Cognitive impairment in multiple sclerosis: clinical management, MRI, and therapeutic avenues

Ralph H B Benedict, Maria Pia Amato, John DeLuca, Jeroen J G Geurts, Ralph H B Benedict, Maria Pia Amato, John DeLuca, Jeroen J G Geurts

Abstract

Multiple sclerosis is a chronic, demyelinating disease of the CNS. Cognitive impairment is a sometimes neglected, yet common, sign and symptom with a profound effect on instrumental activities of daily living. The prevalence of cognitive impairment in multiple sclerosis varies across the lifespan and might be difficult to distinguish from other causes in older age. MRI studies show that widespread changes to brain networks contribute to cognitive dysfunction, and grey matter atrophy is an early sign of potential future cognitive decline. Neuropsychological research suggests that cognitive processing speed and episodic memory are the most frequently affected cognitive domains. Narrowing evaluation to these core areas permits brief, routine assessment in the clinical setting. Owing to its brevity, reliability, and sensitivity, the Symbol Digit Modalities Test, or its computer-based analogues, can be used to monitor episodes of acute disease activity. The Symbol Digit Modalities Test can also be used in clinical trials, and data increasingly show that cognitive processing speed and memory are amenable to cognitive training interventions.

Copyright © 2020 Elsevier Ltd. All rights reserved.

Figures

Figure 1
Figure 1
SDMT decline and recovery curves in patients with cognitive relapse Change from baseline in the difference between relapsing (defined by clinical diagnosis of gadolinium enhancement on MRI) patients and stable patients in raw SDMT score. For each study, the mean of the stable control group is subtracted from the mean SDMT score of the relapsing group. The relapsing and stable groups are generally well matched at baseline with the difference in scores ranging from −0·7 to 0·6. In each study, the relapsing group recovers after the relapse timepoint, to varying degrees, seldom returning to a difference score of 0. SDMT=Symbol Digit Modalities Test.
Figure 2
Figure 2
Brain MRI of a 53-year-old man with relapsing-remitting multiple sclerosis Contrast axial brain MRI scan images obtained from the patient (described in panel 3) during and after relapse with documented cognitive impairment. MRI was obtained on a 3·0T GE Signa Excite HD 12 Twin-Speed scanner (GE, Milwaukee, WI, USA). At both timepoints, T1-weighted images were acquired with a single-dose intravenous bolus of 0·1 mmol/kg gadolinium-pentetic acid 5 min after injection. The lesions that appear by use of this method represent a breakdown of the blood–brain barrier, allowing myelin-reactive T cells to enter the CNS and cause a cascade of inflammatory changes that lead to oedema, demyelination, and axonal loss. During the relapse timepoint, several gadolinium-enhancing MRI brain lesions of 0·8 cm3 or greater volume were present (arrows). In total, 13 lesions were identified but not all are visible in these sections. The gadolinium-enhancing lesions were no longer observable at the recovery timepoint, indicating a recovery of the blood–brain barrier, although some tissue damage (not shown) might persist.

References

    1. Benedict RHB, DeLuca J, Enzinger C, Geurts JJG, Krupp LB, Rao SM. Neuropsychology of multiple sclerosis: looking back and moving forward. J Int Neuropsychol Soc. 2017;23:832–842.
    1. Glanz BI, Holland CM, Gauthier SA, et al. Cognitive dysfunction in patients with clinically isolated syndromes or newly diagnosed multiple sclerosis. Mult Scler. 2007;13:1004–1010.
    1. Rao SM, Leo GJ, Bernardin L, Unverzagt F. Cognitive dysfunction in multiple sclerosis. I. Frequency, patterns, and prediction. Neurology. 1991;41:685–691.
    1. Benedict RHB, Cookfair D, Gavett R, et al. Validity of the Minimal Assessment of Cognitive Function In Multiple Sclerosis (MACFIMS) J Int Neuropsychol Soc. 2006;12:549–558.
    1. Ruano L, Portaccio E, Goretti B, et al. Age and disability drive cognitive impairment in multiple sclerosis across disease subtypes. Mult Scler. 2017;23:1258–1267.
    1. Amato MP, Hakiki B, Goretti B, et al. Association of MRI metrics and cognitive impairment in radiologically isolated syndromes. Neurology. 2012;78:309–314.
