Neuroplastic effects of combined computerized physical and cognitive training in elderly individuals at risk for dementia: an eLORETA controlled study on resting states

Charis Styliadis, Panagiotis Kartsidis, Evangelos Paraskevopoulos, Andreas A Ioannides, Panagiotis D Bamidis, Charis Styliadis, Panagiotis Kartsidis, Evangelos Paraskevopoulos, Andreas A Ioannides, Panagiotis D Bamidis

Abstract

The present study investigates whether a combined cognitive and physical training may induce changes in the cortical activity as measured via electroencephalogram (EEG) and whether this change may index a deceleration of pathological processes of brain aging. Seventy seniors meeting the clinical criteria of mild cognitive impairment (MCI) were equally divided into 5 groups: 3 experimental groups engaged in eight-week cognitive and/or physical training and 2 control groups: active and passive. A 5-minute long resting state EEG was measured before and after the intervention. Cortical EEG sources were modelled by exact low resolution brain electromagnetic tomography (eLORETA). Cognitive function was assessed before and after intervention using a battery of neuropsychological tests including the minimental state examination (MMSE). A significant training effect was identified only after the combined training scheme: a decrease in the post- compared to pre-training activity of precuneus/posterior cingulate cortex in delta, theta, and beta bands. This effect was correlated to improvements in cognitive capacity as evaluated by MMSE scores. Our results indicate that combined physical and cognitive training shows indices of a positive neuroplastic effect in MCI patients and that EEG may serve as a potential index of gains versus cognitive declines and neurodegeneration. This trial is registered with ClinicalTrials.gov Identifier NCT02313935.

Figures

Figure 1
Figure 1
Flow of participants within the 3 experimental and 2 control groups.
Figure 2
Figure 2
Grand average of eLORETA solutions (i.e., CDR at PCu/PCC voxels at P < 0.05, corrected) modelling the EEG source for delta band in the LLM group on the corresponding axial (left view) and sagittal (right view) generic MRI slices. The left side of the maps (left view) corresponds to the left hemisphere. The power estimate was scaled based on the averaged maximum value indicated in the scale bar. Similar illustrations but of fewer voxels apply for the theta, beta 1, and beta 2 bands.
Figure 3
Figure 3
Visualization of the negative correlation of delta (r = −0.546, P = 0.043) (a) and theta (r = −0.633, P = 0.015) (b) bands among the MMSE score post- to pre-difference of each participant and the CDR post- to pre-difference of PCu/PCC activity that was statistically significant at P < 0.05, corrected.

References

    1. Fratiglioni L., Paillard-Borg S., Winblad B. An active and socially integrated lifestyle in late life might protect against dementia. The Lancet Neurology. 2004;3(6):343–353. doi: 10.1016/s1474-4422(04)00767-7.
    1. Woodard J. L., Sugarman M. A., Nielson K. A., et al. Lifestyle and genetic contributions to cognitive decline and hippocampal structure and function in healthy aging. Current Alzheimer Research. 2012;9(4):436–446. doi: 10.2174/156720512800492477.
    1. Woodard J. L., Seidenberg M., Nielson K. A., et al. Prediction of cognitive decline in healthy older adults using fMRI. Journal of Alzheimer's Disease. 2010;21(3):871–885. doi: 10.3233/jad-2010-091693.
    1. Clark C. M., Davatzikos C., Borthakur A., et al. Biomarkers for early detection of Alzheimer pathology. NeuroSignals. 2008;16(1):11–18. doi: 10.1159/000109754.
    1. Sperling R. A., Aisen P. S., Beckett L. A., et al. Toward defining the preclinical stages of Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimer's & Dementia. 2011;7(3):280–292. doi: 10.1016/j.jalz.2011.03.003.
    1. Styliadis C., Kartsidis P., Paraskevopoulos E. Neuroimaging approaches for elderly studies. In: Bamidis P. D., Tarnanas I., Hadjileontiadis L., Tsolaki M., editors. Handbook of Research on Innovations in the Diagnosis and Treatment of Dementia. Hershey, Pa, USA: IGI Global; 2015. pp. 1–439.
    1. Arnáiz E., Almkvist O. Neuropsychological features of mild cognitive impairment and preclinical Alzheimer's disease. Acta Neurologica Scandinavica, Supplement. 2003;107(supplement 179):34–41.
