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Table of Contents
Vol. 27, No. 1, 2009
Issue release date: February 2009
Section title: Review Article
Free Access
Dement Geriatr Cogn Disord 2009;27:1–10
(DOI:10.1159/000182420)

Functional Magnetic Resonance Imaging of Compensatory Neural Recruitment in Aging and Risk for Alzheimer’s Disease: Review and Recommendations

Han S.D.a–c · Bangen K.J.d · Bondi M.W.e, f
aDepartment of Psychology, Loyola University Chicago, Chicago, Ill., bDepartment of Neurology and cNeuroscience Institute, Loyola University Medical Center, Maywood, Ill., dSDSU/UCSD Joint Doctoral Program, eDepartment of Psychiatry, University of California San Diego School of Medicine, and fPsychology Service, VA San Diego Healthcare System, San Diego, Calif., USA
email Corresponding Author

Abstract

There has been a recent proliferation of functional magnetic resonance imaging (fMRI) studies that interpret between-group or within-group differences in brain response patterns as evidence for compensatory neural recruitment. However, it is currently a challenge to determine whether these observed differences are truly attributable to compensatory neural recruitment or whether they are indicative of some other cognitive or physiological process. Therefore, the need for a standardized set of criteria for interpreting whether differences in brain response patterns are compensatory in nature is great. Focusing on studies of aging and potentially prodromal Alzheimer’s disease conditions (genetic risk, mild cognitive impairment), we critically review the functional neuroimaging literature purporting evidence for compensatory neural recruitment. Finally, we end with a comprehensive model set of criteria for ascertaining the degree to which a ‘compensatory’ interpretation may be supported. This proposed model addresses significant brain region, activation pattern, and behavioral performance considerations, and is therefore termed the Region-Activation-Performance model (RAP model).

© 2008 S. Karger AG, Basel


  

Key Words

  • Aging
  • Alzheimer’s disease
  • APOE
  • Compensation
  • Dedifferentiation
  • Dementia
  • Functional magnetic resonance imaging
  • Functional neuroimaging
  • Region-Activation-Performance model (RAP model)

