- P-ISSN1226-9654
- E-ISSN2733-466X
- KCI
우울한 노인과 정상 노인의 휴지기 기능적 두뇌 네트워크 차이: 현저성 네트워크 연결성과 전체 뇌 네트워크 효율성을 중심으로
Differences in Resting-State Functional Network between Depressed and Non-Depressed Elderlies
김호영 (전북대학교)
초록
휴지기 fMRI 연구에서 현저성 네트워크는 우울 증상과 관련된 정서 조절 및 동기화된 행동과정을 설명할 수 있는 네트워크로 증상의 신경학적인 이해를 돕고, 치료 효과에도 중요한 네트워크로 알려져 있으나, 우울한 노인을 대상으로 한 연구는 부족한 상태이다. 본 연구는 노인우울 집단 18명과, 우울집단과 연령, 성별, 교육 수준이 동등한 비우울 비교집단 18명의 휴지기 상태에서 뇌의 기능적 네트워크를 네트워크 기반 통계(NBS)를 사용하여 비교하였다. 이를 위하여 우울과 관련된 현저성 네트워크 내의 영역들간 연결성(intranetwork connectivity)과 현저성 네트워크, 집행통제 네트워크, 그리고 기본 모드 네트워크 간 연결성(internetwork connectivity)에서 집단 간 차이를 확인하였다. 그 결과, 비우울 비교집단에 비해 우울집단은 현저성 네트워크 내의 미상핵과 편도체간의 연결성이 유의미하게 낮은 것으로 나타났다. 네트워크들 간의 연결성 분석 결과에서는 비우울 비교집단에 비해 우울집단은 집행 통제 네트워크의 좌측 전전두피질과 현저성 네트워크의 좌측 섬엽과의 연결성은 유의하게 더 높았고, 좌측 전전두피질과 기본 모드 네트워크의 양측 두정피질과의 연결성은 유의하게 낮게 나타났다. 또한, 대뇌의 전체 네트워크들을 포함하여 네트워크 효율성의 차이를 확인하기 위해 그래프 이론에 기반하여 분석하였다. 작은 세상 네트워크에서 우울 집단이 유의미하게 낮은 것으로 나타났으며, 이를 이루고 있는 네트워크 통합 지표인 평균 최단경로 길이는 집단 간 차이가 없었으나 네트워크 분리 지표인 군집 계수는 현저성 네트워크, 기본 모드 네트워크 및 측두엽에서 유의미하게 낮은 것으로 나타났다. 본 연구 결과는 우울한 노인들의 증상 기저의 신경심리적 특성을 이해하는데 도움이 될 것이며, 네트워크 연결성과 효율성이 저하된 영역들을 밝힘으로써 경두개 자기자극법과 같은 뇌자극 치료 시 단서가 될 것이다.
- keywords
- late-life depression, resting-state network, network based statistics, graph theory. salience network, 노년기 우울, 휴지기 네트워크, 네트워크 기반 통계(NBS), 그래프 이론, 현저성 네트워크
Abstract
Late-life depression(LLD) is overshadowed by the general physical symptoms of the elderly, making it difficult to diagnose and treatment accurately. In the rs-fMRI study, salience network is a suitable network to describe emotional control and goal-directed behavior processes related to depression symptoms, and is known to be an important network for therapeutic effects, but studies for depressed elderly people are lacking. In this study, we compared the resting-state of 18 LLD group (GDS M=21.78 SD=3.30) and 18 randomized control group(GDS M=8.78 SD=4.42). We used a network based statistic (NBS) for searching network dynamics within the salience network(intra/inter). Thus, connectivity within salience network(caudate-amygdala) was significantly lower in the depressed group, and connectivity between networks(insula-prefrontal cortex-lateral parietal cortex) was found to be contrary to the prior study. In addition, we used a graph theory analysis for identifying inconsistent network topology between groups, LLD group was found to be significantly lower in the small-worldness and clustering coefficient(salience network, default mode network, temporal lobe) although there were no differences between the two groups in characteristic path length. Reduced intra-network connectivity seems to be related to difficulties in behavior and emotion regulation, while reduced inter-network connectivity seems to reflect a reduction in goal-directed behavior rather than a negative reflection on the past. The results of this study suggest that there is intended to help neuropsychological understanding of the symptoms of depressed elderly people, and also help with treatment using TMS(transcranial magnetic stimulation) by examining areas of poor network connectivity and efficiency.
