リケラボ論文検索は、全国の大学リポジトリにある学位論文・教授論文を一括検索できる論文検索サービスです。

リケラボ 全国の大学リポジトリにある学位論文・教授論文を一括検索するならリケラボ論文検索大学・研究所にある論文を検索できる

リケラボ 全国の大学リポジトリにある学位論文・教授論文を一括検索するならリケラボ論文検索大学・研究所にある論文を検索できる

大学・研究所にある論文を検索できる 「Psychological resilience is correlated with dynamic changes in functional connectivity within the default mode network during a cognitive task」の論文概要。リケラボ論文検索は、全国の大学リポジトリにある学位論文・教授論文を一括検索できる論文検索サービスです。

コピーが完了しました

URLをコピーしました

論文の公開元へ論文の公開元へ
書き出し

Psychological resilience is correlated with dynamic changes in functional connectivity within the default mode network during a cognitive task

Miyagi, Takashi 京都大学 DOI:10.14989/doctor.k23069

2021.03.23

概要

【背景】ストレスに対するヒトの反応は、うつ病や心的外傷後ストレス障害(PTSD)などの発症から無症状まで幅広い。レジリエンスは負荷やストレスを跳ね返す個人特性であり、関連する脳領域やネットワークの報告がある。機能的結合性(FC)は異なる脳領域間の時系列データの相関で定義され、ネットワーク内の領域間の機能的なつながりを推定できる。FC とレジリエンスについて、安静時の機能的 MRI(fMRI)では、低レジリエンス群である PTSD 患者は健常者よりデフォルトモードネットワーク(DMN)内の FC が低かった、健常者では DMN のFC とレジリエンスに負の相関があった、と報告されているが、レジリエンスは動的なプロセスにおける特性であることから、安静時だけでなく課題時の動的変化に本質的な面が反映されている可能性がある。また、レジリエンス研究の多くで情動課題が用いられているが、レジリエンスの概念は情動面だけでなく認知的な側面を含み、うつ病や PTSD の患者で注意障害を認めることや、レジリエンスと注意機能に正の相関の報告もあることから、本研究では安静時および注意課題時の DMN の FC 変化とレジリエンスが相関するという仮説を立てた。

【方法】89 名の健常被験者を対象に、レジリエンスを Connor-Davidson Resilience Scale(CD-RISC)で測定し、安静時とオドボール課題が連続する fMRI 撮像を実施した。安静時(6 分)と課題時(6 分)をそれぞれ前半と後半に分け、課題前半と課題後半の成績の指標(反応時間、変動係数、正答率)を計算し、DMN を構成する関心領域間の FC を安静時後半、課題前半、課題後半の各時間帯で算出した。課題の成績の指標と CD-RISC の相関をみた。また、安静時後半から課題前半(スイッチング)および課題前半から課題後半(サステイニング)の FC変化を算出し、その FC 変化と CD-RISC の相関を計算した。

【結果】課題前半と後半の成績の各指標に有意差はなかった。前半や後半の成績、前半と後半の成績の差や比は、いずれも CD-RISC と有意な相関はなかった。被験者全体では、DMN 内の FC は、スイッチングで増加し、サステイニングで減少した。FC 変化と CD-RISC の相関は、特に脳梁膨大後部/後部帯状皮質と海馬傍皮質を結ぶ FC について、スイッチング時の増加と CD-RISC に負の相関を認めた。

【考察】全体では、DMN 内の FC は安静時後半から課題前半にかけて増加していた。DMN は当初課題時に不活化される領域として同定されたが、その後課題負荷が小さい場合には活動が持続したという報告や FC が増加したという報告があり、今回の課題も正答率が高かったことから、これらの報告と矛盾しない。課題前半から後半にかけての FC 減少は、注意課題の前と後で DMN の活動が低下したという報告があり、「精神的疲労」を反映している可能性がある。DMN 内の FC のスイッチング時の増加と CD-RISC の負の相関から、レジリエンスが高い被験者では、認知負荷時の DMN の FC の恒常性が高いことが示唆された。特に、脳梁膨大後部/後部帯状皮質と海馬傍皮質を結ぶ FC は、うつ病に関する先行研究で寛解した患者群で悲哀気分を誘発する課題で健常群より増加しており、患者群で日常生活の悲哀気分や反芻が強いほど高いと報告された部位と同じであったことから、この FC の増加はレジリエンスの低い健常者とうつ病患者に共通したマーカーの可能性がある。認知負荷時の DMN の FC 変化がレジリエンスの新たなバイオマーカーとなることが示唆された。

この論文で使われている画像

参考文献

1. Southwick, S. M. & Charney, D. S. The science of resilience: Implications for the prevention and treatment of depression. Science 338, 79–82. https://doi.org/10.1126/science.1222942 (2012).