References

  1. Han SD, Houston WS, Jak AJ, Eyler LT, Nagel BJ, Fleisher AS, Brown GG, Corey-Bloom J, Salmon DP, Thal LJ, Bondi MW: Verbal paired-associate learning by APOE genotype in non-demented older adults: fMRI evidence of a right hemisphere compensatory response. Neurobiol Aging 2007;28:238–247.
  2. Li SC, Lindenberger U: Cross-level unification: a computational exploration of the link between deterioration or cognitive abilities in old age; in Nilsson LG, Markowitsch HJ (eds): Cognitive Neuroscience of Memory. Seattle, Hogrefe & Huber, 1999, pp 103–146.
  3. Welford AT: Performance, biological mechanisms and age: a theoretical sketch; inWelford AT, Birren JE (eds): Behavior, Aging, and the Nervous System. Springfield, Thomas, 1965, pp 3–20.
  4. Salthouse T: Initiating the formalization of theories of cognitive aging. Psychol Aging 1988;3:3–16.
  5. Cabeza R, Grady CL, Nyberg L, McIntosh AR, Tulving E, Kapur S, et al: Age-related differences in neural activity during memory encoding and retrieval: a positron emission tomography study. J Neurosci 1997;17:391–400.
  6. Grady CL, Bernstein LJ, Beig S, Siegenthaler AL: The effects of encoding task on age-related differences in the functional neuroanatomy of face memory. Psychol Aging 2002;17:17–23.
  7. Cabeza R: Hemispheric asymmetry reduction in older adults: the HAROLD model. Psychol Aging 2002;17:85–100.
  8. Reuter-Lorenz PA, Jonides J, Smith ES, Hartley A, Miller A, Marshuetz C, et al: Age differences in the frontal lateralization of verbal and spatial working memory revealed by PET. J Cogn Neurosci 2000;12:174–187.
  9. Cabeza R, Anderson ND, Locantore JK, McIntosh AR: Aging gracefully: compensatory brain activity in high-performing older adults. NeuroImage 2002;17:1394–1402.
  10. Anderson KE, Perera GM, Hilton J, Zubin N, Dela Paz R, Stern Y: Functional magnetic resonance imaging study of word recognition in normal elders. Prog Neuropsychopharmacol Biol Psychiatry 2002;26:647–650.
  11. Grady CL, Maisog JM, Horwitz B, Ungerleider LG, Mentis MJ, Salerno JA, et al: Age-related changes in cortical blood flow activation during visual processing of faces and location. J Neurosci 1994;14:1450–1462.
  12. Davis SW, Dennis NA, Daselaar SM, Fleck MS, Cabeza R: Que PASA? The posterior-anterior shift in aging. Cereb Cortex 2008;18:1201–1209.
  13. Beason-Held LL, Kraut MA, Resnick SM: II. Temporal patterns of longitudinal change in aging brain function. Neurobiol Aging 2008;29:497–513.
  14. Li SC, Lindenberger U, Sikstrom S: Aging cognition: from neuromodulation to representation. Trends Cogn Sci 2001;5:479–486.
  15. Iidaka T, Sadato N, Yamada H, Murata T, Omori M, Yonekura Y: An fMRI study of the functional neuroanatomy of picture encoding in younger and older adults. Cogn Brain Res 2001;11:1–11.
  16. Erickson KI, Colcombe SJ, Wadhwa R, Bherer L, Peterson MS, Scalf PE, Kim JS, Alvarado M, Kramer AF: Training-induced plasticity in older adults: effects of training on hemispheric asymmetry. Neurobiol Aging 2007;28:272–283.
  17. Colombe SJ, Kramer AF, Erickson KI, Scalf P: The implications of cortical recruitment and brain morphology for individual differences in inhibitory function in aging humans. Psychol Aging 2005;20:363–375.
  18. Cabeza R: Cognitive neuroscience of aging: Contributions of functional neuroimaging. Scand J Psychol 2001;42:277–286.
  19. D’Esposito M, Zarahn E, Aguirre GK, Rypma B: The effect of normal aging on the coupling of neural activity to the BOLD hemodynamic response. NeuroImage 1999;10:6–14.
  20. Li SC, Sikstrom S: Integrative neurocomputational perspectives on cognitive aging, neuromodulation, and representation. Neurosci Biobehav Rec 2002;26:795–808.
  21. Bookheimer SY, Strojwas MH, Cohen MS, Saunders AM, Pericak-Vance MA, Mazziotta JC, Small GW: Patterns of brain activation in people at risk for Alzheimer’s disease. N Engl J Med 2000;343:450–456.
  22. Cohen JD, Forman SD, Braver TS, Casey BJ, Servan-Schrieber D, Noll DC: Activation of the prefrontal cortex in a nonspatial working memory task with functional MRI. Hum Brain Mapp 1994;1:293–304.
  23. Bondi MW, Houston WS, Eyler LT, Brown GG: FMRI evidence of compensatory mechanisms in older adults at genetic risk for Alzheimer disease. Neurology 2005;64:501–508.
  24. Burggren AC, Small GW, Sabb FW, Bookheimer SY: Specificity of brain activation patterns in people at genetic risk for Alzheimer disease. Am J Geriatr Psychiatry 2002;10:44–51.
  25. Dickerson BC, Salat DH, Bates JF, et al: Medial temporal lobe function and structure in mild cognitive impairment. Ann Neurol 2004;56:27–35.
  26. Kircher TT, Weis S, Freymann K, Erb M, Jessen F, Grodd W, Heun R, Leube DT: Hippocampal activation in patients with mild cognitive impairment is necessary for successful memory encoding. J Neurol Neurosurg Psychiatry 2007;78:812–818.
  27. Hamalainen A, Pihlajamaki M, Tanila H, Hanninen T, Niskanen E, Tervo S, Karjalainen PA, Vanninen RL, Soininen H: Increased fMRI responses during encoding in mild cognitive impairment. Neurobiol Aging 2007;28:1889–1903.
  28. Buxton RB, Uludag K, Dubowitz DJ, Liu TT: Modeling the hemodynamic response to brain activation. NeuroImage 2004;23(suppl 1):S220–S233.
  29. Attwell D, Laughlin SB: An energy budget for signaling in the grey matter of the brain. J Cereb Blood Flow Metab 2001;21:1133–1145.
  30. Hyder F: Neuroimaging with calibrated fMRI. Stroke 2004;35(11 suppl 1):2635–2641.

