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Accueil Tous les numéros Volume 204 / Numéro 2 (2010) Biologie Aujourd'hui, 204 2 (2010) 145-158 Références
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Numéro
Biologie Aujourd'hui
Volume 204, Numéro 2, 2010
Journée Claude Bernard 2009 : LA MÉMOIRE - Aspects physiologiques, pathologiques et thérapeutiques
Page(s) 145 - 158
DOI https://doi.org/10.1051/jbio/2010010
Publié en ligne 21 juin 2010
  • Alzheimer’s Disease International. World Alzheimer Report 2009. [Google Scholar]
  • Apostolova L.G., Thompson P.M., Mapping progressive brain structural changes in early Alzheimer’s disease and mild cognitive impairment. Neuropsychologia, 2008, 46, 1597–1612. [CrossRef] [PubMed] [Google Scholar]
  • Bakkour A., Morris J.C., Dickerson B.C., The cortical signature of prodromal AD: regional thinning predicts mild AD dementia. Neurology, 2009, 72, 1048–1055. [CrossRef] [PubMed] [Google Scholar]
  • Baron J.C., Bousser M.G., Comar D., Castaigne P., Crossed cerebellar diaschisis in human supratentorial infarction. Ann Neurol, 1980, 8, 128. [Google Scholar]
  • Baron J.C., Chételat G., Desgranges B., Perchey G., Landeau B., de la Sayette V., Eustache F., In vivo mapping of gray matter loss with voxel-based morphometry in mild Alzheimer’s disease. NeuroImage, 2001, 14, 298–309. [CrossRef] [PubMed] [Google Scholar]
  • Bookheimer S.Y., Strojwas M.H., Cohen M.S., Saunders A.M., Pericak-Vance M.A., Mazziotta J.C., Small G.W., Patterns of brain activation in people at risk for Alzheimer’s disease. N Engl J Med, 2000, 343, 450–456. [CrossRef] [PubMed] [Google Scholar]
  • Buckner R.L., Andrews-Hanna J.R., Schacter D.L., The brain’s default network: anatomy, function, and relevance to disease. Ann NY Acad Sci, 2008, 1124, 1–38. [CrossRef] [Google Scholar]
  • Chételat G., Desgranges B., de la Sayette V., Viader F., Eustache F., Baron J.C., Mapping gray matter loss with voxel-based morphometry in mild cognitive impairment. Neuroreport, 2002, 13, 1939–1943. [CrossRef] [PubMed] [Google Scholar]
  • Chételat G., Desgranges B., de la Sayette V., Viader F., Berkouk K., Landeau B., Lalevee C., Le Doze F., Dupuy B., Hannequin D., Baron J.C., Eustache F., Dissociating atrophy and hypometabolism impact on episodic memory in mild cognitive impairment. Brain, 2003, 126, 1955–1967. [CrossRef] [PubMed] [Google Scholar]
  • Chételat G., Desgranges B., de la Sayette V., Viader F., Eustache F., Baron J.C., Mild cognitive impairment: Can FDG-PET predict who is to rapidly convert to Alzheimer’s disease? Neurology, 2003b, 60, 1374–1377. [Google Scholar]
  • Chételat G., Eustache F., Viader F., de la Sayette V., Pelerin A., Mezenge F., Hannequin D., Dupuy B., Baron J.C., Desgranges B., FDG-PET measurement is more accurate than neuropsychological assessments to predict global cognitive deterioration in patients with mild cognitive impairment. Neurocase, 2005, 11, 14–25. [CrossRef] [PubMed] [Google Scholar]
  • Chételat G., Desgranges B., Landeau B., Mezenge F., Poline J.B., de la Sayette V., Viader F., Eustache F., Baron J.C., Direct voxel-based comparison between grey matter hypometabolism and atrophy in Alzheimer’s disease. Brain, 2008, 131, 60–71. [CrossRef] [PubMed] [Google Scholar]
  • DeKosky S.T., Ikonomovic M.D., Styren S.D., Beckett L., Wisniewski S., Bennett D.A., Cochran E.J., Kordower J.H., Mufson E.J., Upregulation of choline acetyltransferase activity in hippocampus and frontal cortex of elderly subjects with mild cognitive impairment. Ann Neurol, 2002, 51, 145–155. [CrossRef] [PubMed] [Google Scholar]
  • Desgranges B., Baron J.C., de la Sayette V., Petit-Taboué M.C., Benali K., Landeau B., Lechevalier B., Eustache F., The neural substrates of memory systems impairment in Alzheimer’s disease. A PET study of resting brain glucose utilization. Brain, 1998, 121, 611–631. [CrossRef] [PubMed] [Google Scholar]