2. American Psychological Association. Building your resilience. http://www.apa.org/topics/resilience (2020).

3. Dedovic, K., D’Aguiar, C. & Pruessner, J. C. What stress does to your brain: A review of neuroimaging studies. Can. J. Psychiatry 54, 6–15. https://doi.org/10.1177/070674370905400104 (2009).

4. Bremner, J. D. Neuroimaging in posttraumatic stress disorder and other stress-related disorders. Neuroimaging Clin. N. Am. 17, 523–538. https://doi.org/10.1016/j.nic.2007.07.003 (2007) (ix).

5. Jovanovic, T. & Ressler, K. J. How the neurocircuitry and genetics of fear inhibition may inform our understanding of PTSD. Am. J. Psychiatry 167, 648–662. https://doi.org/10.1176/appi.ajp.2009.09071074 (2010).

6. Menon, V. & Uddin, L. Q. Saliency, switching, attention and control: A network model of insula function. Brain Struct. Funct. 214, 655–667. https://doi.org/10.1007/s00429-010-0262-0 (2010).

7. Aertsen, A. M., Gerstein, G. L., Habib, M. K. & Palm, G. Dynamics of neuronal firing correlation: Modulation of “effective connectivity”. J. Neurophysiol. 61, 900–917. https://doi.org/10.1152/jn.1989.61.5.900 (1989).

8. Friston, K. J., Frith, C. D., Liddle, P. F. & Frackowiak, R. S. Functional connectivity: The principal-component analysis of large (PET) data sets. J. Cereb. Blood Flow Metab. 13, 5–14. https://doi.org/10.1038/jcbfm.1993.4 (1993).

9. Raichle, M. E. et al. A default mode of brain function. Proc. Natl. Acad. Sci. USA 98, 676–682. https://doi.org/10.1073/pnas.98.2.676 (2001).

10. Greicius, M. D., Krasnow, B., Reiss, A. L. & Menon, V. Functional connectivity in the resting brain: A network analysis of the default mode hypothesis. Proc. Natl. Acad. Sci. USA 100, 253–258. https://doi.org/10.1073/pnas.0135058100 (2003).

11. Buckner, R. L., Andrews-Hanna, J. R. & Schacter, D. L. The brain’s default network: Anatomy, function, and relevance to disease. Ann. N Y Acad. Sci. 1124, 1–38. https://doi.org/10.1196/annals.1440.011 (2008).

12. Andrews-Hanna, J. R., Reidler, J. S., Huang, C. & Buckner, R. L. Evidence for the default network’s role in spontaneous cognition. J. Neurophysiol. 104, 322–335. https://doi.org/10.1152/jn.00830.2009 (2010).

13. Doucet, G. et al. Patterns of hemodynamic low-frequency oscillations in the brain are modulated by the nature of free thought during rest. NeuroImage 59, 3194–3200. https://doi.org/10.1016/j.neuroimage.2011.11.059 (2012).

14. Andrews-Hanna, J. R., Reidler, J. S., Sepulcre, J., Poulin, R. & Buckner, R. L. Functional-anatomic fractionation of the brain’s default network. Neuron 65, 550–562. https://doi.org/10.1016/j.neuron.2010.02.005 (2010).

15. Doucet, G. et al. Brain activity at rest: A multiscale hierarchical functional organization. J. Neurophysiol. 105, 2753–2763. https:// doi.org/10.1152/jn.00895.2010 (2011).

16. Bluhm, R. L. et al. Alterations in default network connectivity in posttraumatic stress disorder related to early-life trauma. J. Psychiatry Neurosci. 34, 187–194 (2009).

17. Hemington, K. S. et al. Patients with chronic pain exhibit a complex relationship triad between pain, resilience, and within-and cross-network functional connectivity of the default mode network. Pain 159, 1621–1630. https://doi.org/10.1097/j.pain.00000 00000001252 (2018).

18. Miller, D. R. et al. Default mode network subsystems are differentially disrupted in posttraumatic stress disorder. Biol. Psychiatry Cogn. Neurosci. Neuroimaging 2, 363–371. https://doi.org/10.1016/j.bpsc.2016.12.006 (2017).

19. Hutchison, R. M. et al. Dynamic functional connectivity: Promise, issues, and interpretations. NeuroImage 80, 360–378. https:// doi.org/10.1016/j.neuroimage.2013.05.079 (2013).

20. Shirer, W. R., Ryali, S., Rykhlevskaia, E., Menon, V. & Greicius, M. D. Decoding subject-driven cognitive states with whole-brain connectivity patterns. Cereb. Cortex 22, 158–165. https://doi.org/10.1093/cercor/bhr099 (2012).