    1. McKay KA, Manouchehrinia A, Berrigan L, Fisk JD, Olsson T, Hillert J. Long-term cognitive outcomes in patients with pediatric-onset vs adult-onset multiple sclerosis. JAMA Neurol. 2019;76:1028–1034.
    1. Duquin JA, Parmenter BA, Benedict RH. Influence of recruitment and participation bias in neuropsychological research among MS patients. J Int Neuropsychol Soc. 2008;14:494–498.
    1. Jakimovski D, Weinstock-Guttman B, Roy S, et al. Cognitive profiles of aging in multiple sclerosis. Front Aging Neurosci. 2019;11:105.
    1. Brandstadter R, Fabian M, Leavitt VM, et al. Word-finding difficulty is a prevalent disease-related deficit in early multiple sclerosis. Mult Scler. 2019 doi: 10.1177/1352458519881760. published online Nov 19.
    1. Johnen A, Landmeyer NC, Bürkner PC, Wiendl H, Meuth SG, Holling H. Distinct cognitive impairments in different disease courses of multiple sclerosis: a systematic review and meta-analysis. Neurosci Biobehav Rev. 2017;83:568–578.
    1. De Stefano N, Giorgio A, Tintoré M, et al. Radiologically isolated syndrome or subclinical multiple sclerosis: MAGNIMS consensus recommendations. Mult Scler. 2018;24:214–221.
    1. Cortese M, Riise T, Bjørnevik K, et al. Preclinical disease activity in multiple sclerosis: a prospective study of cognitive performance prior to first symptom. Ann Neurol. 2016;80:616–624.
    1. Branco M, Ruano L, Portaccio E, et al. Aging with multiple sclerosis: prevalence and profile of cognitive impairment. Neurol Sci. 2019;40:1651–1657.
    1. Portaccio E, Stromillo ML, Goretti B, et al. Neuropsychological and MRI measures predict short-term evolution in benign multiple sclerosis. Neurology. 2009;73:498–503.
    1. Razzolini L, Portaccio E, Stromillo ML, et al. The dilemma of benign multiple sclerosis: can we predict the risk of losing the “benign status”? A 12-year follow-up study. Mult Scler Relat Disord. 2018;26:71–73.
    1. Rovaris M, Riccitelli G, Judica E, et al. Cognitive impairment and structural brain damage in benign multiple sclerosis. Neurology. 2008;71:1521–1526.
    1. Amato MP, Krupp LB, Charvet LE, Penner I, Till C. Pediatric multiple sclerosis: cognition and mood. Neurology. 2016;87(suppl 2):S82–S87.
    1. Amato MP, Goretti B, Ghezzi A, et al. Cognitive and psychosocial features of childhood and juvenile MS. Neurology. 2008;70:1891–1897.
    1. Charvet LE, O'Donnell EH, Belman AL, et al. Longitudinal evaluation of cognitive functioning in pediatric multiple sclerosis: report from the US Pediatric Multiple Sclerosis Network. Mult Scler. 2014;20:1502–1510.
    1. Amato MP, Goretti B, Ghezzi A, et al. Neuropsychological features in childhood and juvenile multiple sclerosis: five-year follow-up. Neurology. 2014;83:1432–1438.
    1. Till C, Racine N, Araujo D, et al. Changes in cognitive performance over a 1-year period in children and adolescents with multiple sclerosis. Neuropsychology. 2013;27:210–219.
    1. Waldman A, Ness J, Pohl D, et al. Pediatric multiple sclerosis: clinical features and outcome. Neurology. 2016;87(suppl 2):S74–S81.
    1. Wimo A, Winblad B, Shah SN, Chin W, Zhang R, McRae T. Impact of donepezil treatment for Alzheimer's disease on caregiver time. Curr Med Res Opin. 2004;20:1221–1225.
    1. Krupp LB, Christodoulou C, Melville P, et al. Multicenter randomized clinical trial of donepezil for memory impairment in multiple sclerosis. Neurology. 2011;76:1500–1507.
    1. Smith EE, Beaudin AE. New insights into cerebral small vessel disease and vascular cognitive impairment from MRI. Curr Opin Neurol. 2018;31:36–43.
