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Cognition in Early Relapsing-Remitting Multiple Sclerosis: Consequences May Be Relative to Working Memory

Published online by Cambridge University Press:  18 July 2013

Lindsay I. Berrigan ,
Jo-Anne LeFevre ,
Laura M. Rees ,
Jason Berard ,
Mark S. Freedman  and
Lisa A.S. Walker
Lindsay I. Berrigan*
Affiliation:
Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada
Jo-Anne LeFevre
Affiliation:
Department of Psychology, Carleton University, Ottawa, Ontario, Canada Institute of Cognitive Science, Carleton University, Ottawa, Ontario, Canada
Laura M. Rees
Affiliation:
Department of Psychology, Carleton University, Ottawa, Ontario, Canada School of Psychology, University of Ottawa, Ottawa, Ontario, Canada Neuropsychology Service, The Ottawa Hospital, Ottawa, Ontario, Canada The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
Jason Berard
Affiliation:
School of Psychology, University of Ottawa, Ottawa, Ontario, Canada The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
Mark S. Freedman
Affiliation:
The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Division of Neurology, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
Lisa A.S. Walker
Affiliation:
School of Psychology, University of Ottawa, Ottawa, Ontario, Canada Neuropsychology Service, The Ottawa Hospital, Ottawa, Ontario, Canada The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Division of Neurology, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
*
Correspondence and reprint requests to: Lindsay I. Berrigan, Department of Psychiatry, Dalhousie University, 5909 Veterans’ Memorial Lane, 8th floor, Abbie J. Lane Memorial Building, QEII Health Sciences Center, Halifax, NS, B3 H 2E2. E-mail: [email protected]
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Abstract

The Relative Consequence Model proposes multiple sclerosis (MS) patients have a fundamental deficit in processing speed that compromises other cognitive functions. The present study examined the mediating role of processing speed, as well as working memory, in the MS-related effects on other cognitive functions for early relapsing-remitting patients. Seventy relapsing-remitting MS patients with disease duration not greater than 10 years and 72 controls completed tasks assessing processing speed, working memory, learning, and executive functioning. The possible mediating roles of speed and working memory in the MS-related effects on other cognitive functions were evaluated using structural equation modeling. Processing speed was not significantly related to group membership and could not have a mediating role. Working memory was related to group membership and functioned as a mediating/intervening factor. The results do not support the Relative Consequence Model in this sample and they challenge the notion that working memory impairment only emerges at later disease stages. The results do support a mediating/intervening role of working memory. These results were obtained for early relapsing-remitting MS patients and should not be generalized to the broader MS population. Instead, future research should examine the relations that exist at other disease stages. (JINS, 2013, 19, 1–12)

Keywords

Multiple sclerosisCognitive functioningInformation processing speedWorking memory
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 19 , Issue 8 , September 2013 , pp. 938 - 949
Copyright
Copyright © The International Neuropsychological Society 2013 

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References

