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Neuropsychology of Multiple Sclerosis: Looking Back and Moving Forward

Published online by Cambridge University Press:  04 December 2017

Ralph H.B. Benedict ,
John DeLuca ,
Christian Enzinger ,
Jeroen J.G. Geurts ,
Lauren B. Krupp  and
Stephen M. Rao
Ralph H.B. Benedict
Affiliation:
Department of Neurology, University of Buffalo, Buffalo, New York
John DeLuca
Affiliation:
Kessler Foundation, West Orange, New Jersey; Rutgers New Jersey Medical School, Newark, New Jersey
Christian Enzinger
Affiliation:
Research Unit for Neuronal Repair and Plasticity, Department of Neurology, Medical University of Graz, Austria
Jeroen J.G. Geurts
Affiliation:
Department of Anatomy & Neurosciences, VU University Medical Center, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
Lauren B. Krupp
Affiliation:
NYU Langone Multiple Sclerosis Comprehensive Care Center, Department of Neurology, New York University Langone Medical Center, New York, New York
Stephen M. Rao*
Affiliation:
Schey Center for Cognitive Neuroimaging, Lou Ruvo Center for Brain Health, Neurological Institute, Cleveland Clinic, Cleveland, Ohio
*
Correspondence and reprint requests to: Stephen M. Rao, Schey Center for Cognitive Neuroimaging, Neurological Institute, Cleveland Clinic, 9500 Euclid Avenue/U10, Cleveland, OH 44195. E-mail: [email protected]
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Abstract

The neuropsychological aspects of multiple sclerosis (MS) have evolved over the past three decades. What was once thought to be a rare occurrence, cognitive dysfunction is now viewed as one of the most disabling symptoms of the disease, with devastating effects on patients’ quality of life. This selective review will highlight major innovations and scientific discoveries in the areas of neuropathology, neuroimaging, diagnosis, and treatment that pertain to our understanding of the neuropsychological aspects of MS. Specifically, we focus on the recent discovery that MS produces pathogical lesions of gray matter (GM) that have consequences for cognitive functions. Methods for imaging these GM lesions in MS are discussed along with multimodal imaging studies that integrate structural and functional imaging methods to provide a better understanding of the relationship between cognitive test performance and functional reserve. Innovations in the screening and comprehensive assessment of cognitive disorders are presented along with recent research that examines cognitive dysfunction in pediatric MS. Results of innovative outcome studies in cognitive rehabilitation are discussed. Finally, we highlight trends for potential future innovations over the next decade. (JINS, 2017, 23, 832–842)

Keywords

Multiple sclerosisNeuropsychologyCognitionNeuropathologyMRIGray matterRehabilitation
Type
Section 2 – Neurological Disorders
Information
Journal of the International Neuropsychological Society , Volume 23 , Special Issue 9-10: Special Issue: Commemoration of the 50th Anniversary of the International Neuropsychological Society , October 2017 , pp. 832 - 842
Copyright
Copyright © The International Neuropsychological Society 2017 

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References

REFERENCES

Akbar, N., Banwell, B., Sled, J.G., Binns, M.A., Doesburg, S.M., Rypma, B., & Till, C. (2016). Brain activation patterns and cognitive processing speed in patients with pediatric-onset multiple sclerosis. Journal of Clinical and Experimental Neuropsychology, 38(4), 393–403. doi: 10.1080/13803395.2015.1119255 CrossRefGoogle ScholarPubMed
Amato, M.P., Bartolozzi, M.L., Zipoli, V., Portaccio, E., Mortilla, M., Guidi, L., & De Stefano, N. (2004). Neocortical volume decrease in relapsing-remitting MS patients with mild cognitive impairment. Neurology, 63(1), 89–93.Google Scholar
Amato, M.P., Goretti, B., Ghezzi, A., Hakiki, B., Niccolai, C., & Lori, S., . . . MS Study Group of the Italian Neurological Society. (2014). Neuropsychological features in childhood and juvenile multiple sclerosis: Five-year follow-up. Neurology, 83(16), 1432–1438. doi: 10.1212/WNL.0000000000000885 Google Scholar
