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Computer-aided cognitive rehabilitation improves cognitive performances and induces brain functional connectivity changes in relapsing remitting multiple sclerosis patients: an exploratory study

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Abstract

To better understand the effects of short-term computer-based cognitive rehabilitation (cCR) on cognitive performances and default mode network (DMN) intrinsic functional connectivity (FC) in cognitively impaired relapsing remitting (RR) multiple sclerosis (MS) patients. Eighteen cognitively impaired RRMS patients underwent neuropsychological evaluation by the Rao’s brief repeatable battery and resting-state functional magnetic resonance imaging to evaluate FC of the DMN before and after a short-term (8 weeks, twice a week) cCR. A control group of 14 cognitively impaired RRMS patients was assigned to an aspecific cognitive training (aCT), and underwent the same study protocol. Correlations between DMN and cognitive performances were also tested. After cCR, there was a significant improvement of the following tests: SDMT (p < 0.01), PASAT 3″ (p < 0.00), PASAT 2″ (p < 0.03), SRT-D (p < 0.02), and 10/36 SPART-D (p < 0.04); as well as a significant increase of the FC of the DMN in the posterior cingulate cortex (PCC) and bilateral inferior parietal cortex (IPC). After cCR, a significant negative correlation between Stroop Color–Word Interference Test and FC in the PCC emerged. After aCT, the control group did not show any significant effect either on FC or neuropsychological tests. No significant differences were found in brain volumes and lesion load in both groups when comparing data acquired at baseline and after cCR or aCT. In cognitively impaired RRMS patients, cCR improves cognitive performances (i.e., processing speed and visual and verbal sustained memory), and increases FC in the PCC and IPC of the DMN. This exploratory study suggests that cCR may induce adaptive cortical reorganization favoring better cognitive performances, thus strengthening the value of cognitive exercise in the general perspective of building either cognitive or brain reserve.

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References

  1. Julian LJ (2011) Cognitive functioning in multiple sclerosis. Neurol Clin 29:507–525

    Article  PubMed  Google Scholar 

  2. Chiaravalloti ND, DeLuca J (2008) Cognitive impairment in multiple sclerosis. Lancet Neurol 7:1139–1151

    Article  PubMed  Google Scholar 

  3. Benedict RH, Weinstock-Guttman B, Fishman I, Sharma J, Tjoa CW, Bakshi R (2004) Prediction of neuropsychological impairment in multiple sclerosis: comparison of conventional magnetic resonance imaging measures of atrophy and lesion burden. Arch Neurol 61:226–230

    Article  PubMed  Google Scholar 

  4. Zivadinov R, Sepcic J, Nasuelli D, De Masi R, Bragadin LM, Tommasi MA, Zambito-Marsala S et al (2001) A longitudinal study of brain atrophy and cognitive disturbances in the early phase of relapsing-remitting multiple sclerosis. J Neurol Neurosurg Psychiatry 70:773–780

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  5. Benedict RH, Bruce JM, Dwyer MG, Abdelrahman N, Hussein S, Weinstock-Guttman B, Garg N et al (2006) Neocortical atrophy, third ventricular width, and cognitive dysfunction in multiple sclerosis. Arch Neurol 63:1301–1306

    Article  PubMed  Google Scholar 

  6. Amato MP, Bartolozzi ML, Zipoli V, Portaccio E, Mortilla M, Guidi L, Siracusa G et al (2004) Neocortical volume decrease in relapsing-remitting MS patients with mild cognitive impairment. Neurology 63:89–93

    Article  CAS  PubMed  Google Scholar 

  7. Pelletier J, Suchet L, Witjas T, Habib M, Guttmann CR, Salamon G, Lyon-Caen O et al (2001) A longitudinal study of callosal atrophy and interhemispheric dysfunction in relapse-remitting multiple sclerosis. Arch Neurol 58:105–111

    Article  CAS  PubMed  Google Scholar 

  8. Roosendaal SD, Moraal B, Pouwels PJ, Vrenken H, Castelijns JA, Barkhof F, Geurts JJ (2009) Accumulation of cortical lesions in MS: relation with cognitive impairment. Mult Scler 15:708–714