  • Desgranges B., Baron J.C., Lalevee C., Giffard B., Viader F., de la Sayette V., Eustache F., The neural substrates of episodic memory impairment in Alzheimer’s disease as revealed by FDG-PET: relationship to degree of deterioration. Brain, 2002, 125, 1116–1124. [CrossRef] [PubMed] [Google Scholar]
  • Drzezga A., Grimmer T., Henriksen G., Stangier I., Perneczky R., Diehl-Schmid J., Mathis C.A., Klunk W.E., Price J., DeKosky S., Wester H.J., Schwaiger M., Kurz A., Imaging of amyloid plaques and cerebral glucose metabolism in semantic dementia and Alzheimer’s disease. NeuroImage, 2008, 39, 619–633. [CrossRef] [PubMed] [Google Scholar]
  • Duyckaerts C., Potier M.C., Delatour B., Alzheimer disease models and human neuropathology: similarities and differences. Acta Neuropathol, 2008, 115, 5–38. [CrossRef] [PubMed] [Google Scholar]
  • Duyckaerts C., Delatour B., Potier M.C., Classification and basic pathology of Alzheimer disease. Acta Neuropathol, 2009, 118, 5–36. [CrossRef] [PubMed] [Google Scholar]
  • Eustache F., Desgranges B., Giffard B., de la Sayette V., Baron J.C., Entorhinal cortex disruption causes memory deficit in early Alzheimer’s disease as shown by PET. Neuroreport, 2001, 12, 683–685. [CrossRef] [PubMed] [Google Scholar]
  • Eustache F., Piolino P., Giffard B., Viader F., de la Sayette V., Baron J.C., Desgranges B., In the course of time: a PET study of the cerebral substrates of autobiographical amnesia in Alzheimer’s disease. Brain, 2004, 127, 1549–1560. [CrossRef] [PubMed] [Google Scholar]
  • Fouquet M., Villain N., Chételat G., Eustache F., Desgranges B., Cerebral imaging and physiopathology of Alzheimer’s disease. Psychol Neuropsychiatr Vieil, 2007, 5, 269–279. [PubMed] [Google Scholar]
  • Fouquet M., Desgranges B., Landeau B., Duchesnay E., Mezenge F., de la Sayette V., Viader F., Baron J.C., Eustache F., Chételat G., Longitudinal brain metabolic changes from amnestic mild cognitive impairment to Alzheimer’s disease. Brain, 2009, 132, 2058–2067. [CrossRef] [PubMed] [Google Scholar]
  • Good C.D., Scahill R.I., Fox N.C., Ashburner J., Friston K.J., Chan D., Crum W.R., Rossor M.N., Frackowiak R.S., Automatic differentiation of anatomical patterns in the human brain: validation with studies of degenerative dementias. NeuroImage, 2002, 17, 29–46. [CrossRef] [PubMed] [Google Scholar]
  • Helmer C., Pasquier F., Dartigues J.F., Epidemiology of Alzheimer disease and related disorders. Med Sci (Paris), 2006, 22, 288–296. [CrossRef] [EDP Sciences] [PubMed] [Google Scholar]
  • Herholz K., Salmon E., Perani D., Baron J.C., Holthoff V., Frolich L., Schonknecht P., Ito K., Mielke R., Kalbe E., Zundorf G., Delbeuck X., Pelati O., Anchisi D., Fazio F., Kerrouche N., Desgranges B., Eustache F., Beuthien-Baumann B., Menzel C., Schroder J., Kato T., Arahata Y., Henze M., Heiss W.D., Discrimination between Alzheimer dementia and controls by automated analysis of multicenter FDG PET. NeuroImage, 2002, 17, 302–316. [CrossRef] [PubMed] [Google Scholar]
  • Jagust W., Reed B., Mungas D., Ellis W., Decarli C., What does fluorodeoxyglucose PET imaging add to a clinical diagnosis of dementia? Neurology, 2007, 69, 871–877. [CrossRef] [PubMed] [Google Scholar]
  • Langbaum J.B., Chen K., Lee W., Reschke C., Bandy D., Fleisher A.S., Alexander G.E., Foster N.L., Weiner M.W., Koeppe R.A., Jagust W.J., Reiman E.M., Categorical and correlational analyses of baseline fluorodeoxyglucose positron emission tomography images from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). NeuroImage, 2009, 45, 1107–1116. [CrossRef] [PubMed] [Google Scholar]
  • Mevel K., Desgranges B., Baron J.C., Landeau B., de la Sayette V., Viader F., Eustache F., Chételat G., Detecting hippocampal hypometabolism in Mild Cognitive Impairment using automatic voxel-based approaches. NeuroImage, 2007, 37, 18–25. [Google Scholar]