Arnett, P.A., Rao, S.M., Bernardin, L., Grafman, J., Yetkin, F.Z., & Lobeck, L. (1994). Relationship between frontal lobe lesions and Wisconsin Card Sorting Test performance in patients with multiple sclerosis. Neurology, 44(3 Pt 1), 420–425.Google Scholar
Audoin, B., Zaaraoui, W., Reuter, F., Rico, A., Malikova, I., Confort-Gouny, S., & Ranjeva, J.P. (2010). Atrophy mainly affects the limbic system and the deep grey matter at the first stage of multiple sclerosis. Journal of Neurology, Neurosurgery, and Psychiatry, 81(6), 690–695. doi: 10.1136/jnnp.2009.188748 Google Scholar
Barcellos, L.F., Bellesis, K.H., Shen, L., Shao, X., Chinn, T., Frndak, S., & Benedict, R.H. (2017). Remote assessment of verbal memory in MS patients using the California Verbal Learning Test. Multiple Sclerosis, 1352458517694087. doi: 10.1177/1352458517694087 Google Scholar
Batista, S., Zivadinov, R., Hoogs, M., Bergsland, N., Heininen-Brown, M., Dwyer, M.G., & Benedict, R.H. (2012). Basal ganglia, thalamus and neocortical atrophy predicting slowed cognitive processing in multiple sclerosis. Jorunal of Neurology, 259(1), 139–146. doi: 10.1007/s00415-011-6147-1 Google Scholar
Beatty, W.W., & Goodkin, D.E. (1990). Screening for cognitive impairment in multiple sclerosis. An evaluation of the Mini-Mental State Examination. Archives of Neurology, 47(3), 297–301.Google Scholar
Benedict, R.H., Amato, M.P., Boringa, J., Brochet, B., Foley, F., Fredrikson, S., & Langdon, D. (2012). Brief International Cognitive Assessment for MS (BICAMS): International standards for validation. BMC Neurology, 12, 55. doi: 10.1186/1471-2377-12-55 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, 14(3 Suppl), 36S–45S. doi: 10.1177/1051228404266267 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., DeLuca, J., Phillips, G., LaRocca, N., Hudson, L.D., Rudick, R., & Multiple Sclerosis Outcome Assessments Consortium. (2017). Validity of the Symbol Digit Modalities Test as a cognition performance outcome measure for multiple sclerosis. Multiple Sclerosis, 1352458517690821. doi: 10.1177/1352458517690821 Google ScholarPubMed
Benedict, R.H., Fischer, J.S., Archibald, C.J., Arnett, P.A., Beatty, W.W., Bobholz, J., & Munschauer, F. (2002). Minimal neuropsychological assessment of MS patients: A consensus approach. The Clinical neuropsychologist, 16(3), 381–397. doi: 10.1076/clin.16.3.381.13859 Google Scholar
Benedict, R.H., Morrow, S.A., Weinstock Guttman, B., Cookfair, D., & Schretlen, D.J. (2010). Cognitive reserve moderates decline in information processing speed in multiple sclerosis patients. Journal of the International Neuropsychological Society, 16(5), 829–835. doi: 10.1017/S1355617710000688 Google Scholar
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(2), 201–206. doi: 10.1136/jnnp.2008.148403 Google Scholar
Benedict, R.H., Rodgers, J.D., Emmert, N., Kininger, R., & Weinstock-Guttman, B. (2014). Negative work events and accommodations in employed multiple sclerosis patients. Multiple Sclerosis, 20(1), 116–119. doi: 10.1177/1352458513494492 Google Scholar
Bergsland, N., Horakova, D., Dwyer, M.G., Dolezal, O., Seidl, Z.K., Vaneckova, M., & Zivadinov, R. (2012). Subcortical and cortical gray matter atrophy in a large sample of patients with clinically isolated syndrome and early relapsing-remitting multiple sclerosis. AJNR American Journal of Neuroradiology, 33(8), 1573–1578. doi: 10.3174/ajnr.A3086 Google Scholar
Bo, L., Vedeler, C.A., Nyland, H., Trapp, B.D., & Mork, S.J. (2003). Intracortical multiple sclerosis lesions are not associated with increased lymphocyte infiltration. Multiple Sclerosis, 9(4), 323–331.Google Scholar
Bobholz, J.A., Rao, S.M., Lobeck, L., Elsinger, C., Gleason, A., Kanz, J., & Maas, E. (2006). fMRI study of episodic memory in relapsing-remitting MS: Correlation with T2 lesion volume. Neurology, 67(9), 1640–1645. doi: 10.1212/01.wnl.0000242885.71725.76 Google Scholar