- keywords
- late-life depression, resting-state network, network based statistics, graph theory. salience network, 노년기 우울, 휴지기 네트워크, 네트워크 기반 통계(NBS), 그래프 이론, 현저성 네트워크
참고문헌
Ajilore, O., Lamar, M., Leow, A., Zhang, A., Yang, S., &Kumar, A. (2014). Graph theory analysis of cortical-subcortical networks in late-life depression. The American Journal of Geriatric Psychiatry, 22, 195-206.
American Psychiatric Association. (2013). DSM-5. American Psychiatric Association.
An, H. J., & Chey, J. Y. (2004). A Standardization study of the story recall test in the elderly Korean population. Korean Journal of Clinical Psychology, 23, 435-454.
Bae, J. N., & Cho, M. J. (2004). Development of the Korean version of the geriatric depression scale and its short form among elderly psychiatric patients. Journal of Psychosomatic Research, 57, 297-305.
Behzadi, Y., Restom, K., Liau, J., & Liu, T. T. (2007). A component based noise correction method for BOLD and perfusion based fMRI. Neuroimage, 37, 90-101.
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society:Series B, 57, 289-300.
Bohr, I. J., Kenny, E., Blamire, A., O'Brien, J. T., Thomas, A. J., Richardson, J., & Kaiser, M. (2013). Resting-state functional connectivity in late-life depression: Higher global connectivity and more long distance connections. Frontiers in Psychiatry, 3(116). 1-14.
Buckner, R. L., Andrews-Hanna, J. R., & Schacter, D. L. (2008). The brain's default network: Anatomy, function, and relevance to disease. Annals of the New York Academy of Sciences, 1124, 1-38.
Bullmore, E., & Sporns, O. (2009). Complex brain networks:graph theoretical analysis of structural and functional systems. Nature Reviews Neuroscience, 10, 186-198.
Bunge, S. A., Hazeltine, E., Scanlon, M. D., Rosen, A. C., & Gabrieli, J. D. E. (2002). Dissociable contributions of prefrontal and parietal cortices to response selection. Neuroimage, 17, 1562-1571.
Buschman, T. J., & Miller, E. K. (2007). Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices. Science, 315, 1860-1862.
Chey, J. Y., Lee, J. E., Kim, M. J., & Kim, H. Y. (2006). Development and standarization of the elderly verbal learning test. Korean Journal of Psychology General, 25, 141-173.
Chey, J. Y. (2007). Elderly memory disorder scale. Seoul, Korea: Hakjisa
Crittenden, B. M., Mitchell, D. J., & Duncan, J. (2015). Recruitment of the default mode network during a demanding act of executive control. Elife, 4, e06481.
Downar, J., Crawley, A. P., Mikulis, D. J., & Davis, K. D. (2000). A multimodal cortical network for the detection of changes in the sensory environment. Nature Neuroscience, 3, 277-283.
Elderkin-Thompson, V., Hellemann, G., Pham, D., & Kumar, A. (2009). Prefrontal brain morphology and executive function in healthy and depressed elderly. International Journal of Geriatric Psychiatry, 24, 459-468.
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, 189-198.
Fox, M. D., & Greicius, M. (2010). Clinical applications of resting state functional connectivity. Frontiers in Systems Neuroscience, 4(19), 1-13.
Fox, M. D., Halko, M. A., Eldaief, M. C., & Pascual-Leone, A. (2012). Measuring and manipulating brain connectivity with resting state functional connectivity magnetic resonance imaging and transcranial magnetic stimulation. Neuroimage, 62, 2232–2243.
Glover, J., & Srinivasan, S. (2013). Assessment of the person with late-life depression. Psychiatric Clinics of North America, 36, 545-560.