21. Schafer, J. et al. Is trait resilience characterized by specific patterns of attentional bias to emotional stimuli and attentional control?. J. Behav. Ther. Exp. Psychiatry 48, 133–139. https://doi.org/10.1016/j.jbtep.2015.03.010 (2015).

22. Vasterling, J. J. et al. Attention, learning, and memory performances and intellectual resources in Vietnam veterans: PTSD and no disorder comparisons. Neuropsychology 16, 5–14. https://doi.org/10.1037//0894-4105.16.1.5 (2002).

23. van der Meere, J., Borger, N. & van Os, T. Sustained attention in major unipolar depression. Percept. Mot. Skills 104, 1350–1354. https://doi.org/10.2466/pms.104.4.1350-1354 (2007).

24. van der Werff, S. J., van den Berg, S. M., Pannekoek, J. N., Elzinga, B. M. & van der Wee, N. J. Neuroimaging resilience to stress: A review. Front. Behav. Neurosci. 7, 39. https://doi.org/10.3389/fnbeh.2013.00039 (2013).

25. Bennett, C. M. & Miller, M. B. How reliable are the results from functional magnetic resonance imaging?. Ann. N Y Acad. Sci. 1191, 133–155. https://doi.org/10.1111/j.1749-6632.2010.05446.x (2010).

26. Huettel, S. A. & McCarthy, G. What is odd in the oddball task? Prefrontal cortex is activated by dynamic changes in response strategy. Neuropsychologia 42, 379–386. https://doi.org/10.1016/j.neuropsychologia.2003.07.009 (2004).

27. Kim, H. Involvement of the dorsal and ventral attention networks in oddball stimulus processing: A meta-analysis. Hum. Brain Mapp. 35, 2265–2284. https://doi.org/10.1002/hbm.22326 (2014).

28. Kong, F., Wang, X., Hu, S. & Liu, J. Neural correlates of psychological resilience and their relation to life satisfaction in a sample of healthy young adults. NeuroImage 123, 165–172. https://doi.org/10.1016/j.neuroimage.2015.08.020 (2015).

29. Waugh, C. E., Wager, T. D., Fredrickson, B. L., Noll, D. C. & Taylor, S. F. The neural correlates of trait resilience when anticipating and recovering from threat. Soc. Cogn. Affect. Neurosci. 3, 322–332. https://doi.org/10.1093/scan/nsn024 (2008).

30. Sidlauskaite, J. et al. Anticipatory processes in brain state switching—Evidence from a novel cued-switching task implicating default mode and salience networks. NeuroImage 98, 359–365. https://doi.org/10.1016/j.neuroimage.2014.05.010 (2014).

31. Connor, K. M. & Davidson, J. R. Development of a new resilience scale: The Connor-Davidson Resilience Scale (CD-RISC). Depress. Anxiety 18, 76–82. https://doi.org/10.1002/da.10113 (2003).

32. Ito M. N. S., Shirai, A. & Kim, Y. Cross-cultural validity of the ConnorDavidson Scale: Data from Japanese population. Poster presented at 25th Annual Meeting, International Society of Traumatic Stress Studies (ISTSS), Atlanta, GA, November 2009. (2009).

33. Whitfield-Gabrieli, S. & Nieto-Castanon, A. Conn: A functional connectivity toolbox for correlated and anticorrelated brain networks. Brain Connect. 2, 125–141. https://doi.org/10.1089/brain.2012.0073 (2012).

34. Kucyi, A. & Davis, K. D. Dynamic functional connectivity of the default mode network tracks daydreaming. NeuroImage 100, 471–480. https://doi.org/10.1016/j.neuroimage.2014.06.044 (2014).

35. Figley, C. R., Asem, J. S., Levenbaum, E. L. & Courtney, S. M. Effects of body mass index and body fat percent on default mode, executive control, and salience network structure and function. Front. Neurosci. 10, 234. https://doi.org/10.3389/fnins.2016.00234 (2016).

36. Zhang, W. et al. Acute stress alters the “default” brain processing. NeuroImage 189, 870–877. https://doi.org/10.1016/j.neuroimage.2019.01.063 (2019).

37. Sripada, R. K. et al. Neural dysregulation in posttraumatic stress disorder: Evidence for disrupted equilibrium between salience and default mode brain networks. Psychosom. Med. 74, 904–911. https://doi.org/10.1097/PSY.0b013e318273bf33 (2012).

38. Greicius, M. D. & Menon, V. Default-mode activity during a passive sensory task: Uncoupled from deactivation but impacting activation. J. Cogn. Neurosci. 16, 1484–1492. https://doi.org/10.1162/0898929042568532 (2004).

