Hostname: page-component-cd9895bd7-dk4vv Total loading time: 0 Render date: 2024-12-25T01:11:36.684Z Has data issue: false hasContentIssue false
  • English
  • Français

Neuropsychological patterns in magnetic resonance imaging-defined subgroups of patients with degenerative dementia

Published online by Cambridge University Press:  01 May 2009

JOHN LISTERUD ,
CHIVON POWERS ,
PEACHIE MOORE ,
DAVID J. LIBON  and
MURRAY GROSSMAN
JOHN LISTERUD
Affiliation:
Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania
CHIVON POWERS
Affiliation:
Department of Neurology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania
PEACHIE MOORE
Affiliation:
Department of Neurology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania
DAVID J. LIBON
Affiliation:
Department of Neurology, Drexel University College of Medicine, Philadelphia, Pennsylvania
MURRAY GROSSMAN*
Affiliation:
Department of Neurology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania
*
*Correspondence and reprint requests to: Murray Grossman, Department of Neurology—2 Gibson, University of Pennsylvania School of Medicine, 3400 Spruce Street, Philadelphia, Pennsylvania 19104-4283. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

We hypothesized that specific neuropsychological deficits were associated with specific patterns of atrophy. A magnetic resonance imaging volumetric study and a neuropsychological protocol were obtained for patients with several frontotemporal lobar dementia phenotypes including a social/dysexecutive (SOC/EXEC, n = 17), progressive nonfluent aphasia (n = 9), semantic dementia (n = 7), corticobasal syndrome (n = 9), and Alzheimer’s disease (n = 21). Blinded to testing results, patients were partitioned according to pattern of predominant cortical atrophy; our partitioning algorithm had been derived using seriation, a hierarchical classification technique. Neuropsychological test scores were regressed versus these atrophy patterns as fixed effects using the covariate total atrophy as marker for disease severity. The results showed the model accounted for substantial variance. Furthermore, the “large-scale networks” associated with each neuropsychological test conformed well to the known literature. For example, bilateral prefrontal cortical atrophy was exclusively associated with SOC/EXEC dysfunction. The neuropsychological principle of “double dissociation” was supported not just by such active associations but also by the “silence” of locations not previously implicated by the literature. We conclude that classifying patients with degenerative dementia by specific pattern of cortical atrophy has the potential to predict individual patterns of cognitive deficits. (JINS, 2009, 15, 459–470.)

Keywords

Frontotemporal lobar dementiaMRICortical atrophyNeuropsychological functioningSemantic dementiaProgressive nonfluent aphasia
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 15 , Issue 3 , May 2009 , pp. 459 - 470
Copyright
Copyright © The International Neuropsychological Society 2009

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

REFERENCES

Abrahams, S., Goldstein, L.H., Simmons, S., Brammer, M.J., Williams, S.C.R., Vincent, P., Giampietro, V.P., Andrew, C.M., & Leigh, P.N. (2003). Functional magnetic resonance imaging of verbal fluency and confrontation naming using compressed image acquisition to permit overt responses. Human Brain Mapping, 20, 29–40.CrossRefGoogle ScholarPubMed
Ardila, A., Ostrosky-Solís, F., & Bernal, B. (2006). Cognitive testing toward the future: The example of Semantic Verbal Fluency (ANIMALS). International Journal of Psychology, 41(5), 324–332.CrossRefGoogle Scholar
