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Perseverative errors on the Wisconsin Card Sorting Test and brain perfusion imaging in mild Alzheimer's disease

Published online by Cambridge University Press:  04 August 2011

Seishi Terada ,
Shuhei Sato ,
Hajime Honda ,
Yuki Kishimoto ,
Naoya Takeda ,
Etsuko Oshima ,
Osamu Yokota  and
Yosuke Uchitomi
Seishi Terada*
Affiliation:
Department of Neuropsychiatry, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
Shuhei Sato
Affiliation:
Department of Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
Hajime Honda
Affiliation:
Department of Neuropsychiatry, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
Yuki Kishimoto
Affiliation:
Department of Neuropsychiatry, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
Naoya Takeda
Affiliation:
Department of Neuropsychiatry, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
Etsuko Oshima
Affiliation:
Department of Neuropsychiatry, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
Osamu Yokota
Affiliation:
Department of Neuropsychiatry, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
Yosuke Uchitomi
Affiliation:
Department of Neuropsychiatry, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
*
Correspondence should be addressed to: Dr. Seishi Terada, Department of Neuropsychiatry, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences 2-5-1 Shikata-cho, Kita-ku, Okayama 700-8558, Japan. Phone: +81-86-235-7242, Fax: +81-86-235-7246. Email: terada@cc.okayama-u.ac.jp.
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Abstract

Background: The Wisconsin Card Sorting Test (WCST) has long been used to investigate deficits in executive function in humans. The majority of studies investigating deficient WCST performance focused on the number of categories achieved (CA) and the number of perseverative errors of the Nelson type (PEN). However, there is insufficient evidence that these two measures reflect the same neural deficits.

Methods: Twenty AD patients with high PEN scores, and 20 age- and sex-matched AD patients with low PEN scores were selected. All 40 subjects underwent brain SPECT, and the SPECT images were analyzed by Statistical Parametric Mapping.

Results: No significant differences were found between high and low PEN score groups with respect to years of education, Addenbrooke's Cognitive Examination scores, and Mini-Mental State Examination scores. However, higher z scores for hypoperfusion in the bilateral rectal and orbital gyri were observed in the high PEN score group compared with the low PEN score group.

Conclusions: Our results suggest that functional activity of the bilateral rectal and orbital gyri is closely related to PEN scores on a modified WCST (mWCST). The PEN score on a mWCST might be a promising index of dysfunction of the orbitofrontal area among patients with mild AD.

Keywords

Alzheimer's disease (AD)cerebral blood flow (CBF)perseverationperseverative errors of Nelson type (PEN)Wisconsin card sorting test (WCST)
Type
Research Article
Information
International Psychogeriatrics , Volume 23 , Issue 10 , December 2011 , pp. 1552 - 1559
Copyright
Copyright © International Psychogeriatric Association 2011