    External Resources

  31. Davis TL, Kwong KK, Weisskoff RM, Rosen BR: Calibrated functional MRI: mapping the dynamics of oxidative metabolism. Proc Natl Acad Sci USA 1998;95:1834–1839.
  32. D’Esposito M, Deouell LY, Gazzaley A: Alterations in the BOLD fMRI signal with ageing and disease: a challenge for neuroimaging. Nat Rev Neurosci 2003;4:863–872.
  33. Bentourkia M, Bol A, Ivanoiu A, Labar D, Sibomana M, Coppens A, Michel C, Cosnard G, De Volder AG: Comparison of regional cerebral blood flow and glucose metabolism in the normal brain: effect of aging. J Neurol Sci 2000;181:19–28.
  34. Claus JJ, Breteler MM, Hasan D, Krenning EP, Bots ML, Grobbee DE, Van Swieten JC, Van Harskamp F, Hofman A: Regional cerebral blood flow and cerebrovascular risk factors in the elderly population. Neurobiol Aging 1998;19:57–64.
  35. Kawamura J, Terayama Y, Takashima S, Obara K, Pavol MA, Meyer JS, Mortel KF, Weather S: Leuko-araiosis and cerebral perfusion in normal aging. Exp Aging Res 1993;19:225–240.
  36. Markus H, Cullinane M: Severely impaired cerebrovascular reactivity predicts stroke and TIA risk in patients with carotid artery stenosis and occlusion. Brain 2001;124(pt 3):457–467.
  37. Yamaguchi T, Kanno I, Uemura K, Shishido F, Inugami A, Ogawa T, Murakami M, Suzuki K: Reduction in regional cerebral metabolic rate of oxygen during human aging. Stroke 1986;17:1220–1228.
  38. Buckner RL, Snyder AZ, Sanders AL, Raichle ME, Morris JE: Functional brain imaging of young, nondemented, and demented older adults. J Cog Neurosci 2000;12(suppl 2):24–34.
  39. Tekes A, Mohamed MA, Browner NM, Calhoun VD, Yousem DM: Effect of age on visuomotor functional MR imaging. Acad Radiol 2005;12:739–745.
  40. Uspenskaia O, Liedetrau M, Herms J, Danek A, Hamann GF: Aging is associated with increased collagen type IV accumulation in the basal lamina of human cerebral microvessels. BMC Neurosci 2004;5:37.
  41. Dixon RA, Hopp GA, Cohen A-L, de Frias CM, Backman L: Self-reported memory compensation: similar patterns in Alzheimer’s disease and very old adult samples. J Clin Exp Neuropsychol 2003;25:382–390.
  42. Aine CJ, Woodruff CC, Knoefel JE, Adair JC, Hudson D, Qualls C, Bockholt J, Best E, Kovacevic S, Cobb W, Padilla D, Hart B, Stephen JM: Aging: Compensation or maturation? NeuroImage 2006;32:1891–1904.
  43. Braak H, Braak E: Frequency stages of Alzheimer-related lesions in different age categories. Neurobiol Aging 1997;18:351–357.
  44. Jak AJ, Houston WS, Nagel BJ, Corey-Bloom J, Bondi MW: Differential cross-sectional and longitudinal impact of APOE genotype on hippocampal volumes in nondemented older adults. Dement Geriatr Cogn Disord 2007;23:382–389.
  45. Cabeza R, McIntosh AR, Grady CL, Nyberg L, Houle S, Tulving, E: Age-related changes in neural interactions during memory encoding and retrieval: A network analysis of PET data. Brain Cogn 1997;35:369–372.

