Concluding remarks

Unlike the disorders reviewed in the remainder of this volume, ageing is not pathological - although it serves as a strong risk factor for many neurodegenerative disorders. In some conditions (e.g. Alzheimer’s disease, Parkinson’s disease), it can be difficult to discriminate between these conditions and healthy ageing, with early stages of these diseases showing very subtle impairments compared to healthy ageing. This is an active area of research, as is the topic of how to predict a person’s ‘brain age’ - the trajectory' towards successful ageing, cognitive decline or dementia. Cortico-basal ganglia, cortico-cerebellar circuits and the interaction between them support important motor and non-motor cognitive processes. These circuits deteriorate with age, resulting in subtle but similar impairments to those found in neurodegenerative illnesses.


Ap amyloid-beta

Ap+ amyloid-beta positive

Ap- amyloid-beta negative

DTI diffusion tensor imaging

FDG fludeoxyglucose

fMRI functional magnetic resonance imaging

HAROLD hemispheric asymmetry reduction in old age ICA independent component analysis

PASA posterior to anterior shift in ageing

PET positron emission tomography

Further reading

Bernard, J. A. & Seidler, R. D. (2014). Moving forward: age effects on the cerebellum underlie cognitive and motor declines. Neuroscience & Biobehavioral Reviews, 42, 193-207. Bostan, A. C. & Strick, P. L. (2018). The basal ganglia and the cerebellum: nodes in an integrated network. Nature Reviews Neuroscience, doi:10.1038/s41583-018-0002-7 Haines, D. & Mihailoff, G. (2018). The pons and cerebellum. In D. Haines & G. Mihailoff (eds), Fundamental Neuroscience for Basic and Clinical Applications, vol. 5 (pp. 172—182). Oxford: Elsevier.

Wichmann, T. & DeLong, M. R. (2013). The basal ganglia. In E. Kandel, J. Schwartz, T. Jessell, S. Siegelbaum & A. Hudspeth (eds), Principles of Neural Science (pp. 982—998). New York: McGraw Hill.


Aizenstein, H. J., Nebes, R. D., Saxton, ). A., Price, J. C., Mathis, C. A., Tsopelas, N. D.,

. . . Houck, P. R. (2008). Frequent amyloid deposition without significant cognitive impairment among the elderly. Archives of Neurology, 65(11), 1509-1517.

Alexander, G. E., Chen, K., Merkley, T. L., Reiman, E. M., Caselli, R.J., Aschenbrenner, M.,

. . . Teipel, S. ). (2006). Regional network of magnetic resonance imaging gray matter volume in healthy aging. Neuroreport, 17(10), 951—956.

Alexopoulos, G. S. Sc Kelly, R. E. (2017) Late-life depression: translating neurobiological hypotheses into novel treatments. In R. Cabeza, L. Nyberg & D. C. Park (eds), Cognitive Neuroscience of Ageing. New York: Oxford University Press.

Allen, E. A., Erhardt, E. B., Damaraju, E., Gruner, W., Segall, J. M., Silva, R. F., . . . Kalyanam, R. (2011). A baseline for the multivariate comparison of resting-state networks. Frontiers in Systems Neuroscience, 5, 2.

Andrews-Hanna, J. R., Snyder, A. Z., Vincent, J. L., Lustig, C., Head, D., Raichle, M. E. & Buckner, R. L. (2007). Disruption oflarge-scale brain systems in advanced aging. Neuron, 56(5), 924-935.

Andrews-Hanna, J. R., Smallwood, J. & Spreng, R. N. (2014). The default network and self-generated thought: component processes, dynamic control, and clinical relevance. Annals of the New York Academy of Sciences, 1316(), 29-52.

Anguera, J. A., Reuter-Lorenz, P. A., Willingham, D. T. & Seidler, R. D. (2011). Failure to engage spatial working memory contributes to age-related declines in visuomotor learning. Journal of Cognitive Neuroscience, 25(1), 11-25.

Apostolova, L. G., Hwang,K. S., Andrawis, }. P., Green, A. E.,Babakchanian,S., Morra.J. H.,

. . . Shaw, L. M. (2010). 3D PIB and CSF biomarker associations with hippocampal atrophy in ADNI subjects. Neurobiology of Aging, 51(8), 1284—1303.

Arnemann, K. L., Stober, F., Narayan, S., Rabinovici, G. D. & Jagust, W. J. (2018). Metabolic brain networks in aging and preclinical Alzheimer’s disease. Neuroimage: Clinical, 17, 987-999.

Backman, L., Lindenberger, U., Li, S.-C. & Nyberg, L. (2010). Linking cognitive aging to alterations in dopamine neurotransmitter functioning: recent data and future avenues. Neuroscience & Biobehavioral Reviews, 54(5), 670-677.

Baker, J. E., Lim, Y. Y., Pietrzak, R. H., Hassenstab, J., Snyder, P. J.. Masters, C. L. Sc Maruff, P. (2017). Cognitive impairment and decline in cognitively normal older adults with high amyloid-p: a meta-analysis. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, 6, 108-121.

Becker, J. A., Hedden, T., Carmasin, J., Maye, J., Rentz, D. M., Putcha, D., . . . Salloway, S.