    Article  CAS  PubMed  Google Scholar 

  9. Pliskin NH, Hamer DP, Goldstein DS, Towle VL, Reder AT, Noronha A, Arnason BG (1996) Improved delayed visual reproduction test performance in multiple sclerosis patients receiving interferon beta-1b. Neurology 47:1463–1468

    Article  CAS  PubMed  Google Scholar 

  10. Morrow SA, O’Connor PW, Polman CH, Goodman AD, Kappos L, Lublin FD, Rudick RA et al (2010) Evaluation of the symbol digit modalities test (SDMT) and MS neuropsychological screening questionnaire (MSNQ) in natalizumab-treated MS patients over 48 weeks. Mult Scler 16(1):385–392

    Google Scholar 

  11. Fischer JS, Priore RL, Jacobs LD, Cookfair DL, Rudick RA, Herndon RM, Richert JR, Salazar AM et al (2000) Neuropsychological effects of interferon beta-1a in relapsing multiple sclerosis. Multiple Sclerosis Collaborative Research Group. Ann Neurol 48:885–892

    Article  CAS  PubMed  Google Scholar 

  12. Mattioli M, Stampatori C, Zanotti D, Parrinello G, Capra R (2010) Efficacy and specificity of intensive cognitive rehabilitation of attention and executive functions in multiple sclerosis. J Neurol Sci 288:101–105

    Article  PubMed  Google Scholar 

  13. Chiaravalloti ND, Demaree H, Gaudino EA, DeLuca J (2003) Can the repetition effect maximize learning in multiple sclerosis? Clin Rehabil 17:58–68

    Article  PubMed  Google Scholar 

  14. Lincoln NB, Dent A, Harding J, Weyman N, Nicholl C, Blumhardt LD, Playford ED (2002) Evaluation of cogni-tive assessment and cognitive intervention for people with multiple sclerosis. J Neurol Neurosurg Psychiatry 72:93–98

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  15. Plohmann AM, Kappos L, Ammann W, Thordai A, Wittwer A, Huber S, Bellaiche Y et al (1998) Computer assisted retraining of attentional impairments in patients with multiple sclerosis. J Neurol Neurosurg Psychiatry 64:455–462

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  16. CRIMS Trial, Solari A, Motta A, Mendozzi L, Pucci E, Forni M, Mancardi G, Pozzilli C (2004) Computer-aided retrain-ing of memory and attention in people with multiple sclero-sis: a randomized, double-blind controlled trial. J Neurol Sci 222:99–104

    Article  Google Scholar 

  17. Fink F, Rischkau E, Butt M, Klein J, Eling P, Hildebrandt H (2010) Efficacy of an executive function intervention programme in MS: a placebo-controlled and pseudorandomized trial. Mult Scler 16:1148–1151

    Article  PubMed  Google Scholar 

  18. Stuifbergen AK, 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. Clin Rehabil 26:882–893

    Article  PubMed  Google Scholar 

  19. Amato M, Goretti B, Viterbo R, Portaccio E, Niccolai C, Hakiki B, Iaffaldano P et al (2014) Computer-assisted rehabilitation of attention in patients with multiple sclerosis: results of a randomized, double-blind trial. Mult Scler 20:91–98

    Article  CAS  PubMed  Google Scholar 

  20. Filippi M, Riccitelli G, Mattioli F, Capra R, Stampatori C, Pagani E, Valsasina P et al (2012) Multiple sclerosis: effects of cognitive rehabilitation on structural and functional MR imaging measures—an explorative study. Radiology 262:932–940

    Article  PubMed  Google Scholar 

  21. Sastre-Garriga J, Alonso J, Renom M, Arévalo MJ, González I, Galán I, Montalban X et al (2011) A functional magnetic resonance proof of concept pilot trial of cognitive rehabilitation in multiple sclerosis. Mult Scler 17:457–467

    Article  CAS  PubMed  Google Scholar 

  22. Chiaravalloti ND, Wylie G, Leavitt V, Deluca J (2012) Increased cerebral activation after behavioral treatment for memory deficits in MS. J Neurol 259:1337–1346

    Article  PubMed  Google Scholar 

  23. Biswal BB, Van Kylen J, Hyde JS (1997) Simultaneous assessment of flow and BOLD signals in resting-state functional connectivity maps. NMR Biomed 10:165–170