39. Hampson, M., Driesen, N. R., Skudlarski, P., Gore, J. C. & Constable, R. T. Brain connectivity related to working memory performance. J. Neurosci. 26, 13338–13343. https://doi.org/10.1523/JNEUROSCI.3408-06.2006 (2006).

40. Fransson, P. & Marrelec, G. The precuneus/posterior cingulate cortex plays a pivotal role in the default mode network: Evidence from a partial correlation network analysis. NeuroImage 42, 1178–1184. https://doi.org/10.1016/j.neuroimage.2008.05.059 (2008).

41. Bluhm, R. L. et al. Default network connectivity during a working memory task. Hum. Brain Mapp. 32, 1029–1035. https://doi. org/10.1002/hbm.21090 (2011).

42. Goparaju, B., Rana, K. D., Calabro, F. J. & Vaina, L. M. A computational study of whole-brain connectivity in resting state and task fMRI. Med. Sci. Monit. 20, 1024–1042. https://doi.org/10.12659/MSM.891142 (2014).

43. Kiehl, K. A., Laurens, K. R., Duty, T. L., Forster, B. B. & Liddle, P. F. Neural sources involved in auditory target detection and novelty processing: an event-related fMRI study. Psychophysiology 38, 133–142 (2001).

44. Gui, D. et al. Resting spontaneous activity in the default mode network predicts performance decline during prolonged attention workload. NeuroImage 120, 323–330. https://doi.org/10.1016/j.neuroimage.2015.07.030 (2015).

45. Hahn, B., Ross, T. J. & Stein, E. A. Cingulate activation increases dynamically with response speed under stimulus unpredictability. Cereb. Cortex 17, 1664–1671. https://doi.org/10.1093/cercor/bhl075 (2007).

46. Zamoscik, V., Huffziger, S., Ebner-Priemer, U., Kuehner, C. & Kirsch, P. Increased involvement of the parahippocampal gyri in a sad mood predicts future depressive symptoms. Soc. Cogn. Affect. Neurosci. 9, 2034–2040. https://doi.org/10.1093/scan/nsu006 (2014).

47. Bonanno, G. A. Loss, trauma, and human resilience: Have we underestimated the human capacity to thrive after extremely aversive events?. Am. Psychol. 59, 20–28. https://doi.org/10.1037/0003-066X.59.1.20 (2004).

48. Pietrzak, R. H. et al. Psychosocial buffers of traumatic stress, depressive symptoms, and psychosocial difficulties in veterans of Operations Enduring Freedom and Iraqi Freedom: The role of resilience, unit support, and postdeployment social support. J. Affect. Disord. 20, 188–192. https://doi.org/10.1016/j.jad.2009.04.015 (2010).

49. Cerella, J. Information processing rates in the elderly. Psychol. Bull. 98, 67–83 (1985).

50. Matsuoka, K., Uno, M., Kasai, K., Koyama, K. & Kim, Y. Estimation of premorbid IQ in individuals with Alzheimer’s disease using Japanese ideographic script (Kanji) compound words: Japanese version of National Adult Reading Test. Psychiatry Clin. Neurosci. 60, 332–339. https://doi.org/10.1111/j.1440-1819.2006.01510.x (2006).

51. Oldfield, R. C. The assessment and analysis of handedness: The Edinburgh inventory. Neuropsychologia 9, 97–113. https://doi. org/10.1016/0028-3932(71)90067-4 (1971).

52. Fujiwara, H. et al. Martial arts “Kendo” and the motivation network during attention processing: An fMRI study. Front. Hum. Neurosci. 13, 170. https://doi.org/10.3389/fnhum.2019.00170 (2019).

53. Griffanti, L. et al. ICA-based artefact removal and accelerated fMRI acquisition for improved resting state network imaging. NeuroImage 95, 232–247. https://doi.org/10.1016/j.neuroimage.2014.03.034 (2014).

54. Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L. & Petersen, S. E. Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. NeuroImage 59, 2142–2154. https://doi.org/10.1016/j.neuroimage.2011.10.018 (2012).

55. Nilsonne, G. et al. Intrinsic brain connectivity after partial sleep deprivation in young and older adults: Results from the Stockholm Sleepy Brain study. Sci. Rep. 7, 9422. https://doi.org/10.1038/s41598-017-09744-7 (2017).

56. Zhang, J. T. et al. Decreased functional connectivity between ventral tegmental area and nucleus accumbens in Internet gaming disorder: Evidence from resting state functional magnetic resonance imaging. Behav. Brain Funct. 11, 37. https://doi.org/10.1186/ s12993-015-0082-8 (2015).

57. Habas, C. et al. Distinct cerebellar contributions to intrinsic connectivity networks. J. Neurosci. 29, 8586–8594. https://doi. org/10.1523/JNEUROSCI.1868-09.2009 (2009).

参考文献をもっと見る