    1. Marrie RA, Fisk J, Tremlett H, et al. Differing trends in the incidence of vascular comorbidity in MS and the general population. Neurol Clin Pract. 2016;6:120–128.
    1. Foong J, Rozewicz L, Chong WK, Thompson AJ, Miller DH, Ron MA. A comparison of neuropsychological deficits in primary and secondary progressive multiple sclerosis. J Neurol. 2000;247:97–101.
    1. Comi G, Rovaris M, Leocani L, Martinelli V, Filippi M. Assessment of the damage of the cerebral hemispheres in MS using neuroimaging techniques. J Neurol Sci. 2000;172(suppl 1):S63–S66.
    1. Rovaris M, Iannucci G, Falautano M, et al. Cognitive dysfunction in patients with mildly disabling relapsing-remitting multiple sclerosis: an exploratory study with diffusion tensor MR imaging. J Neurol Sci. 2002;195:103–109.
    1. Deloire MS, Salort E, Bonnet M, et al. Cognitive impairment as marker of diffuse brain abnormalities in early relapsing remitting multiple sclerosis. J Neurol Neurosurg Psychiatry. 2005;76:519–526.
    1. Vrenken H, Geurts JJ, Knol DL, et al. Whole-brain T1 mapping in multiple sclerosis: global changes of normal-appearing gray and white matter. Radiology. 2006;240:811–820.
    1. Geurts JJ, Pouwels PJ, Uitdehaag BM, Polman CH, Barkhof F, Castelijns JA. Intracortical lesions in multiple sclerosis: improved detection with 3D double inversion-recovery MR imaging. Radiology. 2005;236:254–260.
    1. Nelson F, Datta S, Garcia N, et al. Intracortical lesions by 3T magnetic resonance imaging and correlation with cognitive impairment in multiple sclerosis. Mult Scler. 2011;17:1122–1129.
    1. Houtchens MK, Benedict RHB, Killiany R, et al. Thalamic atrophy and cognition in multiple sclerosis. Neurology. 2007;69:1213–1223.
    1. Benedict RH, Ramasamy D, Munschauer F, et al. Memory impairment in multiple sclerosis: correlation with deep grey matter and mesial temporal atrophy. J Neurol Neurosurg Psychiatry. 2009;80:201–206.
    1. Amato MP, Bartolozzi ML, Zipoli V, et al. Neocortical volume decrease in relapsing-remitting MS patients with mild cognitive impairment. Neurology. 2004;63:89–93.
    1. Bisecco A, Rocca MA, Pagani E, et al. Connectivity-based parcellation of the thalamus in multiple sclerosis and its implications for cognitive impairment: a multicenter study. Hum Brain Mapp. 2015;36:2809–2825.
    1. Benedict RH, Hulst HE, Bergsland N, et al. Clinical significance of atrophy and white matter mean diffusivity within the thalamus of multiple sclerosis patients. Mult Scler. 2013;19:1478–1484.
    1. Sicotte NL, Kern KC, Giesser BS, et al. Regional hippocampal atrophy in multiple sclerosis. Brain. 2008;131:1134–1141.
    1. Hulst HE, Schoonheim MM, Roosendaal SD, et al. Functional adaptive changes within the hippocampal memory system of patients with multiple sclerosis. Hum Brain Mapp. 2012;33:2268–2280.
    1. Geurts JJ, Bö L, Roosendaal SD, et al. Extensive hippocampal demyelination in multiple sclerosis. J Neuropathol Exp Neurol. 2007;66:819–827.
    1. Meijer KA, Eijlers AJC, Douw L, et al. Increased connectivity of hub networks and cognitive impairment in multiple sclerosis. Neurology. 2017;88:2107–2114.
    1. d'Ambrosio A, Valsasina P, Gallo A, et al. Reduced dynamics of functional connectivity and cognitive impairment in multiple sclerosis. Mult Scler. 2020;26:476–488.
    1. Rocca MA, Valsasina P, Absinta M, et al. Default-mode network dysfunction and cognitive impairment in progressive MS. Neurology. 2010;74:1252–1259.
    1. Tona F, Petsas N, Sbardella E, et al. Multiple sclerosis: altered thalamic resting-state functional connectivity and its effect on cognitive function. Radiology. 2014;271:814–821.