Baddeley, A. (2003). Working memory: Looking backward and looking forward. Nature, 4, 829–839.Google Scholar
Braak, H. & Braak, E. (1991). Neuropathological, staging of Alzheimer-related changes. Acta Neuropathologica, 82, 239–259.CrossRefGoogle ScholarPubMed
Brambati, S.M., Myers, D., Wilson, A., Rankin, K.P., Allison, S.C., Rosen, H.J., Miller, B.L., & Gorno-Tempini, M.L. (2006). The anatomy of category-specific object naming in neurodegenerative diseases. Journal of Cognitive Neuroscience, 18, 1644–1653.CrossRefGoogle ScholarPubMed
Bright, P., Moss, H.E., Longe, O., Stamatakis, E.A., & Tyler, L.K. (2007). Conceptual structure modulates anteromedial temporal involvement in processing verbally presented object properties. Cerebral Cortex, 17(5), 1066–1073.CrossRefGoogle ScholarPubMed
Caramazza, A. & Shelton, J.R. (1998). Domain-specific knowledge systems in the brain: The animate-inanimate distinction. Journal of Cognitive Neuroscience, 10, 1–34.CrossRefGoogle ScholarPubMed
Clark, D.G., Charuvastra, A., Miller, B.L., Shapira, J.S., & Mendez, M.F. (2005). Fluent versus nonfluent primary progressive aphasia: A comparison of clinical and functional neuroimaging features. Brain, 94, 54–60.Google ScholarPubMed
Climer, S. & Weixiong, Z. (2006). Rearrangement clustering: Pitfalls, remedies, and applications. Journal of Machine Learning Research, 7, 919–943.Google Scholar
Cohen, J.D., Perlstein, W.M., Braver, T.S., Nystrom, L.E., Noll, D.C., Jonides, J., & Smith, E.E. (1997). Temporal dynamics of brain activation during a working memory task. Nature, 386, 604–608.CrossRefGoogle ScholarPubMed
Costafreda, S.G., Fu, C.H.Y., Lee, L., Brian, E.B., Brammer, M.J., & David, A.S. (2006). A systematic review and quantitative appraisal of fMRI studies of verbal fluency: Role of the left inferior frontal gyrus. Human Brain Mapping, 27(10), 799–810.CrossRefGoogle ScholarPubMed
Culham, J.C. & Kanwisher, N.G. (2001). Neuroimaging of cognitive functions in human parietal cortex. Current Opinion in Neurobiology, 11(2), 157–163.CrossRefGoogle ScholarPubMed
Cummings, J.L., Mega, M., Grey, K., Rosenberg-Thompson, S., Carusi, D.A., & Gornbein, J. (1994). The Neuropsychiatric Inventory: Comprehensive assessment of psychopathology in dementia. Neurology, 44, 2308–2314.CrossRefGoogle ScholarPubMed
Damasio, A.R., Van Hoesen, G.W., & Hyman, B.T. (1990). Reflections on the selectivity of neuropathologic changes in Alzheimer’s disease. In Schwartz, M. (Ed.), Modular deficits in Alzheimer-type dementia (pp. 83–100). Cambridge, MA: MIT Press.Google Scholar
Damasio, H., Grabowski, T.J., Tranel, D., Hichwa, R.D., & Damasio, A.R. (1996). A neural basis for lexical retrieval. Nature, 380, 499–505.CrossRefGoogle ScholarPubMed
DeLeon, J., Gottesman, R.F., Kleinman, J.T., Newhart, M., Davis, C., Heidler-Gary, J., Lee, A., & Hillis, A.E. (2007). Neural regions essential for distinct cognitive processes underlying picture naming. Brain, 130(5), 1408–1422.CrossRefGoogle ScholarPubMed
Eberling, J.L., Reed, B.R., Baker, M.G., & Jagust, W.J. (1993). Cognitive correlates of regional cerebral blood flow in Alzheimer’s disease. Archives of Neurology, 50(7), 761–766.CrossRefGoogle ScholarPubMed
Evans, A.C., Collins, D.L., Mills, S.R., Brown, E.D., Kelly, R.L., & Peters, T.M. (1993, October). 3D statistical neuroanatomical models from 305 MRI volumes. Paper presented at the Nuclear Science Symposium and Medical Imaging Conference, San Francisco, CA.CrossRefGoogle Scholar
Farias, S.T., Harrington, G., Broomand, C., & Seyal, M. (2005). Differences in functional MR imaging activation patterns associated with confrontation naming and responsive naming. American Journal of Neuroradiology, 26, 2492–2499.Google Scholar
