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Working memory deficits in multiple sclerosis: Comparison between the n-back task and the Paced Auditory Serial Addition Test

Published online by Cambridge University Press:  08 September 2006

BRETT A. PARMENTER
Affiliation:
Division of Developmental and Behavioral Neurosciences, Department of Neurology/The Jacobs Neurological Institute, University at Buffalo, State University of New York, School of Medicine and Biomedical Sciences, Buffalo, New York
JANET L. SHUCARD
Affiliation:
Division of Developmental and Behavioral Neurosciences, Department of Neurology/The Jacobs Neurological Institute, University at Buffalo, State University of New York, School of Medicine and Biomedical Sciences, Buffalo, New York
RALPH H.B. BENEDICT
Affiliation:
Division of Developmental and Behavioral Neurosciences, Department of Neurology/The Jacobs Neurological Institute, University at Buffalo, State University of New York, School of Medicine and Biomedical Sciences, Buffalo, New York
DAVID W. SHUCARD
Affiliation:
Division of Developmental and Behavioral Neurosciences, Department of Neurology/The Jacobs Neurological Institute, University at Buffalo, State University of New York, School of Medicine and Biomedical Sciences, Buffalo, New York

Abstract

Working memory (WM) deficits are common in multiple sclerosis (MS). The Paced Auditory Serial Addition Test (PASAT) is used frequently to measure WM in clinical settings. The n-back paradigm is used often in experimental studies of WM. One unique component of the n-back task is that it provides a measure of reaction time (RT), an additional behavioral index of processing speed and task difficulty. Despite the use of both tasks to measure WM, their common variance has not been documented. We tested 32 MS patients and 20 controls; performance measures were obtained for both tasks. Compared with controls, MS patients generally had poorer performance on both the PASAT and n-back task. MS patients also had slower RTs on the n-back than controls and showed more slowing than controls as a function of WM load. Correlational analyses showed a high correspondence between performance measures on the PASAT and n-back. Principal components analysis pointed to a common feature of the PASAT, n-back, and specific other neuropsychological measures, that is, processing speed. Although the PASAT and n-back were shown to have a significant amount of shared variance, each test has specific advantages and disadvantages for use in clinical populations (JINS, 2006, 12, 677–687.)

Type
Research Article
Copyright
© 2006 The International Neuropsychological Society

