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Default Network Connectivity Is Linked to Memory Status in Multiple Sclerosis

Published online by Cambridge University Press:  23 September 2014

Victoria M. Leavitt ,
Jessica Paxton  and
James F. Sumowski
Victoria M. Leavitt*
Affiliation:
Columbia University Multiple Sclerosis Clinical Care and Research Center, Cognitive Neuroscience Division, Department of Neurology, Columbia University Medical Center, New York, New York
Jessica Paxton
Affiliation:
SUNY Plattsburgh, Plattsburgh, New York
James F. Sumowski
Affiliation:
Kessler Foundation, Cognitive Neuroscience Laboratory, West Orange, New Jersey
*
Correspondence and reprint requests to: Victoria Leavitt, Columbia University Multiple Sclerosis Clinical Care and Research Center, Cognitive Neuroscience Division, Department of Neurology, Columbia University Medical Center, 630 W. 168th Street, P&S Box 16, New York, NY 10032. E-mail: vl2337@cumc.columbia.edu
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Abstract

Memory impairment affects 50% of multiple sclerosis (MS) patients. Altered resting-state functional connectivity (FC) has been observed in the default network (DN) of MS patients. No study to date has examined the association of DN FC to its behavioral concomitant, memory. The approach of the present study represents a methodological shift allowing straightforward interpretation of FC alterations in MS, as it presupposes specificity of a network to its paired cognitive function. We examined FC from fMRI collected during rest in the DN of 43 MS patients with and without memory-impairment. Memory-intact patients showed increased DN FC relative to memory-impaired patients. There were no regions of higher FC in memory-impaired patients. DN FC was positively correlated with memory function, such that higher FC was associated with better memory performance. Results were unchanged after controlling for cognitive efficiency, supporting specificity of the DN to memory and not cognitive status more generally. These findings support DN FC as a marker of memory function in MS patients that can be targeted by future treatment interventions. Pairing a functional network with its behavioral concomitant represents a straightforward method for interpreting FC alterations in patients with MS. (JINS, 2014, 20, 1–8)

Keywords

Multiple sclerosisMemoryDefault networkFunctional connectivityfMRICognition

Information

Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 20 , Issue 9 , October 2014 , pp. 937 - 944
Copyright
Copyright © The International Neuropsychological Society 2014 

