nyberg L (2005) Common fronto-parietal activity in attention, memory, and consciousness: shared demands on integration? Conscious Cogn 14(2):390–425CrossRefGoogle Scholar
  36. 36.
    Park JG, Ramar K, Olson EJ et al (2011) Updates on definition, consequences, and management of obstructive sleep apnea. Mayo Clinic Proc 86(6):549–555CrossRefGoogle Scholar
  37. 37.
    Peng B (2016) Image processing methods to elucidate spatial characteristics of retinal microglia after optic nerve transection. Scientific Reports 6:21816CrossRefGoogle Scholar
  38. 38.
    Peng DC, Dai XJ, Gong HH, Li HJ, Nie X, Zhang W (2014) Altered intrinsic regional brain activity in male patients with severe obstructive sleep apnea: a resting-state functional magnetic resonance imaging study. Neuropsychiatr Dis Treat 10:1819–1826Google Scholar
  39. 39.
    Prilipko O, Huynh N, Schwartz S et al (2011) Task positive and default mode networks during a parametric working memory task in obstructive sleep apnea patients and healthy controls. Sleep 34(3):293–301CrossRefGoogle Scholar
  40. 40.
    Punjabi NM (2008) The epidemiology of adult obstructive sleep apnea. Proc Am Thorac Soc 5(2):136–143CrossRefGoogle Scholar
  41. 41.
    Raichle ME (2010) Two views of brain function. Trends Cogn Sci 14(4):180–190CrossRefGoogle Scholar
  42. 42.
    Raichle ME, MacLeod AM, Snyder AZ et al (2001) A default mode of brain function. PNAS 98(2):676–682CrossRefGoogle Scholar
  43. 43.
    Redline S, Budhiraja R, Kapur V et al (2007) The scoring of respiratory events in sleep: reliability and validity. Journal of clinical sleep medicine: JCSM: official publication of the American Academy of Sleep Medicine 3(2):169–200Google Scholar
  44. 44.
    Sarchielli P, Presciutti O, Alberti A et al (2008) A 1H magnetic resonance spectroscopy study in patients with obstructive sleep apnea. Eur J Neurol 15(10):1058–1064CrossRefGoogle Scholar
  45. 45.
    Saunamäki T, Jehkonen M (2007) A review of executive functions in obstructive sleep apnea syndrome. Acta Neurol Scand 115(1):1–11CrossRefGoogle Scholar
  46. 46.
    Seneviratne U, Puvanendran K (2004) Excessive daytime sleepiness in obstructive sleep apnea: prevalence, severity, and predictors. Sleep Med 5(4):339–343CrossRefGoogle Scholar
  47. 47.
    Shen Y, Cao X, Tan T, Shan C, Wang Y, Pan J, He H, Yuan TF (2016) 10-Hz repetitive transcranial magnetic stimulation of the left dorsolateral prefrontal cortex reduces heroin cue craving in long-term addicts. Biol Psychiatry 80(3):e13–e14CrossRefGoogle Scholar
  48. 48.
    Shin MS, Park SY, Park SR, Seol SH, Kwon JS (2006) Clinical and empirical applications of the Rey-Osterrieth complex figure test. Nat Protoc 1(2):892–899CrossRefGoogle Scholar
  49. 49.
    Song XW, Dong ZY, Long XY et al (2011) REST: a toolkit for resting-state functional magnetic resonance imaging data processing. PLoS One 6(9):e25031CrossRefGoogle Scholar
  50. 50.
    Squire LR, Stark CE, Clark RE (2004) The medial temporal lobe. Annu Rev Neurosci 27:279–306CrossRefGoogle Scholar
  51. 51.
    Sun Y (2016) A multilayer perceptron based smart pathological brain detection system by fractional Fourier entropy. J Med Syst 40(7):173CrossRefGoogle Scholar
  52. 52.
    Supekar K, Uddin LQ, Prater K et al (2010) Development of functional and structural connectivity within the default mode network in young children. NeuroImage 52(1):290–301CrossRefGoogle Scholar
  53. 53.
    Thomas RJ, Rosen BR, Stern CE, Weiss JW, Kwong KK (2005) Functional imaging of working memory in obstructive sleep-disordered breathing. J Appl Physiol 98(6):2226–2234CrossRefGoogle Scholar
  54. 54.
    Tregear S, Reston J, Schoelles K, Phillips B (2009) Obstructive sleep apnea and risk of motor vehicle crash: systematic review and meta-analysis. J Clin Sleep Med 5(6):573–581Google Scholar
  55. 55.
    Uddin LQ et al (2009) Functional connectivity of default mode network components: correlation, anticorrelation, and causality. Hum Brain Mapp 30(2):625–637CrossRefGoogle Scholar
  56. 56.
    Wang Y, Shen Y, Cao X, Shan C, Pan J, He H, Ma Y, Yuan TF (2016) Transcranial direct current stimulation of the frontal-parietal-temporal area attenuates cue-induced craving for heroin. J Psychiatr Res 79:1–3CrossRefGoogle Scholar
  57. 57.
    Wilson CR, Gaffan D, Browning PG, Baxter MG (2010) Functional localiza-tion within the prefrontal cortex: missing the forest for the trees? Trends Neurosci 33(12):533–540CrossRefGoogle Scholar
  58. 58.
    Xu F, Frazier DT (1997) Respiratory-related neurons of the fastigial nucleus in response to chemical and mechanical challenges. Journal of applied physiology (Bethesda, Md.: 1985) 82(4):1177–1184CrossRefGoogle Scholar
  59. 59.
    Yeon JE, Suk TW, Joo LM et al (2010) Reduced brain gray matter concentration in patients with obstructive sleep apnea syndrome. Sleep 33(2):235–241CrossRefGoogle Scholar
  60. 60.
    Yuan TF (2015) Detection of subjects and brain regions related to Alzheimer’s disease using 3D MRI scans based on eigenbrain and machine learning. Front Comput Neurosci 9(66):1–15Google Scholar
  61. 61.
    Zang YF, Jiang TZ, Lu YL et al (2004) Regional homogeneity approach to fMRI data analysis. Neuro Image 22(1):394–400Google Scholar
  62. 62.
    Zhang Q, Wang D, Qin W et al (2013) Altered resting-state brain activity in obstructive sleep apnea. Sleep 36(5):651–659CrossRefGoogle Scholar
  63. 63.
    Zhao XH, Wang PJ, Li CB et al (2007) Altered default mode network activity in patient with anxiety disorders:all fMRI study. Eur J Radiol 63(3):373–378CrossRefGoogle Scholar
  64. 64.
    Zhou XX, Wu L (2016) Comparison of machine learning methods for stationary wavelet entropy-based multiple sclerosis detection: decision tree, k-nearest neighbors, and support vector machine. SIMULATION 92(9):861–871CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Yu -Ting Liu
    • 2
  • Hui-Jun Li
    • 3
  • Ting Chen
    • 1
  • Ya-Qing Huang
    • 1
  • Lian Zhang
    • 4
  • Hui-Xin Zhang
    • 1
  • Zhi-chun Huang
    • 4
  • Bin Liu
    • 1
    Email author
  • Ming Yang
    • 3
    Email author
  1. 1.Department of RadiologyZhongda Hospital, SEU (Southeast University)NanjingChina
  2. 2.Medical School of SEUNanjingChina
  3. 3.Department of Radiology, Children’s HospitalNanjing Medical UniversityNanjingChina
  4. 4.Department of Otolaryngology-Head and Neck SurgeryZhongda Hospital, SEUNanjingChina

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