    External Resources

  46. Daselaar SM, Prince SE, Cabeza R: When less means more: deactivations during encoding that predict subsequent memory. NeuroImage 2004;23:921–927.
  47. Hayes SM, Cabeza R: Imaging aging: present and future; in Hofer SM, Alwin DF (eds): Handbook of Cognitive Aging: Interdisciplinary Perspectives. Thousand Oaks, Sage, 2008, pp 308–326.
  48. Fazekas F, Schmidt R, Kleinert R, et al: The spectrum of age-associated brain abnormalities: their measurement and histopathological correlates. J Neural Transm Suppl 1998;53:31–39.
  49. Bangen KJ, Restom K, Liu TT, Jak AJ, Perthen JE, Wierenga CE, Salmon DP, Bondi MW: Differential age effects on cerebral blood flow and BOLD response to encoding: associations with cognition and stroke risk. Neurobiol Aging 2007, Epub ahead of print.
  50. Poldrack RA: Imaging brain plasticity: conceptual and methodological issues – A theoretical review. NeuroImage 2000;12:1–13.
  51. Schlaggar BL, Brown TT, Lugar HM, Visscher KM, Miezin FM, Petersen SE: Functional neuroanatomical differences between adults and school-age children in the processing of single words. Science 2002;296:1476–1479.
  52. Bartzokis G: Schizophrenia breakdown in the well-regulated lifelong process of brain development and maturation. Neuropsychopharmacology 2002;27:672–683.
  53. Benes FM, Turtle M, Khan Y, Farol P: Myelination of a key relay zone in the hippocampal formation occurs in the human brain during childhood, adolescence, and adulthood. Arch Gen Psychiatry 1994;51:477–484.
  54. Raz N, Lindenberger U, Rodrigue KM, Kennedy KM, Head D, Williamson A, Dahle C, Gerstorf D, Acker JD: Regional brain changes in aging healthy adults: general trends, individual differences and modifiers. Cereb Cortex 2005;15:1676–1689.
  55. Cook IA, Bookheimer S, Mickes L, Leuchter AF, Kumar A: Aging and brain activation with working memory tasks: an fMRI study of connectivity. Int J Geriatr Psychiatry 2007;22:332–342.
  56. Nielson KA, Langenecker SA, Garavan HP: Differences in the functional neuroanatomy of inhibitory control across the adult life span. Psychol Aging 2002;17:56–71.
  57. Gould RL, Arroyo B, Brown RG, Owen AM, Bullmore ET, Howard RJ: Brain mechanisms of successful compensation during learning in Alzheimer disease. Neurology 2006;67:1011–1017.
  58. Stern Y: What is cognitive reserve? Theory and research application of the reserve concept. J Int Neuropsychol Soc 2002;8:448–460.
  59. Madden DJ, Turkington TG, Provenzale JM, Denny LL, Hawk TC, Gottlob LT, et al: Adult age differences in the functional neuroanatomy of verbal recognition memory. Hum Brain Mapp 1999;7:115–135.
  60. Brown GG, Perthen JE, Liu TT, Buxton RB: A primer on functional magnetic resonance imaging. Neuropsychol Rev 2007;17:107–125.

  

Author Contacts

S. Duke Han, PhD
Department of Psychology
6525 N. Sheridan Road
Chicago, IL 60626 (USA)
Tel. +1 773 508 3073, Fax +1 773 508 8713, E-Mail dhan2@luc.edu

  

Article Information

Accepted: October 1, 2008
Published online: December 16, 2008
Number of Print Pages : 10
Number of Figures : 1, Number of Tables : 0, Number of References : 60

  

Publication Details

Dementia and Geriatric Cognitive Disorders

Vol. 27, No. 1, Year 2009 (Cover Date: February 2009)

Journal Editor: Chan-Palay V. (New York, N.Y.)
ISSN: 1420-8008 (Print), eISSN: 1421-9824 (Online)

For additional information: http://www.karger.com/DEM


Copyright / Drug Dosage / Disclaimer

Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher or, in the case of photocopying, direct payment of a specified fee to the Copyright Clearance Center.
Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in goverment regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug.
Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.

Abstract

There has been a recent proliferation of functional magnetic resonance imaging (fMRI) studies that interpret between-group or within-group differences in brain response patterns as evidence for compensatory neural recruitment. However, it is currently a challenge to determine whether these observed differences are truly attributable to compensatory neural recruitment or whether they are indicative of some other cognitive or physiological process. Therefore, the need for a standardized set of criteria for interpreting whether differences in brain response patterns are compensatory in nature is great. Focusing on studies of aging and potentially prodromal Alzheimer’s disease conditions (genetic risk, mild cognitive impairment), we critically review the functional neuroimaging literature purporting evidence for compensatory neural recruitment. Finally, we end with a comprehensive model set of criteria for ascertaining the degree to which a ‘compensatory’ interpretation may be supported. This proposed model addresses significant brain region, activation pattern, and behavioral performance considerations, and is therefore termed the Region-Activation-Performance model (RAP model).