Flicker, C., Ferris, S.H., & Reisberg, B. (1991). Mild cognitive impairment in the elderly: Predictors of dementia. Neurology, 41(7), 1006–1009.CrossRefGoogle ScholarPubMed
Forman, S.D., Cohen, J., Fitzgerald, M., Eddy, W.F., Mintun, M., & Noll, D.C. (1995). Improved assessment of significant activation in functional magnetic resonance imaging (fMRI): Use of a cluster-size threshold. Magnetic Resonance in Medicine, 33, 636–647.CrossRefGoogle ScholarPubMed
Frisoni, G.B., Laakso, M.P., Beltramello, A., Geroldi, C., Bianchetti, A., Soininen, H., & Trabucchi, M. (1999). Hippocampal atrophy and entorhinal cortex atrophy in frontotemporal dementia and Alzheimer’s disease. Neurology, 52, 91–100.CrossRefGoogle ScholarPubMed
Galton, C.J., Patterson, K., Graham, K.S., Lambon-Ralph, M.A., Williams, G., Antoun, N., Sahakian, B.J., & Hodges, J.R. (2001). Differing patterns of temporal atrophy in Alzheimer’s disease and semantic dementia. Neurology, 57, 216–225.CrossRefGoogle ScholarPubMed
Gathercole, S.E., Pickering, S.J., Ambridge, B., & Wearing, H. (2004). The structure of working memory from 4 to 15 years of age. Developmental Psychology, 40(2), 177–190.CrossRefGoogle Scholar
Gelman, R. (1990). First principles organize attention to and learning about relevant data: Number and the animate-inanimate distinction as examples. Cognitive Science, 14(1), 79–106.Google Scholar
Gerlach, C. (2007). A review of functional imaging studies on category specificity. Journal of Cognitive Neuroscience, 19(2), 296–314.CrossRefGoogle ScholarPubMed
Gluck, M. (2001). Multimedia exploratory data analysis for geospatial data mining: The case for augmented seriation. Journal of the American Society for Information Science and Technology, 52(8), 686–696.CrossRefGoogle Scholar
Gluck, M., Lixin, Y., Boryung, J., Woo Seob, J., & Ching Tung, C. (1999, July). Augmented seriation: Usability of a visual and auditory tool for geographic pattern discovery with risk perception data. Paper presented at the GeoComputation ’99, Fredricksburgh, VA.Google Scholar
Grossman, M. (2002). Frontotemporal dementia: A review. Journal of the International Neuropsychological Society, 8, 564–583.CrossRefGoogle ScholarPubMed
Grossman, M. & Ash, S. (2004). Primary progressive aphasia: A review. Neurocase, 10, 3–18.CrossRefGoogle ScholarPubMed
Grossman, M., M. D’Esposito, M., Hughes, E., Onishi, K., Biassou, N., White-Devine, T., & Robinson, K.M. (1996). Language comprehension profiles in Alzheimer’s disease, multi-infarct dementia, and frontotemporal degeneration. Neurology, 47, 183–189.CrossRefGoogle ScholarPubMed
Grossman, M., Koenig, P., DeVita, C., Glosser, G., Alsop, D., Detre, J., & Gee, J. (2002). The neural basis for category-specific knowledge: An fMRI study. NeuroImage, 15(4), 936–948.CrossRefGoogle ScholarPubMed
Grossman, M., Libon, D.J., Forman, M.S., Massimo, L., Wood, E., Moore, P., Anderson, C., Farmer, J., Chatterjee, A., Clark, C.M., Coslett, H.B., Hurtig, H.I., Lee, V.M., & Trojanowski, J.Q. (2007). Distinct antemortem profiles in patients with pathologically diagnosed frontotemporal dementia. Archives of Neurology, 64(11), 1601–1609.CrossRefGoogle ScholarPubMed
Grossman, M., McMillan, C., Moore, P., Ding, L., Glosser, G., Work, M., & Gee, J. (2004). What’s in a name: Voxel-based morphometric analyses of MRI and naming difficulty in Alzheimer’s disease, frontotemporal dementia, and corticobasal degeneration. Brain, 127, 628–649.CrossRefGoogle Scholar
Grossman, M. & Mickanin, J. (1994). Picture comprehension in probable Alzheimer’s disease. Brain and Cognition, 26, 43–64.CrossRefGoogle ScholarPubMed