(2011). Amyloid-P associated cortical thinning in clinically normal elderly. Annals of Neurology, 69(6), 1032-1042.

Bennett, D., Schneider, J., Arvartitakis, Z., Kelly, J., Aggarwal, N.. Shah, R. & Wilson, R. (2006). Neuropathology of older persons without cognitive impairment from two community-based studies. Neurology, 66(12), 1837-1844.

Bennett, D. A., Beckett, L. A., Murray, A. M., Shannon, К. M., Goetz, C. G., Pilgrim, D. M. Sc Evans, D. A. (1996). Prevalence of parkinsonian signs and associated mortality in a community population of older people. New England Journal of Medicine, 534(2), 71-76.

Bennett, I. J. Sc Madden, D. J. (2014). Disconnected aging: cerebral white matter integrity and age-related differences in cognition. Neuroscience, 216, 187—205.

Bennett, I. J., Madden, D. J., Vaidya, C. J., Howard, D. V. Sc Howard Jr, J. H. (2010). Age-related differences in multiple measures of white matter integrity: a diffusion tensor imaging study of healthy aging. Human Brain Mapping, 31(3), 378-390.

Bernard, J. A., Peltier, S, J., Wiggins, J. L., Jaeggi, S. M., Buschkuehl, M., Fling, B. W., . . . Seidler, R. D. (2013). Disrupted cortico-cerebeUar connectivity in older adults. Neuroimage, 83, 103-119.

Bernard, J. A. & Seidler, R. D. (2014). Moving forward: age effects on the cerebellum underlie cognitive and motor declines. Neuroscience & Biobehavioral Reviews, 42, 193-207.

Betzel, R. F., Byrge, L., He, Y., Goni, J., Zuo, X.-N. & Spoms, O. (2014). Changes in structural and functional connectivity among resting-state networks across the human lifespan. Neuroimage, 102, 345-357.

Bishop, N. A., Lu, T. & Yankner, B. A. (2010). Neural mechanisms of ageing and cognitive decline. Nature, 464(7288), 529.

Bo,J., Peltier, S., Noll, D. & Seidler, R. (2011). Age differences in symbolic representations of motor sequence learning. Neuroscience Letters, 504{1), 68-72.

Bonifazi, P., Erramuzpe, A., Diez, I., Gabilondo, I., Boisgontier, M. P., Pauwels, L., . . . Cortes, J. M. (2018). Structure-function multi-scale connectomics reveals a major role of the fronto-striato-thalamic circuit in brain aging. Human Brain Mapping, 39(12), 4663-4677.

Bostan, A. C., Dum, R. P. & Strick, P. L. (2010). The basal ganglia communicate with the cerebellum. Proceedings of the National Academy of Sciences, 107(18), 8452-8456.

Bostan, A. C. & Strick, P. L. (2018). The basal ganglia and the cerebellum: nodes in an integrated network. Nature Reviews Neuroscience, 1.

Braak, H., Thai. D. R., Ghebremedhin, E. & Del Tredici, K. (2011). Stages ofthe pathologic process in Alzheimer disease: age categories from 1 to 100 years .Journal of Neuropathology & Experimental Neurology, 70(11), 960-969.

Buchman, A. S., Shulntan, J. M., Nag, S., Leurgans, S. E., Arnold, S. E., Morris, M. C., . . . Bennett, D. A. (2012). Nigral pathology and parkinsonian signs in elders without Parkinson disease. Annals of Neurology, 71(2), 258-266.

Buckner, R. L. (2013). The cerebellum and cognitive function: 25 years of insight from anatomy and neuroimaging. Neuron, 80(3), 807-815.

Buckner, R. L., Andrews-Hanna, ). R. & Schacter, D. L. (2008). The brain’s default network. Annals of the New York Academy of Sciences, 1124(1), 1-38.

Cabeza, R. (2002). Hemispheric asymmetry reduction in older adults: the HAROLD model. Psychology and Aging, 17(1), 85.

Cabeza, R., Nyberg, L. & Park, D. C. (2017). Cognitive Neuroscience of Aging Linking Cognitive and Cerebral Aging. Oxford: Oxford University Press.

Caligiore, D., Pezzulo, G., Baldassarre, G., Bostan, A. C., Strick, P. L., Doya, K.,. . . Jorntell, H. (2017). Consensus paper: towards a systems-level view of cerebellar function: the interplay between cerebellum, basal ganglia, and cortex. The Cerebellum, 16(1), 203-229.

Campbell, K. L., Grady, C. L., Ng, C. & Hasher, L. (2012). Age differences in the frontoparietal cognitive control network: implications for distractibility. Neuropsyclwlogia, 50(9), 2212-2223.

Cao, M„ Wang, J.-H., Dai, Z.-J., Cao, X.-Y., Jiang, L.-L., Fan, F.-M.....Dong, Q.

(2014). Topological organization of the human brain functional connectome across the lifespan. Developmental Cognitive Neuroscience, 7, 76-93.

Cavallari, M., Moscufo, N., Skudlarski, P., Meier, D., Panzer, V. P., Pearlson, G. D., . . . Guttmann, C. R. (2013). Mobility impairment is associated with reduced microstruc- tural integrity of the inferior and superior cerebellar peduncles in elderly with no clinical signs of cerebellar dysfunction. Neuroimage: Clinical, 2, 332-340.