Amato, M.P., Portaccio, E., Goretti, B., Zipoli, V., Hakiki, B., Giannini, M., Razzolini, L. (2010). Cognitive impairment in early stages of multiple sclerosis. Neurological Sciences, 31(Suppl. 2), S211–S214.CrossRefGoogle ScholarPubMed
Arbuckle, J.L. (2009). AMOS 18 User's Guide. Chicago: SPSS.Google Scholar
Archibald, C.J., Fisk, J.D. (2000). Information processing efficiency in patients with multiple sclerosis. Journal of Clinical and Experimental Neuropsychology, 22, 686–701.CrossRefGoogle ScholarPubMed
Arnett, P.A., Higginson, C.I., Voss, W.D., Bender, W.I., Wurst, J.M., Tippin, J.M. (1999). Depression in multiple sclerosis: Relationship to working memory capacity. Neuropsychology, 13, 546–556.CrossRefGoogle ScholarPubMed
Audoin, B., Guye, M., Reuter, F., Au Duong, M.V., Confort-Gouny, S., Malikova, I., Ranjeva, J.P. (2007). Structure of the WM bundles constituting the working memory system in early multiple sclerosis: A quantitative DTI tractography study. Neuroimage, 36, 1324–1330.CrossRefGoogle ScholarPubMed
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, 690–695.CrossRefGoogle ScholarPubMed
Baddeley, A.D. (2003). Working memory: Looking back and looking forward. Nature Reviews Neuroscience, 4, 829–839.CrossRefGoogle ScholarPubMed
Benedict, R.H.B. (1997). Brief Visuospatial Memory Test–Revised: Professional Manual. Odessa, FL: Psychological Assessment Resources, Inc.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, 549–558.CrossRefGoogle ScholarPubMed
Benedict, R.H., Wahlig, E., Bakshi, R., Fishman, I., Munschauer, F., Zivadinov, R., Weinstock-Guttman, B. (2005). Predicting quality of life in multiple sclerosis: Accounting for physical disability, fatigue, cognition, mood disorder, personality, and behavior change. Journal of the Neurological Sciences, 15, 29–34.CrossRefGoogle Scholar
Benton, A.L., Hamsher, K. deS. (1976). Multilingual Aphasia Examination. Iowa City, IA: University of Iowa.Google Scholar
Chard, D.T., Griffin, C.M., Rashid, W., Davies, G.R., Altmann, D.R., Kapoor, R., Miller, D.H. (2004). Progressive grey matter atrophy in clinically early relapsing-remitting multiple sclerosis. Multiple Sclerosis, 10, 387–391.CrossRefGoogle ScholarPubMed
Chiaravalloti, N.D., Christodoulou, C., Demaree, H.A., DeLuca, J. (2003). Differentiating simple versus complex processing speed: Influence on new learning and memory performance. Journal of Clinical and Experimental Neuropsychology, 25, 489–501.CrossRefGoogle ScholarPubMed
Clemmons, D.C., Fraser, R.T., Rosenbaum, G., Getter, A., Johnson, E. (2004). An abbreviated neuropsychological battery in multiple sclerosis vocational rehabilitation: Findings and implications. Rehabilitation Psychology, 49, 100–105.CrossRefGoogle Scholar
Conway, A.R.A., Kane, M.J., Bunting, M.F., Hambrick, D.Z., Wilhelm, O., Engle, R.W. (2005). Working memory span tasks: A methodological review and user's guide. Psychonomic Bulletin & Review, 12, 769–786.CrossRefGoogle ScholarPubMed
Covey, T.J., Zivadinov, R., Shucard, J.L., Shucard, D.W. (2011). Information processing speed, neural efficiency, and working memory performance in multiple sclerosis: Differential relationships with structural magnetic resonance imaging. Journal of Clinical and Experimental Neuropsychology, 33, 1129–1145.CrossRefGoogle ScholarPubMed
Cutter, G.R., Baier, M.L., Rudick, R.A., Cookfair, D.L., Fischer, J.S., Petkau, J., Willoughby, E. (1999). Development of a multiple sclerosis functional composite as a clinical trial outcome measure. Brain, 122, 871–882.CrossRefGoogle ScholarPubMed
De Sonneville, L.M.J., Boringa, J.B., Reuling, I.E.W., Lazeron, R.H.C., Ader, H.J., Polman, C.H. (2002). Information processing characteristics in subtypes of multiple sclerosis. Neuropsychologia, 40, 1751–1765.CrossRefGoogle ScholarPubMed
