Hostname: page-component-586b7cd67f-r5fsc Total loading time: 0 Render date: 2024-12-05T02:08:44.907Z Has data issue: false hasContentIssue false
  • English
  • Français

Practice Effect and Beyond: Reaction to Novelty as an Independent Predictor of Cognitive Decline Among Older Adults

Published online by Cambridge University Press:  15 November 2010

Yana Suchy ,
Matthew L. Kraybill  and
Emilie Franchow
Yana Suchy*
Affiliation:
Department of Psychology, University of Utah, Salt Lake City, Utah
Matthew L. Kraybill
Affiliation:
Department of Psychology, University of Utah, Salt Lake City, Utah
Emilie Franchow
Affiliation:
Department of Psychology, University of Utah, Salt Lake City, Utah
*
Correspondence and reprint requests to: Yana Suchy, Department of Psychology, University of Utah, 380 S. 1530 E., Room 502, Salt Lake City, UT 84112-0251. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Practice Effects (PE) have been gaining interest as an early marker of pathological cognitive decline among older adults, with cognitively compromised individuals exhibiting diminished or absent PE, presumably due to reduced ability to learn. However, the opposite pattern has also been observed, with MCI participants showing larger PEs than controls. In this prospective cohort study, we examined the possibility that individuals with incipient cognitive decline may be more “thrown” by task novelty, which may inflate PE due to diminished performance during the first exposure to the task. We assessed Novelty Effect (NE) and Learning (LRN) on a motor task in 50 community-dwelling independent older adults who expressed a concern about their cognition. Results showed that larger NE was associated with greater cognitive decline 17 months later, reliably classifying participants into decliners and nondecliners. LRN did not independently explain any variance in future cognitive change, but moderated the relationship between NE and decline and correlated with the level of cognition at baseline and follow-up. These findings highlight the differing contributions of NE and LRN to PE, and demonstrate that NE may be sensitive to depletion of cognitive reserve among individuals who are on the verge of exhibiting a reliable cognitive decline. (JINS, 2011, 17, 000–000)