© 2008 S. Karger AG, Basel


  

Author Contacts

S. Duke Han, PhD
Department of Psychology
6525 N. Sheridan Road
Chicago, IL 60626 (USA)
Tel. +1 773 508 3073, Fax +1 773 508 8713, E-Mail dhan2@luc.edu

  

Article Information

Accepted: October 1, 2008
Published online: December 16, 2008
Number of Print Pages : 10
Number of Figures : 1, Number of Tables : 0, Number of References : 60

  

Publication Details

Dementia and Geriatric Cognitive Disorders

Vol. 27, No. 1, Year 2009 (Cover Date: February 2009)

Journal Editor: Chan-Palay V. (New York, N.Y.)
ISSN: 1420-8008 (Print), eISSN: 1421-9824 (Online)

For additional information: http://www.karger.com/DEM


Article / Publication Details

First-Page Preview
Abstract of Review Article

Accepted: 10/1/2008
Published online: 12/16/2008
Issue release date: February 2009

Number of Print Pages: 10
Number of Figures: 1
Number of Tables: 0

ISSN: 1420-8008 (Print)
eISSN: 1421-9824 (Online)

For additional information: http://www.karger.com/DEM


Copyright / Drug Dosage

Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher or, in the case of photocopying, direct payment of a specified fee to the Copyright Clearance Center.
Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in goverment regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug.
Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.