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References

REFERENCES

Achiron, A., Polliack, M., Rao, S.M., Barak, Y., Lavie, M., Appelboim, N., & Harel, Y. (2005). Cognitive patterns and progression in multiple sclerosis: Construction and validation of percentile curves. Journal of Neurology, Neurosurgery, and Psychiatry, 76, 744749.Google Scholar
Amato, M.P., Ponziani, G., Pracucci, G., Bracco, L., Siracusa, G., & Amaducci, L. (1995). Cognitive impairment in early-onset multiple sclerosis: Pattern, predictors, and impact on everyday life in a 4-year follow-up. Archives of Neurology, 52, 168172.Google Scholar
Audoin, B., Ibarrola, D., AuDuong, M.V., Pelletier, J., Confort-Gouny, S., Malikova, I., Ali-Cherif, A., Cozzone, P.J., & Ranjeva, J.P. (2005). Functional MRI study of PASAT in normal subjects. Magma, 18, 96102.Google Scholar
Baddeley, A. (1992). Working memory. Science, 255, 556558.Google Scholar
Baddeley, A. (2003). Working memory: Looking back and looking forward. Nature Reviews Neuroscience, 4, 829839.Google Scholar
Beck, A.T., Steer, R.A., & Brown, G.K. (1996). Beck Depression Inventory—second edition manual. San Antonio, TX: The Psychological Corporation.
Benedict, R.H.B., Weinstock-Guttman, B., Fishman, I., Sharma, J., Tjoa, C.W., & Bakshi, R. (2004). Prediction of neuropsychological impairment in multiple sclerosis: Comparison of conventional magnetic resonance imaging measures of atrophy and lesion burden. Archives of Neurology, 61, 226230.Google Scholar
Brassington, J.C. & Marsh, N.V. (1998). Neuropsychological aspects of multiple sclerosis. Neuropsychology Review, 8, 4377.Google Scholar
Braver, T.S., Barch, D.M., Kelley, W.M., Buckner, R.L., Cohen, N.J., Miezin, F.M., Snyder, A.Z., Ollinger, J.M., Akbudak, E., Conturo, T.E., & Petersen, S.E. (2001). Direct comparison of prefrontal cortex regions engaged by working and long-term memory tasks. Neuroimage, 14, 4859.Google Scholar
Brittain, J.L., LaMarche, J.A., Reeder, K.P., Roth, D.L., & Boll, T.J. (1991). Effects of age and IQ on paced auditory serial addition task (PASAT) performance. The Clinical Neuropsychologist, 5, 163175.Google Scholar
Carlson, S., Martinkauppi, S., Rämä, P., Salli, E., Korvenoja, A., & Aronen, H.J. (1998). Distribution of cortical activation during visuospatial n-back tasks as revealed by functional magnetic resonance imaging. Cerebral Cortex, 8, 743752.Google Scholar
Carter, C.S., Perlstein, W., Ganguli, R., Brar, J., Mintun, M., & Cohen, J.D. (1998). Functional hypofrontality and working memory dysfunction in schizophrenia. The American Journal of Psychiatry, 155, 12851287.Google Scholar
Cattell, R.B. (1966). The scree test for the number of factors. Multivariate Behavioral Research, 1, 245276.Google Scholar
Chiaravalloti, N.D., Christodoulou, C., Demaree, H.A., & DeLuca, J. (2003). Differentiating simple versus complex processing speed: Influence of new learning and memory performance. Journal of Clinical and Experimental Neuropsychology, 25, 489501.Google Scholar
Chronicle, E.P. & MacGregor, N.A. (1998). Are PASAT scores related to mathematical ability? Neuropsychological Rehabilitation, 8, 273282.Google Scholar
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, 5156.Google Scholar
Deary, I.J., Langan, S.J., Hepburn, D.A., & Frier, B.M. (1991). Which abilities does the PASAT test? Personality and Individual Differences, 12, 983987.Google Scholar
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, 550562.Google Scholar
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, 661663.Google Scholar
Denney, D.R., Lynch, S.G., Parmenter, B.A., & Horne, N. (2004). Cognitive impairment in relapsing and primary progressive multiple sclerosis: Mostly a matter of speed. Journal of the International Neuropsychological Society, 10, 948956.Google Scholar
Diamond, B.J., DeLuca, J., Kim, H., & Kelley, S.M. (1997). The question of disproportionate impairments in visual and auditory information processing in multiple sclerosis. Journal of Clinical and Experimental Neuropsychology, 19, 3442.Google Scholar
Ferguson, B., Matyszak, M.K., Esiri, M.M., & Perry, V.H. (1997). Axonal damage in acute multiple sclerosis lesions. Brain, 120, 393399.Google Scholar