    1. Galluzzi S., Cimaschi L., Ferrucci L., Frisoni G. B. Mild cognitive impairment: clinical features and review of screening instruments. Aging Clinical and Experimental Research. 2001;13(3):183–202. doi: 10.1007/bf03351477.
    1. Petersen R. C., Doody R., Kurz A., et al. Current concepts in mild cognitive impairment. Archives of Neurology. 2001;58(12):1985–1992. doi: 10.1001/archneur.58.12.1985.
    1. Petersen R. C., Smith G. E., Ivnik R. J., et al. Apolipoprotein E status as a predictor of the development of Alzheimer's disease in memory-impaired individuals. The Journal of the American Medical Association. 1995;273(16):1274–1278. doi: 10.1001/jama.1995.03520400044042.
    1. Larrieu S., Letenneur L., Orgogozo J. M., et al. Incidence and outcome of mild cognitive impairment in a population-based prospective cohort. Neurology. 2002;59(10):1594–1599. doi: 10.1212/01.wnl.0000034176.07159.f8.
    1. Petersen R. C. Mild cognitive impairment as a diagnostic entity. Journal of Internal Medicine. 2004;256(3):183–194. doi: 10.1111/j.1365-2796.2004.01388.x.
    1. Bamidis P. D., Vivas A. B., Styliadis C., et al. A review of physical and cognitive interventions in aging. Neuroscience & Biobehavioral Reviews. 2014;44: 206–220. doi: 10.1016/j.neubiorev.2014.03.019.
    1. Busse A. L., Gil G., Santarém J. M., Filho W. J. Physical activity and cognition in the elderly: a review. Dementia e Neuropsychologia. 2009;3(3):204–208.
    1. Colcombe S. J., Kramer A. F. Fitness effects on the cognitive function of older adults: a meta-analytic study. Psychological Science. 2003;14(2):125–130. doi: 10.1111/1467-9280.t01-1-01430.
    1. Tardif S., Simard M. Cognitive stimulation programs in healthy elderly: a review. International Journal of Alzheimer's Disease. 2011;2011:13. doi: 10.4061/2011/378934.378934
    1. Kramer A. F., Erickson K. I. Capitalizing on cortical plasticity: influence of physical activity on cognition and brain function. Trends in Cognitive Sciences. 2007;11(8):342–348. doi: 10.1016/j.tics.2007.06.009.
    1. Cotman C. W., Berchtold N. C., Christie L.-A. Exercise builds brain health: key roles of growth factor cascades and inflammation. Trends in Neurosciences. 2007;30(9):464–472. doi: 10.1016/j.tins.2007.06.011.
    1. Smith J. C., Nielson K., Woodard J., Seidenberg M., Rao S. M. Physical activity and brain function in older adults at increased risk for Alzheimer’s disease. Brain Sciences. 2013;3(1):54–83. doi: 10.3390/brainsci3010054.
    1. Schooler C., Mulatu M. S. The reciprocal effects of leisure time activities and intellectual functioning in older people: a longitudinal analysis. Psychology and Aging. 2001;16(3):466–482. doi: 10.1037//0882-7974.16.3.466.
    1. Belleville S. Cognitive training for persons with mild cognitive impairment. International Psychogeriatrics. 2008;20(1):57–66. doi: 10.1017/S104161020700631X.
    1. Simon S. S., Yokomizo J. E., Bottino C. M. C. Cognitive intervention in amnestic Mild Cognitive Impairment: a systematic review. Neuroscience & Biobehavioral Reviews. 2012;36(4):1163–1178. doi: 10.1016/j.neubiorev.2012.01.007.
    1. Damoiseaux J. S., Beckmann C. F., Arigita E. J. S., et al. Reduced resting-state brain activity in the ‘default network’ in normal aging. Cerebral Cortex. 2008;18(8):1856–1864. doi: 10.1093/cercor/bhm207.
    1. Raichle M. E., Snyder A. Z. A default mode of brain function: a brief history of an evolving idea. NeuroImage. 2007;37(4):1083–1090. doi: 10.1016/j.neuroimage.2007.02.041.