Chan, M. Y„ Park, D. C„ Savalia, N. K.. Petersen, S. E. & Wig, G. S. (2014). Decreased segregation of brain systems across the healthy adult lifespan. Proceedings of the National Academy of Sciences, 111(46), E4997-E5006.

Chen, Z., Jamadar, S. D., Li, S., Sforazzini, F., Baran, J., Ferris, N., . . . Egan, G. F. (2018). From simultaneous to synergistic MR-PET brain imaging: a review of hybrid MR-PET imaging methodologies. Human Brain Mapping, 39( 12), 5126-5144.

Chetelat, G., La Joie, R., Villain, N.. Perrotin, A., de La Sayette, V., Eustache, F. & Vandenberghe, R. (2013). Amyloid imaging in cognitively normal individuals, at-risk populations and preclinical Alzheimer’s disease. Neuroimage: Clinical, 2, 356-365.

Cole, J. FI., Marioni, R. E.. Harris, S. E. & Dear)', I. ). (2018). Brain age and other bodily ‘ages’: implications for neuropsychiatry. Molecular Psychiatry, 1. doi: 10.1038/s41380- 018-0098-1.

Courchesne, E., Chisum, H. J., Townsend, J., Cowles, A., Covington, J., Egaas, B., . . . Press, G. A. (2000). Normal brain development and aging: quantitative analysis at in vivo MR imaging in healthy volunteers. Radiology, 216(3), 672-682.

Craik, F. I. & Hay, J. F. (1999). Aging and judgments of duration: effects of task complexity and method of estimation. Perception & Psychophysics, 61(3), 549-560.

Damoiseaux, J. S. (2017). Effects of aging on functional and structural brain connectivity. Neuroimage, 160, 32-40.

Damoiseaux, J. S., Beckmann, C., Arigita, E. S., Barkhof, F., Scheltens, P., Stain, C., . . . Rombouts, S. (2007). Reduced resting-state brain activity in the ‘default network’ in normal aging. Cerebral Cortex, /8(8), 1856-1864.

Daugherty, A. & Raz, N. (2013). Age-related differences in iron content of subcortical nuclei observed in vivo: a meta-analysis. Neuroimage, 70, 113-121.

Davis, S. W„ Dennis, N. A., Daselaar, S. M„ Fleck, M. S. & Cabeza, R. (2007). Que PASA? The posterior-anterior shift in aging. Cerebral Cortex, 18(5), 1201-1209.

DeCarlo, C. A.. Tuokko, H. A.. Williams, D„ Dixon, R. A. & MacDonald, S. W. (2014). BioAge: toward a multi-determined, mechanistic account of cognitive aging. Ageing Research Reviews, 18, 95-105.

DeLong, M. R. & Wichmann, T. (2015). Basal ganglia circuits as targets for neuromodulation in Parkinson disease. JAMA Neurology, 72(11), 1354—1360.

Dickstein, D. L., Kabaso, D., Rocher, A. B., Luebke, J. I., Wearne, S. L. & Hof, P. R. (2007). Changes in the structural complexity of the aged brain. Aging Cell, 6(3), 275-284.

Dore, V., Villemagne, V. L., Bourgeat, P., Fripp.J., Acosta, O., Chetelat, G., . . . Masters, C. L. (2013). Cross-sectional and longitudinal analysis of the relationship between Ap deposition, cortical thickness, and memory in cognitively unimpaired individuals and in Alzheimer disease. JAMA Neurology, 70(7), 903—911.

Doya, K. (2000). Complementary roles of basal ganglia and cerebellum in learning and motor control. Current Opinion in Neurobiology, 10(b), 732-739.

Eckert, M. A., Keren, N. I., Roberts, D. R., Calhoun, V. D. & Harris, К. C. (2010). Age- related changes in processing speed: unique contributions of cerebellar and prefrontal cortex. Frontiers in Human Neuroscience, 4, 10.

Elman, J. A., Oh, H„ Madison, С. M„ Baker, S. L„ Vogel, J. W„ Marks, S. M.....

Jagust, W. J. (2014). Neural compensation in older people with brain amyloid-p deposition. Nature Neuroscience, 17(10), 1316.

Farquhar, M. (1995). Elderly people’s definitions of quality of life. Social Science & Medicine, 4/(10), 1439-1446.

Fearnley.J. M. & Lees, A.J. (1991). Ageing and Parkinson’s disease: substantia nigra regional selectivity. Brain, 114(5), 2283-2301.

Fjell, A. M. Ik Walhovd, К. B. (2010). Structural brain changes in aging: courses, causes and cognitive consequences. Reviews in the Neurosciences, 21(3), 187-222.

Fjell, A. M., Walhovd, K. 13., Fennema-Notestine, C., McEvoy, L. K., Hagler, D. )., Holland, D., . . . Dale, A. M. (2009). One-year brain atrophy evident in healthy aging. Journal of Neuroscience, 29(48), 15223-15231.

Fjell, A. M., Westlye, L. T., Grydeland, H., Amlien, I„ Espeseth, T., Reinvang, I.....