Keywords

Practice effectNoveltyLearningAgingCognitive reserveCognitive decline
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 17 , Issue 1 , January 2011 , pp. 101 - 111
Copyright
Copyright © The International Neuropsychological Society 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Agosta, F., Rocca, M.A., Pagani, E., Absinta, M., Magnani, G., Marcone, A., Filippi, M. (2010). Sensorimotor network rewiring in mild cognitive impairment and Alzheimer’s disease. Human Brain Mapping, 31(4), 515–525.CrossRefGoogle ScholarPubMed
Andel, R., Vigen, C., Mack, W.J., Clark, L.J., Gatz, M. (2006). The effect of education and occupational complexity on rate of cognitive decline in Alzheimer’s patients. Journal of the International Neuropsychological Society, 12(1), 147–152.Google Scholar
Attix, D.K., Story, T.J., Chelune, G.J., Ball, J.D., Stutts, M.L., Hart, R.P., Barth, J.T. (2009). The prediction of change: Normative neuropsychological trajectories. The Clinical Neuropsychologist, 23(1), 21–38.CrossRefGoogle ScholarPubMed
Bosch, B., Bartres-Faz, D., Rami, L., Arenaza-Urquijo, E.M., Fernandez-Espejo, D., Junque, C., Molinuevo, J.L. (2010). Cognitive reserve modulates task-induced activations and deactivations in healthy elders, amnestic mild cognitive impairment and mild Alzheimer’s disease. Cortex: A Journal Devoted to the Study of the Nervous System and Behavior, 46(4), 451–461.CrossRefGoogle ScholarPubMed
Brovelli, A., Laksiri, N., Nazarian, B., Meunier, M., Boussaoud, D. (2008). Understanding the neural computations of arbitrary visuomotor learning through FMRI and associative learning theory. Cerebral Cortex, 18(7), 1485–1495.Google Scholar
Busch, R.M., Chelune, G.J., Suchy, Y. (Eds.). (2005). Using norms in neuropsychological assessment of the elderly. New York: Guilford Press.Google Scholar
Chelune, G.J., Naugle, R.I., Lueders, H., Sedlak, J., Awad, I.A. (1993). Individual change after epilepsy surgery: Practice effects and base-rate information. Neuropsychology, 7(1), 41–52.CrossRefGoogle Scholar
Cooper, D.B., Lacritz, L.H., Weiner, M.F., Rosenberg, R.N., Cullum, C.M. (2004). Category fluency in mild cognitive impairment: Reduced effect of practice in test-retest conditions. Alzheimer Disease and Associated Disorders, 18(3), 120–122.Google Scholar
Corral, M., Rodriguez, M., Amenedo, E., Sanchez, J.L., Diaz, F. (2006). Cognitive reserve, age, and neuropsychological performance in healthy participants. Developmental Neuropsychology, 29(3), 479–491.CrossRefGoogle ScholarPubMed
Darby, D., Maruff, P., Collie, A., McStephen, M. (2002). Mild cognitive impairment can be detected by multiple assessments in a single day. Neurology, 59(7), 1042–1046.Google Scholar
Dickerson, B.C., Salat, D.H., Greve, D.N., Chua, E.F., Rand-Giovannetti, E., Rentz, D.M., Sperling, R.A. (2005). Increased hippocampal activation in mild cognitive impairment compared to normal aging and AD. Neurology, 65(3), 404–411.CrossRefGoogle ScholarPubMed
Duff, K., Beglinger, L.J., Moser, D.J., Paulsen, J.S., Schultz, S.K., Arndt, S. (in press). Predicting cognitive change in older adults: the relative contribution of practice effects. Archives of Clinical Neuropsychology.Google Scholar
Duff, K., Beglinger, L.J., Schultz, S.K., Moser, D.J., McCaffrey, R.J., Haase, R.F., Paulsen, J.S. (2007). Practice effects in the prediction of long-term cognitive outcome in three patient samples: A novel prognostic index. Archives of Clinical Neuropsychology, 22(1), 15–24.Google Scholar
Duff, K., Beglinger, L.J., Van Der Heiden, S., Moser, D.J., Arndt, S., Schultz, S.K., Paulsen, J.S. (2008). Short-term practice effects in amnestic mild cognitive impairment: Implications for diagnosis and treatment. International Psychogeriatrics, 20(5), 986–999.Google Scholar
Ernst, T., Yakupov, R., Nakama, H., Crocket, G., Cole, M., Watters, M., Ricardo-Dukelow, M.L., Chang, L. (2009). Declined neural efficiency in cognitively stable human immunodeficiency virus patients. Annals of Neurology, 65(3), 316–325.CrossRefGoogle ScholarPubMed
Falleti, M.G., Maruff, P., Collie, A., Darby, D.G. (2006). Practice effects associated with the repeated assessment of cognitive function using the CogState battery at 10-minute, one week and one month test-retest intervals. Journal of Clinical and Experimental Neuropsychology, 28(7), 1095–1112.CrossRefGoogle ScholarPubMed
Garrett, D.D., Grady, C.L., Hasher, L. (2010). Everyday memory compensation: The impact of cognitive reserve, subjective memory, and stress. Psychology and Aging, 25(1), 74–83.Google Scholar
Geary, E.K., Kraus, M.F., Pliskin, N.H., Little, D.M. (2010). Verbal learning differences in chronic mild traumatic brain injury. Journal of the International Neuropsychological Society, 16(3), 506–516.Google Scholar
Geerlings, M.I., Jonker, C., Bouter, L.M., Ader, H.J., Schmand, B. (1999). Association between memory complaints and incident Alzheimer’s disease in elderly people with normal baseline cognition. The American Journal of Psychiatry, 156(4), 531–537.Google Scholar