Bodini, B., Khaleeli, Z., Cercignani, M., Miller, D.H., Thompson, A.J., & Ciccarelli, O. (2009). Exploring the relationship between white matter and gray matter damage in early primary progressive multiple sclerosis: An in vivo study with TBSS and VBM. Human Brain Mapping, 30(9), 2852–2861. doi: 10.1002/hbm.20713 CrossRefGoogle Scholar
Bodini, B., Veronese, M., Garcia-Lorenzo, D., Battaglini, M., Poirion, E., Chardain, A., & Stankoff, B. (2016). Dynamic imaging of individual remyelination profiles in multiple sclerosis. Annals of Neurology. [Epub ahead of print]. doi: 10.1002/ana.24620 Google Scholar
Calabrese, M., Agosta, F., Rinaldi, F., Mattisi, I., Grossi, P., Favaretto, A., & Filippi, M. (2009). Cortical lesions and atrophy associated with cognitive impairment in relapsing-remitting multiple sclerosis. Archives of Neurology, 66(9), 1144–1150. doi: 10.1001/archneurol.2009.174 Google Scholar
Calabrese, M., & Gallo, P. (2009). Magnetic resonance evidence of cortical onset of multiple sclerosis. Multiple Sclerosis, 15(8), 933–941. doi: 10.1177/1352458509106510 Google Scholar
Carone, D.A., Benedict, R.H., Munschauer, F.E. III, Fishman, I., & Weinstock-Guttman, B. (2005). Interpreting patient/informant discrepancies of reported cognitive symptoms in MS. Journal of the International Neuropsychological Society, 11(5), 574–583. doi: 10.1017/S135561770505068X Google Scholar
Charcot, J.M. (1877). Lectures on the diseases of the nervous system delivered at La Salpetriere. London: New Sydenham Society.Google Scholar
Charvet, L.E., Cersosimo, B., Schwarz, C., Belman, A., & Krupp, L.B. (2016). Behavioral symptoms in pediatric multiple sclerosis: Relation to fatigue and cognitive impairment. Journal of Child Neurology, 31(8), 1062–1067. doi: 10.1177/0883073816636227 CrossRefGoogle ScholarPubMed
Charvet, L.E., O’Donnell, E.H., Belman, A.L., Chitnis, T., Ness, J.M., & Parrish, J., . . . Centers, US Network of Pediatric MS Centers. (2014). Longitudinal evaluation of cognitive functioning in pediatric multiple sclerosis: Report from the US Pediatric Multiple Sclerosis Network. Multiple Sclerosis, 20(11), 1502–1510. doi: 10.1177/1352458514527862 CrossRefGoogle ScholarPubMed
Charvet, L.E., Shaw, M., Frontario, A., Langdon, D., & Krupp, L. (2017). Cognitive impairment in pediatric-onset multiple sclerosis is detected by the Brief International Cognitive Assessment for Multiple Sclerosis and computerized cognitive testing. Multiple Sclerosis. [Epub ahead of print]. doi: 10.1177/1352458517701588 Google Scholar
Chiaravalloti, N.D., Genova, H.M., & DeLuca, J. (2015). Cognitive rehabilitation in multiple sclerosis: The role of plasticity. Frontirs in Neurology, 6, 67. doi: 10.3389/fneur.2015.00067 Google Scholar
Chiaravalloti, N.D., Moore, N.B., Nikelshpur, O.M., & DeLuca, J. (2013). An RCT to treat learning impairment in multiple sclerosis: The MEMREHAB trial. Neurology, 81(24), 2066–2072. doi: 10.1212/01.wnl.0000437295.97946.a8 Google Scholar
Damjanovic, D., Valsasina, P., Rocca, M.A., Stromillo, M.L., Gallo, A., Enzinger, C., & Filippi, M. (2017). Hippocampal and deep gray matter nuclei atrophy is relevant for explaining cognitive impairment in MS: A multicenter study. AJNR American Journal of Neuroradiology, 38(1), 18–24. doi: 10.3174/ajnr.A4952 Google Scholar
das Nair, R., Martin, K.J., & Lincoln, N.B. (2016). Memory rehabilitation for people with multiple sclerosis. The Cochrane Database of Systematic Reviews, 3, CD008754. doi: 10.1002/14651858.CD008754.pub3 Google Scholar
DeLuca, J., Barbieri-Berger, S., & Johnson, S.K. (1994). The nature of memory impairments in multiple sclerosis: Acquisition versus retrieval. Journal of Clinical and Experimental Neuropsychology, 16(2), 183–189. doi: 10.1080/01688639408402629 Google Scholar
DeLuca, J., Leavitt, V.M., Chiaravalloti, N., & Wylie, G. (2013). Memory impairment in multiple sclerosis is due to a core deficit in initial learning. Journal of Neurology, 260(10), 2491–2496. doi: 10.1007/s00415–013-6990-3 Google Scholar