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References

Ambach, W., Stark, R., Peper, M. and Vaitl, D. (2008). An interfering go/no-go task does not affect accuracy in a Concealed Information Test. International Journal of Psychophysiology, 68, 6–16. doi: 10.1016/j.ijpsycho.2007.11.004.CrossRefGoogle ScholarPubMed
Berman, K. F. et al. (1995). Physiological activation of a cortical network during performance of the Wisconsin Card Sorting Test: a positron emission tomography study. Neuropsychologia, 33, 1027–1046. doi: 10.1016/0028-3932(95)00035-2.CrossRefGoogle ScholarPubMed
Bhanji, J. P., Beer, J. S. and Bunge, S. A. (2010). Taking a gamble or playing by the rules: dissociable prefrontal systems implicated in probabilistic versus deterministic rule-based decisions. Neuroimage, 49, 1810–1819. doi: 10.1016/j.neuroimage.2009.09.030.CrossRefGoogle ScholarPubMed
Braak, H. and Braak, E. (1991). Neuropathological stageing of Alzheimer-related changes. Acta Neuropathologica, 82, 239–259.CrossRefGoogle ScholarPubMed
Bradley, K. M. et al. (2002). Cerebral perfusion SPET correlated with Braak pathological stage in Alzheimer's disease. Brain, 125, 1772–1781. doi:10.1093/brain/awf185.CrossRefGoogle ScholarPubMed
de Wit, S., Corlett, P. R., Aitken, M. R., Dickinson, A. and Fletcher, P. C. (2009). Differential engagement of the ventromedial prefrontal cortex by goal-directed and habitual behavior toward food pictures in humans. Journal of Neuroscience, 29, 11330–11338. doi: 10.1523/JNEUROSCI.1639-09.2009.CrossRefGoogle ScholarPubMed
Drewe, E. A. (1975). Go–no go learning after frontal lobe lesions in humans. Cortex, 11, 8–16.CrossRefGoogle ScholarPubMed
Dubois, B., Slachevsky, A., Litvan, I. and Pillon, B. (2000). The FAB: a frontal assessment battery at bedside. Neurology, 55, 1621–1626.CrossRefGoogle ScholarPubMed
Folstein, M. F., Folstein, S. E. and McHugh, P. R. (1975). “Mini-mental state:” a practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatry Research, 12, 189–198.CrossRefGoogle ScholarPubMed
Fouquet, M. et al. (2009). Longitudinal brain metabolic changes from amnestic mild cognitive impairment to Alzheimer's disease. Brain, 132, 2058–2067. doi: 10.1093/brain/awp132.CrossRefGoogle ScholarPubMed
Friston, K. J., Ashburner, J., Poline, J. B., Frith, C. D., Heather, J. D. and Frackowiak, R. S. J. (1995). Spatial realignment and normalization of images. Human Brain Mapping, 2, 165–189.CrossRefGoogle Scholar
Hartstra, E., Oldenburg, J. F., Van Leijenhorst, L., Rombouts, S. A. and Crone, E. A. (2010). Brain regions involved in the learning and application of reward rules in a two-deck gambling task. Neuropsychologia, 48, 1438–1446. doi: 10.1016/j.neuropsychologia.2010.01.012.CrossRefGoogle Scholar
Hokoishi, K. et al. (2001). Interrater reliability of the Physical Self-Maintenance Scale and the Instrumental Activities of Daily Living Scale in a variety of health professional representatives. Aging and Mental Health, 5, 38–40.CrossRefGoogle Scholar
Hughes, C. P., Berg, L., Danziger, W. L., Coben, L. A. and Martin, R. L. (1982). A new clinical scale for the staging of dementia. British Journal of Psychiatry, 140, 566–572.CrossRefGoogle ScholarPubMed
Johnson, J. K., Head, E., Kim, R., Starr, A. and Cotman, C. W. (1999). Clinical and pathological evidence for a frontal variant of Alzheimer disease. Archives of Neurology, 56, 1233–1239.CrossRefGoogle ScholarPubMed
Johnson, K. A., Mueller, S. T., Walshe, T. M., English, R. J. and Holman, B. L. (1987). Cerebral perfusion imaging in Alzheimer's disease: use of single photon emission computed tomography and iofetamine hydrochloride I 123. Archives of Neurology, 44, 165–168.CrossRefGoogle ScholarPubMed
Konishi, S., Hayashi, T., Uchida, I., Kikyo, H., Takahashi, E. and Miyashita, Y. (2002). Hemispheric asymmetry in human lateral prefrontal cortex during cognitive set shifting. Proceedings of the National Academy of Science of the United States of America, 99, 7803–7808. doi: 10.1073/pnas.122644899.CrossRefGoogle ScholarPubMed