Grossman, M., Payer, F., Onishi, K., D’Esposito, M., Morrison, D., Sadek, A., & Alavi, A. (1998). Language comprehension and regional cerebral defects in frontotemporal degeneration and Alzheimer’s disease. Neurology, 50, 157–163.CrossRefGoogle ScholarPubMed
Grossman, M., Payer, F., Onishi, K., White-Devine, T., D’Esposito, M., Robinson, K.M., & Alavi, A. (1997). Constraints on the cerebral basis for semantic processing from neuroimaging studies of Alzheimer’s disease. Journal of Neurology, Neurosurgery, and Psychiatry, 63, 152–158.CrossRefGoogle ScholarPubMed
Henry, T.R., Buchtel, H.A., Koeppe, R.A., Pennell, P.B., Kluin, K.J., & Minoshima, S. (1998). Absence of normal activation of the left anterior fusiform gyrus during naming in left temporal lobe epilepsy. Neurology, 50(3), 787–790.CrossRefGoogle ScholarPubMed
Honey, G.D., Bullmore, E.T., & Sharma, T. (2000). Prolonged reaction time to a verbal working memory task predicts increased power of posterior parietal cortical activation. NeuroImage, 12(5), 495–503.CrossRefGoogle ScholarPubMed
Huff, F.J., Becker, J.T., Belle, S., Nebes, R.D., Holland, A.L., & Boller, F. (1987). Cognitive deficits and clinical diagnosis of Alzheimer’s. Neurology, 37, 1119–1124.CrossRefGoogle ScholarPubMed
Kaplan, E., Goodglass, H., & Weintraub, S. (1983). The Boston Naming Test. Philadelphia, PA: Lea & Febiger.Google Scholar
Kasniak, A.W. (1988). Cognition in Alzheimer’s disease: Theoretic models and clinical implications. Neurobiology of Aging, 9(1), 92–94.CrossRefGoogle Scholar
Kendall, D.G. (1975). Review lecture: The recovery of structure from fragmentary information. Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences, 279(1291), 547–582.Google Scholar
Kertesz, A., McMonagle, P., Blair, M., Davidson, W., & Munoz, D.G. (2005). The evolution and pathology of frontotemporal dementia. Brain, 128, 1996–2005.CrossRefGoogle ScholarPubMed
Kertesz, A., Nadkarni, N., Davidson, W., & Thomas, A.W. (2000). The Frontal Behavioral Inventory in the differential diagnosis of frontotemporal dementia. Journal of the International Neuropsychological Society, 6, 460–468.CrossRefGoogle ScholarPubMed
Knopman, D.S., Boeve, B.F., Parisi, J.E., Dickson, D.W., Smith, G.E., Ivnik, R.J., Josephs, K.A., & Petersen, R.C. (2005). Antemortem diagnosis of frontotemporal lobar degeneration. Annals of Neurology, 57(4), 480–488.CrossRefGoogle ScholarPubMed
Knopman, D.S., Petersen, R.C., Edland, S.D., Cha, R.H., & Rocca, W.A. (2004). The incidence of frontotemporal lobar degeneration in Rochester, Minnesota, 1990 through 1994. Neurology, 62, 506–508.CrossRefGoogle ScholarPubMed
Kolb, B. & Whishaw, I.Q. (1995). Fundamentals of human neuropsychology (4th ed.). San Francisco, CA: Worth Publishing.Google Scholar
Listerud, J., Troiani, V., Moore, P., & Grossman, M. (2007, April). Patterns of cortical atrophy obtained by seriation cluster analysis which distinguish subgroups of FTD, AD, and CBD; Abstract # 952476. Paper presented at the American Association of Neurology, Boston.Google Scholar
Litvan, I., Agid, Y., Sastrj, N., Jankovic, J., Wenning, G.K., Goetz, C.G., Verny, M., Brandel, J.P., Jellinger, K., Chaudhuri, K.R., McKee, A., Lai, E.C., Pearce, R.K., & Bartko, J.J. (1997). What are the obstacles for an accurate clinical diagnosis of Pick’s disease? A clinicopathologic study. Neurology, 49, 62–69.CrossRefGoogle ScholarPubMed
Macaluso, E., Frith, C.D., & Driver, J. (2002). Directing attention to locations and to sensory modalities: Multiple levels of selective processing revealed with PET. Cerebral Cortex, 12, 357–368.CrossRefGoogle ScholarPubMed
Maldjian, J.A., Laurienti, P.J., & Burdette, J.H. (2003). An automated method for neuroanatomic and cytoarchitectonic atlas based interrogation of fMRI data sets. NeuroImage, 19, 1233–1239.CrossRefGoogle ScholarPubMed