References

  1. Han SD, Houston WS, Jak AJ, Eyler LT, Nagel BJ, Fleisher AS, Brown GG, Corey-Bloom J, Salmon DP, Thal LJ, Bondi MW: Verbal paired-associate learning by APOE genotype in non-demented older adults: fMRI evidence of a right hemisphere compensatory response. Neurobiol Aging 2007;28:238–247.
  2. Li SC, Lindenberger U: Cross-level unification: a computational exploration of the link between deterioration or cognitive abilities in old age; in Nilsson LG, Markowitsch HJ (eds): Cognitive Neuroscience of Memory. Seattle, Hogrefe & Huber, 1999, pp 103–146.
  3. Welford AT: Performance, biological mechanisms and age: a theoretical sketch; inWelford AT, Birren JE (eds): Behavior, Aging, and the Nervous System. Springfield, Thomas, 1965, pp 3–20.
  4. Salthouse T: Initiating the formalization of theories of cognitive aging. Psychol Aging 1988;3:3–16.
  5. Cabeza R, Grady CL, Nyberg L, McIntosh AR, Tulving E, Kapur S, et al: Age-related differences in neural activity during memory encoding and retrieval: a positron emission tomography study. J Neurosci 1997;17:391–400.
  6. Grady CL, Bernstein LJ, Beig S, Siegenthaler AL: The effects of encoding task on age-related differences in the functional neuroanatomy of face memory. Psychol Aging 2002;17:17–23.
  7. Cabeza R: Hemispheric asymmetry reduction in older adults: the HAROLD model. Psychol Aging 2002;17:85–100.
  8. Reuter-Lorenz PA, Jonides J, Smith ES, Hartley A, Miller A, Marshuetz C, et al: Age differences in the frontal lateralization of verbal and spatial working memory revealed by PET. J Cogn Neurosci 2000;12:174–187.
  9. Cabeza R, Anderson ND, Locantore JK, McIntosh AR: Aging gracefully: compensatory brain activity in high-performing older adults. NeuroImage 2002;17:1394–1402.
  10. Anderson KE, Perera GM, Hilton J, Zubin N, Dela Paz R, Stern Y: Functional magnetic resonance imaging study of word recognition in normal elders. Prog Neuropsychopharmacol Biol Psychiatry 2002;26:647–650.
  11. Grady CL, Maisog JM, Horwitz B, Ungerleider LG, Mentis MJ, Salerno JA, et al: Age-related changes in cortical blood flow activation during visual processing of faces and location. J Neurosci 1994;14:1450–1462.
  12. Davis SW, Dennis NA, Daselaar SM, Fleck MS, Cabeza R: Que PASA? The posterior-anterior shift in aging. Cereb Cortex 2008;18:1201–1209.
  13. Beason-Held LL, Kraut MA, Resnick SM: II. Temporal patterns of longitudinal change in aging brain function. Neurobiol Aging 2008;29:497–513.
  14. Li SC, Lindenberger U, Sikstrom S: Aging cognition: from neuromodulation to representation. Trends Cogn Sci 2001;5:479–486.
  15. Iidaka T, Sadato N, Yamada H, Murata T, Omori M, Yonekura Y: An fMRI study of the functional neuroanatomy of picture encoding in younger and older adults. Cogn Brain Res 2001;11:1–11.
  16. Erickson KI, Colcombe SJ, Wadhwa R, Bherer L, Peterson MS, Scalf PE, Kim JS, Alvarado M, Kramer AF: Training-induced plasticity in older adults: effects of training on hemispheric asymmetry. Neurobiol Aging 2007;28:272–283.
  17. Colombe SJ, Kramer AF, Erickson KI, Scalf P: The implications of cortical recruitment and brain morphology for individual differences in inhibitory function in aging humans. Psychol Aging 2005;20:363–375.
  18. Cabeza R: Cognitive neuroscience of aging: Contributions of functional neuroimaging. Scand J Psychol 2001;42:277–286.
  19. D’Esposito M, Zarahn E, Aguirre GK, Rypma B: The effect of normal aging on the coupling of neural activity to the BOLD hemodynamic response. NeuroImage 1999;10:6–14.
  20. Li SC, Sikstrom S: Integrative neurocomputational perspectives on cognitive aging, neuromodulation, and representation. Neurosci Biobehav Rec 2002;26:795–808.
  21. Bookheimer SY, Strojwas MH, Cohen MS, Saunders AM, Pericak-Vance MA, Mazziotta JC, Small GW: Patterns of brain activation in people at risk for Alzheimer’s disease. N Engl J Med 2000;343:450–456.
  22. Cohen JD, Forman SD, Braver TS, Casey BJ, Servan-Schrieber D, Noll DC: Activation of the prefrontal cortex in a nonspatial working memory task with functional MRI. Hum Brain Mapp 1994;1:293–304.
  23. Bondi MW, Houston WS, Eyler LT, Brown GG: FMRI evidence of compensatory mechanisms in older adults at genetic risk for Alzheimer disease. Neurology 2005;64:501–508.
  24. Burggren AC, Small GW, Sabb FW, Bookheimer SY: Specificity of brain activation patterns in people at genetic risk for Alzheimer disease. Am J Geriatr Psychiatry 2002;10:44–51.
  25. Dickerson BC, Salat DH, Bates JF, et al: Medial temporal lobe function and structure in mild cognitive impairment. Ann Neurol 2004;56:27–35.
  26. Kircher TT, Weis S, Freymann K, Erb M, Jessen F, Grodd W, Heun R, Leube DT: Hippocampal activation in patients with mild cognitive impairment is necessary for successful memory encoding. J Neurol Neurosurg Psychiatry 2007;78:812–818.
  27. Hamalainen A, Pihlajamaki M, Tanila H, Hanninen T, Niskanen E, Tervo S, Karjalainen PA, Vanninen RL, Soininen H: Increased fMRI responses during encoding in mild cognitive impairment. Neurobiol Aging 2007;28:1889–1903.
  28. Buxton RB, Uludag K, Dubowitz DJ, Liu TT: Modeling the hemodynamic response to brain activation. NeuroImage 2004;23(suppl 1):S220–S233.
  29. Attwell D, Laughlin SB: An energy budget for signaling in the grey matter of the brain. J Cereb Blood Flow Metab 2001;21:1133–1145.
  30. Hyder F: Neuroimaging with calibrated fMRI. Stroke 2004;35(11 suppl 1):2635–2641.