    1. Greicius M. D., Krasnow B., Reiss A. L., Menon V. Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proceedings of the National Academy of Sciences of the United States of America. 2003;100(1):253–258. doi: 10.1073/pnas.0135058100.
    1. Greicius M. D., Menon V. Default-mode activity during a passive sensory task: uncoupled from deactivation but impacting activation. Journal of Cognitive Neuroscience. 2004;16(9):1484–1492. doi: 10.1162/0898929042568532.
    1. Raichle M. E., MacLeod A. M., Snyder A. Z., Powers W. J., Gusnard D. A., Shulman G. L. A default mode of brain function. Proceedings of the National Academy of Sciences of the United States of America. 2001;98(2):676–682. doi: 10.1073/pnas.98.2.676.
    1. Buckner R. L., Snyder A. Z., Shannon B. J., et al. Molecular, structural, and functional characterization of Alzheimer's disease: evidence for a relationship between default activity, amyloid, and memory. Journal of Neuroscience. 2005;25(34):7709–7717. doi: 10.1523/jneurosci.2177-05.2005.
    1. Garcés P., Ángel Pineda-Pardo J., Canuet L., et al. The default mode network is functionally and structurally disrupted in amnestic mild cognitive impairment—a bimodal MEG–DTI study. NeuroImage: Clinical. 2014;6:214–221. doi: 10.1016/j.nicl.2014.09.004.
    1. Greicius M. D., Srivastava G., Reiss A. L., Menon V. Default-mode network activity distinguishes Alzheimer's disease from healthy aging: Evidence from functional MRI. Proceedings of the National Academy of Sciences of the United States of America. 2004;101(13):4637–4642. doi: 10.1073/pnas.0308627101.
    1. Petrella J. R., Sheldon F. C., Prince S. E., Calhoun V. D., Doraiswamy P. M. Default mode network connectivity in stable vs progressive mild cognitive impairment. Neurology. 2011;76(6):511–517. doi: 10.1212/WNL.0b013e31820af94e.
    1. Baker M., Akrofi K., Schiffer R., Boyle M. W. O. EEG patterns in mild cognitive impairment (MCI) patients. The Open Neuroimaging Journal. 2008;2:52–55. doi: 10.2174/1874440000802010052.
    1. van der Hiele K., Vein A. A., Reijntjes R. H. A. M., et al. EEG correlates in the spectrum of cognitive decline. Clinical Neurophysiology. 2007;118(9):1931–1939. doi: 10.1016/j.clinph.2007.05.070.
    1. Gianotti L. R. R., Künig G., Lehmann D., et al. Correlation between disease severity and brain electric LORETA tomography in Alzheimer's disease. Clinical Neurophysiology. 2007;118(1):186–196. doi: 10.1016/j.clinph.2006.09.007.
    1. Jelic V., Johansson S.-E., Almkvist O., et al. Quantitative electroencephalography in mild cognitive impairment: longitudinal changes and possible prediction of Alzheimer's disease. Neurobiology of Aging. 2000;21(4):533–540. doi: 10.1016/s0197-4580(00)00153-6.
    1. Huang C., Wahlund L.-O., Dierks T., Julin P., Winblad B., Jelic V. Discrimination of Alzheimer's disease and mild cognitive impairment by equivalent EEG sources: a cross-sectional and longitudinal study. Clinical Neurophysiology. 2000;111(11):1961–1967. doi: 10.1016/s1388-2457(00)00454-5.
    1. Babiloni C., Binetti G., Cassetta E., et al. Sources of cortical rhythms change as a function of cognitive impairment in pathological aging: a multicenter study. Clinical Neurophysiology. 2006;117(2):252–268. doi: 10.1016/j.clinph.2005.09.019.
    1. Fabel K., Wolf S. A., Ehninger D., Babu H., Leal-Galicia P., Kempermann G. Additive effects of physical exercise and environmental enrichment on adult hippocampal neurogenesis in mice. Frontiers in Neuroscience. 2009;3, article 50 doi: 10.3389/neuro.22.002.2009.
    1. Fabel K., Kempermann G. Physical activity and the regulation of neurogenesis in the adult and aging brain. NeuroMolecular Medicine. 2008;10(2):59–66. doi: 10.1007/s12017-008-8031-4.
