Intra-individual variability as a measure of information processing difficulties in multiple sclerosis

International Journal of MS Care

Volumn 14, Issue 2, 2012, Pages 77-83

  Wojtowicz, Magdalena ^a   Berrigan, Lindsay I ^a   Fisk, John D ^b  

^a DALHOUSIE UNIVERSITY   (Canada)

^b QUEEN ELIZABETH II HEALTH SCIENCES CENTRE   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84868290187     PISSN: 15372073     EISSN: None     Source Type: Journal    
DOI: 10.7224/1537-2073-14.2.77     Document Type: Article

References (25)

1. Rao S, Leo G, Bernardin L, Unverzagt F. Cognitive dysfunction in multiple sclerosis: frequency, patterns, and predictions. Neurology. 1991;41:685-691.
2. Benedict RH, Cookfair D, Gavett R, et al. Validity of the minimal assessment of cognitive function in multiple sclerosis. J Int Neuropsychol Soc. 2006;12:549-558.
3. Chiaravalloti ND, DeLuca J. Cognitive impairment in multiple sclerosis. Lancet Neurology. 2009;7:1139-1151.
4. Salthouse TA. The processing-speed theory of adult age differences in cognition. Psychol Rev. 1996;103:403-428.
5. DeLuca J, Chelune GJ, Tulsky DS, Lengenfelder J, Chiaravalloti ND. Is speed of processing or working memory the primary information processing deficit in multiple sclerosis? J Clin Exp Neuropsychol. 2004;26:550-562.
6. Smith A. Symbol Digit Modalities Test: Manual. Los Angeles, CA: Western Psychological Services; 1982.
7. Gronwall D. Paced Auditory Serial-Addition Task: a measure of recovery from concussion. Percept Mot Skills. 1977;44:367-373.
8. Tombaugh TN, Rees LM. Computerized Test of Information Processing. Toronto, Canada: Multi-Health Systems Inc; 2008.
9. Tombaugh TN, Berrigan LI, Walker LA, Freedman MS. The Computerized Test of Information Processing (CTIP) offers an alternative to the PASAT for assessing cognitive processing speed in individuals with multiple sclerosis. Cogn Behav Neurol. 2010;23:192-198.
10. Archibald CJ, Fisk JD. Information processing efficiency in patients with multiple sclerosis. J Clin Exp Neuropsychol. 2000;22:686-701.
11. MacDonald SWS, Nyberg L, Backman L. Intra-individual variability in behavior: links to brain structure, neurotransmission and neuronal activity. Trends Neurosci. 2006;29:474-480.
12. Slifkin AB, Newell KM. Is variability in human performance a reflection of system noise? Curr Direct Psychol Sci. 1998;7:170-177.
13. Li S, Aggen SH, Nesselroade JR, Baltes PB. Short-term fluctuations in elderly people's sensorimotor functioning predict text and spatial memory performance: the Macarthur Successful Aging Studies. Gerontology. 2000;47:100-116.
14. Hultsch DF, MacDonald SWS, Hunter MA, Levy-Bencheton J, Strauss E. Intra-individual variability in cognitive performance in older adults: comparison of adults with mild dementia, adults with arthritis, and healthy adults. Neuropsychol. 2000;14:588-598.
15. MacDonald SWS, Li SC, Bäckman L. Neural underpinnings of within-person variability in cognitive functioning. Psychol Aging. 2009;24:792-808.
16. Westerberg H, Hirvikoski T, Forssberg H, Klingberg T. Visuo-spatial working memory span: a sensitive measure of cognitive deficits in children with ADHD. Child Neuropsychol. 2004;10:155-161.
17. Burton CL, Strauss E, Hultsch DF, Moll A, Hunter MA. Intra-individual variability as a marker of neurological dysfunction: a comparison of Alzheimer's disease and Parkinson's disease. J Clin Exp Neuropsychol. 2006;28:67-83.
18. McDonald WI, Compston A, Edan G, et al. Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the Diagnosis of Multiple Sclerosis. Ann Neurol. 2001;50:121-127.
19. Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale. Neurology. 1983;33:1444-1452.
20. O'Connor P, Devonshire V, Canadian Network of MS Clinics. The use of disease-modifying agents in multiple sclerosis-by the Canadian network of MS clinics. Can J Neurol Sci. 2008;35:127-132.
21. Beck AT, Steer RA, Brown GK. BDI Fast Screen for Medical Patients: Manual. London, UK: The Psychological Corporation; 2000.
22. Korostil M, Feinstein A. Anxiety disorders and their clinical correlates in multiple sclerosis patients. Mult Scler. 2007;13:67-72.
23. Demaree HA, Gaudino E, DeLuca J. The relationship between depressive symptoms and cognitive dysfunction in multiple sclerosis. Cogn Neuropsychiatry. 2003;8:161-171.
24. Benedict RH, Fishman I, McClellan MM, Bakshi R, Weinstock-Guttman B. Validity of the Beck Depression Inventory-Fast Screen in multiple sclerosis. Mult Scler. 2003;9:393-396.
25. Bruce JM, Bruce AS, Arnett PA. Response variability is associated with self-reported cognitive fatigue in multiple sclerosis. Neuropsychology. 2010;24:77-83.