    1. Meijer KA, van Geest Q, Eijlers AJC, Geurts JJG, Schoonheim MM, Hulst HE. Is impaired information processing speed a matter of structural or functional damage in MS? Neuroimage Clin. 2018;20:844–850.
    1. Eijlers AJC, van Geest Q, Dekker I, et al. Predicting cognitive decline in multiple sclerosis: a 5-year follow-up study. Brain. 2018;141:2605–2618.
    1. Smith A. Western Psychological Services; Los Angeles, CA: 1982. Symbol Digit Modalities Test: manual.
    1. Rao SM. National Multiple Sclerosis Society; New York, NY: 1991. A manual for the brief, repeatable battery of neuropsychological tests in multiple sclerosis.
    1. Benedict RH, DeLuca J, Phillips G, LaRocca N, Hudson LD, Rudick R. Validity of the Symbol Digit Modalities Test as a cognition performance outcome measure for multiple sclerosis. Mult Scler. 2017;23:721–733.
    1. Langdon DW, Amato MP, Boringa J, et al. Recommendations for a Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) Mult Scler. 2012;18:891–898.
    1. Benedict RH, Smerbeck A, Parikh R, Rodgers J, Cadavid D, Erlanger D. Reliability and equivalence of alternate forms for the Symbol Digit Modalities Test: implications for multiple sclerosis clinical trials. Mult Scler. 2012;18:1320–1325.
    1. Sumowski JF, Benedict R, Enzinger C, et al. Cognition in multiple sclerosis: state of the field and priorities for the future. Neurology. 2018;90:278–288.
    1. Rey A. L'examen psychologique dans les cas d'encephalopathie traumatique. Arch Psychol. 1941;28:286–340.
    1. Delis DC, Kramer JH, Kaplan E, Ober BA. 2nd edn. The Psychological Corporation; San Antonio, TX: 2000. Califorina Verbal Learning Test.
    1. Benedict RHB. Psychological Assessment Resources; Odessa, FL: 1997. Brief Visuospatial Memory Test revised professional manual.
    1. Stegen S, Stepanov I, Cookfair D, et al. Validity of the California Verbal Learning Test-II in multiple sclerosis. Clin Neuropsychol. 2010;24:189–202.
    1. Benedict RHB, Drake AS, Irwin LN, et al. Benchmarks of meaningful impairment on the MSFC and BICAMS. Mult Scler. 2016;22:1874–1882.
    1. Goverover Y, Chiaravalloti N, DeLuca J. Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) and performance of everyday life tasks: actual reality. Mult Scler. 2016;22:544–550.
    1. LaRocca NG, Hudson LD, Rudick R, et al. The MSOAC approach to developing performance outcomes to measure and monitor multiple sclerosis disability. Mult Scler. 2018;24:1469–1484.
    1. Motl RW, Cohen JA, Benedict R, et al. Validity of the timed 25-foot walk as an ambulatory performance outcome measure for multiple sclerosis. Mult Scler. 2017;23:704–710.
    1. Feys P, Lamers I, Francis G, et al. The Nine-Hole Peg Test as a manual dexterity performance measure for multiple sclerosis. Mult Scler. 2017;23:711–720.
    1. Balcer LJ, Raynowska J, Nolan R, et al. Validity of low-contrast letter acuity as a visual performance outcome measure for multiple sclerosis. Mult Scler. 2017;23:734–747.
    1. Goldman MD, LaRocca NG, Rudick RA, et al. Evaluation of multiple sclerosis disability outcome measures using pooled clinical trial data. Neurology. 2019;93:e1921–e1931.
    1. Corfield F, Langdon D. A systematic review and meta-analysis of the Brief Cognitive Assessment for Multiple Sclerosis (BICAMS) Neurol Ther. 2018;7:287–306.
    1. Wojcik CM, Beier M, Costello K, et al. Computerized neuropsychological assessment devices in multiple sclerosis: a systematic review. Mult Scler. 2019;25:1848–1869.
    1. Wojcik CM, Rao SM, Schembri AJ, et al. Necessity of technicians for computerized neuropsychological assessment devices in multiple sclerosis. Mult Scler. 2020;26:109–113.
    1. Mahad DH, Trapp BD, Lassmann H. Pathological mechanisms in progressive multiple sclerosis. Lancet Neurol. 2015;14:183–193.