De Stefano, D., LeFevre, J.-A. (2004). The role of working memory in mental arithmetic. European Journal of Cognitive Psychology, 16, 353–386.CrossRefGoogle Scholar
De Stefano, N., Matthew, P.M., Fillipi, M., Agosta, F., DeLuca, M., Bartolozzi, M.L., Smith, S.M. (2003). Evidence of early cortical atrophy in MS: Relevance to white matter changes and disability. Neurology, 60, 1157–1162.CrossRefGoogle ScholarPubMed
Delis, D.C., Kaplan, E., Kramer, J.H. (2001). The Delis-Kaplan Executive Function System. San Antonio, TX: The Psychological Corporation.Google Scholar
Deloire, M.S.A., Salort, E., Bonnet, M., Arimone, Y., Boudineau, M., Amieva, H., Brochet, B. (2005). Cognitive impairment as marker of diffuse brain abnormalities in early relapsing remitting multiple sclerosis. Journal of Neurology, Neurosurgery, and Psychiatry, 76, 519–526.CrossRefGoogle ScholarPubMed
DeLuca, J., Barbieri-Berger, S., Johnson, S.K. (1994). The nature of memory impairment in multiple sclerosis: Acquisition versus retrieval. Journal of Clinical and Experimental Neuropsychology, 16, 183–189.CrossRefGoogle ScholarPubMed
DeLuca, J., Chelune, G.J., Tulsky, D.S., Lengenfelder, J., Chiaravalloti, N.D. (2004). Is speed of processing or working memory the primary information processing deficit in multiple sclerosis? Journal of Clinical and Experimental Neuropsychology, 26, 550–562.CrossRefGoogle ScholarPubMed
DeLuca, J., Gaudino, E.A., Diamond, B.J., Christodoulou, C., Engel, R.A. (1998). Acquisition and storage deficits in multiple sclerosis. Journal of Clinical and Experimental Neuropsychology, 20, 376–390.CrossRefGoogle ScholarPubMed
Demaree, H.A., DeLuca, J., Gaudino, E.A., Diamond, B.J. (1999). Speed of information processing as a key deficit in multiple sclerosis: Implications for rehabilitation. Journal of Neurology, Neurosurgery, and Psychiatry, 67, 661–663.CrossRefGoogle ScholarPubMed
Demaree, H.A., Frazier, T.W., Johnson, C.E. (2008). Information processing speed: Measurement issues and its relationships with other neuropsychological constructs. In J. DeLuca & J. H. Kalmar (Eds.), Information processing speed in clinical populations (pp. 53–78). New York, NY: Taylor & Francis.Google Scholar
Denney, D., Lynch, S., Parmenter, B., Horne, N. (2004). Cognitive impairment in relapsing and primary progressive multiple sclerosis: Mostly a matter of speed. Journal of the International Neuropsychological Society, 10, 948–956.CrossRefGoogle ScholarPubMed
D'Esposito, M., Onishi, K., Thompson, H., Robinson, K., Armstrong, C., Grossman, M. (1996). Working memory impairments in multiple sclerosis: Evidence from a dual-task paradigm. Neuropsychology, 10, 51–56.CrossRefGoogle Scholar
Diamond, B.J., DeLuca, J., Kim, H., Kelly, S.M. (1997). The question of disproportionate impairments in visual and auditory information processing in multiple sclerosis. Journal of Clinical and Experimental Neuropsychology, 19, 34–42.CrossRefGoogle ScholarPubMed
Engle, R. (2005). Reading Span Task. Atlanta, GA: Georgia Institute of Technology.Google Scholar
Foong, J., Rozewicz, L., Quaghebeur, G., Davie, C.A., Kartsounis, L.D., Thompson, A.J., Ron, M.A. (1997). Executive function in multiple sclerosis. Brain, 120, 15–26.CrossRefGoogle ScholarPubMed
Forn, C., Belenguer, A., Belloch, V., Sanjuan, A., Parcet, M.A., Avila, C. (2011). Anatomical and functional differences between the Paced Auditory Serial Addition Test and the Symbol Digit Modalities Test. Journal of Clinical and Experimental Neuropsychology, 33, 42–50.CrossRefGoogle ScholarPubMed