Fisk, J.D. & Archibald, C.J. (2001). Limitations of the paced auditory serial addition test as a measure of working memory in patients with multiple sclerosis. Journal of the International Neuropsychological Society, 7, 363372.Google Scholar
Gevins, A.S., Morgan, N.H., Bressler, S.L., Cutillo, B.A., White, R.M., Illes, J., Greer, D.S., Doyle, J.C., & Zeitlin, G.M. (1987). Human neuroelectric patterns predict performance accuracy. Science, 235, 580585.Google Scholar
Gevins, A., Smith, M.E., Le, J., Leong, H., Bennett, J., Martin, N., McEvoy, L., Du, R., & Whitfield, S. (1996). High resolution evoked potential imaging of the cortical dynamics of human working memory. Electroencphalography and Clinical Neurophysiology, 98, 327348.Google Scholar
Gow, A.J. & Deary, I.J. (2004). Is the PASAT past it? Testing attention and concentration without numbers. Journal of Clinical and Experimental Neuropsychology, 26, 723736.Google Scholar
Grigsby, J., Ayarbe, S.D., Kravcisin, N., & Busenbark, D. (1994). Working memory impairment among persons with chronic progressive multiple sclerosis. Journal of Neurology, 241, 125131.Google Scholar
Gronwall, D.M.A. (1977). Paced auditory serial addition task: A measure of recovery from concussion. Perceptual and Motor Skills, 44, 367373.Google Scholar
Gronwall, D. & Wrightson, P. (1981). Memory and information processing capacity after closed head injury. Journal of Neurology, Neurosurgery, and Psychiatry, 44(10), 889895.Google Scholar
Heaton, R.K., Grant, I., & Matthews, C.G. (1991). Comprehensive norms for an expanded Halstead-Reitan Battery: Demographic corrections, research findings, and clinical applications. Odessa, FL: Psychological Assessment Resources.
Heaton, R.K., Nelson, L.M., Thompson, D.S., Burks, J.S., & Franklin, G.M. (1985). Neuropsychological findings in relapsing-remitting and chronic progressive multiple sclerosis. Journal of Consulting and Clinical Psychology, 53, 103110.Google Scholar
Hillary, F.G., Chiaravalloti, N.D., Ricker, J.H., Steffener, J., Bly, B.M., Lange, G., Liu, W.C., Kalnin, A.J., & DeLuca, J. (2003). An investigation of working memory rehearsal in multiple sclerosis using fMRI. Journal of Clinical and Experimental Neuropsychology, 25, 965978.CrossRefGoogle Scholar
Holdwick, D.J. & Wingenfeld, S.A. (1999). The subjective experience of PASAT testing: Does the PASAT induce negative mood? Archives of Clinical Neuropsychology, 14, 273284.Google Scholar
Johnson, M.K. (1992). MEM: Mechanisms of recollection. Journal of Cognitive Neuroscience, 4, 268280.Google Scholar
Kail, R. (1998). Speed of information processing in patients with multiple sclerosis. Journal of Clinical and Experimental Neuropsychology, 20, 98106.Google Scholar
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, 2839.Google Scholar
Litvan, I., Grafman, J., Vendrell, P., Martinez, J.M., Junqué, C., Vendrell, J.M., & Barraquer-Bordas, L. (1988). Multiple memory deficits in patients with multiple sclerosis: Exploring the working memory system. Archives of Neurology, 45, 607610.Google Scholar
Manoach, D.S., Schlaug, G., Siewert, B., Darby, D.G., Bly, B.M., Benfield, A., Edelman, R.R., & Warach, S. (1997). Prefrontal cortex fMRI signal changes are correlated with working memory load. Neuroreport, 8, 545549.Google Scholar
McDonald, W.I., Compston, A., Edan, G., Goodkin, D., Hartung, H.P., Lublin, F.D., McFarland, H.F., Paty, D.W., Polman, C.H., Reingold, S.C., Sandberg-Wollheim, M., Sibley, W., Thompson, A., Vanden Noort, S., Weinshenker, B.Y., & Wolinsky, J.S. (2001). Recommended diagnostic criteria for multiple sclerosis: Guidelines from the International Panel on the diagnosis of multiple sclerosis. Annals of Neurology, 50, 121127.Google Scholar
Miller, A.E. (1996). Clinical features. In S.D. Cook (Ed.), Handbook of Multiple Sclerosis. 2nd ed, revised and expanded (pp. 201222). New York: Marcel Dekker, Inc.
Missonnier, P., Gold, G., Leonards, U., Costa-Fazio, L., Michel, J.-P., Ibáñez, V., & Giannakopoulos, P. (2004). Aging and working memory: Early deficits in EEG activation of posterior cortical areas. Journal of Neural Transmission, 111, 11411154.Google Scholar
Penner, I.K., Rausch, M., Kappos, L., Opwis, K., & Radü, E.W. (2003). Analysis of impairment related functional architecture in MS patients during performance of different attention tasks. Journal of Neurology, 250, 461472.Google Scholar
Perry, S. (1994). Living with multiple sclerosis. Brookfield, VT: Ashgate Publishing Limited.