Goulden, N., Khusnulina, A., Davis, N. J., Bracewell, R. M., Bokde, A. L., McNulty, J. P., & Mullins, P. G. (2014). The salience network is responsible for switching between the default mode network and the central executive network: replication from DCM. Neuroimage, 99, 180-190.
Hamilton, J. P., Furman, D. J., Chang, C., Thomason, M. E., Dennis, E., & Gotlib, I. H. (2011). Default-mode and task-positive network activity in major depressive disorder: implications for adaptive and maladaptive rumination. Biological Psychiatry, 70, 327-333.
Hamilton, J. P., Chen, M. C., & Gotlib, I. H. (2013). Neural systems approaches to understanding major depressive disorder: an intrinsic functional organization perspective. Neurobiology of Disease, 52, 4-11.
Han, J. W., Kim, T. H., Jhoo, J. H., Park, J. H., Kim, J. L., Ryu, S. H., & Do, Y. J. (2010). A normative study of the mini-mental state examination for dementia screening and its short form in the Korean elderly. Journal of Korea Geriatric Psychiatry, 14, 27-37.
Hays, J., Saunders, W., Flint, E., Kaplan, B., & Blazer, D. (1997). Depression and social support as risk factors for functional disability in late life. Aging and Mental Health, 3, 209-220.
Honey, C. J., Sporns, O., Cammoun, L., Gigandet, X., Thiran, J. P., Meuli, R., & Hagmann, P. (2009). Predicting human resting-state functional connectivity from structural connectivity. Proceedings of the National Academy of Sciences, 106, 2035-2040.
Hosseini, S. M. H., Hoeft, F., & Kesler, S. R. (2012). GAT:A Graph-Theoretical analysis toolbox for analyzing between-group differences in large-scale structural and functional brain networks. PLoS ONE, 7(7), e40709.
Hwang, S. T., Chey, J. Y., Kim, J. H., Park, K. B., Hong, S. H., & Oh, S. W. (2012). Standardization of the K-WAIS-IV and K-WMS-IV. In Proceedings of Korean Psychological Association Annual Conference. 1. 139-139.
Johnstone, T., van Reekum, C. M., Urry, H. L., Kalin, N. H., & Davidson, R. J. (2007). Failure to regulate:counterproductive recruitment of top-down prefrontalsubcortical circuitry in major depression. Journal of Neuroscience, 27, 8877-8884.
Jung, I. K., Kwak, D. I., Joe, S. H., & Lee, H. S. (1997). A study of standardization of korean form of geriatric depression scale. Korean Association for Geriatric Psychiatry, 1, 61-72.
Kang, Y., Chin, J. H., Na, D. L., Lee, J., & Park, J. S. (2000). A normative study of the Korean version of controlled oral word association test in the elderly. Korean Journal of Clinical Psychology, 19, 385-392.
Kang, Y., Jang. S. M., & Na, D. L. (2012). Seoul Neuropsychological Screening Battery-II Manual. Seoul, Korea: Human Brain Researching & Consulting.
Kastner, S., Pinsk, M. A., De Weerd, P., Desimone, R., &Ungerleider, L. G. (1999). Increased activity in human visual cortex during directed attention in the absence of visual stimulation. Neuron, 22, 751-761.
Kos, C., van Tol, M. J., Marsman, J. B. C., Knegtering, H., & Aleman, A. (2016). Neural correlates of apathy in patients with neurodegenerative disorders, acquired brain injury, and psychiatric disorders. Neuroscience &Biobehavioral Reviews, 69, 381-401.
Lee, T. W., Liu, H. L., Wai, Y. Y., Ko, H. J., & Lee, S. H. (2013). Abnormal neural activity in partially remitted late-onset depression: an fMRI study of one-back working memory task. Psychiatry Research:Neuroimaging, 213, 133-141.
Leech, R., & Sharp, D. J. (2013). The role of the posterior cingulate cortex in cognition and disease. Brain, 137, 12-32.
Lemogne, C., Delaveau, P., Freton, M., Guionnet, S., &Fossati, P. (2012). Medial prefrontal cortex and the self in major depression. Journal of Affective Disorders, 136, e1-e11.