    1. González-Palau F., Franco M., Bamidis P. D., et al. The effects of a computer-based cognitive and physical training program in a healthy and mildly cognitive impaired aging sample. Aging & Mental Health. 2014;18(7):838–846. doi: 10.1080/13607863.2014.899972.
    1. Oswald W. D., Gunzelmann T., Rupprecht R., Hagen B. Differential effects of single versus combined cognitive and physical training with older adults: the SimA study in a 5-year perspective. European Journal of Ageing. 2006;3(4):179–192. doi: 10.1007/s10433-006-0035-z.
    1. Frantzidis C. A., Ladas A.-K. I., Vivas A. B., Tsolaki M., Bamidis P. D. Cognitive and physical training for the elderly: evaluating outcome efficacy by means of neurophysiological synchronization. International Journal of Psychophysiology. 2014;93:1–11. doi: 10.1016/j.ijpsycho.2014.01.007.
    1. Bamidis P. D. Long Lasting Memories Project Deliverable D1.4 Final Report. 2012.
    1. Frantzidis C. A., Vivas A. B., Tsolaki A., Klados M. A., Tsolaki M. N., Bamidis P. D. Functional disorganization of small-world brain networks in mild Alzheimer's Disease and amnestic Mild Cognitive Impairment: an EEG study using Relative Wavelet Entropy (RWE) Frontiers in Aging Neuroscience. 2014;6, article 224 doi: 10.3389/fnagi.2014.00224.
    1. Hughes C. P., Berg L., Danziger W. L., Coben L. A., Martin R. L. A new clinical scale for the staging of dementia. British Journal of Psychiatry. 1982;140(6):566–572. doi: 10.1192/bjp.140.6.566.
    1. Folstein M. F., Folstein S. E., McHugh P. R. ‘Mini-mental state’. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research. 1975;12:189–198.
    1. Roth M., Tym E., Mountjoy C. Q., et al. CAMDEX. A standardised instrument for the diagnosis of mental disorder in the elderly with special reference to the early detection of dementia. British Journal of Psychiatry. 1986;149:698–709. doi: 10.1192/bjp.149.6.698.
    1. Anthony J. C., LeResche L., Niaz U., von Korff M. R., Folstein M. F. Limits of the ‘mini-mental state’ as a screening test for dementia and delirium among hospital patients. Psychological Medicine. 1982;12(2):397–408. doi: 10.1017/s0033291700046730.
    1. Grut M., Fratiglioni L., Viitanen M., Winblad B. Accuracy of the Mini-Mental Status Examination as a screening test for dementia in a Swedish elderly population. Acta Neurologica Scandinavica. 1993;87(4):312–317.
    1. Fountoulakis K. N., Tsolaki M., Chantzi H., Kazis A. Mini mental state examination (MMSE): a validation study in Greece. American Journal of Alzheimer's Disease. 2000;15(6):342–345. doi: 10.1177/153331750001500604.
    1. Smith G. E., Housen P., Yaffe K., et al. A cognitive training program based on principles of brain plasticity: results from the improvement in memory with plasticity-based adaptive cognitive training (IMPACT) study. Journal of the American Geriatrics Society. 2009;57(4):594–603. doi: 10.1111/j.1532-5415.2008.02167.x.
    1. Konstantinidis E. I., Billis A. S., Mouzakidis C. A., Zilidou V. I., Antoniou P. E., Bamidis P. D. Design, implementation and wide pilot deployment of FitForAll: an easy to use exergaming platform improving physical fitness and life quality of senior citizens. IEEE Journal of Biomedical and Health Informatics. 2014 doi: 10.1109/jbhi.2014.2378814.
    1. Billis A. S., Konstantinidis E. I., Mouzakidis C. A., Tsolaki M. N., Pappas C., Bamidis P. D. A game-like interface for training seniors’ dynamic balance and coordination. In: Bamidis P., Pallikarakis N., editors. XII Mediterranean Conference on Medical and Biological Engineering and Computing 2010. Vol. 29. Berlin, Germany: Springer; 2010. pp. 691–694. (IFMBE Proceedings).
    1. Bamidis P. D., Fissler P., Papageorgiou S. G., et al. Gains in cognition through combined cognitive and physical training: dosage and severity of neurocognitive disorder matters. Frontiers in Aging Neuroscience. Under review.