  • Mevel K., Grassiot B., Chételat G., Defer G., Desgranges B., Eustache F., The Default Mode Network: cognitive role and pathological disturbances. Rev Neurol (Paris). Sous Presse. [Google Scholar]
  • Misra C., Fan Y., Davatzikos C., Baseline, longitudinal patterns of brain atrophy in MCI patients, and their use in prediction of short-term conversion to AD: results from ADNI. NeuroImage, 2009, 44, 1415–1422. [CrossRef] [PubMed] [Google Scholar]
  • Mosconi L., Brain glucose metabolism in the early and specific diagnosis of Alzheimer’s disease. FDG-PET studies in MCI and AD. Eur J Nucl Med Mol Imaging, 2005, 32, 486–510. [CrossRef] [PubMed] [Google Scholar]
  • Mosconi L., Pupi A., de Leon M.J., Brain glucose hypometabolism and oxidative stress in preclinical Alzheimer’s disease. Ann NY Acad Sci, 2008, 1147, 180–195. [CrossRef] [Google Scholar]
  • Mueller S.G., Weiner M.W., Selective effect of age, and Apo e4, and Alzheimer’s disease on hippocampal subfields. Hippocampus, 2009, 19, 558–564. [CrossRef] [PubMed] [Google Scholar]
  • Peters F., Collette F., Degueldre C., Sterpenich V., Majerus S., Salmon E., The neural correlates of verbal short-term memory in Alzheimer’s disease: an fMRI study. Brain, 2009, 132, 1833–1846. [CrossRef] [PubMed] [Google Scholar]
  • Prvulovic D., Van de Ven V., Sack A.T., Maurer K., Linden D.E., Functional activation imaging in aging and dementia. Psychiatry Res, 2005, 140, 97–113. [PubMed] [Google Scholar]
  • Risacher S.L., Saykin A.J., West J.D., Shen L., Firpi H.A., McDonald B.C., Baseline MRI predictors of conversion from MCI to probable AD in the ADNI cohort. Curr Alzheimer Res, 2009, 6, 347–361. [CrossRef] [PubMed] [Google Scholar]
  • Salmon E., Kerrouche N., Perani D., Lekeu F., Holthoff V., Beuthien-Baumann B., Sorbi S., Lemaire C., Collette F., Herholz K., On the multivariate nature of brain metabolic impairment in Alzheimer’s disease. Neurobiol Aging, 2009, 30, 186–197. [CrossRef] [PubMed] [Google Scholar]
  • Schroeter M.L., Stein T., Maslowski N., Neumann J., Neural correlates of Alzheimer’s disease and mild cognitive impairment: a systematic and quantitative meta-analysis involving 1351 patients. NeuroImage, 2009, 47, 1196–1206. [CrossRef] [PubMed] [Google Scholar]
  • Schwindt G.C., Black S.E., Functional imaging studies of episodic memory in Alzheimer’s disease: a quantitative meta-analysis. NeuroImage, 2009, 45, 181–190. [Google Scholar]
  • Seo S.W., Im K., Lee J.M., Kim Y.H., Kim S.T., Kim S.Y., Yang D.W., Kim S.I., Cho Y.S., Na D.L., Cortical thickness in single- versus multiple-domain amnestic mild cognitive impairment. NeuroImage, 2007, 36, 289–297. [CrossRef] [PubMed] [Google Scholar]
  • Talairach J., Tournoux P., Co-planar stereotaxic atlas of the human brain. 1988, Thieme, New York. [Google Scholar]
  • Thompson P.M., Hayashi K.M., de Zubicaray G., Janke A.L., Rose S.E., Semple J., Herman D., Hong M.S., Dittmer S.S., Doddrell D.M., Toga A.W., Dynamics of gray matter loss in Alzheimer’s disease. J Neurosci, 2003, 23, 994–1005. [Google Scholar]
  • Vemuri P., Wiste H.J., Weigand S.D., Shaw L.M., Trojanowski J.Q., Weiner M.W., Knopman D.S., Petersen R.C., Jack C.R.Jr., MRI and CSF biomarkers in normal, MCI, and AD subjects: predicting future clinical change. Neurology, 2009, 73, 294–301. [CrossRef] [PubMed] [Google Scholar]
  • Villain N., Desgranges B., Viader F., de la Sayette V., Mezenge F., Landeau B., Baron J.C., Eustache F., Chételat G., Relationships between hippocampal atrophy, white matter disruption, and gray matter hypometabolism in Alzheimer’s disease. J Neurosci, 2008, 28, 6174–6181. [CrossRef] [PubMed] [Google Scholar]
  • Villain N., Fouquet M., Baron J.C., Mezenge F., Landeau B., de la Sayette V., Viader F., Eustache F., Desgranges B., Chételat G., Sequential relationships between gray matter and white matter atrophy and brain metabolic abnormalities in early Alzheimer’s disease. Soumis. [Google Scholar]

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