Walhovd, K. 13. (2013). Critical ages in the life course of the adult brain: nonlinear subcortical aging. Neurobiology of Aging, 34(10), 2239-2247.

Fornito, A., Zalesky, A. & Breakspear, M. (2015). The connectomics of brain disorders. Nature Remews Neuroscience, 16(3), 159.

Fox, P. T., Laird, A. R. & Lancaster, J. L. (2005). Coordinate-based voxel-wise metaanalysis: dividends of spatial normalization. Report of a virtual workshop. Human Brain Mapping, 25(1), 1-5.

Gao, F„ Edden, R. A., Li, M„ Puts, N. A.. Wang, G„ Liu, C.....Zhao, C. (2013). Edited

magnetic resonance spectroscopy detects an age-related decline in brain GABA levels. Neuroimage, 78, 75-82.

Geerligs, L., Renken, R. J., Saliasi, E., Maurits, N. M. Sc Lorist, M. M. (2014). A brain-wide study of age-related changes in functional connectivity. Cerebral Cortex, 25(7), 1987-1999. Geerligs, L., Rubinov, M. & Henson, R. N. (2015). State and trait components of functional connectivity: individual differences vary with mental state. Journal of Neuroscience, 35(41), 13949-13961.

Giorgio, A., Santelli, L., Tomassini, V., Bosnell, R., Smith, S., De Stefano, N. & Johansen-Berg, H. (2010). Age-related changes in grey and white matter structure throughout adulthood. Neuroimage, 5/(3), 943-951.

Good, C., Johnsrude, I., Ashburner, J., Henson, R., Friston, K. & Frackowiak, R. (2001). A voxel-based morphometric study of ageing in 465 normal adult human brains. Neuroimage, /4(1 Pt 1), 21-36.

Grady, C. (2012). The cognitive neuroscience of ageing. Nature Reviews Neuroscience, /3(7), 491. Grady, C., Sarraf, S., Saverino, C. Sc Campbell, K. (2016). Age differences in the functional interactions among the default, frontoparietal control, and dorsal attention networks. Neurobiology of Aging, 41, 159-172.

Grady, C. L., Springer, M. V., Hongwanishkul, D., McIntosh, A. R. & Winocur, G. (2006). Age-related changes in brain activity across the adult lifespan. Journal of Cognitive Neuroscience, 18(2), 227-241.

Griffanti, L., Stratmann, P., Rolinski, M., Filippini, N., Zsoldos, E., Mahmood, A., . . . Kivimaki, M. (2018). Exploring variability in basal ganglia connectivity with functional MRI in healthy aging. Brain Imaging and Behavior, /2(6), 1822-1827 Guerreiro, R. & Bras, J. (2015). The age factor in Alzheimer’s disease. Genome Medicine, 7(1), 106.

Haines, D. & Mihailoff G. (2018). Fundamental Neuroscience for Basic and Clinical Applications, vol. 5. Oxford: Elsevier.

Hardy, J. Sc Selcoe, D. J. (2002). The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics. Science, 297, 353-356.

Harris, J. J., Jolivet, R. Sc Attwell, D. (2012). Synaptic energy use and supply. Neuron, 75(5), 762-777.

Haycock, J. W., Becker, L., Ang, L.. Furukawa, Y.. Homykiewicz, O. Sc Kish, S. J. (2003). Marked disparity between age-related changes in dopamine and other presynaptic dopaminergic markers in human striatum. Journal of Neurochemistry, 87(3), 574—585.

Hedman, A. M.. van Haren, N. E., Schnack, H. G., Kahn, R. S. Sc Hulshoff Pol, H. E.

(2012). Human brain changes across the life span: a review of 56 longitudinal magnetic resonance imaging studies. Human Brain Mapping, 33(8), 1987-2002.

Heuninckx, S., Wenderoth, N., Debaere, F., Peeters, R. & Swinnen, S. P. (2005). Neural basis of aging: the penetration of coalition into action control. Journal of Neuroscience, 25(29), 6787-6796.

Heuninckx, S., Wenderoth, N. & Swinnen, S. P. (2008). Systems neuroplasticity in the aging brain: recruiting additional neural resources for successful motor performance in elderly persons. Journal of Neuroscience, 28(1), 91—99.

Hoshi, E., Tremblay, L., Feger, J., Carras, P. L. & Strick, P. L. (2005). The cerebellum communicates with the basal ganglia. Nature Neuroscience, 2(11), 1491.

Houk, J., Bastianen, C., Fansler, D., Fishbach, A., Fraser, D., Reber, P., . . . Simo, L. (2007). Action selection and refinement in subcortical loops through basal ganglia and cerebellum. Philosophical Transactions of the Royal Society of London В: Biological Sciences, 562(1485), 1573-1583.

Hulst, T., van der Geest, |. N., Thiirling, M., Goericke, S., Frens, M. A., Timmann, D. & Donchin, O. (2015). Ageing shows a pattern of cerebellar degeneration analogous, but not equal, to that in patients suffering from cerebellar degenerative disease. Neuroimage, 116, 196—206.

Iyo, M. & Yamasaki, T. (1993). The detection of age-related decrease of dopamine Dl, D2 and serotonin 5-HT2 receptors in living human brain. Progress in Neuro-psychopharmacology & Biological Psychiatry, 17(3), 415-421.