    1. Mahncke H. W., Connor B. B., Appelman J., et al. Memory enhancement in healthy older adults using a brain plasticity-based training program: a randomized, controlled study. Proceedings of the National Academy of Sciences of the United States of America. 2006;103(33):12523–12528. doi: 10.1073/pnas.0605194103.
    1. Mahncke H. W., Bronstone A., Merzenich M. M. Chapter 6 Brain plasticity and functional losses in the aged: scientific bases for a novel intervention. Progress in Brain Research. 2006;157:81–109. doi: 10.1016/S0079-6123(06)57006-2.
    1. Snowden M., Steinman L., Mochan K., et al. Effect of exercise on cognitive performance in community-dwelling older adults: review of intervention trials and recommendations for public health practice and research. Journal of the American Geriatrics Society. 2011;59(4):704–716. doi: 10.1111/j.1532-5415.2011.03323.x.
    1. Tseng C.-N., Gau B.-S., Lou M.-F. The effectiveness of exercise on improving cognitive function in older people: a systematic review. The Journal of Nursing Research. 2011;19(2):119–131. doi: 10.1097/jnr.0b013e3182198837.
    1. Miron-Shatz T., Hansen M. M., Grajales F. J., Martin-Sanchez F., Bamidis P. D. Social media for the promotion of holistic self-participatory care: an evidence based approach. Contribution of the IMIA social media working group. Yearbook of Medical Informatics. 2013;8(1):162–168.
    1. Oostenveld R., Fries P., Maris E., Schoffelen J.-M. FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Computational Intelligence and Neuroscience. 2011;2011:9. doi: 10.1155/2011/156869.156869
    1. Jung T.-P., Makeig S., Humphries C., et al. Removing electroencephalographic artifacts by blind source separation. Psychophysiology. 2000;37(2):163–178. doi: 10.1017/s0048577200980259.
    1. Wyckoff S., Mayer K., Sherlin L., Strehl U. Exact low-resolution electromagnetic brain tomography (eloreta) of adult ADHD: pre/post findings following neurofeedback therapy. Journal of Neurotherapy. 2011:420–422.
    1. Lakshminarayanan M. Y., Horton R. The general linear model. Technometrics. 1988;30(1):p. 130. doi: 10.2307/1270349.
    1. Nichols T. E., Holmes A. P. Nonparametric permutation tests for functional neuroimaging: a primer with examples. Human Brain Mapping. 2002;15(1):1–25. doi: 10.1002/hbm.1058.
    1. Nichols T. E. Multiple testing corrections, nonparametric methods, and random field theory. NeuroImage. 2012;62(2):811–815. doi: 10.1016/j.neuroimage.2012.04.014.
    1. Prichep L. S., John E. R., Ferris S. H., et al. Quantitative EEG correlates of cognitive deterioration in the elderly. Neurobiology of Aging. 1994;15(1):85–90.
    1. Schreiter-Gasser U., Gasser T., Ziegler P. Quantitative EEG analysis in early onset Alzheimer's disease: correlations with severity, clinical characteristics, visual EEG and CCT. Electroencephalography and Clinical Neurophysiology. 1994;90(4):267–272. doi: 10.1016/0013-4694(94)90144-9.
    1. Grunwald M., Busse F., Hensel A., et al. Correlation between cortical θ activity and hippocampal volumes in health, mild cognitive impairment, and mild dementia. Journal of Clinical Neurophysiology. 2001;18(2):178–184. doi: 10.1097/00004691-200103000-00010.
    1. Jelic V., Shigeta M., Jnlin P., Almkvist O., Winblad B., Wahhmd L. O. Quantitative electroencephalography power and coherence in Alzheimer's disease and mild cognitive impairment. Dementia. 1996;7(6):314–323.
    1. Babiloni C., Binetti G., Cassetta E., et al. Mapping distributed sources of cortical rhythms in mild Alzheimer's disease. A multicentric EEG study. NeuroImage. 2004;22(1):57–67. doi: 10.1016/j.neuroimage.2003.09.028.
    1. Jeong J. EEG dynamics in patients with Alzheimer's disease. Clinical Neurophysiology. 2004;115(7):1490–1505. doi: 10.1016/j.clinph.2004.01.001.