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References

Anderson, V.M., Fisniku, L.K., Khaleeli, Z, et al. (2010). Hippocampal atrophy in relapsing-remitting and primary progressive MS: a comparative study. Multiple sclerosis, 16, 1083–1090.CrossRefGoogle ScholarPubMed
Bai, F., Zhang, Z., Yu, H., Shi, Y., Yuan, Y., Zhu, W., … Qian, Y. (2008). Default-mode network activity distinguishes amnestic type mild cognitive impairment from healthy aging: A combined structural and resting-state functional MRI study. Neuroscience Letters, 428(1), 111–115. doi: 10.1016/j.neulet.2008.04.021.Google Scholar
Benedict, R.H., Carone, D.A., & Bakshi, R. (2004). Correlating brain atrophy with cognitive dysfunction, mood disturbances, and personality disorder in multiple sclerosis. Journal of neuroimaging: official journal of the American Society of Neuroimaging, 14, 36S–45S.Google Scholar
Benedict, R.H., Cookfair, D., Gavett, R., Gunther, M., Munschauer, F., Garg, N., & Weinstock-Guttman, B. (2006). Validity of the minimal assessment of cognitive function in multiple sclerosis (MACFIMS). Journal of the International Neuropsychological Society, 12(4), 549–558.Google Scholar
Benedict, R.H., Bruce, J.M., Dwyer, M.G., Abdelrahman, N., Hussein, S., Weinstock-Guttman, B., & Zivadinov, R. (2006). Neocortical atrophy third ventricular width, and cognitive dysfunction in multiple sclerosis. Archives of Neurology, 63(9), 1301–1306.CrossRefGoogle ScholarPubMed
Benedict, R.H., Ramasamy, D., Munschauer, F., Weinstock-Guttman, B., & Zivadinov, R. (2009). Memory impairment in multiple sclerosis: correlation with deep grey matter and mesial temporal atrophy. Journal of neurology, neurosurgery, and psychiatry, 80, 201–206.Google Scholar
Bermel, R.A., & Bakshi, R. (2006). The measurement and clinical relevance of brain atrophy in multiple sclerosis. The Lancet Neurology, 5, 158–170.Google Scholar
Chard, D., & Miller, D. (2009). Grey matter pathology in clinically early multiple sclerosis: evidence from magnetic resonance imaging. Journal of the neurological sciences, 282, 5–11.Google Scholar
Christodoulou, C., Krupp, L.B., Liang, Z, et al. (2003). Cognitive performance and MR markers of cerebral injury in cognitively impaired MS patients. Neurology, 60, 1793–1798.Google Scholar
Cruz-Gomez, A.J., Ventura-Campos, N., Belenguer, A., Avila, C., & Forn, C. (2014). The link between resting state functional connectivity and cognition in MS patients. Multiple Sclerosis, 20(3), 338–348. doi: 10.1177/1352458513495584.Google Scholar
Fisher, E., Lee, J.C., Nakamura, K., & Rudick, R.A. (2008). Gray matter atrophy in multiple sclerosis: a longitudinal study. Annals of neurology, 64, 255–265.Google Scholar
Greicius, M.D., Krasnow, B., Reiss, A.L., & Menon, V. (2003). Functional connectivity in the resting brain: A network analysis of the default mode hypothesis. Proceedings of the National Academy of Sciences of the United States of America, 100(1), 253–258.CrossRefGoogle Scholar
Greicius, M.D., Srivastava, G., Reiss, A.L., & Menon, V. (2004). Default-mode network activity distinguishes Alzheimer’s disease from healthy aging: Evidence from functional MRI. Proceedings of the National Academy of Sciences of the United States of America, 101(13), 4637–4642.Google Scholar
Hawellek, D.J., Hipp, J.F., Lewis, C.M., Corbetta, M., & Engel, A.K. (2011). Increased functional connectivity indicates the severity of cognitive impairment in multiple sclerosis. Proceedings of the National Academy of Sciences of the United States of America, 108(47), 19066–19071.Google Scholar
Killgore, W.D., Schwab, Z.J., & Weiner, M.R. (2012). Self-reported nocturnal sleep duration is associated with next-day resting state functional connectivity. Neuroreport, 23(13), 741–745. doi: 10.1097/WNR.0b013e3283565056.CrossRefGoogle ScholarPubMed
Leavitt, V.M., Cirnigliaro, C., Cohen, A., Farag, A., Brooks, M., Wecht, J.M., & Sumowski, J.F. (2014). Aerobic exercise increases hippocampal volume and improves memory in multiple sclerosis: Preliminary findings. Neurocase, 20(6), 695–697.Google Scholar
Lucchinetti, C., Bruck, W., Parisi, J., Scheithauer, B., Rodriguez, M., & Lassmann, H. (2000). Heterogeneity of multiple sclerosis lesions: implications for the pathogenesis of demyelination. Annals of neurology 47, 707–717.Google Scholar
Richiardi, J., Gschwind, M., Simioni, S., Annoni, J.M., Greco, B., Hagmann, P., … Van De Ville, D. (2012). Classifying minimally disabled multiple sclerosis patients from resting state functional connectivity. Neuroimage, 62(3), 2021–2033. doi: 10.1016/j.neuroimage.2012.05.078.Google Scholar
Rocca, M.A., Valsasina, P., Absinta, M., Riccitelli, G., Rodegher, M.E., Misci, P., … Filippi, M. (2010). Default-mode network dysfunction and cognitive impairment in progressive MS. Neurology, 74(16), 1252–1259.CrossRefGoogle ScholarPubMed
Rocca, M.A., Valsasina, P., Martinelli, V., Misci, P., Falini, A., Comi, G., & Filippi, M. (2012). Large-scale neuronal network dysfunction in relapsing-remitting multiple sclerosis. Neurology, 79(14), 1449–1457.Google Scholar
Rombouts, S.A., Barkhof, F., Goekoop, R., Stam, C.J., & Scheltens, P. (2005). Altered resting state networks in mild cognitive impairment and mild Alzheimer’s disease: An fMRI study. Human Brain Mapping, 26(4), 231–239.Google Scholar
Roosendaal, S.D., Schoonheim, M.M., Hulst, H.E., Sanz-Arigita, E.J., Smith, S.M., Geurts, J.J., & Barkhof, F. (2010). Resting state networks change in clinically isolated syndrome. Brain, 133(Pt 6) 1612–1621.Google Scholar
Sanfilipo, M.P., Benedict, R.H., Weinstock-Guttman, B., & Bakshi, R. (2006). Gray and white matter brain atrophy and neuropsychological impairment in multiple sclerosis. Neurology, 66, 685–692.Google Scholar
Sicotte, N.L., Kern, K.C., Giesser, B.S., et al. (2008). Regional hippocampal atrophy in multiple sclerosis. Brain: a journal of neurology, 131, 1134–1141.Google Scholar
Sorg, C., Riedl, V., Muhlau, M., Calhoun, V.D., Eichele, T., Laer, L., … Wohlschlager, A.M. (2007). Selective changes of resting-state networks in individuals at risk for Alzheimer’s disease. Proceedings of the National Academy of Sciences of the United States of America, 104(47), 18760–18765.Google Scholar
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.Google Scholar
Sumowski, J.F., Wylie, G.R., Leavitt, V.M., Chiaravalloti, N.D., & DeLuca, J. (2012). Default network activity is a sensitive and specific biomarker of memory in multiple sclerosis. Multiple Sclerosis, 19(2), 199–208. doi: 10.1177/1352458512448267.Google Scholar
Squire, L.R., Stark, C.E., & Clark, R.E. (2004). The medial temporal lobe. Annual review of neuroscience 27, 279–306.Google Scholar
Thornton, A.E., & Raz, N. (1997). Memory impairment in multiple sclerosis: A quantitative review. Neuropsychology, 11(3), 357–366.Google Scholar
Tomasi, D., & Volkow, N.D. (2011). Association between functional connectivity hubs and brain networks. Neuroimage, 57(3), 908–917.Google Scholar
Wang, L., Zang, Y., He, Y., Liang, M., Zhang, X., Tian, L., … Li, K. (2006). Changes in hippocampal connectivity in the early stages of Alzheimer’s disease: Evidence from resting state fMRI. Neuroimage, 31(2), 496–504.Google Scholar