Feinstein, A., O’Connor, P., Akbar, N., Moradzadeh, L., Scott, C.J., & Lobaugh, N.J. (2010). Diffusion tensor imaging abnormalities in depressed multiple sclerosis patients. Multiple Sclerosis, 16(2), 189–196. doi: 10.1177/1352458509355461 Google Scholar
Feinstein, A., Roy, P., Lobaugh, N., Feinstein, K., O’Connor, P., & Black, S. (2004). Structural brain abnormalities in multiple sclerosis patients with major depression. Neurology, 62(4), 586–590.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(3), 255–265. doi: 10.1002/ana.21436 Google Scholar
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(3), 189–198.CrossRefGoogle ScholarPubMed
Geurts, J.J., Bo, L., Pouwels, P.J., Castelijns, J.A., Polman, C.H., & Barkhof, F. (2005). Cortical lesions in multiple sclerosis: Combined postmortem MR imaging and histopathology. AJNR American Journal of Neuroradiology, 26(3), 572–577.Google Scholar
Geurts, J.J., Bo, L., Roosendaal, S.D., Hazes, T., Daniels, R., Barkhof, F., & van der Valk, P. (2007). Extensive hippocampal demyelination in multiple sclerosis. Journal of Neuropathology and Experimental Neurology, 66(9), 819–827. doi: 10.1097/nen.0b013e3181461f54 Google Scholar
Geurts, J.J., Calabrese, M., Fisher, E., & Rudick, R.A. (2012). Measurement and clinical effect of grey matter pathology in multiple sclerosis. Lancet Neurology, 11(12), 1082–1092. doi: 10.1016/S1474-4422(12)70230-2 Google Scholar
Geurts, J.J., Pouwels, P.J., Uitdehaag, B.M., Polman, C.H., Barkhof, F., & Castelijns, J.A. (2005). Intracortical lesions in multiple sclerosis: Improved detection with 3D double inversion-recovery MR imaging. Radiology, 236(1), 254–260. doi: 10.1148/radiol.2361040450 Google Scholar
Geurts, J.J., Roosendaal, S.D., Calabrese, M., Ciccarelli, O., Agosta, F., Chard, D.T., & Group, M.S. (2011). Consensus recommendations for MS cortical lesion scoring using double inversion recovery MRI. Neurology, 76(5), 418–424. doi: 10.1212/WNL.0b013e31820a0cc4 Google Scholar
Gilmore, C.P., DeLuca, G.C., Bo, L., Owens, T., Lowe, J., Esiri, M.M., & Evangelou, N. (2009). Spinal cord neuronal pathology in multiple sclerosis. Brain Pathology, 19(4), 642–649. doi: 10.1111/j.1750-3639.2008.00228.x Google Scholar
Gilmore, C.P., Donaldson, I., Bo, L., Owens, T., Lowe, J., & Evangelou, N. (2009). Regional variations in the extent and pattern of grey matter demyelination in multiple sclerosis: A comparison between the cerebral cortex, cerebellar cortex, deep grey matter nuclei and the spinal cord. Journal of Neurology, Neurosurgery, and Psychiatry, 80(2), 182–187. doi: 10.1136/jnnp.2008.148767 Google Scholar
Gilmore, C.P., Geurts, J.J., Evangelou, N., Bot, J.C., van Schijndel, R.A., Pouwels, P.J., & Bo, L. (2009). Spinal cord grey matter lesions in multiple sclerosis detected by post-mortem high field MR imaging. Multiple Sclerosis, 15(2), 180–188. doi: 10.1177/1352458508096876 Google Scholar
Haider, L., Simeonidou, C., Steinberger, G., Hametner, S., Grigoriadis, N., Deretzi, G., & Frischer, J.M. (2014). Multiple sclerosis deep grey matter: The relation between demyelination, neurodegeneration, inflammation and iron. Journal of Neurology, Neurosurgery, and Psychiatry, 85(12), 1386–1395. doi: 10.1136/jnnp-2014-307712 Google Scholar
Houtchens, M.K., Benedict, R.H., Killiany, R., Sharma, J., Jaisani, Z., Singh, B., & Bakshi, R. (2007). Thalamic atrophy and cognition in multiple sclerosis. Neurology, 69(12), 1213–1223. doi: 10.1212/01.wnl.0000276992.17011.b5 Google Scholar
Howell, O.W., Reeves, C.A., Nicholas, R., Carassiti, D., Radotra, B., Gentleman, S.M., & Reynolds, R. (2011). Meningeal inflammation is widespread and linked to cortical pathology in multiple sclerosis. Brain, 134(Pt 9), 2755–2771. doi: 10.1093/brain/awr182 Google Scholar
Huitinga, I., De Groot, C.J., Van der Valk, P., Kamphorst, W., Tilders, F.J., & Swaab, D.F. (2001). Hypothalamic lesions in multiple sclerosis. Journal of Neuropathology and Experimental Neurology, 60(12), 1208–1218.Google Scholar