    1. Dierks T., Ihl R., Frölich L., Maurer K. Dementia of the Alzheimer type: effects on the spontaneous EEG described by dipole sources. Psychiatry Research—Neuroimaging. 1993;50(3):151–162. doi: 10.1016/0925-4927(93)90027-f.
    1. Prichep L. S., John E. R., Ferris S. H., et al. Prediction of longitudinal cognitive decline in normal elderly with subjective complaints using electrophysiological imaging. Neurobiology of Aging. 2006;27(3):471–481. doi: 10.1016/j.neurobiolaging.2005.07.021.
    1. Babiloni C., Binetti G., Cassarino A., et al. Sources of cortical rhythms in adults during physiological aging: a multicentric EEG study. Human Brain Mapping. 2006;27(2):162–172. doi: 10.1002/hbm.20175.
    1. Hartikainen P., Soininen H., Partanen J., Helkala E. L., Riekkinen P. Aging and spectral analysis of EEG in normal subjects: a link to memory and CSF AChE. Acta Neurologica Scandinavica. 1992;86(2):148–155. doi: 10.1111/j.1600-0404.1992.tb05057.x.
    1. Jelic V., Dierks T., Amberla K., Almkvist O., Winblad B., Nordberg A. Longitudinal changes in quantitative EEG during long-term tacrine treatment of patients with Alzheimer's disease. Neuroscience Letters. 1998;254(2):85–88. doi: 10.1016/S0304-3940(98)00669-7.
    1. Grunwald M., Hensel A., Wolf H., Weiss T., Gertz H.-J. Does the hippocampal atrophy correlate with the cortical theta power in elderly subjects with a range of cognitive impairment? Journal of Clinical Neurophysiology. 2007;24(1):22–26. doi: 10.1097/WNP.0b013e31802ed5b2.
    1. Fernández A., Arrazola J., Maestú F., et al. Correlations of hippocampal atrophy and focal low-frequency magnetic activity in Alzheimer disease: volumetric MR imaging—magnetoencephalographic study. The American Journal of Neuroradiology. 2003;24(3):481–487.
    1. Babiloni C., Carducci F., Lizio R., et al. Resting state cortical electroencephalographic rhythms are related to gray matter volume in subjects with mild cognitive impairment and Alzheimer's disease. Human Brain Mapping. 2013;34(6):1427–1446. doi: 10.1002/hbm.22005.
    1. Roh J. H., Park M. H., Ko D., et al. Region and frequency specific changes of spectral power in Alzheimer's disease and mild cognitive impairment. Clinical Neurophysiology. 2011;122(11):2169–2176. doi: 10.1016/j.clinph.2011.03.023.
    1. Babiloni C., Frisoni G. B., Vecchio F., et al. Stability of clinical condition in mild cognitive impairment is related to cortical sources of alpha rhythms: an electroencephalographic study. Human Brain Mapping. 2011;32(11):1916–1931. doi: 10.1002/hbm.21157.
    1. Frackowiak R., Friston K., Frith C., Dolan R. J., Mazziotta J. Human Brain Function. New York, NY, USA: Academic Press; 1997.
    1. van Hoesen G. W., Morecraft R. J., Vogt B. A. Neurobiology of Cingulate Cortex and Limbic Thalamus. Boston, Mass, USA: Birkhäuser; 1993. Connections of the monkey cingulate cortex; pp. 249–284.
    1. Cavanna A. E., Trimble M. R. The precuneus: a review of its functional anatomy and behavioural correlates. Brain. 2006;129(3):564–583. doi: 10.1093/brain/awl004.
    1. Khalsa S., Mayhew S. D., Chechlacz M., Bagary M., Bagshaw A. P. The structural and functional connectivity of the posterior cingulate cortex: comparison between deterministic and probabilistic tractography for the investigation of structure-function relationships. NeuroImage. 2014;102, part 1:118–127. doi: 10.1016/j.neuroimage.2013.12.022.
    1. Greicius M. D., Supekar K., Menon V., Dougherty R. F. Resting-state functional connectivity reflects structural connectivity in the default mode network. Cerebral Cortex. 2009;19(1):72–78. doi: 10.1093/cercor/bhn059.