Gluck, M.A., Myers, C.E., Nicolle, M.M., Johnson, S. (2006). Computational models of the hippocampal region: Implications for prediction of risk for Alzheimer’s disease in non-demented elderly. Current Alzheimer Research, 3(3), 247–257.CrossRefGoogle ScholarPubMed
Jansma, J.M., Ramsey, N.F., Slagter, H.A., Kahn, R.S. (2001). Functional anatomical correlates of controlled and automatic processing. Journal of Cognitive Neuroscience, 13(6), 730–743.Google Scholar
Keele, S. (1968). Movement control in skilled motor performance. Psychological Bulletin (70), 387–403.Google Scholar
Keele, S. (1981). Behavioral analysis of movement. In V.B. Brooks (Ed.), Handbook of physiology, section 1, volume 2. Motor control pp. (1391–1414). Bethesda, MD: American Psychological Society.Google Scholar
Klapp, S.T., McRae, J., Long, W. (1978). Response programming vs alternative interpretations of the ‘dit-dah’ reaction time effect. Bulletin of the Psychonomic Society, 11(1), 5–6.Google Scholar
Kraybill, M.L., Suchy, Y. (2008). Evaluating the role of motor regulation in figural fluency: Partialing variance in the Ruff Figural Fluency Test. Journal of Clinical and Experimental Neuropsychology, 30(8), 903–912.Google Scholar
Lenzi, D., Serra, L., Perri, R., Pantano, P., Lenzi, G.L., Paulesu, E., Macaluso, E. (2009). Single domain amnestic MCI: A multiple cognitive domains fMRI investigation. Neurobiology of Aging. doi:10.1016/j.neurobiolaging.2009.09.006Google Scholar
Maassen, G.H., Bossema, E., Brand, N. (2008). Reliable change and practice effects: Outcomes of various indices compared. Journal of Clinical and Experimental Neuropsychology, 31(3), 339–352.CrossRefGoogle ScholarPubMed
Mattis, S.L., Jurica, P.J., Leitten, C.L. (1988). The Dementia Rating Scale. Lutz, FL: Psychological Assessment Resources.Google Scholar
Niti, M., Yap, K.-B., Kua, E.-H., Ng, T.-P. (2009). APOE-É〉4, depressive symptoms, and cognitive decline in Chinese older adults: Singapore longitudinal aging studies. The Journals of Gerontology: Series A: Biological Sciences and Medical Sciences, 64A(2), 306–311.Google Scholar
Pedraza, O., Smith, G.E., Ivnik, R.J., Willis, F.B., Ferman, T.J., Petersen, R.C., Lucas, J.A. (2007). Reliable change on the Dementia Rating Scale. Journal of the International Neuropsychological Society, 13(4), 716–720.Google Scholar
Rapport, L.J., Brines, D.B., Axelrod, B.N., Theisen, M.E. (1997). Full scale IQ as mediator of practice effects: The rich get richer. Clinical Neuropsychologist, 11(4), 375–380.CrossRefGoogle Scholar
Roennlund, M., Loevden, M., Nilsson, L. (2008). Cross-sectional versus longitudinal age gradients of Tower of Hanoi performance: The role of practice effects and cohort differences in education. Aging, Neuropsychology, and Cognition, 15(1), 1–28.Google Scholar
Rypma, B., Berger, J.S., Genova, H.M., Rebbechi, D., D’Esposito, M. (2005). Dissociating age-related changes in cognitive strategy and neural efficiency using event-related fMRI. Cortex: A Journal Devoted to the Study of the Nervous System and Behavior, 41(4), 582–594.CrossRefGoogle ScholarPubMed
Schofield, P.W., Marder, K., Dooneief, G., Jacobs, D.M. (1997). Association of subjective memory complaints with subsequent cognitive decline in community-dwelling elderly individuals with baseline cognitive impairment. The American Journal of Psychiatry, 154(5), 609–615.Google Scholar
Stern, Y. (2002). What is cognitive reserve? Theory and research application of the reserve concept. Journal of the International Neuropsychological Society, 8(3), 448–460.Google Scholar
Stewart, J.C., Rand, K.L., Muldoon, M.F., Kamarck, T.W. (2009). A prospective evaluation of the directionality of the depression-inflammation relationship. Brain, Behavior, and Immunity, 23(7), 936–944.Google Scholar
Suchy, Y., Derbidge, C., Cope, C. (2005). Behavioral dyscontrol scale-electronic version: First examination of reliability, validity, and incremental utility. Clinical Neuropsychologist, 19(1), 4–26.CrossRefGoogle ScholarPubMed
Suchy, Y., Kraybill, M.L. (2007). The relationship between motor programming and executive abilities: Constructs measured by the Push-Turn-Taptap task from the BDS-EV. Journal of Clinical and Experimental Neuropsychology, 29(6), 648–659.Google Scholar
Suchy, Y., Kraybill, M., Larson, J.G.L. (2010). Understanding design fluency: Motor and executive contributions. Journal of the International Neuropsychological Society, 16(1), 26–37.Google Scholar
Thompson, D.N. (1997). Practice effects of advance organization with older adult subjects. Educational Gerontology, 23(3), 207–212.Google Scholar
Wright, D.L., Black, C.B., Immink, M.A., Brueckner, S., Magnuson, C. (2004). Long-term motor programming improvements occur via concatenation of movement sequences during random but not during blocked practice. Journal of Motor Behavior, 36(1), 39–50.Google Scholar
Yesavage, J.A. (1988). Geriatric depression scale. Psychopharmacology Bulletin, 24(4), 709–711.Google ScholarPubMed