Jack, C. R„ Wiste, H. J., Weigand, S. D„ Rocca, W. A., Knopman, D. S„ Mielke, M. M.....

Preboske, G. M. (2014). Age-specific population frequencies of cerebral P-amyloidosis and neurodegeneration among people with normal cognitive function aged 50-89 years: a cross-sectional study. The Lancet Neurology, 15(10), 997-1005.

Jamadar, S. D., Egan, G. F., Calhoun, V. D., Johnson, B. & Fielding, ). (2016). Intrinsic connectivity provides the baseline framework for variability in motor performance: a multivariate fusion analysis of low-and high-frequency resting-state oscillations and anti- saccade performance. Brain Connectivity, 6(6), 505—517.

Jansen, W. J., Ossenkoppele, R., Knol, D. L., Tijms, В. M., Scheltens, P., Verhey, F. R., . . . Alcolea, D. (2015). Prevalence of cerebral amyloid pathology in persons without dementia: a meta-analysis. Journal of the American Medical Association, 515(19), 1924-1938.

Jernigan, T. L., Archibald, S. L., Fennema-Notestine, C., Gamst, A. C., Stout, J. C., Bonner, ). & Hesselink, J. R. (2001). Effects of age on tissues and regions of the cerebrum and cerebellum. Neurobiology of Aging, 22(4), 581—594.

Jia, L., Zhang, W. & Chen, X. (2017). Common methods of biological age estimation. Clinical Interventions in Aging, 12, 759.

Kafri, M., Sasson, E., Assaf, Y., Balash, Y., Aiznstein, O., Hausdorff, J. M. & Giladi, N.

(2013). High-level gait disorder: associations with specific white matter changes observed on advanced diffusion imaging. Journal of Neuroimaging, 23(1), 39^16.

Kalpouzos, G., Chetelat, G., Baron, J.-C., Landeau, B., Mevel, K., Godeau, C., . . . Eustache, F. (2009). Voxel-based mapping of brain gray matter volume and glucose metabolism profiles in normal aging. Neurobiology of Aging, 30(1), 112-124.

Karrer, T. M., Josef, A. K., Mata, R., Morris, E. D. & Samanez-Larkin, G. R. (2017). Reduced dopamine receptors and transporters but not synthesis capacity in normal aging adults: a meta-analysis. Neurobiology of Aging, 51, 36-46.

Kelly, C., de Zubicaray, G., Di Martino, A., Copland, D. A., Reiss, P. T.. Klein, D. F.....

McMahon, K. (2009). L-dopa modulates functional connectivity in striatal cognitive and motor networks: a double-blind placebo-controlled study. Journal of Neuroscience, 29(22), 7364-7378.

Kelly, R. M. & Strick, P. L. (2004). Macro-architecture of basal ganglia loops with the cerebral cortex: use of rabies virus to reveal multisynaptic circuits. Progress in Brain Research, 143, 447-450.

Kety, S. S. (1057). The general metabolism of the brain in vivo. In Metabolism of the Nervous System (pp. 221-237). Oxford: Elsevier.

Khan, S. S., Singer, B. D. & Vaughan, D. E. (2017). Molecular and physiological manifestations and measurement of aging in humans. Aging Cell, 16(4), 624—633.

Kish, S. ]., Shannak, K., Rajput, A., Deck. ]. H. & Homykiewicz, O. (1002). Aging produces a specific pattern of striatal dopamine loss: implications for the etiology of idiopathic Parkinson’s disease. Journal of Neurochemistry, 58(2), 642—648.

Koziol, L. F., Budding, D., Andreasen, N., D’Arrigo, S., Bulgheroni, S., Imamizu, H., . . . Parker, K. (2014). Consensus paper: the cerebellum’s role in movement and cognition. The Cerebellum, 13( 1), 151-177.

Laird, A. R„ Eickhoff, S. B„ Li, K„ Robin, D. A., Glahn, D. C. & Fox, P. T. (2000). Investigating the functional heterogeneity of the default mode network using coordinate- based meta-analytic modeling. Journal of Neuroscience, 20(46), 14406-14505.

Lanciego, J. L., Luquin, N. & Obeso, ). A. (2012). Functional neuroanatomy of the basal ganglia. Cold Spring Harbor Perspectives in Medicine, a000621.

Langan, |„ Peltier, S„ Bo, J.. Fling, B. W„ Welsh, R. C. & Seidler, R. D. (2010). Functional implications of age differences in motor system connectivity. Frontiers in Systems Neuroscience, 4, 17.

Langenecker, S. A., Briceno, E. M., Hamid, N. M. tk Nielson, K. A. (2007). An evaluation of distinct volumetric and functional MRI contributions toward understanding age and task performance: a study in the basal ganglia. Brain Research, 1135, 58-68.

Lim, H. K., Nebes, R., Snitz, B., Cohen, A., Mathis, C., Price, ).,... Aizenstein, H. ).

(2014). Regional amyloid burden and intrinsic connectivity networks in cognitively normal elderly subjects. Brain, 137(12), 3327-3338.

Lisberger, S. & Thach, T. (2013). The cerebellum. In E. Kandel, J. Schwartz, T. Jessell, S. Siegelbaum & A. Hudspeth (eds), Principles of Neural Science (pp. 060—081). New York: McGraw Hill.