Kugo, A. et al. (2007). Japanese version of the Frontal Assessment Battery for dementia. Psychiatry Research, 153, 69–75. doi: 10.1016/j.psychres.2006.04.004.CrossRefGoogle ScholarPubMed
Mathuranath, P. S., Nestor, P. J., Berrios, G. E., Rakowicz, W. and Hodges, J. R. (2000). A brief cognitive test battery to differentiate Alzheimer's disease and frontotemporal dementia. Neurology, 55, 1613–1620.CrossRefGoogle ScholarPubMed
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D. and Stadlan, E. M. (1984). Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's disease. Neurology, 34, 939–944.CrossRefGoogle ScholarPubMed
Milner, B. (1963). Effects of brain lesions on card sorting. Archives of Neurology, 9, 90–100.CrossRefGoogle Scholar
Monchi, O., Petrides, M., Petre, V., Worsley, K. and Dagher, A. (2001). Wisconsin Card Sorting revisited: distinct neural circuits participating in different stages of the task identified by event-related functional magnetic resonance imaging. Journal of Neuroscience, 21, 7733–7741.CrossRefGoogle ScholarPubMed
Nagahama, Y. et al. (2003). Factor structure of a modified version of the wisconsin card sorting test: an analysis of executive deficit in Alzheimer's disease and mild cognitive impairment. Dementia and Geriatric Cognitive Disorders, 16, 103–112. doi: 10.1159/000070683.CrossRefGoogle ScholarPubMed
Nagahama, Y., Okina, T., Suzuki, N., Nabatame, H. and Matsuda, M. (2005). The cerebral correlates of different types of perseveration in the Wisconsin Card Sorting Test. Journal of Neurology, Neurosurgery and Psychiatry, 76, 169–175. doi: 10.1136/jnnp.2004.039818.CrossRefGoogle ScholarPubMed
Nelson, H. E. (1976). A modified card sorting test sensitive to frontal lobe defects. Cortex, 12, 313–324.CrossRefGoogle ScholarPubMed
Pekkala, S., Albert, M. L., Spiro, A. III and Erkinjuntti, T. (2008). Perseveration in Alzheimer's disease. Dementia and Geriatric Cognitive Disorders, 25, 109–114. doi: 10.1159/000112476.CrossRefGoogle ScholarPubMed
Perry, R. J. and Hodges, J. R. (1999). Attention and executive deficits in Alzheimer's disease: a critical review. Brain, 122, 383–404.CrossRefGoogle ScholarPubMed
Perry, R. J., Watson, P. and Hodges, J. R. (2000). The nature and staging of attention dysfunction in early (minimal and mild) Alzheimer's disease: relationship to episodic and semantic memory impairment. Neuropsychologia, 38, 252–271. doi:10.1016/S0028-3932(99)00079-2.CrossRefGoogle ScholarPubMed
Rolls, E. T., Hornak, J., Wade, D. and McGrath, J. (1994). Emotion-related learning in patients with social and emotional changes associated with frontal lobe damage. Journal of Neurology, Neurosurgery and Psychiatry, 57, 1518–1524.CrossRefGoogle ScholarPubMed
Schnyer, D. M., Maddox, W. T., Ell, S., Davis, S., Pacheco, J. and Verfaellie, M. (2009). Prefrontal contributions to rule-based and information-integration category learning. Neuropsychologia, 47, 2995–3006. doi: 10.1016/S0028-3932(99)00079-2.CrossRefGoogle ScholarPubMed
Takeda, N. et al. (2010). Wisconsin card sorting test and brain perfusion imaging in early dementia. Dementia and Geriatric Cognitive Disorders, 29, 21–27. doi: 10.1159/000261645.CrossRefGoogle ScholarPubMed
Takeuchi, R., Yonekura, Y., Matsuda, H. and Konishi, J. (2002). Usefulness of a three-dimensional stereotaxic ROI template on anatomically standardised 99mTc-ECD SPET. European Journal of Nuclear Medicine and Molecular Imaging, 29, 331–341. doi: 10.1007/s00259-001-0715-z.CrossRefGoogle ScholarPubMed
Woodward, M., Brodaty, H., Boundy, K., Ames, D., Blanch, G. and Balshaw, R. (2010). Does executive impairment define a frontal variant of Alzheimer's disease? International Psychogeriatrics, 22, 1280–1290. doi:10.1017/S1041610210001596.CrossRefGoogle ScholarPubMed
Yoshida, H. et al. (2011). Validation of Addenbrooke's cognitive examination for detecting early dementia in a Japanese population. Psychiatry Research, 185, 211–214. doi:10.1016/j.psychres.2009.06.012.CrossRefGoogle Scholar