    External Resources

  31. Davis TL, Kwong KK, Weisskoff RM, Rosen BR: Calibrated functional MRI: mapping the dynamics of oxidative metabolism. Proc Natl Acad Sci USA 1998;95:1834–1839.
  32. D’Esposito M, Deouell LY, Gazzaley A: Alterations in the BOLD fMRI signal with ageing and disease: a challenge for neuroimaging. Nat Rev Neurosci 2003;4:863–872.
  33. Bentourkia M, Bol A, Ivanoiu A, Labar D, Sibomana M, Coppens A, Michel C, Cosnard G, De Volder AG: Comparison of regional cerebral blood flow and glucose metabolism in the normal brain: effect of aging. J Neurol Sci 2000;181:19–28.
  34. Claus JJ, Breteler MM, Hasan D, Krenning EP, Bots ML, Grobbee DE, Van Swieten JC, Van Harskamp F, Hofman A: Regional cerebral blood flow and cerebrovascular risk factors in the elderly population. Neurobiol Aging 1998;19:57–64.
  35. Kawamura J, Terayama Y, Takashima S, Obara K, Pavol MA, Meyer JS, Mortel KF, Weather S: Leuko-araiosis and cerebral perfusion in normal aging. Exp Aging Res 1993;19:225–240.
  36. Markus H, Cullinane M: Severely impaired cerebrovascular reactivity predicts stroke and TIA risk in patients with carotid artery stenosis and occlusion. Brain 2001;124(pt 3):457–467.
  37. Yamaguchi T, Kanno I, Uemura K, Shishido F, Inugami A, Ogawa T, Murakami M, Suzuki K: Reduction in regional cerebral metabolic rate of oxygen during human aging. Stroke 1986;17:1220–1228.
  38. Buckner RL, Snyder AZ, Sanders AL, Raichle ME, Morris JE: Functional brain imaging of young, nondemented, and demented older adults. J Cog Neurosci 2000;12(suppl 2):24–34.
  39. Tekes A, Mohamed MA, Browner NM, Calhoun VD, Yousem DM: Effect of age on visuomotor functional MR imaging. Acad Radiol 2005;12:739–745.
  40. Uspenskaia O, Liedetrau M, Herms J, Danek A, Hamann GF: Aging is associated with increased collagen type IV accumulation in the basal lamina of human cerebral microvessels. BMC Neurosci 2004;5:37.
  41. Dixon RA, Hopp GA, Cohen A-L, de Frias CM, Backman L: Self-reported memory compensation: similar patterns in Alzheimer’s disease and very old adult samples. J Clin Exp Neuropsychol 2003;25:382–390.
  42. Aine CJ, Woodruff CC, Knoefel JE, Adair JC, Hudson D, Qualls C, Bockholt J, Best E, Kovacevic S, Cobb W, Padilla D, Hart B, Stephen JM: Aging: Compensation or maturation? NeuroImage 2006;32:1891–1904.
  43. Braak H, Braak E: Frequency stages of Alzheimer-related lesions in different age categories. Neurobiol Aging 1997;18:351–357.
  44. Jak AJ, Houston WS, Nagel BJ, Corey-Bloom J, Bondi MW: Differential cross-sectional and longitudinal impact of APOE genotype on hippocampal volumes in nondemented older adults. Dement Geriatr Cogn Disord 2007;23:382–389.
  45. Cabeza R, McIntosh AR, Grady CL, Nyberg L, Houle S, Tulving, E: Age-related changes in neural interactions during memory encoding and retrieval: A network analysis of PET data. Brain Cogn 1997;35:369–372.

    External Resources

  46. Daselaar SM, Prince SE, Cabeza R: When less means more: deactivations during encoding that predict subsequent memory. NeuroImage 2004;23:921–927.
  47. Hayes SM, Cabeza R: Imaging aging: present and future; in Hofer SM, Alwin DF (eds): Handbook of Cognitive Aging: Interdisciplinary Perspectives. Thousand Oaks, Sage, 2008, pp 308–326.
  48. Fazekas F, Schmidt R, Kleinert R, et al: The spectrum of age-associated brain abnormalities: their measurement and histopathological correlates. J Neural Transm Suppl 1998;53:31–39.
  49. Bangen KJ, Restom K, Liu TT, Jak AJ, Perthen JE, Wierenga CE, Salmon DP, Bondi MW: Differential age effects on cerebral blood flow and BOLD response to encoding: associations with cognition and stroke risk. Neurobiol Aging 2007, Epub ahead of print.
  50. Poldrack RA: Imaging brain plasticity: conceptual and methodological issues – A theoretical review. NeuroImage 2000;12:1–13.
  51. Schlaggar BL, Brown TT, Lugar HM, Visscher KM, Miezin FM, Petersen SE: Functional neuroanatomical differences between adults and school-age children in the processing of single words. Science 2002;296:1476–1479.
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