Lustig, C., Snyder, A. Z., Bliakta, M., O’Brien, К. C., McAvoy, M., Raichle, M. E., . . . Buckner, R. L. (2003). Functional deactivations: change with age and dementia of the Alzheimer type. Proceedings of the National Academy of Sciences, 100(24), 14504—14500.

Ma, S., Roytt, M., Collan, Y. & Rinne, J. (1000). Unbiased morphometrical measurements show loss of pigmented nigral neurones with ageing. Neuropathology and Applied Neurobiology, 25(5), 304-300.

Maccioni, R. B., Farias, G., Morales, I., Navarrete, L. (2010). The revitalised tau hypothesis on Alzheimer’s disease. Archives of Medical Research, 41, 226-231.

Maillard, P., Carmichael, O., Hetcher, E., Reed, B., Mungas, D. & DeCarli, C. (2012). Coevolution of white matter hyperintensities and cognition in the elderly. Neurology, 79(5), 442-448.

Mak, L. E„ Minuzzi, L„ MacQueen, G„ Hall, G„ Kennedy, S. H. & Milev, R. (2017). The default mode network in healthy individuals: a systematic review and meta-analysis. Brain Connectivity, 7(1), 25-33.

Marchand, W. R., Lee,J. N.. Suchy, Y., Gam, C., Johnson, S., Wood, N. & Chelune, G. (2011). Age-related changes of the functional architecture of the cortico-basal ganglia circuitry during motor task execution. Neuroimage, 55(1), 194—203.

Meier, T. B., Desphande, A. S., Vergun, S., Nair, V. A., Song, J., Biswal, В. B., . . . Prabhakaran, V. (2012). Support vector machine classification and characterization of age-related reorganization of functional brain networks. Neuroimage, (50(1), 601-613.

Miall, R. C. & Wolpert, D. M. (1996). Forward models for physiological motor control. Neural Networks, 9(8), 1265-1279.

Michely, J., Volz, L. )., Hoffstaedter, F., Tittgemeyer, M., Eickhoff S. B., Fink, G. R. & Grefkes, C. (2018). Network connectivity' of motor control in the ageing brain. Neuroimage: Clinical, 18, 445-455.

Miller, T. D„ Ferguson, K. J.. Reid, L. M„ Wardlaw.J. M„ Starr, J. M„ Seckl, J. R.....

MacLullich, A. M. (2013). Cerebellar vermis size and cognitive ability' in community- dwelling elderly men. The Cerebellum, /2(1), 68-73.

Nambu, A. (2008). Seven problems on the basal ganglia. Current Opinion in Neurobiology, 18(b), 595-604.

Nambu, A., Tokuno, H. Sc Takada, M. (2002). Functional significance of the cortico- subthalamo-pallidal ‘hy'perdirect’ pathway'. Neuroscience Research, 43(2), 111-117.

Netuveli, G.. Wiggins, R. D., Hildon, Z.. Montgomery, S. M. & Blane, D. (2006). Quality of life at older ages: evidence from the English longitudinal study of aging (wave 1). Journal of Epidemiology & Community Health, 60(4), 357-363.

Onoda, K., Ishihara, M. Sc Yamaguchi, S. (2012). Decreased functional connectivity by aging is associated with cognitive decline. Journal of Cognitive Neuroscience, 24(11), 2186—2198.

Porges, E. C., Woods, A. J., Edden, R. A., Puts, N. A., Harris, A. D., Chen, H., . . . Williamson, J. B. (2017). Frontal gamma-aminobutyric acid concentrations are associated with cognitive performance in older adults. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 2(1), 38-44.

Price, J. L. Sc Morris, J. C. (1999). Tangles and plaques in nondemented aging and ‘preclini- cal’ Alzheimer’s disease. Annals of Neurology: Official Journal of the American Neurological Association and the Child Neurology Society, 45(3), 358-368.

Prins, N. D. Sc Scheltens, P. (2015). White matter hyperintensities, cognitive impairment and dementia: an update. Nature Reviews Neurology, 11(3), 157.

Rajah, M. N. & D’esposito, M. (2005). Region-specific changes in prefrontal function with age: a review of PET and fMRI studies on working and episodic memory. Brain, 128(9), 1964-1983.

Ramnani, N. (2006). The primate cortico-cerebellar system: anatomy and function. Nature Reviews Neuroscience, 7(7), 511.

Raz, N., Gunning, F. M., Head, D., Dupuis, ). H., McQuain, J., Briggs, S. D., . . . Acker, J. D. (1997). Selective aging of the human cerebral cortex observed in vivo: differential vulnerability of the prefrontal gray matter. Cerebral Cortex, 7(3), 268-282.

Raz, N., Lindenberger, U., Rodrigue, К. M., Kennedy, К. M., Head, D., Williamson, A., . . . Acker, J. D. (2005). Regional brain changes in aging healthy adults: general trends, individual differences and modifiers. Cerebral Cortex, /5(11), 1676-1689.

Reeve, A., Simcox, E. Sc Turnbull, D. (2014). Ageing and Parkinson’s disease: why is advancing age the biggest risk factor? Ageing Research Reviews, 14, 19-30.