    1. Healy BC, Barker L, Bakshi R, et al. Trajectories of Symbol Digit Modalities Test performance in individuals with multiple sclerosis. Mult Scler. 2020 doi: 10.1177/1352458520913439. published online March 31.
    1. Bergsland N, Zivadinov R, Dwyer MG, Weinstock-Guttman B, Benedict RH. Localized atrophy of the thalamus and slowed cognitive processing speed in MS patients. Mult Scler. 2016;22:1327–1336.
    1. Benedict RH, Morrow SA, Weinstock Guttman B, Cookfair D, Schretlen DJ. Cognitive reserve moderates decline in information processing speed in multiple sclerosis patients. J Int Neuropsychol Soc. 2010;16:829–835.
    1. Fuchs TA, Wojcik C, Wilding GE, et al. Trait conscientiousness predicts rate of longitudinal SDMT decline in multiple sclerosis. Mult Scler. 2020;26:245–252.
    1. Lublin FD, Reingold SC, Cohen JA, et al. Defining the clinical course of multiple sclerosis: the 2013 revisions. Neurology. 2014;83:278–286.
    1. Berkovich RR. Acute multiple sclerosis relapse. Continuum (Minneap Minn) 2016;22:799–814.
    1. Lattanzi S, Cagnetti C, Danni M, Provinciali L, Silvestrini M. Oral and intravenous steroids for multiple sclerosis relapse: a systematic review and meta-analysis. J Neurol. 2017;264:1697–1704.
    1. Comi G, Radaelli M. Oral corticosteroids for multiple sclerosis relapse. Lancet. 2015;386:937–939.
    1. Berkovich R, Bakshi R, Amezcua L, et al. Adrenocorticotropic hormone versus methylprednisolone added to interferon β in patients with multiple sclerosis experiencing breakthrough disease: a randomized, rater-blinded trial. Ther Adv Neurol Disord. 2017;10:3–17.
    1. Prado FM, Kosac VA, Dib JG. Cognitive relapse in multiple sclerosis: report of 3 cases. Mult Scler J. 2012;18:1830–1831.
    1. Patzold T, Schwengelbeck M, Ossege LM, Malin JP, Sindern E. Changes of the MS functional composite and EDSS during and after treatment of relapses with methylprednisolone in patients with multiple sclerosis. Acta Neurol Scand. 2002;105:164–168.
    1. Foong J, Rozewicz L, Quaghebeur G, Thompson AJ, Miller DH, Ron MA. Neuropsychological deficits in multiple sclerosis after acute relapse. J Neurol Neurosurg Psychiatry. 1998;64:529–532.
    1. Ozakbas S, Cagiran I, Ormeci B, Idiman E. Correlations between multiple sclerosis functional composite, expanded disability status scale and health-related quality of life during and after treatment of relapses in patients with multiple sclerosis. J Neurol Sci. 2004;218:3–7.
    1. Morrow SA, Jurgensen S, Forrestal F, Munchauer FE, Benedict RH. Effects of acute relapses on neuropsychological status in multiple sclerosis patients. J Neurol. 2011;258:1603–1608.
    1. Benedict RH, Morrow S, Rodgers J, et al. Characterizing cognitive function during relapse in multiple sclerosis. Mult Scler. 2014;20:1745–1752.
    1. Benedict RH, Pol J, Yasin F, et al. Recovery of cognitive function after relapse in multiple sclerosis. Mult Scler. 2020 doi: 10.1177/1352458519898108. published online Jan 23.
    1. Pardini M, Uccelli A, Grafman J, Yaldizli Ö, Mancardi G, Roccatagliata L. Isolated cognitive relapses in multiple sclerosis. J Neurol Neurosurg Psychiatry. 2014;85:1035–1037.
    1. Meli R, Roccatagliata L, Capello E, et al. Ecological impact of isolated cognitive relapses in MS. Mult Scler. 2020;26:114–117.
    1. Benedict RHB, Cox D, Thompson LL, Foley F, Weinstock-Guttman B, Munschauer F. Reliable screening for neuropsychological impairment in multiple sclerosis. Mult Scler. 2004;10:675–678.
