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Siyah Mansoory, Meysam, Chehreh, Ava, Khoshgard, Karim, Rashidi, Iraj, Ebrahiminia, Ali. (1401). Effective Connectivity within the Papez Circuit in the Multiple Sclerosis Patients: A Comparative Study Using Resting-State fMRI. سامانه مدیریت نشریات علمی, 12(2), 149-160. doi: 10.31661/jbpe.v0i0.2003-1090
Meysam Siyah Mansoory; Ava Chehreh; Karim Khoshgard; Iraj Rashidi; Ali Ebrahiminia. "Effective Connectivity within the Papez Circuit in the Multiple Sclerosis Patients: A Comparative Study Using Resting-State fMRI". سامانه مدیریت نشریات علمی, 12, 2, 1401, 149-160. doi: 10.31661/jbpe.v0i0.2003-1090
Siyah Mansoory, Meysam, Chehreh, Ava, Khoshgard, Karim, Rashidi, Iraj, Ebrahiminia, Ali. (1401). 'Effective Connectivity within the Papez Circuit in the Multiple Sclerosis Patients: A Comparative Study Using Resting-State fMRI', سامانه مدیریت نشریات علمی, 12(2), pp. 149-160. doi: 10.31661/jbpe.v0i0.2003-1090
Siyah Mansoory, Meysam, Chehreh, Ava, Khoshgard, Karim, Rashidi, Iraj, Ebrahiminia, Ali. Effective Connectivity within the Papez Circuit in the Multiple Sclerosis Patients: A Comparative Study Using Resting-State fMRI. سامانه مدیریت نشریات علمی, 1401; 12(2): 149-160. doi: 10.31661/jbpe.v0i0.2003-1090

Effective Connectivity within the Papez Circuit in the Multiple Sclerosis Patients: A Comparative Study Using Resting-State fMRI

Journal of Biomedical Physics and Engineering
مقاله 6، دوره 12، شماره 2، خرداد و تیر 2022، صفحه 149-160    اصل مقاله (1.11 M)
نوع مقاله: Original Research
شناسه دیجیتال (DOI): 10.31661/jbpe.v0i0.2003-1090
نویسندگان
Meysam Siyah Mansoory1؛ Ava Chehreh2؛ Karim Khoshgard* 3؛ Iraj Rashidi4؛ Ali Ebrahiminia5
1PhD, Department of Biomedical Engineering, School of Medicine, Kermanshah University of Medical Sciences, Kermanshah, Iran
2MSc Student, Student Research Committee, School of Medicine, Kermanshah University of Medical Sciences, Kermanshah, Iran
3PhD, Department of Medical Physics, School of Medicine, Kermanshah University of Medical Sciences, Kermanshah, Iran
4PhD, Department of Anatomy, School of Medicine, Kermanshah University of Medical Sciences, Kermanshah, Iran
5PhD, Department of Biochemistry & Biophysics, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran
چکیده
Background: Multiple sclerosis (MS) disease causes structural and functional damage to brain. Structural imaging of the MS-induced damage cannot adequately describe the functional impairment of the brain in MS patients. Therefore, it seems that advanced functional imaging analysis such as functional magnetic resonance imaging (fMRI) data is needed for better management of this disease.
Objective: The aim of present study was to evaluate the effective connectivity within the Papez circuit in MS patients using resting-state fMRI.
Material and Methods: In this cross-sectional analytical study, 22 healthy individuals and 24 patients with MS underwent resting-state fMRI. After pre-processing of the obtained data, the time series of Cingulate gyrus (CG), Para hippocampus gyrus (PHG), anterior thalamic nuclei (ATN), Mammillary body (MB), and Hippocampus (HPC) were extracted as the main Papez circuit components. The obtained time series were statistically analyzed as an input of the dynamic causal model in order to evaluate the effective connectivity in the Papez circuit.