Kilsdonk, I.D., Jonkman, L.E., Klaver, R., van Veluw, S.J., Zwanenburg, J.J., Kuijer, J.P., & Geurts, J.J. (2016). Increased cortical grey matter lesion detection in multiple sclerosis with 7 T MRI: A post-mortem verification study. Brain, 139(Pt 5), 1472–1481. doi: 10.1093/brain/aww037 Google Scholar
Koini, M., Filippi, M., Rocca, M.A., Yousry, T., Ciccarelli, O., & Tedeschi, G., . . . MAGNIMS fMRI Study Group. (2016). Correlates of executive functions in multiple sclerosis based on structural and functional MR imaging: Insights from a multicenter study. Radiology, 280(3), 869–879. doi: 10.1148/radiol.2016151809 Google Scholar
Kooi, E.J., Strijbis, E.M., van der Valk, P., & Geurts, J.J. (2012). Heterogeneity of cortical lesions in multiple sclerosis: Clinical and pathologic implications. Neurology, 79(13), 1369–1376. doi: 10.1212/WNL.0b013e31826c1b1c Google Scholar
Krupp, L.B., Christodoulou, C., Melville, P., Scherl, W.F., MacAllister, W.S., & Elkins, L.E. (2004). Donepezil improved memory in multiple sclerosis in a randomized clinical trial. Neurology, 63(9), 1579–1585.Google Scholar
Krupp, L.B., Christodoulou, C., Melville, P., Scherl, W.F., Pai, L.Y., Muenz, L.R., & Wishart, H. (2011). Multicenter randomized clinical trial of donepezil for memory impairment in multiple sclerosis. Neurology, 76(17), 1500–1507. doi: 10.1212/WNL.0b013e318218107a Google Scholar
Kutzelnigg, A., Faber-Rod, J.C., Bauer, J., Lucchinetti, C.F., Sorensen, P.S., Laursen, H., & Lassmann, H. (2007). Widespread demyelination in the cerebellar cortex in multiple sclerosis. Brain Pathology, 17(1), 38–44. doi: 10.1111/j.1750-3639.2006.00041.x Google Scholar
Kutzelnigg, A., Lucchinetti, C.F., Stadelmann, C., Bruck, W., Rauschka, H., Bergmann, M., & Lassmann, H. (2005). Cortical demyelination and diffuse white matter injury in multiple sclerosis. Brain, 128(Pt 11), 2705–2712. doi: 10.1093/brain/awh641 Google Scholar
Langdon, D. (2016). A useful annual review of cognition in relapsing MS is beyond most neurologists - NO. Multiple Sclerosis, 22(6), 728–730. doi: 10.1177/1352458516640610 Google Scholar
Magliozzi, R., Howell, O., Vora, A., Serafini, B., Nicholas, R., Puopolo, M., & Aloisi, F. (2007). Meningeal B-cell follicles in secondary progressive multiple sclerosis associate with early onset of disease and severe cortical pathology. Brain, 130(Pt 4), 1089–1104. doi: 10.1093/brain/awm038 Google Scholar
Mainero, C., Louapre, C., Govindarajan, S.T., Gianni, C., Nielsen, A.S., Cohen-Adad, J., & Kinkel, R.P. (2015). A gradient in cortical pathology in multiple sclerosis by in vivo quantitative 7 T imaging. Brain, 138(Pt 4), 932–945. doi: 10.1093/brain/awv011 Google Scholar
Mike, A., Glanz, B.I., Hildenbrand, P., Meier, D., Bolden, K., Liguori, M., & Guttmann, C.R. (2011). Identification and clinical impact of multiple sclerosis cortical lesions as assessed by routine 3T MR imaging. AJNR American Journal of Neuroradiology, 32(3), 515–521. doi: 10.3174/ajnr.A2340 Google Scholar
Minagar, A., Barnett, M.H., Benedict, R.H., Pelletier, D., Pirko, I., Sahraian, M.A., & Zivadinov, R. (2013). The thalamus and multiple sclerosis: Modern views on pathologic, imaging, and clinical aspects. Neurology, 80(2), 210–219. doi: 10.1212/WNL.0b013e31827b910b Google Scholar
Morrow, S.A., Jurgensen, S., Forrestal, F., Munchauer, F.E., & Benedict, R.H. (2011). Effects of acute relapses on neuropsychological status in multiple sclerosis patients. Journal of Neurology, 258(9), 1603–1608. doi: 10.1007/s00415-011-5975-3 Google Scholar
Morrow, S.A., Smerbeck, A., Patrick, K., Cookfair, D., Weinstock-Guttman, B., & Benedict, R.H. (2013). Lisdexamfetamine dimesylate improves processing speed and memory in cognitively impaired MS patients: A phase II study. Journal of Neurology, 260(2), 489–497. doi: 10.1007/s00415-012-6663-7 Google Scholar
Morrow, S.A., Weinstock-Guttman, B., Munschauer, F.E., Hojnacki, D., & Benedict, R.H. (2009). Subjective fatigue is not associated with cognitive impairment in multiple sclerosis: Cross-sectional and longitudinal analysis. Multiple Sclerosis, 15(8), 998–1005. doi: 10.1177/1352458509106213 Google Scholar