    Article  CAS  PubMed  Google Scholar 

  24. Greicius MD, Krasnow B, Reiss AL, Menon V (2003) Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proc Natl Acad Sci USA 100:253–258

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  25. van de Ven VG, Formisano E, Prvulovic D, Roeder CH, Linden DE (2004) Functional connectivity as revealed by spatial independent component analysis of fMRI measurements during rest. Hum Brain Mapp 22:165–178

    Article  PubMed  Google Scholar 

  26. Esposito F, Scarabino T, Hyvarinen A, Himberg J, Formisano E, Comani S, Tedeschi G et al (2005) Independent component analysis of fMRI group studies by self-organizing clustering. Neuroimage 25:193–205

    Article  PubMed  Google Scholar 

  27. Esposito F, Bertolino A, Scarabino T, Latorre V, Blasi G, Popolizio T, Tedeschi G et al (2006) Independent component model of the default-mode brain function: assessing the impact of active thinking. Brain Res Bull 16(70):263–269

    Article  Google Scholar 

  28. Sorg C, Riedl V, Mühlau M, Calhoun VD, Eichele T, Läer L, Drzezga A et al (2007) Selective changes of resting-state networks in individuals with Alzheimer’s disease. Proc Natl Acad Sci USA 104:18760–18765

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  29. Bonavita S, Gallo A, Sacco R, Corte MD, Bisecco A, Docimo R, Lavorgna L et al (2011) Distributed changes in default-mode resting-state connectivity in multiple sclerosis. Mult Scler 17:411–422

    Article  PubMed  Google Scholar 

  30. Rocca MA, Valsasina P, Absinta M, Riccitelli G, Rodegher ME, Misci P, Rossi P et al (2010) Default-mode network dysfunction and cognitive impairment in progressive MS. Neurology 20(74):1252–1259

    Article  Google Scholar 

  31. Polman CH, Reingold SC, Edan G, Filippi M, Hartung HP, Kappos L, Lublin FD et al (2005) Diagnostic criteria for multiple sclerosis: 2005 revisions to the ‘‘McDonald Criteria’’. Ann Neurol 58:840–846

    Article  PubMed  Google Scholar 

  32. Krupp LB, LaRocca NG, Muir-Nash J, Steinberg AD (1989) The fatigue severity scale. Application to patients with multiple sclerosis and systemic lupus erythematosus. Arch Neurol 46:1121–1123

    Article  CAS  PubMed  Google Scholar 

  33. Solari A, Motta A, Mendozzi L, Aridon P, Bergamaschi R, Ghezzi A, Mancardi GL et al (2004) Italian version of the Chicago multiscale depression inventory: translation, adaptation and testing in people with multiple sclerosis. Neurol Sci 24:375–383

    Article  CAS  PubMed  Google Scholar 

  34. Kurtzke JF (1983) Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 33:1444–1452

    Article  CAS  PubMed  Google Scholar 

  35. Rao SM, Leo GJ, Bernardin L (1991) Cognitive dysfunction in mul-tiple sclerosis: frequency, patterns, and prediction. Neurology 41:685–691

    Article  CAS  PubMed  Google Scholar 

  36. Amato MP, Portaccio E, Goretti B, Zipoli V, Ricchiuti L, De Caro MF, Patti F et al (2006) The Rao’s Brief Repeatable Battery and Stroop Test: normative values with age, education and gender corrections in an Italian population. Mult Scler 12:787–793

    Article  CAS  PubMed  Google Scholar 

  37. Goretti B, Patti F, Cilia S, Mattioli F, Stampatori C, Scarpazza C, Amato MP et al (2014) The Rao’s Brief Repeatable Battery version B: normative values with age, education and gender corrections in an Italian population. Neurol Sci 35:79–82

    Article  CAS  PubMed  Google Scholar 

  38. Hyvärinen A (1999) Fast and robust fixed-point algorithms for independent component analysis. IEEE Trans Neural Netw 10:626–634

    Article  PubMed  Google Scholar 

  39. Mantini D, Perrucci MG, Del Gratta D, Romani GL, Corbetta M (2007) Electrophysiological signatures of resting state networks in the human brain. Proc Natl Acad Sci USA 104:13170–13175