Results: The power of effective connectivity between each pair of tested nodes in Papez circuit was significantly lower in MS patients than healthy subjects. Also, the effective connectivity level of MS patients in direction of HPC→ATN was higher in men than women. In addition, effective self-connection in CG→CG and MB→MB regions in healthy subjects were higher in women than them in men.
Conclusion: The present study reveals significant difference in effective connectivity of the Papez nodes in MS patients than control group, which can be exploited to diagnosis and predict or evaluate the treatment response of these patients.
کلیدواژه‌ها
Functional Neuroimaging؛ Magnetic Resonance Imaging؛ Multiple Sclerosis؛ Brain؛ Effective Connectivity
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مراجع
  1. Staffen W, Mair A, Zauner H, Unterrainer J, et al. Cognitive function and fMRI in patients with multiple sclerosis: evidence for compensatory cortical activation during an attention task. Brain. 2002;125(6):1275-82. doi: 10.1093/brain/awf125. PubMed PMID: 12023316.
  2. Moore NM. Physical Symptoms and Psychological Distress in Multiple Sclerosis. Chester, Pennsylvania, United States: Widener University; 2018.
  3. Bonavita S, Gallo A, Sacco R, Corte MD, et al. Distributed changes in default-mode resting-state connectivity in multiple sclerosis. Mult Scler. 2011;17(4):411-22. doi: 10.1177/1352458510394609. PubMed PMID: 21239414.
  4. Dobryakova E, Costa SL, Wylie GR, DeLuca J, Genova HM. Altered effective connectivity during a processing speed task in individuals with multiple sclerosis. J Int Neuropsychol Soc. 2016;22(2):216. doi: 10.1017/S1355617715001034. PubMed PMID: 26888618.
  5. Friston KJ. Functional and effective connectivity in neuroimaging: a synthesis. Human Brain Mapping. 1994;2(1-2):56-78. doi: 10.1002/hbm.460020107.
  6. Hawellek DJ, Hipp JF, Lewis CM, Corbetta M, Engel AK. Increased functional connectivity indicates the severity of cognitive impairment in multiple sclerosis. Proc Natl Acad Sci U S A. 2011;108(47):19066-71. doi: 10.1073/pnas.1110024108. PubMed PMID: 22065778. PubMed PMCID: PMC3223469.
  7. Lowe MJ, Phillips MD, Lurito JT, Mattson D, et al. Multiple sclerosis: low-frequency temporal blood oxygen level–dependent fluctuations indicate reduced functional connectivity—initial results. Radiology. 2002;224(1):184-92. doi: 10.1148/radiol.2241011005. PubMed PMID: 12091681.
  8. Rocca MA, Valsasina P, Absinta M, Riccitelli G, et al. Default-mode network dysfunction and cognitive impairment in progressive MS. Neurology. 2010;74(16):1252-9. doi: 10.1212/WNL.0b013e3181d9ed91. PubMed PMID: 20404306.
  9. Rao SM, Leo GJ, Bernardin L, Unverzagt F. Cognitive dysfunction in multiple sclerosis: I. Frequency, patterns, and prediction. Neurology. 1991;41(5):685-91. doi: 10.1212/WNL.41.5.685. PubMed PMID: 2027484.
  10. Albo Z, Di Prisco GV, Vertes RP. Multisite Spike-Field Coherence, Theta Rhythmicity, and Information Flow Within Papez’s Circuit. Humana, Totowa, NJ: Springer; 2011. p. 191-213.
  11. Polman CH, Reingold SC, Banwell B, Clanet M, et al. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol. 2011;69(2):292-302. doi: 10.1002/ana.22366. PubMed PMID: 21387374. PubMed PMCID: PMC3084507.
  12. Yan C, Zang Y. DPARSF: a MATLAB toolbox for” pipeline” data analysis of resting-state fMRI. Front Syst Neurosci. 2010;4:13. doi: 10.3389/fnsys.2010.00013. PubMed PMID: 20577591. PubMed PMCID: PMC2889691.