Lezak, M. D., Howieson, D. B., Loring, D. W., & Fischer, J. S. (2004). Neuropsychological Assessment. USA:Oxford University Press.
Li, W., Ward, B. D., Liu, X., Chen, G., Jones, J. L., Antuono, P. G., & Goveas, J. S. (2015). Disrupted small world topology and modular organization of functional networks in late-life depression with and without amnestic mild cognitive impairment. Journal of Neurology, Neurosurgery & Psychiatry, 86(10), 1097-1105.
Li, W., Wang, Y., Ward, B. D., Antuono, P. G., Li, S. J., & Goveas, J. S. (2017). Intrinsic inter-network brain dysfunction correlates with symptom dimensions in late-life depression. Journal of Psychiatric Research, 87, 71–80.
Lichtenberger, E. O., & Kaufman, A. S. (2012). Essentials of WAIS-IV assessment. Hoboken, NJ: John Wiley & Sons.
Lim, H. K., Jung, W. S., & Aizenstein, H. J. (2013). Aberrant topographical organization in gray matter structural network in late life depression: A graph theoretical analysis. International Psychogeriatrics, 25, 1929-1940.
Manoliu, A., Meng, C., Brandl, F., Doll, A., Tahmasian, M., Scherr, M., & Riedl, V. (2014). Insular dysfunction within the salience network is associated with severity of symptoms and aberrant inter-network connectivity in major depressive disorder. Frontiers in Human Neuroscience, 7, 930.
Menon, V. (2011). Large-scale brain networks and psychopathology: A unifying triple network model. Trends in Cognitive Sciences, 15, 483-506.
Menon V. (2015) Salience Network. In W. Toga (Ed.), Brain Mapping: An Encyclopedic Reference. Academic Press:Elsevier.
Onoda, K., & Yamaguchi, S. (2015). Dissociative contributions of the anterior cingulate cortex to apathy and depression: Topological evidence from resting-state functional MRI. Neuropsychologia, 77, 10–18.
Palaniyappan, L., & Liddle, P. F. (2012). Does the salience network play a cardinal role in psychosis? An emerging hypothesis of insular dysfunction. Journal of Psychiatry & Neuroscience. 37, 17-27.
Park, E. H., & Chey, J. Y. (2000). Elderly normative study of the short form Korean-Boston Naming Test. Korea Journal of Neuroscience, 11, 59-68.
Park, H. J., & Friston, K. (2013). Structural and functional brain networks: from connections to cognition. Science, 342(6158), 1238411.
Park, M. S., & Chey, J. Y. (2003). A normative study of the modified trail making test for elderly Korean people. Korean Journal of Clinical Psychology, 22(1), 247-259.
Peters, S. K., Dunlop, K., & Downar, J. (2016). Cortico-Striatal-Thalamic loop circuits of the salience network: A central pathway in psychiatric disease and treatment. Frontiers in Systems Neuroscience, 10, 55–23.
Raz, N., Gunning, F. M., Head, D., Dupuis, J. H., McQuain, J., Briggs, S. D., & Acker, J. D. (1997). Selective aging of the human cerebral cortex observed in vivo:differential vulnerability of the prefrontal gray matter. Cerebral Cortex, 7(3), 268-282.
Rogers, M. A., Kasai, K., Koji, M., Fukuda, R., Iwanami, A., Nakagome, K., & Kato, N. (2004). Executive and prefrontal dysfunction in unipolar depression: a review of neuropsychological and imaging evidence. Neuroscience Research, 50(1), 1-11.
Roose. S. P., & Schatzberg. A. F. (2005). The efficacy of antidepressants in the treatment of late-life depression. Journal of Clinical Psychopharmacology. 25(4), S1-S7.
Rubinov, M., Knock, S. A., Stam, C. J., Micheloyannis, S., Harris, A. W., Williams, L. M., & Breakspear, M. (2009). Small‐world properties of nonlinear brain activity in schizophrenia. Human Brain Mapping, 30, 403-416.
Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: uses and interpretations. Neuroimage, 52, 1059-1069.
Scahill, R. I., Frost, C., Jenkins, R., Whitwell, J. L., Rossor, M. N., & Fox, N. C. (2003). A longitudinal study of brain volume changes in normal aging using serial registered magnetic resonance imaging. Archives of Neurology, 60, 989-994.
Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., & Greicius, M. D. (2007). Dissociable intrinsic connectivity networks for salience processing and executive control. The Journal of Neuroscience, 27, 2349-2356.
Sheline, Y. I., Barch, D. M., Price, J. L., Rundle, M. M., Vaishnavi, S. N., Snyder, A. Z., & Raichle, M. E. (2009). The default mode network and self-referential processes in depression. Proceedings of the National Academy of Sciences, 106, 1942-1947.
Shin, J. H., Um, Y. H., Lee, C. U., Lim, H. K., & Seong, J. K. (2018). Multiple cortical thickness sub-networks and cognitive impairments in first episode, drug naïve patients with late life depression: A graph theory analysis. Journal of Affective Disorders, 229, 538–545.
Singer, T., Critchley, H. D., & Preuschoff, K. (2009). A common role of insula in feelings, empathy and uncertainty. Trends in Cognitive Sciences, 13, 334-340.
Shirer, W. R., Ryali, S., Rykhlevskaia, E., Menon, V., &Greicius, M. D. (2012). Decoding subject-driven cognitive states with whole-brain connectivity patterns. Cerebral Cortex, 22(1), 158-165.
Smith, S. M., Beckmann, C. F., Andersson, J., Auerbach, E. J., Bijsterbosch, J., Douaud, G., & Kelly, M. (2013). Resting-state fMRI in the human connectome project. Neuroimage, 80, 144-168.
Song, H. J., & Chey, J. (2006). A normative study of the digit span and the spatial span for the elderly Koreans. Korean Journal of Clinical Psychology, 25, 505-532.
Spreng, R. N., Mar, R. A., & Kim, A. S. (2009). The common neural basis of autobiographical memory, prospection, navigation, theory of mind, and the default mode: a quantitative meta-analysis. Journal of Cognitive Neuroscience, 21, 489-510.
Sridharan, D., Levitin, D. J., & Menon, V. (2008). A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks. Proceedings of the National Academy of Sciences, 105, 12569-12574.
Suo, X., Du Lei, L. L., Li, W., Dai, J., Wang, S., He, M., & Gong, Q. (2018). Psychoradiological patterns of small-world properties and a systematic review of connectome studies of patients with 6 major psychiatric disorders. Journal of Psychiatry & Neuroscience, 43, 416-427.
Van Wijk, B. C., Stam, C. J., & Daffertshofer, A. (2010). Comparing brain networks of different size and connectivity density using graph theory. PloS ONE, 5(10), e13701.
Veer, I. M., Beckmann, C., Van Tol, M. J., Ferrarini, L., Milles, J., Veltman, D., & Rombouts, S. A. (2010). Whole brain resting-state analysis reveals decreased functional connectivity in major depression. Frontiers in systems neuroscience, 4, 41.
Volkmar, F. R. (2005). Handbook of autism and pervasive developmental disorder. Hoboken, NJ: John Wiley &Sons.
Yesavage, J. A., Brink, T. L., Rose, T. L., Lum, O., Huang, V., Adey, M. & Leirer, V. O. (1983). Development and validation of a geriatric depression screening scale: A preliminary report. Journal of Psychiatric Research, 17, 37-49.
Yue, Y., Yuan, Y., Hou, Z., Jiang, W., Bai, F., & Zhang, Z. (2013). Abnormal functional connectivity of amygdala in late-onset depression was associated with cognitive deficits. PLoS ONE, 8(9). e75058.
Yuen, G. S., Gunning, F. M., Hoptman, M. J., AbdelMalak, B., McGovern, A. R., Seirup, J. K., & Alexopoulos, G. S. (2014). The salience network in the apathy of late-life depression. International Journal of Geriatric Psychiatry, 29, 1116–1124.
Zhao, X., Liu, Y., Wang, X., Liu, B., Xi, Q., Guo, Q. &Wang, P. (2012). Disrupted small-world brain networks in moderate Alzheimer's disease: A resting-state fMRI study. PloS ONE, 7(3). e33540.
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