Fry, A.F., Hale, S. (1996). Processing speed, working memory, and fluid intelligence: evidence for developmental cascade. Psychological Science, 7, 237–241.CrossRefGoogle Scholar
Glanz, B.I., Holland, C.M., Gauthier, S.A., Amunwa, E.L., Liptak, Z., Houtchens, M.K., Weiner, H.L. (2007). Cognitive dysfunction in patients with clinically isolated syndrome or newly diagnosed multiple sclerosis. Multiple Sclerosis, 13, 1004–1010.CrossRefGoogle ScholarPubMed
Gmeindl, L., Courtney, S.M. (2012). Deconstructing spatial working memory and attention deficits in multiple sclerosis. Neuropsychology, 26, 57–70.CrossRefGoogle ScholarPubMed
Gronwall, D. (1977). Paced Auditory Serial-Addition Task: A measure of recovery from concussion. Perceptual and Motor Skills, 44, 367–373.CrossRefGoogle ScholarPubMed
Hayes, A.F. (2009). Beyond Baron and Kenny: Statistical mediation analysis in the new millennium. Communication Monographs, 76, 408–420.CrossRefGoogle Scholar
Huijbregts, S.C.J., Kalkers, N.F., de Sonneville, L.M.J., de Groot, V., Polman, C.H. (2006). Cognitive impairment and decline in different MS subtypes. Journal of the Neurological Sciences, 245, 187–194.CrossRefGoogle ScholarPubMed
Julian, L.J., Vella, L., Vollmer, T., Hadjimichael, O., Mohr, D.C. (2008). Employment in multiple sclerosis. Exiting and re-entering the work force. Journal of Neurology, 255, 1354–1360.CrossRefGoogle ScholarPubMed
Kail, R. (2006). Longitudinal evidence that increases in processing speed and working memory enhance children's reasoning. Psychological Science, 18, 312–313.CrossRefGoogle Scholar
Kail, R., Salthouse, T.A. (1994). Processing speed as a mental capacity. Acta Psychologica, 86, 199–225.CrossRefGoogle ScholarPubMed
Kurtzke, J.F. (1983). Rating neurologic impairment in multiple sclerosis: An expanded disability status scale (EDSS). Neurology, 33, 1444–1452.CrossRefGoogle ScholarPubMed
Lengenfelder, J., Bryant, D., Diamond, B.J., Kalmar, J.H., Moore, N.B., DeLuca, J. (2006). Processing speed interacts with working memory efficiency in multiple sclerosis. Archives of Clinical Neuropsychology, 21, 229–238.CrossRefGoogle ScholarPubMed
Lengenfelder, J., Chiaravalloti, N.D., Ricker, J.H., DeLuca, J. (2003). Deciphering components of impaired working memory in multiple sclerosis. Cognitive and Behavioral Neurology, 16, 28–39.CrossRefGoogle ScholarPubMed
Litvan, I., Grafman, J., Vendrell, P., Martinez, J.M. (1988). Slowed information processing in multiple sclerosis. Archives of Neurology, 45, 281–285.CrossRefGoogle ScholarPubMed
McCabe, D.P., Roediger, H.L., McDaniel, M.A., Balota, D.A., Hambrick, D.Z. (2010). The relationship between working memory capacity and executive functioning: Evidence for an executive attention construct. Neuropsychology, 24, 222–243.CrossRefGoogle ScholarPubMed
McDonald, T., Compston, A., Edan, G. (2001). Recommended diagnostic criteria for multiple sclerosis: Guidelines from the international panel on the diagnosis of multiple sclerosis. Annals of Neurology, 50, 121–127.CrossRefGoogle ScholarPubMed
Parmenter, B.A., Shucard, J.L., Schucard, D.W. (2007). Information processing deficits in multiple sclerosis: A matter of complexity. Journal of the International Neuropsychological Society, 13, 417–423.CrossRefGoogle ScholarPubMed
Portaccio, E., Amato, M.P., Bartolozzi, M.L., Zipoli, V., Mortilla, M., Guidi, L., De Stefano, N. (2006). Neocortical volume decrease in relapsing-remitting multiple sclerosis with mild cognitive impairment. Journal of the Neurological Sciences, 245, 195–199.CrossRefGoogle ScholarPubMed