  13. Calhoun V, Adali T, Liu J. A feature-based approach to combine functional MRI, structural MRI and EEG brain imaging data. International Conference of the IEEE Engineering in Medicine and Biology Society. New York, NY, USA: IEEE; 2006. doi: 10.1109/IEMBS.2006.259810.
  14. Friston KJ, Dolan RJ. Computational and dynamic models in neuroimaging. Neuroimage. 2010;52(3):752-65. doi: 10.1016/j.neuroimage.2009.12.068. PubMed PMID: 20036335. PubMed PMCID: PMC2910283.
  15. Biswal B, Zerrin Yetkin F, Haughton VM, Hyde JS. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med. 1995;34(4):537-41. doi: 10.1002/mrm.1910340409. doi: 10.1002/mrm.1910340409. PubMed PMID: 8524021.
  16. Friston KJ, Kahan J, Biswal B, Razi A. A DCM for resting state fMRI. Neuroimage. 2014;94:396-407. doi: 10.1016/j.neuroimage.2013.12.009. PubMed PMID: 24345387. PubMed PMCID: PMC4073651.
  17. Friston K, Penny W. Post hoc Bayesian model selection. Neuroimage. 2011;56(4):2089-99. doi: 10.1016/j.neuroimage.2011.03.062. PubMed PMID: 21459150. PubMed PMCID: PMC3112494.
  18. Razi A, Kahan J, Rees G, Friston KJ. Construct validation of a DCM for resting state fMRI. Neuroimage. 2015;106:1-4. doi: 10.1016/j.neuroimage.2014.11.027. PubMed PMID: 25463471. PubMed PMCID: PMC4295921.
  19. Stephan KE, Harrison LM, Kiebel SJ, David O, et al. Dynamic causal models of neural system dynamics: current state and future extensions. Journal of Biosciences. 2007;32(1):129-44. PubMed PMID: 17426386. PubMed PMCID: PMC2636905. doi: 10.1007/s12038-007-0012-5.
  20. Stephan KE, Penny WD, Daunizeau J, Moran RJ, Friston KJ. Bayesian model selection for group studies. Neuroimage. 2009;46(4):1004-17. doi: 10.1016/j.neuroimage.2009.03.025. PubMed PMID: 19306932. PubMed PMCID: PMC2703732.
  21. Scalfari A, Knappertz V, Cutter G, Goodin DS, et al. Mortality in patients with multiple sclerosis. Neurology. 2013;81(2):184-92. doi: 10.1212/WNL.0b013e31829a3388. PubMed PMID: 23836941. PubMed PMCID: PMC3770174.
  22. Morris G, Berk M. The many roads to mitochondrial dysfunction in neuroimmune and neuropsychiatric disorders. BMC Medicine. 2015;13(1):1-24. doi: 10.1186/s12916-015-0310-y. PubMed PMID: 25889215. PubMed PMCID: PMC4382850.
  23. Denic A, Johnson AJ, Bieber AJ, Warrington AE, et al. The relevance of animal models in multiple sclerosis research. Pathophysiology. 2011;18(1):21-9. PubMed PMID: 20537877. PubMed PMCID: PMC3858209. doi: 10.1016/j.pathophys.2010.04.004.
  24. Kuhlmann T, Remington L, Maruschak B, Owens T, Brück W. Nogo-A is a reliable oligodendroglial marker in adult human and mouse CNS and in demyelinated lesions. Journal of Neuropathology & Experimental Neurology. 2007;66(3):238-46. doi: 10.1097/01.jnen.0000248559.83573.71. PubMed PMID: 17356385.
  25. Geurts JJ, Calabrese M, Fisher E, Rudick RA. Measurement and clinical effect of grey matter pathology in multiple sclerosis. The Lancet Neurology. 2012;11(12):1082-92. doi: 10.1016/S1474-4422(12)70230-2. PubMed PMID: 23153407.
  26. Matsui T, Tamura K, Koyano KW, Takeuchi D, et al. Direct comparison of spontaneous functional connectivity and effective connectivity measured by intracortical microstimulation: an fMRI study in macaque monkeys. Cerebral Cortex. 2011;21(10):2348-56. doi: 10.1093/cercor/bhr019. PubMed PMID: 21368090.