Nelson, F., Akhtar, M.A., Zuniga, E., Perez, C.A., Hasan, K.M., Wilken, J., & Steinberg, J.L. (2017). Novel fMRI working memory paradigm accurately detects cognitive impairment in multiple sclerosis. Multiple Sclerosis, 23(6), 836–847. doi: 10.1177/1352458516666186 CrossRefGoogle ScholarPubMed
Nelson, F., Datta, S., Garcia, N., Rozario, N.L., Perez, F., Cutter, G., & Wolinsky, J.S. (2011). Intracortical lesions by 3T magnetic resonance imaging and correlation with cognitive impairment in multiple sclerosis. Multiple Sclerosis, 17(9), 1122–1129. doi: 10.1177/1352458511405561 Google Scholar
Nelson, F., Poonawalla, A., Datta, S., Wolinsky, J., & Narayana, P. (2014). Is 3D MPRAGE better than the combination DIR/PSIR for cortical lesion detection at 3T MRI? Multiple Sclerosis and Related Disorders, 3(2), 253–257. doi: 10.1016/j.msard.2013.10.002 Google Scholar
Nelson, F., Poonawalla, A., Hou, P., Wolinsky, J.S., & Narayana, P.A. (2008). 3D MPRAGE improves classification of cortical lesions in multiple sclerosis. Multiple Sclerosis, 14(9), 1214–1219. doi: 10.1177/1352458508094644 Google Scholar
Nelson, F., Poonawalla, A.H., Hou, P., Huang, F., Wolinsky, J.S., & Narayana, P.A. (2007). Improved identification of intracortical lesions in multiple sclerosis with phase-sensitive inversion recovery in combination with fast double inversion recovery MR imaging. AJNR American Journal of Neuroradiology, 28(9), 1645–1649. doi: 10.3174/ajnr.A0645 Google Scholar
Nielsen, A.S., Kinkel, R.P., Tinelli, E., Benner, T., Cohen-Adad, J., & Mainero, C. (2012). Focal cortical lesion detection in multiple sclerosis: 3 Tesla DIR versus 7 Tesla FLASH-T2. Journal of Magnetic Resonance Imaging, 35(3), 537–542. doi: 10.1002/jmri.22847 Google Scholar
O’Brien, A., Gaudino-Goering, E., Shawaryn, M., Komaroff, E., Moore, N.B., & DeLuca, J. (2007). Relationship of the Multiple Sclerosis Neuropsychological Questionnaire (MSNQ) to functional, emotional, and neuropsychological outcomes. Archives of Clinical Neuropsychology, 22(8), 933–948. doi: 10.1016/j.acn.2007.07.002 Google Scholar
Pardini, M., Uccelli, A., Grafman, J., Yaldizli, O., Mancardi, G., & Roccatagliata, L. (2014). Isolated cognitive relapses in multiple sclerosis. Journal of Neurology, Neurosurgery, and Psychiatry, 85(9), 1035–1037. doi: 10.1136/jnnp2013-307275 Google Scholar
Peterson, J.W., Bo, L., Mork, S., Chang, A., & Trapp, B.D. (2001). Transected neurites, apoptotic neurons, and reduced inflammation in cortical multiple sclerosis lesions. Annals of Neurology, 50(3), 389–400.Google Scholar
Popescu, V., Klaver, R., Voorn, P., Galis-de Graaf, Y., Knol, D.L., Twisk, J.W., & Geurts, J.J. (2015). What drives MRI-measured cortical atrophy in multiple sclerosis? Multiple Sclerosis, 21(10), 1280–1290. doi: 10.1177/1352458514562440 Google Scholar
Preziosa, P., Rocca, M.A., Pagani, E., Stromillo, M.L., Enzinger, C., Gallo, A., & Group, M.S. (2016). Structural MRI correlates of cognitive impairment in patients with multiple sclerosis: A Multicenter Study. Human Brain Mapping, 37(4), 1627–1644. doi: 10.1002/hbm.23125 Google Scholar
Rao, S.M. (1991). A manual for the brief, repeatable battery of neuropsychological tests in multiple sclerosis. New York: National Multiple Sclerosis Society.Google Scholar
Rao, S.M. (1995). Neuropsychology of multiple sclerosis. Current Opinion in Neurology, 8(3), 216–220.Google Scholar
Rao, S.M., Glatt, S., Hammeke, T.A., McQuillen, M.P., Khatri, B.O., Rhodes, A.M., & Pollard, S. (1985). Chronic progressive multiple sclerosis. Relationship between cerebral ventricular size and neuropsychological impairment. Archives of Neurology, 42(7), 678–682.Google Scholar
Rao, S.M., Leo, G.J., Bernardin, L., & Unverzagt, F. (1991). Cognitive dysfunction in multiple sclerosis. I. Frequency, patterns, and prediction. Neurology, 41(5), 685–691.Google Scholar