    1. Giedraitiene N, Kaubrys G, Kizlaitiene R. Cognition during and after multiple sclerosis relapse as assessed with the Brief International Cognitive Assessment for Multiple Sclerosis. Sci Rep. 2018;8
    1. Giedraitiene N, Kaubrys G. Distinctive pattern of cognitive disorders during multiple sclerosis relapse and recovery based on computerized CANTAB tests. Front Neurol. 2019;10:572.
    1. Kalincik T, Manouchehrinia A, Sobisek L, et al. Towards personalized therapy for multiple sclerosis: prediction of individual treatment response. Brain. 2017;140:2426–2443.
    1. Landmeyer NC, Bürkner PC, Wiendl H, et al. Disease-modifying treatments and cognition in relapsing-remitting multiple sclerosis: a meta-analysis. Neurology. 2020;94:e2373–e2383.
    1. Benedict RH, Cohan S, Lynch SG, et al. Improved cognitive outcomes in patients with relapsing-remitting multiple sclerosis treated with daclizumab beta: results from the DECIDE study. Mult Scler. 2018;24:795–804.
    1. Benedict RH, de Seze J, Hauser SL, et al. Impact of ocrelizumab on cognition in patients at increased risk of progressive disease. 2018 Annual Meeting of the Consortium of Multiple Sclerosis Centers; Nashville, TN, USA; May 30–June 2, 2018 (abstr 209).
    1. Benedict RHB, Cree B, Tomic D, et al. Impact of siponimod on cognition in patients with secondary progressive multiple sclerosis: results from phase 3 EXPAND study. 70th Annual Meeting of the American Academy of Neurology; Los Angeles, CA, USA; April 21–27, 2018 (abstr 004).
    1. Deluca J, Cohen J, Cree BAC, et al. Sustained improvement in cognitive processing speed in multiple sclerosis patients completing 18 months of ozanimod treatment: results from the phase 3 SUNBEAM trial. Mult Scler J. 2019;25:N22.
    1. Chen MH, Goverover Y, Genova HM, DeLuca J. Cognitive efficacy of pharmacologic treatments in multiple sclerosis: a systematic review. CNS Drugs. 2020;34:599–628.
    1. De Giglio L, De Luca F, Gurreri F, et al. Effect of dalfampridine on information processing speed impairment in multiple sclerosis. Neurology. 2019;93:e733–e746.
    1. Satchidanand N, Drake A, Smerbeck A, et al. Dalfampridine benefits ambulation but not cognition in multiple sclerosis. Mult Scler. 2020;26:91–98.
    1. Cerasa A, Gioia MC, Valentino P, et al. Computer-assisted cognitive rehabilitation of attention deficits for multiple sclerosis: a randomized trial with fMRI correlates. Neurorehabil Neural Repair. 2013;27:284–295.
    1. Messinis L, Nasios G, Kosmidis MH, et al. Efficacy of a computer-assisted cognitive rehabilitation intervention in relapsing-remitting multiple sclerosis patients: a multicenter randomized controlled trial. Behav Neurol. 2017;2017
    1. Messinis L, Kosmidis MH, Nasios G, et al. Do secondary progressive multiple sclerosis patients benefit from computer- based cognitive neurorehabilitation? A randomized sham controlled trial. Mult Scler Relat Disord. 2020;39
    1. Charvet LE, Yang J, Shaw MT, et al. Cognitive function in multiple sclerosis improves with telerehabilitation: results from a randomized controlled trial. PLoS One. 2017;12
    1. Amato MP, Goretti B, Viterbo RG, et al. Computer-assisted rehabilitation of attention in patients with multiple sclerosis: results of a randomized, double-blind trial. Mult Scler. 2014;20:91–98.
    1. Chiaravalloti ND, Goverover Y, Costa SL, et al. A pilot study examining speed of processing training (SPT) to improve processing speed in persons with multiple sclerosis. Front Neurol. 2018;9:685.
    1. Chiaravalloti ND, Moore NB, Nikelshpur OM, DeLuca J. An RCT to treat learning impairment in multiple sclerosis: the MEMREHAB trial. Neurology. 2013;81:2066–2072.
    1. Ernst A, Sourty M, Roquet D, et al. Benefits from an autobiographical memory facilitation programme in relapsing-remitting multiple sclerosis patients: a clinical and neuroimaging study. Neuropsychol Rehabil. 2018;28:1110–1130.