Martin, A. (1990). Neuropsychology of Alzheimer’s disease: The case for subgroups. In Schwartz, M. (Ed.), Modular deficits in Alzheimer-type dementia, Vol. 5 (pp. 43–175). Cambridge, MA: MIT Press.Google Scholar
Martin, A. & Chao, L.L. (2001). Semantic memory and the brain: Structure and processes. Current Opinion in Neurobiology, 11(2), 194–201.CrossRefGoogle ScholarPubMed
Martin, A., Wiggs, C.L., Ungerleider, L.G., & Haxby, J.V. (1996). Neural correlates of category-specific knowledge. Nature, 379(6566), 649–652.CrossRefGoogle ScholarPubMed
McKhann, G., Trojanowski, J.Q., Grossman, M., Miller, B.L., Dickson, D., & Albert, M. (2001). Clinical and pathological diagnosis of frontotemporal dementia: Report of a work group on frontotemporal dementia and Pick’s disease. Archives of Neurology, 58, 1803–1809.CrossRefGoogle Scholar
Mesulam, M.M. (1982). Slowly progressive aphasia without generalized dementia. Annals of Neurology, 11, 592–598.CrossRefGoogle ScholarPubMed
Mesulam, M.M. (2000a). Aging, Alzheimer’s disease, and dementia: Clinical and neurobiological perspectives. In Mesulam, M.M. (Ed.), Principles of behavioral and cognitive neurology (2nd ed., pp. 439–522). New York: Oxford University Press.CrossRefGoogle Scholar
Mesulam, M.M. (2000b). Behavioral neuroanatomy: Large-scale networks, association cortex, frontal syndromes, the limbic system, and hemispheric specializations. In Mesulam, M.M. (Ed.), Principles of behavioral and cognitive neurology (2nd ed., pp. 1–120). New York: Oxford University Press.CrossRefGoogle Scholar
Mickanin, J., Grossman, M., Onishi, K., Auriacombe, S., & Clark, C. (1994). Verbal and non-verbal fluency in patients with probable Alzheimer’s disease. Neuropsychology, 8, 385–394.CrossRefGoogle Scholar
Morris, J.C., Heyman, A., & Mohs, R.C. (1989). The consortium to establish a registry for Alzheimer’s disease (CERAD). Part I. Clinical and neuropsychological assessment of Alzheimer’s disease. Neurology, 39, 1159–1165.Google Scholar
Mummery, C.J., Patterson, K., Hodges, J.R., & Wise, R.J. (1996). Generating ‘tiger’ as an animal name or a word beginning with T: Differences in brain activation. Proceedings of the Royal Society of London-Series B: Biological Sciences, 263, 989–995.Google ScholarPubMed
Mummery, C.J., Patterson, K., Price, C.J., & Hodges, J.R. (2000). A voxel-based morphometry study of semantic dementia: Relationship between temporal lobe atrophy and semantic memory. Annals of Neurology, 47, 36–45.3.0.CO;2-L>CrossRefGoogle ScholarPubMed
Nagy, Z., Hindley, N.J., Braak, H., Braak, E., Yilmazer-Hanke, D.M., Schultz, C., Barnetson, L., King, E.M.F., Jobst, K.A., & Smith, A.D. (1999). The progression of Alzheimer’s disease from limbic regions to the neocortex: Clinical, radiological and pathological relationships. Dementia and Geriatric Cognitive Disorder, 10, 115–120.CrossRefGoogle Scholar
Neary, D., Snowden, J.S., Gustafson, L., Passant, U., Stuss, D., Black, S., Freedman, M., Kertesz, A., Robert, P.H., Albert, M., Boone, K., Miller, B.L., Cummings, J., & Benson, D.F. (1998). Frontotemporal lobar degeneration: A consensus on clinical diagnostic criteria. Neurology, 51, 1546–1554.CrossRefGoogle ScholarPubMed
Neary, D., Snowden, J.S., Mann, D.M.A., Gustafson, L., Passant, U., Brun, A., & Englund, B. (1994). Clinical and neuropathological criteria for frontotemporal dementia. Journal of Neurology, Neurosurgery, and Psychiatry, 57, 416–418.Google Scholar
New, J., Cosmides, L., & Tooby, J. (2007). Category-specific attention for animals reflects ancestral priorities, not expertise. Proceedings of the National Academy of Sciences of the United States of America, 104(42), 16598–16603.CrossRefGoogle Scholar