  27. Zhang Y, Gong X, Yin Z, Cui L, Yang J, et al. Association between NRGN gene polymorphism and resting-state hippocampal functional connectivity in schizophrenia. BMC Psychiatry. 2019;19(1):108. doi: 10.1186/s12888-019-2088-5. PubMed PMID: 30953482. PubMed PMCID: PMC6451258.
  28. Rocca MA, Valsasina P, Martinelli V, Misci P, et al. Large-scale neuronal network dysfunction in relapsing-remitting multiple sclerosis. Neurology. 2012;79(14):1449-57. doi: 10.1212/WNL.0b013e31826d5f10. PubMed PMID: 22955126.
  29. Louapre C, Perlbarg V, García-Lorenzo D, et al. Brain networks disconnection in early multiple sclerosis cognitive deficits: an anatomofunctional study. Human Brain Mapping. 2014;35(9):4706-17. doi: 10.1002/hbm.22505. PubMed PMID: 24687771. PubMed PMCID: PMC6869493.
  30. MacDonald AW, Jones JA. Functional imaging in clinical assessment? The rise of neurodiagnostics with fMRI. New York, NY: Oxford Handbook of Personality Assessment: Oxford University Press; 2009. p. 364-74. doi: 10.1093/oxfordhb/9780195366877.013.0019.
  31. Thompson AJ, Banwell BL, Barkhof F, et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. The Lancet Neurology. 2018;17(2):162-73. doi: 10.1016/S1474-4422(17)30470-2. PubMed PMID: 29275977.
  32. Katdare A, Ursekar M. Systematic imaging review: multiple sclerosis. Annals of Indian Academy of Neurology. 2015;18(Suppl 1):S24-9. doi: 10.4103/0972-2327.164821. PubMed PMID: 26538845. PubMed PMCID: PMC4604694.
  33. Elamin M, Bak TH, Doherty CP, Pender N, Abrahams S. Role of Neuropsychology in Neurodegeneration. Switzerland: Springer, Cham; 2016. p. 29-55.
  34. Urbach H, Egger K, Rutkowski K, Nakagawa JM, et al. Bilateral cingulum fiber reductions in temporal lobe epilepsy with unilateral hippocampal sclerosis. European Rournal of Radiology. 2017;94:53-7. doi:10.1016/j.ejrad.2017.07.015.
  35. Davatzikos C, Resnick SM. Sex differences in anatomic measures of interhemispheric connectivity: correlations with cognition in women but not men. J Neurosci. 1999;19(10):4065-72. doi: 10.1523/JNEUROSCI.19-10-04065.1999. PubMed PMID: 10234034. PubMed PMCID: PMC6782697.
  36. Kern KC, Ekstrom AD, Suthana NA, Giesser BS, et al. Fornix damage limits verbal memory functional compensation in multiple sclerosis. Neuroimage. 2012;59(3):2932-40. doi: 10.1016/j.neuroimage.2011.09.071. PubMed PMID: 22001266.
  37. Pagani E, Rocca MA, Gallo A, Rovaris M, et al. Regional brain atrophy evolves differently in patients with multiple sclerosis according to clinical phenotype. American Journal of Neuroradiology. 2005;26(2):341-6. PubMed PMID: 15709132.
  38. White AT, Lee JN, Light AR, Light KC. Brain activation in multiple sclerosis: a BOLD fMRI study of the effects of fatiguing hand exercise. Multiple Sclerosis Journal. 2009;15(5):580-6. doi: 10.1177/1352458508100034. PubMed PMID: 19299441.
  39. Geurts JJ, Bö L, Roosendaal SD, Hazes T, et al, Huitinga I, Van Der Valk P. Extensive hippocampal demyelination in multiple sclerosis. Journal of Neuropathology & Experimental Neurology. 2007;66(9):819-27. doi: 10.1097/nen.0b013e3181461f54.
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