Reeves, S., Bench, C. Sc Howard, R. (2002). Ageing and the nigrostriatal dopaminergic system. International Journal of Geriatric Psychiatry, 17(4), 359-370.

Reuter-Lorenz, P. A. Sc Cappell, K. A. (2008). Neurocognitive aging and the compensation hypothesis. Current Directions in Psychological Science, /7(3), 177-182.

Ronnlund, M., Nyberg, L., Backman, L. Sc Nilsson, L.-G. (2005). Stability, growth, and decline in adult life span development of declarative memory: cross-sectional and longitudinal data from a population-based study. Psychology and Aging, 20(1), 3.

Rosano, C., Aizenstein, H. J., Studenski, S. & Newman, A. B. (2007). A regions-of-interest volumetric analysis of mobility limitations in community-dwelling older adults. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 62(9), 1048-1055.

Rudow, G., O’Brien, R., Savonenko, A. V., Resnick, S. M., Zonderman, A. B., Pletnikova, O.,

. . . West, M. ). (2008). Morphometry of the human substantia nigra in ageing and Parkinson’s disease. Acta Neuropathologica, ti5{4), 461.

Rugg, M. D. (2017). Intepreting age-related differences in memory-related neural activity. In R. Cabeza, L. Nyberg & D. C. Park (eds), Cognitive Neuroscience of Ageing. New York: Oxford University Press, doi: 10.1093/acprof:oso/9780199372935.001.0001 Safe, A., Cooper, S. Sc Windsor, A. (1992). Cerebellar ataxia in the elderly. Journal of the Royal Society of Medicine, 85(8), 449.

Salat, D. H., Buckner, R. L., Snyder, A. Z., Greve, D. N., Desikan, R. S., Busa, E., . . . Fischl, B. (2004). Thinning of the cerebral cortex in aging. Cerebral Cortex, 14(7), 721-730.

Salat, D. H., Greve, D. N.. Pacheco, J. L.. Quinn, В. T., Helmer, K. G., Buckner, R. L. & Fischl, B. (2009). Regional white matter volume differences in nondemented aging and Alzheimer’s disease. Neuroimage, 44(4), 1247-1258.

Salthouse, T. (2010). Selective review of cognitive aging. Journal of the International Neuropsychological Society, 16(5), 754—760.

Salthouse, T. (2012). Consequences of age-related cognitive declines. Annual Review of Psychology, 6.1, 201-226.

Sambataro, F., Murty, V. P., Callicott, J. H., Tan, H.-Y., Das, S., Weinberger, D. R. & Mattay, V. S. (2010). Age-related alterations in default mode network: impact on working memory performance. Neurobiology of Aging, 31(5), 839-852.

Scahill, R. I., Frost, C„ Jenkins, R„ Whitwell, J. L„ Rossor, M. N. Sc Fox, N. C. (2003). A longitudinal study of brain volume changes in normal aging using serial registered magnetic resonance imaging. Archives of Neurology, 60(7), 989-994.

Schmahmann, J. D. (1991). An emerging concept: the cerebellar contribution to higher function. Archives of Neurology, 48(11), 1178-1187.

Schmahmann, J. D. (2000). The role of the cerebellum in affect and psychosis. Journal of Neurolinguistics, 13(2-5), 189-214.

Scholl. M., Lockhart, S. N.. Schonhaut, D. R., O’Neil, J. P., Janabi, M., Ossenkoppele, R.,

. . . Schwimmer, H. D. (2016). PET imaging of tau deposition in the aging human brain. Neuron, 89(5), 971-982.

Seidler, R. D., Bernard, J. A., Burutolu, T. B., Fling, B. W., Gordon. M. T., Gwin.J. T.....

Lipps, D. B. (2010). Motor control and aging: links to age-related brain structural, functional, and biochemical effects. Neuroscience & Biobeliavioral Reviews, 34(5), 721-733. Sepulcre, J., Schultz, A. P., Sabuncu, M., Gomez-Isla, T., Chhatwal, J., Becker, A., . . . Johnson, K. A. (2016). In vivo tau, amyloid, and gray matter profiles in the aging brain. Journal of Neuroscience, 46(28), 7364—7374.

Severson, J., Marcusson, J., Winblad, B. Sc Finch, C. (1982). Age-correlated loss of dopaminergic binding sites in human basal ganglia. Journal of Neurochemistry, 39(6), 1623-1631.

Sheline, Y. I., Raichle, M. E., Snyder, A. Z., Morris,J. C., Head, D., Wang, S. Sc Mintun, M. A. (2010). Amyloid plaques disrupt resting state default mode network connectivity in cognitively normal elderly. Biological Psychiatry, 67(6), 584—587.

Shiloh, Y. Sc Lederman, H. M. (2017). Ataxia-telangiectasia (AT): an emerging dimension of premature ageing. Ageing Research Reviews, 33, 76-88.

Sokoloff, L. (1960). The metabolism of the central nervous system in vivo. Handbook of Physiology, Section I, Neurophysiology, 3, 1843-1864.

Solesio-Jofre, E., Serbruyns, L., Woolley, D. G., Mantini, D., Beets, I. A. Sc Swinnen, S. P. (2014). Aging effects on the resting state motor network and interlimb coordination. Human Brain Mapping, J5(8), 3945-3961.