Ober, B.A., Jagust, W.J., Koss, E., Delis, D.C., & Friedland, R.P. (1991). Visuoconstructive performance in Alzheimer’s disease and regional cerebral glucose metabolism. Journal of Clinical and Experimental Neuropsychology, 13, 752–772.CrossRefGoogle ScholarPubMed
Peltier, S., Stilla, R., Mariola, E., LaConte, S., Hu, X., & Sathian, K. (2007). Activity and effective connectivity of parietal and occipital cortical regions during haptic shape perception. Neuropsychologia, 45(3), 476–483.CrossRefGoogle ScholarPubMed
Petrie, W.M.F. (1899). Sequences in prehistoric remains. Journal of Anthropological Institute, 29, 295–301.Google Scholar
Piaget, J. (1998). Chapter V: Seriatin, qualitative similarity and ordinal correspondence. In Hodgson, F.M. & Gattegno, C. (Eds.), The child’s conception of number: Jean Piaget: Selected works (pp. 96–121). London, UK: Routledge.Google Scholar
Pick, A. (1977). On the relation between aphasia and senile atrophy of the brain. In Rottenberg, D.A. & Hoschberg, F.H. (Eds.), Neurological classics in modern translation (pp. 35–40). New York: Hafner.Google Scholar
Ratnavalli, E., Brayne, C., Dawson, K., & Hodges, J.R. (2002). The prevalence of frontotemporal dementia. Neurology, 58, 1615–1621.CrossRefGoogle ScholarPubMed
Rosso, S.M., Kaat, L.D., Baks, T., Joosse, M., de, K.I., Pijnenburg, Y.A.L., de Jong, D., Dooijes, D., Kamphorst, W., Ravid, R., Niermeijer, M.F., Verheij, F., Kremer, H.P., Scheltens, P., van Duijn, C.M., Heutink, P., & van Swieten, J.C. (2003). Frontotemporal dementia in the Netherlands: Patient characteristics and prevalence estimates from a population-based study. Brain, 126, 2016–2022.CrossRefGoogle ScholarPubMed
Talbot, P.R., Lloyd, J.J., Snowden, J.S., Neary, D., & Testa, H.J. (1998). A clinical role for 99mTc HMPAO SPECT in the investigation of dementia? Journal of Neurology, Neurosurgery, and Psychiatry, 64, 306–313.CrossRefGoogle ScholarPubMed
Teuber, H.L. (1955). Physiological psychology. Annual Review of Psychology, 9, 267–296.CrossRefGoogle Scholar
Thompson-Schill, S.L. (2003). Neuroimaging studies of semantic memory: Inferring “how” from “where”. Neuropsychologia, 41(3), 280–292.CrossRefGoogle Scholar
Troster, A.L., Butters, N., Salmon, D.P., Cullum, C.M., Jacobs, D., Brandt, J., & White, R.F. (1993). The diagnostic utility of savings scores: Differentiating Alzheimer’s and Huntington’s diseases with the logical memory and visual reproduction tests. Journal of Clinical and Experimental Neuropsychology, 15(5), 773–788.CrossRefGoogle ScholarPubMed
Votaw, J.R., Faber, T.L., Popp, C.A., Henry, T.R., Trudeau, J.D., Woodard, J.L., Mao, H., Hoffman, J.M., & Song, A.W. (1999). A confrontational naming task produces congruent increases and decreases in PET and fMRI. NeuroImage, 10(4), 347–356.CrossRefGoogle ScholarPubMed
Welsh, K.A., Butters, N., Hughes, J., Mohs, R., & Heyman, A. (1991). Detection of abnormal memory decline in mild cases of Alzheimer’s disease using CERAD neuropsychological measures. Archives of Neurology, 48, 278–281.CrossRefGoogle ScholarPubMed
Welsh, K.A., Butters, N., Hughes, J.P., Mohs, R.C., & Heyman, A. (1992). Detection and staging of dementia in Alzheimer’s disease: Use of the neuropsychological measures developed for the Consortium to Establish a Registry for Alzheimer’s Disease. Archives of Neurology, 49, 448–452.CrossRefGoogle ScholarPubMed
Williams, G.B., Nestor, P.J., & Hodges, J.R. (2005). Neural correlates of semantic and behavioural deficits in frontotemporal dementia. NeuroImage, 24, 1042–1051.CrossRefGoogle ScholarPubMed