    1. Zhou Y., Dougherty J. H., Jr., Hubner K. F., Bai B., Cannon R. L., Hutson R. K. Abnormal connectivity in the posterior cingulate and hippocampus in early Alzheimer's disease and mild cognitive impairment. Alzheimer's and Dementia. 2008;4(4):265–270. doi: 10.1016/j.jalz.2008.04.006.
    1. Fellgiebel A., Müller M. J., Wille P., et al. Color-coded diffusion-tensor-imaging of posterior cingulate fiber tracts in mild cognitive impairment. Neurobiology of Aging. 2005;26(8):1193–1198. doi: 10.1016/j.neurobiolaging.2004.11.006.
    1. Albert M. S., DeKosky S. T., Dickson D., et al. The diagnosis of mild cognitive impairment due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimer's and Dementia. 2011;7(3):270–279. doi: 10.1016/j.jalz.2011.03.008.
    1. McKhann G. M., Knopman D. S., Chertkow H., et al. The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimer's and Dementia. 2011;7(3):263–269. doi: 10.1016/j.jalz.2011.03.005.
    1. Jack C. R., Jr., Albert M. S., Knopman D. S., et al. Introduction to the recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimer's and Dementia. 2011;7(3):257–262. doi: 10.1016/j.jalz.2011.03.004.
    1. Dubois B., Feldman H. H., Jacova C., et al. Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS-ADRDA criteria. The Lancet Neurology. 2007;6(8):734–746. doi: 10.1016/s1474-4422(07)70178-3.
    1. Minoshima S., Giordani B., Berent S., Frey K. A., Foster N. L., Kuhl D. E. Metabolic reduction in the posterior cingulate cortex in very early Alzheimer's disease. Annals of Neurology. 1997;42(1):85–94. doi: 10.1002/ana.410420114.
    1. Mosconi L. Brain glucose metabolism in the early and specific diagnosis of Alzheimer's disease: FDG-PET studies in MCI and AD. European Journal of Nuclear Medicine and Molecular Imaging. 2005;32(4):486–510. doi: 10.1007/s00259-005-1762-7.
    1. Anchisi D., Borroni B., Franceschi M., et al. Heterogeneity of brain glucose metabolism in mild cognitive impairment and clinical progression to alzheimer disease. Archives of Neurology. 2005;62(11):1728–1733. doi: 10.1001/archneur.62.11.1728.
    1. Herholz K. Cerebral glucose metabolism in preclinical and prodromal Alzheimers disease. Expert Review of Neurotherapeutics. 2010;10(11):1667–1673. doi: 10.1586/ern.10.136.
    1. Alexander G. E., Chen K., Pietrini P., Rapoport S. I., Reiman E. M. Longitudinal PET evaluation of cerebral metabolic decline in dementia: a potential outcome measure in Alzheimer's disease treatment studies. American Journal of Psychiatry. 2002;159(5):738–745. doi: 10.1176/appi.ajp.159.5.738.
    1. Mattia D., Babiloni F., Romigi A., et al. Quantitative EEG and dynamic susceptibility contrast MRI in Alzheimer's disease: a correlative study. Clinical Neurophysiology. 2003;114(7):1210–1216. doi: 10.1016/s1388-2457(03)00085-3.
    1. Passero S., Rocchi R., Vatti G., Burgalassi L., Battistini N. Quantitative EEG mapping, regional cerebral blood flow, and neuropsychological function in Alzheimer's disease. Dementia. 1995;6(3):148–156.
    1. Buchan R. J., Nagata K., Yokoyama E., et al. Regional correlations between the EEG and oxygen metabolism in dementia of Alzheimer's type. Electroencephalography and Clinical Neurophysiology. 1997;103(3):409–417. doi: 10.1016/s0013-4694(97)00015-5.
    1. Jonkman E. J., Poortvliet D. C. J., Veering M. M., de Weerd A. W., John E. R. The use of neurometrics in the study of patients with cerebral ischaemia. Electroencephalography and Clinical Neurophysiology. 1985;61(5):333–341. doi: 10.1016/0013-4694(85)91023-5.
    1. Szelies B., Grond M., Herholz K., Kessler J., Wullen T., Heiss W.-D. Quantitative EEG mapping and PET in Alzheimer's disease. Journal of the Neurological Sciences. 1992;110(1-2):46–56. doi: 10.1016/0022-510x(92)90008-9.