Peyser, J.M. & Poser, C.M. (1986). Neuropsychological correlate of multiple sclerosis. In S.B. Filskov & T.J. Boll (Eds.). Handbook of clinical neuropsychology (pp. 364397). New York: John Wiley & Sons, Inc.
Ragland, J.D., Turetsky, B.I., Gur, R.C., Gunning-Dixon, F., Turner, T., Schroeder, L., Chan, R., & Gur, R.E. (2002). Working memory for complex figures: An fMRI comparison of letter and fractal n-back tasks. Neuropsychology, 16, 370379.Google Scholar
Raine, C.S. & Cross, A.H. (1989). Axonal dystrophy as a consequence of long-term demyelination. Laboratory Investigation, 60, 714725.Google Scholar
Rao, S.M., Leo, G.J., Bernardin, L., & Unverzagt, F. (1991). Cognitive dysfunction in multiple sclerosis: Frequency, patterns, and prediction. Neurology, 41, 685691.Google Scholar
Reitan, R.M. & Wolfson, D. (1985). The Halstead-Reitan Neuropsychological Test Battery: Therapy and clinical interpretation. Tucson, AZ: Neuropsychological Press.
Roman, D.D., Edwall, G.E., Buchanan, R.J., & Patton, J.H. (1991). Extended normal for the paced auditory serial addition task. Clinical Neuropsychologist, 5, 3340.Google Scholar
Segalowitz, S.J., Wintink, A.J., & Cudmore, L.J. (2001). P3 topographical change with task familiarization and task complexity. Cognitive Brain Research, 12, 451457.Google Scholar
Shucard, J.L., Parrish, J., Shucard, D.W., McCabe, D.C., Benedict, R.H.B., & Ambrus, J. (2004). Working memory and processing speed deficits in systemic lupus erythematosus as measured by the paced auditory serial addition test. Journal of the International Neuropsychological Society, 10, 3545.Google Scholar
Simon, J.H., Jacobs, L.D., Campion, M.K., Rudick, R.A., Cookfair, D.L., Herndon, R.M., Richert, J.R., Salazar, A.M., Fischer, J.S., Goodkin, D.E., Simonian, N., Lajaunie, M., Miller, D.E., Wende, K., Martens-Davidson, A., Kinkel, P.R., Munschauer, F.E., Brownscheidle, C.M., & the Multiple sclerosis Collaborative Research Group (MSCRG). (1999). A longitudinal study of brain atrophy in relapsing multiple sclerosis. Neurology, 53, 139148.Google Scholar
Snyder, P.J., Aniskiewicz, A.S., & Snyder, A.M. (1993). Quantitative MRI correlates and diagnostic utility of multi-modal measures of executive control in multiple sclerosis. Journal of Clinical and Experimental Neuropsychology, 15, 18.Google Scholar
Stuss, D.T., Stethem, L.L., & Poirier, C.A. (1987). Comparison of three tests of attention and rapid information processing across six age groups. The Clinical Neuropsychologist, 1, 138152.Google Scholar
Sweet, L.H., Rao, S.M., Primeau, M., Mayer, A.R., & Cohen, R.A. (2004). Functional magnetic resonance imaging of working memory among multiple sclerosis patients. Journal of Neuroimaging, 14, 150157.Google Scholar
Trapp, B.D., Peterson, J., Ransohoff, R.M., Rudick, R., Mork, S., & Bo, L. (1998). Axonal transaction in the lesions of multiple sclerosis. The New England Journal of Medicine, 338, 278285.Google Scholar
Ward, T. (1997). A note of caution for clinicians using the Paced Auditory Serial Addition Task. British Journal of Clinical Psychology, 36, 303307.Google Scholar
Wechsler, D. (1997a). Wechsler Adult Intelligence Scale—Third Edition: Administration and scoring manual. San Antonio, TX: The Psychological Corporation.
Wechsler, D. (1997b). Wechsler Memory Scale—Third Edition: Administration and scoring manual. San Antonio, TX: The Psychological Corporation.
Weins, A.N., Fuller, K.H., & Crossen, J.R. (1997). Paced auditory serial addition test: Adult norms and moderator variables. Journal of Clinical and Experimental Neuropsychology, 19, 473483.Google Scholar
Wishart, H.A., Saykin, A.J., McDonald, B.C., Mamourian, A.C., Flashman, L.A., Schuschu, K.R., Ryan, K.A., Fadul, C.E., & Kasper, L.H. (2004). Brain activation patterns associated with working memory in relapsing-remitting MS. Neurology, 62, 234238.Google Scholar
Zivadinov, R., Sepcic, J., Nasuelli, D., De Masi, R., Monti Bragadin, L., Tommasi, M.A., Zambito-Marsala, S., Moretti, R., Bratina, A., Ukmar, M., Possi-Mucelli, R.S., Grop, A., Cazzato, G., & Zorzon, M. (2001). A longitudinal study of brain atrophy and cognitive disturbances in the early phase of relapsing-remitting multiple sclerosis. Journal of Neurology, Neurosurgery, and Psychiatry, 70, 773780.Google Scholar