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  40. van den Heuvel MP, Mandl RC, Kahn RS, Hulshoff Pol HE (2009) Functionally linked resting-state networks reflect the underlying structural connectivity architecture of the human brain. Hum Brain Mapp 30:3127–3141

    Article  PubMed  Google Scholar 

  41. Esposito F, Aragri A, Pesaresi I, Cirillo S, Tedeschi G, Marciano E, Goebel R et al (2008) Independent component model of the default-mode brain function: combining individual-level and population-level analyses in resting-state fMRI. Magn Reson Imaging 26:905–913

    Article  PubMed  Google Scholar 

  42. Forman SD, Cohen JD, Fitzgerald M, Eddy WF, Mintun MA, Noll DC (1995) Improved assessment of significant activation in functional magnetic resonance imaging (fMRI): use of a cluster-size threshold. Magn Reson Med 33:636–647

    Article  CAS  PubMed  Google Scholar 

  43. Battaglini M, Jenkinson M, De Stefano N (2012) Evaluating and reducing the impact of white matter lesions on brain volume measurements. Hum Brain Mapp 33:2062–2071

    Article  PubMed  Google Scholar 

  44. Smith SM, Zhang Y, Jenkinson M, Chen J, Matthews PM, Federico A, De Stefano N (2002) Accurate, robust, and automated longitudinal and cross-sectional brain change analysis. Neuroimage 17:479–489

    Article  PubMed  Google Scholar 

  45. Bermel RA, Bakshi R (2006) The measurement and clinical relevance of brain atrophy in multiple sclerosis. Lancet Neurol 5:158–170

    Article  PubMed  Google Scholar 

  46. Damoiseaux JS, Rombouts SA, Barkhof F, Scheltens P, Stam CJ, Smith SM, Beckmann CF (2006) Consistent resting-state networks across healthy subjects. Proc Natl Acad Sci USA 103:13848–13853

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  47. Staffen W, Mair A, Zauner H, Unterrainer J, Niederhofer H, Kutzelnigg A, Ritter S et al (2002) Cognitive function and fMRI in patients with multiple sclerosis: evidence for compensatory cortical activation during an attention task. Brain 125:1275–1282

    Article  CAS  PubMed  Google Scholar 

  48. Mainero C, Caramia F, Pozzilli C, Pisani A, Pestalozza I, Borriello G, Bozzao L et al (2004) fMRI evidence of brain reorganization during attention and memory tasks in multiple sclerosis. Neuroimage 21:858–867

    Article  PubMed  Google Scholar 

  49. Chiaravalloti N, Hillary F, Ricker J, Christodoulou C, Kalnin A, Liu WC, Steffener J et al (2005) Cerebral activation patterns during working memory performance in multiple sclerosis using fMRI. J Clin Exp Neuropsychol 27:33–54

    Article  PubMed  Google Scholar 

  50. Audoin B, Ibarrola D, Ranjeva JP, Confort-Gouny S, Malikova I, Ali-Chérif A, Pelletier J et al (2003) Compensatory cortical activation observed by fMRI during a cognitive task at the earliest stage of MS. Hum Brain Mapp 20:51–58

    Article  PubMed  Google Scholar 

  51. Sweet LH, Rao SM, Primeau M, Mayer AR, Cohen RA (2004) Functional magnetic resonance imaging of working memory among multiple sclerosis patients. J Neuroimaging 14:150–157

    Article  PubMed  Google Scholar 

  52. Esposito F, Pignataro G, Di Renzo G, Spinali A, Paccone A, Tedeschi G, Annunziato L (2010) Alcohol increases spontaneous BOLD signal fluctuations in the visual network. Neuroimage 53:534–543

    Article  CAS  PubMed  Google Scholar 

  53. Esposito F, Tessitore A, Giordano A, De Micco R, Paccone A, Conforti R, Pignataro G et al (2013) Rhythm-specific modulation of the sensorimotor network in drug-naive patients with Parkinson’s disease by levodopa. Brain 136:710–725

    Article  PubMed  Google Scholar 

  54. Penner IK, Kappos L, Opwis K (2005) Induced changes in brain activation using a computerized attention training in patients with multiple sclerosis (MS). In: Opwis K, Penner IK (eds) Proceedings of KogWis05. The German Cognitive Science Conference. Schwabe, Basel, pp 150–154