    1. Mousavi S, Zare H, Etemadifar M, Taher Neshatdoost H. Memory rehabilitation for the working memory of patients with multiple sclerosis (MS) J Clin Exp Neuropsychol. 2018;40:405–410.
    1. Goverover Y, Chiaravalloti N, Genova H, DeLuca J. A randomized controlled trial to treat impaired learning and memory in multiple sclerosis: the self-GEN trial. Mult Scler. 2018;24:1096–1104.
    1. Psychometrica Computation of effect sizes.
    1. Lampit A, Heine J, Finke C, et al. Computerized cognitive training in multiple sclerosis: a systematic review and meta-analysis. Neurorehabil Neural Repair. 2019;33:695–706.
    1. Mattioli F, Bellomi F, Stampatori C, Capra R, Miniussi C. Neuroenhancement through cognitive training and anodal tDCS in multiple sclerosis. Mult Scler. 2016;22:222–230.
    1. Filippi M, Riccitelli G, Mattioli F, et al. Multiple sclerosis: effects of cognitive rehabilitation on structural and functional MR imaging measures—an explorative study. Radiology. 2012;262:932–940.
    1. Fuchs TA, Ziccardi S, Benedict RHB, et al. Functional connectivity and structural disruption in the default-mode network predicts cognitive rehabilitation outcomes in multiple sclerosis. J Neuroimaging. 2020;30:523–530.
    1. Dobryakova E, Wylie GR, DeLuca J, Chiaravalloti ND. Functional brain activity 6 months after memory retraining in multiple sclerosis: the MEMREHAB trial. Brain Imaging Behav. 2014;8:403–406.
    1. Leavitt VM, Wylie GR, DeLuca J, Chiaravalloti ND. Increased functional connectivity within memory networks following memory rehabilitation in multiple sclerosis. Brain Imaging Behav. 2014;8:394–402.
    1. Chiaravalloti ND, Moore NB, DeLuca J. The efficacy of the modified Story Memory Technique in progressive MS. Mult Scler. 2020;26:354–362.
    1. Martínez-González AE, Piqueras JA. Long-term effectiveness of combined cognitive-behavioral and neuropsychological intervention in a case of multiple sclerosis. Neurocase. 2015;21:584–591.
    1. Charvet L, Shaw M, Dobbs B, et al. Remotely supervised transcranial direct current stimulation increases the benefit of at-home cognitive training in multiple sclerosis. Neuromodulation. 2018;21:383–389.
    1. Sandroff BM, Motl RW, Scudder MR, DeLuca J. Systematic, evidence-based review of exercise, physical activity, and physical fitness effects on cognition in persons with multiple sclerosis. Neuropsychol Rev. 2016;26:271–294.
    1. Motl RW, Sandroff BM, Benedict RH. Cognitive dysfunction and multiple sclerosis: developing a rationale for considering the efficacy of exercise training. Mult Scler. 2011;17:1034–1040.
    1. Sandroff BM, Johnson CL, Motl RW. Exercise training effects on memory and hippocampal viscoelasticity in multiple sclerosis: a novel application of magnetic resonance elastography. Neuroradiology. 2017;59:61–67.
    1. Frndak SE, Kordovski VM, Cookfair D, et al. Disclosure of disease status among employed multiple sclerosis patients: association with negative work events and accommodations. Mult Scler. 2015;21:225–234.
    1. Strober L, Chiaravalloti N, Moore N, et al. Unemployment in multiple sclerosis (MS): utility of the MS Functional Composite and cognitive testing. Mult Scler. 2014;20:112–115.
    1. Barcellos LF, Bellesis KH, Shen L, et al. Remote assessment of verbal memory in MS patients using the California Verbal Learning Test. Mult Scler. 2018;24:354–357.
    1. Kalb R, Beier M, Benedict RH, et al. Recommendations for cognitive screening and management in multiple sclerosis care. Mult Scler. 2018;24:1665–1680.
    1. Saccà F, Costabile T, Carotenuto A, et al. The EDSS integration with the Brief International Cognitive Assessment for Multiple Sclerosis and orientation tests. Mult Scler. 2017;23:1289–1296.

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