Rao, S.M., Leo, G.J., Ellington, L., Nauertz, T., Bernardin, L., & Unverzagt, F. (1991). Cognitive dysfunction in multiple sclerosis. II. Impact on employment and social functioning. Neurology , 41(5), 692–696.Google Scholar
Rao, S.M., Leo, G.J., Haughton, V.M., St Aubin-Faubert, P., & Bernardin, L. (1989). Correlation of magnetic resonance imaging with neuropsychological testing in multiple sclerosis. Neurology, 39(2 Pt 1), 161–166.Google Scholar
Rao, S.M., Leo, G.J., & St Aubin-Faubert, P. (1989). On the nature of memory disturbance in multiple sclerosis. Journal of Clinical and Experimental Neuropsychology, 11(5), 699–712. doi: 10.1080/01688638908400926 Google Scholar
Rao, S.M., Losinski, G., Mourany, L., Schindler, D., Mamone, B., Reece, C., & Alberts, J. (2017). Processing speed test: Validation of a self-administered, iPad(R)-based tool for screening cognitive dysfunction in a clinic setting. Multiple Sclerosis, 1352458516688955. doi: 10.1177/1352458516688955 Google Scholar
Rao, S.M., St Aubin-Faubert, P., & Leo, G.J. (1989). Information processing speed in patients with multiple sclerosis. Journal of Clinical and Experimental Neuropsychology, 11(4), 471–477. doi: 10.1080/01688638908400907 Google Scholar
Riccitelli, G., Rocca, M.A., Pagani, E., Rodegher, M.E., Rossi, P., Falini, A., & Filippi, M. (2011). Cognitive impairment in multiple sclerosis is associated to different patterns of gray matter atrophy according to clinical phenotype. Human Brain Mapping, 32(10), 1535–1543. doi: 10.1002/hbm.21125 Google Scholar
Rocca, M.A., Absinta, M., Amato, M.P., Moiola, L., Ghezzi, A., Veggiotti, P., & Filippi, M. (2014). Posterior brain damage and cognitive impairment in pediatric multiple sclerosis. Neurology, 82(15), 1314–1321. doi: 10.1212/WNL.0000000000000309 Google Scholar
Rocca, M.A., Pravata, E., Valsasina, P., Radaelli, M., Colombo, B., Vacchi, L., & Filippi, M. (2015). Hippocampal-DMN disconnectivity in MS is related to WM lesions and depression. Human Brain Mapping, 36(12), 5051–5063. doi: 10.1002/hbm.22992 Google Scholar
Romero, K., Shammi, P., & Feinstein, A. (2015). Neurologists accuracy in predicting cognitive impairment in multiple sclerosis. Multiple Sclerosis and Related Disorders, 4(4), 291–295. doi: 10.1016/j.msard.2015.05.009 Google Scholar
Roosendaal, S.D., Moraal, B., Pouwels, P.J., Vrenken, H., Castelijns, J.A., Barkhof, F., &Geurts, J.J. (2009). Accumulation of cortical lesions in MS: Relation with cognitive impairment. Multiple Sclerosis, 15(6), 708–714. doi: 10.1177/1352458509102907 CrossRefGoogle ScholarPubMed
Roosendaal, S.D., Moraal, B., Vrenken, H., Castelijns, J.A., Pouwels, P.J., Barkhof, F., &Geurts, J.J. (2008). In vivo MR imaging of hippocampal lesions in multiple sclerosis. Journal of Magnetic Resonance Imaging, 27(4), 726–731. doi: 10.1002/jmri.21294 Google Scholar
Roy, S., Schwartz, C.E., Duberstein, P., Dwyer, M.G., Zivadinov, R., Bergsland, N., & Benedict, R.H. (2016). Synergistic Effects of Reserve and Adaptive Personality in Multiple Sclerosis. Journal of the International Neuropsychological Society, 22(9), 920–927. doi: 10.1017/S1355617716000333 Google Scholar
Sandroff, B.M., Motl, R.W., Scudder, M.R., & DeLuca, J. (2016). Systematic, evidence-based review of exercise, physical activity, and physical fitness effects on cognition in persons with multiple sclerosis. Neuropsychology Review, 26(3), 271–294. doi: 10.1007/s11065-016-9324-2 Google Scholar
Sandroff, B.M., Schwartz, C.E., & DeLuca, J. (2016). Measurement and maintenance of reserve in multiple sclerosis. Journal of Neurology, 263(11), 2158–2169. doi: 10.1007/s00415-016-8104-5 Google Scholar
Sandry, J., Akbar, N., Zuppichini, M., & DeLuca, J. (2016). Cognitive rehabilitation in multiple sclerosis. In M.-K. Sun (Ed.), Research progress in Alzheimer’s disease and Dementia, (Vol. 6, pp. 195–233). New York: Nova Science Publisher.Google Scholar
Schoonheim, M.M., Popescu, V., Rueda Lopes, F.C., Wiebenga, O.T., Vrenken, H., Douw, L., & Barkhof, F. (2012). Subcortical atrophy and cognition: Sex effects in multiple sclerosis. Neurology, 79(17), 1754–1761. doi: 10.1212/WNL.0b013e3182703f46 CrossRefGoogle ScholarPubMed