    Google Scholar 

  55. Parisi L, Rocca MA, Valsasina P, Panicari L, Mattioli F, Filippi M (2012) Cognitive rehabilitation correlates with the functional connectivity of the anterior cingulate cortex in patients with multiple sclerosis. Brain Imaging Behav 8(3):387–393. doi:10.1007/s11682-012-9160-9

    Article  Google Scholar 

  56. Parisi L, Rocca MA, Mattioli F, Copetti M, Capra R, Valsasina P, Stampatori C et al (2013) Changes of brain resting state functional connectivity predict the persistence of cognitive rehabilitation effects in patients with multiple sclerosis. Mult Scler 20(6):686–694. doi:10.1177/l1352458513505692

    Article  PubMed  Google Scholar 

  57. Cerasa A, Gioia MC, Valentino P, Nisticò R, Chiriaco C, Pirritano D, Tomaiuolo F et al (2013) Computer-assisted cognitive rehabilitation of attention deficits for multiple sclerosis: a randomized trial with FMRI correlates. Neurorehabil Neural Repair 27:284–295

    Article  PubMed  Google Scholar 

  58. Leavitt VM, Wylie GR, Girgis PA, DeLuca J, Chiaravalloti ND (2012) Increased functional connectivity within memory networks following memory rehabilitation in multiple sclerosis. Brain Imaging Behav 8(3):394–402. doi:10.1007/s11682-012-9183-2

    Article  Google Scholar 

  59. Guimarães J, Sá MJ (2012) Cognitive dysfunction in multiple sclerosis. Front Neurol 3:74

    Article  PubMed Central  PubMed  Google Scholar 

  60. Loaiza VM, McCabe DP, Youngblood JL, Rose NS, Myerson J (2011) The influence of levels of processing on recall from working memory and delayed recall tasks. J Exp Psychol Learn Mem Cogn 37:1258–1263

    Article  PubMed  Google Scholar 

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Acknowledgments

This work was supported by Ministero della Salute (grant n. RFPS-2007-6-657805). The authors take full responsibility for the data, the analyses, and interpretation, and the conduct of the present research. The authors have full access to all of the data that can be accessed.

Conflicts of interest

R. Sacco, M. Della Corte, S. Esposito, M. Sparaco, A. d’Ambrosio, R. Docimo, A. Bisecco, L. Lavorgna, D. Corbo, S. Cirillo, F. Esposito, report no disclosures. A. Gallo and S. Bonavita received speakers honoraria from Biogen Idec, Novartis, and Merck-Serono. G. Tedeschi has received compensation for consulting services and/or speaking activities from Bayer Schering Pharma, Biogen Idec, Merck Serono, and Teva Pharmaceutical Industries; and receives research support from Biogen Idec, Merck Serono, and Fondazione Italiana Sclerosi Multipla.

Ethical standard

This study was approved by the Local Ethical Committees on human studies and written informed consent from each subject was obtained prior to their enrolment.

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Authors and Affiliations

  1. Department of Medical, Surgical, Neurological, Metabolic and Aging Sciences, Second University of Naples, Piazza Miraglia 2, 80138, Naples, Italy

    S. Bonavita, R. Sacco, M. Della Corte, S. Esposito, M. Sparaco, A. d’Ambrosio, R. Docimo, A. Bisecco, L. Lavorgna, A. Gallo & G. Tedeschi

  2. MRI Center “SUN_FISM”, Neurological Institute for Diagnosis and Care “Hermitage Capodimonte”, Naples, Italy

    S. Bonavita, M. Della Corte, D. Corbo, S. Cirillo, A. Gallo, F. Esposito & G. Tedeschi

  3. Neuroradiology Service, Department of Radiology, Second University of Naples, Naples, Italy

    S. Cirillo

  4. Department of Medicine and Surgery, University of Salerno, Baronissi (Salerno), Italy

    F. Esposito

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  1. S. Bonavita
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  2. R. Sacco
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Bonavita, S., Sacco, R., Della Corte, M. et al. Computer-aided cognitive rehabilitation improves cognitive performances and induces brain functional connectivity changes in relapsing remitting multiple sclerosis patients: an exploratory study . J Neurol 262, 91–100 (2015). https://doi.org/10.1007/s00415-014-7528-z

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