Sperling, R. A., Aisen, P. S., Beckett, L, A., Bennett, D. A., Craft, S., Fagan, A. M., . . . Montine, T. J. (2011). 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 and Dementia, 7(3), 280-292.

Spoms, O. (2013). Network attributes for segregation and integration in the human brain. Current Opinion in Neurobiology, 23(2), 162-171.

Spreng, R. N., Stevens, W. D., Viviano, J. D. & Schacter, D. L. (2016). Attenuated anticorrelation between the default and dorsal attention networks with aging: evidence from task and rest. Neurobiology of Aging, 45, 149-160.

Su, L., Wang, L., Chen, F., Shen, H., Li, B. & Hu, D. (2012). Sparse representation of brain aging: extracting covariance patterns from structural MRI. PloS One, 7(5), e36147.

Sudarsky, L. & Ronthal, M. (1983). Gait disorders among elderly patients: a survey study of 50 patients. Archives of Neurology, 40(12), 740-743.

Svennerholm, L., Bostrom, K. & Jungbjer, B. (1997). Changes in weight and compositions of major membrane components of human brain during the span of adult human life of Swedes. Acta Neuropathologica, 94(4), 345-352.

Tang, Y., Whitman, G. T., Lopez, I. & Baloh, R. W. (2001). Brain volume changes on longitudinal magnetic resonance imaging in normal older people. Journal of Neuroimaging, 11(4), 393-400.

Taniwaki, T., Okayama, A., Yoshiura, T., Togao, O., Nakamura, Y., Yamasaki, T., . . . Kira, J.-i. (2007). Age-related alterations of the functional interactions within the basal ganglia and cerebellar motor loops in vivo. Neuroimage, 36(4), 1263-1276.

Toinasi, D. & Volkow, N. D. (2012). Aging and functional brain networks. Molecular Psychiatry, 17(5), 549.

Vernooij, M. W., Ikram, M. A., Tanghe, H. L., Vincent, A. J., Hofman, A., Krestin, G. P., . . . van der Lugt, A. (2007). Incidental findings on brain MRI in the general population. New England Journal of Medicine, 357(18), 1821-1828.

Villemagne, V. L., Fodero-Tavoletti, M. T., Masters, C. L. & Rowe, С. C. (2015). Tau imaging: early progress and future directions. The Lancet Neurology, /4(1), 114—124.

Walhovd, К. B., Johansen-Berg, H. & Karadottir, R. T. (2014). Unraveling the secrets of white matter-bridging the gap between cellular, animal and human imaging studies. Neuroscience, 276, 2-13.

Walhovd, К. B., Westlye, L. T., Amlien, I., Espeseth, T., Reinvang, L, Raz, N., . . . Fischl, B. (2011). Consistent neuroanatomical age-related volume differences across multiple samples. Neurobiology of Aging, 32(5), 916-932.

Wang, J., Zuo, X., He, Y. (2010). Graph-based network analysis of resting-state functional MRI. Frontiers in Systems Neuroscience, doi:10.3389/fnsys.2010.00016.

Ward, N. & Frackowiak, R. (2003). Age-related changes in the neural correlates of motor performance. Brain, 126(4), 873-888.

Wichmann, T. & DeLong, M. R. (2013). The basal ganglia. In E. Kandel, J. Schwartz, T. Jessell, S. Siegelbaum & A. Hudspeth (eds), Principles of Neural Science (pp. 982—999). New York: McGraw Hill.

Wong, D. F„ Wagner, H. N„ Dannals, R. F„ Links, J. M„ Frost, J. J., Ravert, H. T.....

Douglass, К. H. (1984). Effects of age on dopamine and serotonin receptors measured by positron tomography in the living human brain. Science, 226(4681), 1393-1396.

Woodruff-Рак, D. S.,* Vogel III, R. W.. Ewers, M„ Coffey, J.. Boyko, О. B. & Lemieux, S. K. (2001). MRI-assessed volume of cerebellum correlates with associative learning. Neurobiology of Learning and Memory, 76(3), 342-357.

Wu, T., Zang, Y., Wang, L„ Long, X., Hallett, M., Chen, Y.....Chan, P. (2007).

Aging influence on functional connectivity of the motor network in the resting state. Neuroscience Letters, 422(3), 164—168.

Yamamoto, M., Suhara, T., Okubo, Y., Ichimiya, T., Sudo, Y., Inoue, M., . . . Tanada, S. (2002). Age-related decline of serotonin transporters in living human brain of healthy males. Life Sciences, 71(7), 751-757.

Yin, F., Sancheti, H., Patil, I. & Cadenas, E. (2016). Energy metabolism and inflammation in brain aging and Alzheimer’s disease. Free Radical Biology and Medicine, 100, 108—122. Young, V. G., Halliday, G. M. & Kril. ). J. (2008). Neuropathologic correlates of white matter hyperintensities. Neurology, 71(11), 804—811.

Zhang, H.-Y., Chen, W.-X., Jiao, Y„ Xu, Y„ Zhang, X.-R. Sc Wu, J.-T. (2014). Selective vulnerability related to aging in large-scale resting brain networks. PloS One, 9(10), el 08807.


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