Potagas, C., Giogkaraki, E., Koutsis, G., Mandellos, D., Tsirempolou, E., Sfagos, C., Vassilopoulos, D. (2008). Cognitive impairment in different MS subtypes and clinically isolated syndromes. Journal of the Neurological Sciences, 267, 100–106.CrossRefGoogle ScholarPubMed
Rao, S.M., Leo, G.J., Bernardin, L., Unverzagt, F. (1991). Cognitive dysfunction in multiple sclerosis. I. Frequency, patterns, and prediction. Neurology, 41, 685–691.CrossRefGoogle ScholarPubMed
Reicker, L.I., Tombaugh, T.N., Walker, L., Freedman, M.S. (2007). Reaction time: An alternative method for assessing the effects of multiple sclerosis on information processing speed. Archives of Clinical Neuropsychology, 22, 655–664.CrossRefGoogle ScholarPubMed
Riccitelli, G., Rocca, M.A., Pagani, E., Martinelli, V., Radaelli, M., Falini, A., Filippi, M. (2012). Mapping regional grey and white matter atrophy in relapsing-remitting multiple sclerosis. Multiple Sclerosis, 18, 1027–1037.CrossRefGoogle ScholarPubMed
Ruggieri, R.M., Palermo, R., Vitello, G., Gennuso, M., Settipani, N., Piccoli, F. (2003). Cognitive impairment in patients suffering from relapsing-remitting multiple sclerosis with EDSS ≤3.5. Acta Neurologica Scandinavica, 108, 323–326.CrossRefGoogle Scholar
Salthouse, T.A. (1996). The processing-speed theory of adult age differences in cognition. Psychological Review, 103, 403–428.CrossRefGoogle ScholarPubMed
Salthouse, T.A., Madden, D.J. (2008). Information processing speed and aging. In J. DeLuca & J. H. Kalmar (Eds.), Information processing speed in clinical populations (pp. 221–241). New York, NY: Taylor & Francis.Google Scholar
Schmidt, J.P., Tombaugh, T.N. (1995). The Learning and Memory Battery (LAMB). Toronto: Multi-Health Systems.Google Scholar
Sepulcre, J., Masdeau, J.C., Pastor, M.A., Goni, J., Barbosa, C., Bejarano, B., Villoslada, P. (2009). Brain pathways of verbal working memory: A lesion-function correlation study. Neuroimage, 47, 773–778.CrossRefGoogle ScholarPubMed
Simmons, R.D., Tribe, K.L., McDonald, E.A. (2010). Living with multiple sclerosis: longitudinal changes in employment and the importance of symptom management. Journal of Neurology, 257, 926–936.CrossRefGoogle ScholarPubMed
Smith, A. (1991). Symbol Digit Modalities Test. Los Angeles: Western Psychological Services.Google Scholar
Tombaugh, T.N. (2006). A comprehensive review of the Paced Auditory Serial Addition Test (PASAT). Archives of Clinical Neuropsychology, 21, 53–76.CrossRefGoogle ScholarPubMed
Tombaugh, T., Rees, L. (2008). Computerized Test of Information Processing (CTIP). Toronto: Multi-Health Systems, Inc.Google Scholar
Tombaugh, T.N., Rees, L., Stormer, P., Harrison, A., Smith, A. (2007). The effects of mild and severe traumatic brain injury on speed of information processing as measured by the Computerized Tests of Information Processing (CTIP). Archives of Clinical Neuropsychology, 22, 25–36.CrossRefGoogle ScholarPubMed
Wager, T.D., Smith, E.E. (2003). Neuroimaging studies of working memory: A meta-analysis. Cognitive, Affective, and Behavioral Neuroscience, 3, 255–274.CrossRefGoogle ScholarPubMed
Wechsler, D. (1997). Wechsler Memory Scale-III. San Antonio, TX: The Psychological Corporation.Google Scholar
Wojtowicz, M., Berrigan, L.I., Fisk, J.D. (2012). Intra-individual variability as a measure of information processing difficulties in multiple sclerosis. International Journal MS Care, 14, 77–83.CrossRefGoogle ScholarPubMed
Woodward, T.S., Cairo, T.A., Ruff, C.C., Takane, Y., Hunter, M.A., Ngan, E.T.C. (2006). Functional connectivity reveals load dependent neural systems underlying encoding and maintenance in verbal working memory. Neuroscience, 139, 317–325.CrossRefGoogle ScholarPubMed