Seewann, A., Vrenken, H., Kooi, E.J., van der Valk, P., Knol, D.L., Polman, C.H., & Geurts, J.J. (2011). Imaging the tip of the iceberg: Visualization of cortical lesions in multiple sclerosis. Multiple Sclerosis, 17(10), 1202–1210. doi: 10.1177/1352458511406575 Google Scholar
Sethi, V., Yousry, T.A., Muhlert, N., Ron, M., Golay, X., Wheeler-Kingshott, C., & Chard, D.T. (2012). Improved detection of cortical MS lesions with phase-sensitive inversion recovery MRI. Journal of Neurology, Neurosurgery, and Psychiatry, 83(9), 877–882. doi: 10.1136/jnnp-2012-303023 Google Scholar
Simons, D.J., Boot, W.R., Charness, N., Gathercole, S.E., Chabris, C.F., Hambrick, D.Z., &Stine-Morrow, E.A. (2016). Do “brain-training” programs work? Psychological Science in the Public Interest, 17(3), 103–186. doi: 10.1177/1529100616661983 Google Scholar
Sivaraman, I., & Moodley, M. (2016). Multiple sclerosis in the very young: A case report and review of the literature. Neurodegenerative Disease Management, 6(1), 31–36. doi: 10.2217/nmt.15.70 Google Scholar
Smith, A. (1982). Symbol Digit Modalities Test: Manual. Los Angeles: Western Psychological Services.Google Scholar
Steenwijk, M.D., Geurts, J.J., Daams, M., Tijms, B.M., Wink, A.M., Balk, L.J., & Pouwels, P.J. (2016). Cortical atrophy patterns in multiple sclerosis are non-random and clinically relevant. Brain, 139(Pt 1), 115–126. doi: 10.1093/brain/awv337 Google Scholar
Stuifbergen, A.K., Becker, H., Perez, F., Morison, J., Kullberg, V., & Todd, A. (2012). A randomized controlled trial of a cognitive rehabilitation intervention for persons with multiple sclerosis. Clinical Rehabilitation, 26(10), 882–893. doi: 10.1177/0269215511434997 Google Scholar
Sumowski, J.F., Chiaravalloti, N., Wylie, G., & Deluca, J. (2009). Cognitive reserve moderates the negative effect of brain atrophy on cognitive efficiency in multiple sclerosis. Journal of the International Neuropsychological Society, 15(4), 606–612. doi: 10.1017/S1355617709090912 Google Scholar
Till, C., Racine, N., Araujo, D., Narayanan, S., Collins, D.L., Aubert-Broche, B., & Banwell, B. (2013). Changes in cognitive performance over a 1-year period in children and adolescents with multiple sclerosis. Neuropsychology, 27(2), 210–219. doi: 10.1037/a0031665 Google Scholar
Tillema, J.M., Hulst, H.E., Rocca, M.A., Vrenken, H., Steenwijk, M.D., & Damjanovic, D., . . . MAGNIMS Study Group. (2016). Regional cortical thinning in multiple sclerosis and its relation with cognitive impairment: A multicenter study. Multiple Sclerosis, 22(7), 901–909. doi: 10.1177/1352458515607650 Google Scholar
van Horssen, J., Brink, B.P., de Vries, H.E., van der Valk, P., & Bo, L. (2007). The blood-brain barrier in cortical multiple sclerosis lesions. Journal of Neuropathology and Experimental Neurology, 66(4), 321–328. doi: 10.1097/nen.0b013e318040b2de Google Scholar
Vercellino, M., Masera, S., Lorenzatti, M., Condello, C., Merola, A., Mattioda, A., & Cavalla, P. (2009). Demyelination, inflammation, and neurodegeneration in multiple sclerosis deep gray matter. Journal of Neuropathology and Experimental Neurology, 68(5), 489–502. doi: 10.1097/NEN.0b013e3181a19a5a Google Scholar
Vercellino, M., Plano, F., Votta, B., Mutani, R., Giordana, M.T., & Cavalla, P. (2005). Grey matter pathology in multiple sclerosis. Journal of Neuropathology and Experimental Neurology, 64(12), 1101–1107.Google Scholar
Wegner, C., Esiri, M.M., Chance, S.A., Palace, J., & Matthews, P.M. (2006). Neocortical neuronal, synaptic, and glial loss in multiple sclerosis. Neurology, 67(6), 960–967. doi: 10.1212/01.wnl.0000237551.26858.39 Google Scholar
Zivadinov, R., Havrdova, E., Bergsland, N., Tyblova, M., Hagemeier, J., Seidl, Z., & Horakova, D. (2013). Thalamic atrophy is associated with development of clinically definite multiple sclerosis. Radiology, 268(3), 831–841. doi: 10.1148/radiol.13122424 Google Scholar