    1. Helkala E.-L., Hänninen T., Könönen M., et al. Slow-wave activity in the spectral analysis of the electroencephalogram and volumes of hippocampus in subgroups of Alzheimer's disease patients. Behavioral Neuroscience. 1996;110(6):1235–1243. doi: 10.1037/0735-7044.110.6.1235.
    1. Valladares-Netoa D. C., Buchsbaum M. S., Evans W. J., et al. EEG delta, positron emission tomography, and memory deficit in Alzheimer's disease. Neuropsychobiology. 1995;31(4):173–181. doi: 10.1159/000119189.
    1. Prichep L. S. Quantitative EEG and electromagnetic brain imaging in aging and in the evolution of dementia. Annals of the New York Academy of Sciences. 2007;1097:156–167. doi: 10.1196/annals.1379.008.
    1. Thomas B. P., Yezhuvath U. S., Tseng B. Y., et al. Life-long aerobic exercise preserved baseline cerebral blood flow but reduced vascular reactivity to CO2 . Journal of Magnetic Resonance Imaging. 2013;38(5):1177–1183. doi: 10.1002/jmri.24090.
    1. Erickson K. I., Raji C. A., Lopez O. L., et al. Physical activity predicts gray matter volume in late adulthood: the Cardiovascular Health Study. Neurology. 2010;75(16):1415–1422. doi: 10.1212/wnl.0b013e3181f88359.
    1. Benedict C., Brooks S. J., Kullberg J., et al. Association between physical activity and brain health in older adults. Neurobiology of Aging. 2013;34(1):83–90. doi: 10.1016/j.neurobiolaging.2012.04.013.
    1. Karas G., Scheltens P., Rombouts S., et al. Precuneus atrophy in early-onset Alzheimer's disease: a morphometric structural MRI study. Neuroradiology. 2007;49(12):967–976. doi: 10.1007/s00234-007-0269-2.
    1. Hampstead B. M., Stringer A. Y., Stilla R. F., et al. Activation and effective connectivity changes following explicit-memory training for face-name pairs in patients with mild cognitive impairment: a pilot study. Neurorehabilitation & Neural Repair. 2011;25(3):210–222. doi: 10.1177/1545968310382424.
    1. van Paasschen J., Clare L., Yuen K. S. L., et al. Cognitive rehabilitation changes memory-related brain activity in people with Alzheimer disease. Neurorehabilitation and Neural Repair. 2013;27(5):448–459. doi: 10.1177/1545968312471902.
    1. Langdon K. D., Corbett D. Improved working memory following novel combinations of physical and cognitive activity. Neurorehabilitation and Neural Repair. 2012;26(5):523–532. doi: 10.1177/1545968311425919.
    1. Schaefer S., Schumacher V. The interplay between cognitive and motor functioning in healthy older adults: findings from dual-task studies and suggestions for intervention. Gerontology. 2011;57(3):239–246. doi: 10.1159/000322197.
    1. Shatil E. Does combined cognitive training and physical activity training enhance cognitive abilities more than either alone? A four-condition randomized controlled trial among healthy older adults. Frontiers in Aging Neuroscience. 2013;5, article 8 doi: 10.3389/fnagi.2013.00008.
    1. Kramer A. F., Hahn S., Cohen N. J., et al. Ageing, fitness and neurocognitive function. Nature. 1999;400(6743):418–419. doi: 10.1038/22682.
    1. Voss M. W., Prakash R. S., Erickson K. I., et al. Plasticity of brain networks in a randomized intervention trial of exercise training in older adults. Frontiers in Aging Neuroscience. 2010;2, article 32 doi: 10.3389/fnagi.2010.00032.
    1. Heyn P. C., Johnson K. E., Kramer A. F. Endurance and strength training outcomes on cognitively impaired and cognitively intact older adults: a meta-analysis. Journal of Nutrition, Health and Aging. 2008;12(6):401–409. doi: 10.1007/bf02982674.
    1. Fissler P., Küster O., Schlee W., Kolassa I.-T. Novelty interventions to enhance broad cognitive abilities and prevent dementia: synergistic approaches for the facilitation of positive plastic change. Progress in Brain Research. 2013;207:403–434. doi: 10.1016/b978-0-444-63327-9.00017-5.

Source: PubMed

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