White Matter Integrity Declined Over 6-Months, but Dance Intervention Improved Integrity of the Fornix of Older Adults

Agnieszka Z Burzynska, Yuqin Jiao, Anya M Knecht, Jason Fanning, Elizabeth A Awick, Tammy Chen, Neha Gothe, Michelle W Voss, Edward McAuley, Arthur F Kramer, Agnieszka Z Burzynska, Yuqin Jiao, Anya M Knecht, Jason Fanning, Elizabeth A Awick, Tammy Chen, Neha Gothe, Michelle W Voss, Edward McAuley, Arthur F Kramer

Abstract

Degeneration of cerebral white matter (WM), or structural disconnection, is one of the major neural mechanisms driving age-related decline in cognitive functions, such as processing speed. Past cross-sectional studies have demonstrated beneficial effects of greater cardiorespiratory fitness, physical activity, cognitive training, social engagement, and nutrition on cognitive functioning and brain health in aging. Here, we collected diffusion magnetic resonance (MRI) imaging data from 174 older (age 60-79) adults to study the effects of 6-months lifestyle interventions on WM integrity. Healthy but low-active participants were randomized into Dance, Walking, Walking + Nutrition, and Active Control (stretching and toning) intervention groups (NCT01472744 on ClinicalTrials.gov). Only in the fornix there was a time × intervention group interaction of change in WM integrity: integrity declined over 6 months in all groups but increased in the Dance group. Integrity in the fornix at baseline was associated with better processing speed, however, change in fornix integrity did not correlate with change in processing speed. Next, we observed a decline in WM integrity across the majority of brain regions in all participants, regardless of the intervention group. This suggests that the aging of the brain is detectable on the scale of 6-months, which highlights the urgency of finding effective interventions to slow down this process. Magnitude of WM decline increased with age and decline in prefrontal WM was of lesser magnitude in older adults spending less time sedentary and more engaging in moderate-to-vigorous physical activity. In addition, our findings support the anterior-to-posterior gradient of greater-to-lesser decline, but only in the in the corpus callosum. Together, our findings suggest that combining physical, cognitive, and social engagement (dance) may help maintain or improve WM health and more physically active lifestyle is associated with slower WM decline. This study emphasizes the importance of a physically active and socially engaging lifestyle among aging adults.

Keywords: DTI; brain; diffusion; fitness; fractional anisotropy; physical activity; processing speed; randomized clinical trial.

Figures

Figure 1
Figure 1
Change in diffusivity measures over 6-months in healthy older adults 60–79 years old. Different patterns of overlap of change in diffusivity parameters are represented by different colors. Superior corona radiata (SCR), superior longitudinal fasciculus (SLF), anterior and posterior limb of the internal capsule (ALIC, PLIC), external capsule (EC), fornix (FX), five regions of the corpus callosum (cc1–5), forceps major (fMAJ), forceps minor (fMIN), anterior and posterior cingulum (ACC, PCC), WM containing occipital portion of inferior longitudinal fasciculi and inferior frontal-occipital fasciculi (IFOF_ILF_occ), WM of the straight gyrus (gyrRect), parahippocampal WM (HIPP), ventral prefrontal part of uncinate fasciculus (UNC_pfc), WM containing uncinate and the inferior frontal-occipital fasciculi (IFOF_UNC), and WM of the temporal pole related to inferior longitudinal fasciculus (ILF_temp). Regions are overlaid on the FMRIB58_FA template.
Figure 2
Figure 2
(A) Time × group interaction in diffusivity parameters in the fornix in the four intervention groups. SD, standard deviation; Df, degrees of freedom. (B) Graphic representation of changes (delta) in FA, RD, and MD during 6-months presented in (A). Error bars: standard deviation.
Figure 3
Figure 3
Correlation between fornix FA and processing speed construct at baseline (n = 165).
Figure 4
Figure 4
Correlations between chronological age and % decline in FA over 6-months (n = 174).

References

    1. Adam D., Ramli A., Shahar S. (2016). Effectiveness of a combined dance and relaxation intervention on reducing anxiety and depression and improving quality of life among the cognitively impaired elderly. Sultan Qaboos Univ. Med. J. 16, e47–e53. 10.18295/squmj.2016.16.01.009
    1. Alexander R. P. D., Concha L., Snyder T. J., Beaulieu C., Gross D. W. (2014). Correlations between limbic white matter and cognitive function in temporal-lobe epilepsy, preliminary findings. Front. Aging Neurosci. 6:142. 10.3389/fnagi.2014.00142
    1. Ballesteros S., Mayas J., Prieto A., Toril P., Pita C., Laura P., et al. . (2015). A randomized controlled trial of brain training with non-action video games in older adults: results of the 3-month follow-up. Front. Aging Neurosci. 7:45. 10.3389/fnagi.2015.00045
    1. Bamidis P. D., Fissler P., Papageorgiou S. G., Zilidou V., Konstantinidis E. I., Billis A. S., et al. . (2015). Gains in cognition through combined cognitive and physical training: the role of training dosage and severity of neurocognitive disorder. Front. Aging Neurosci. 7:152. 10.3389/fnagi.2015.00152
    1. Barrick T. R., Charlton R. A., Clark C. A., Markus H. S. (2010). White matter structural decline in normal ageing: a prospective longitudinal study using tract-based spatial statistics. Neuroimage 51, 565–577. 10.1016/j.neuroimage.2010.02.033
    1. Bartzokis G. (2004). Age-related myelin breakdown: a developmental model of cognitive decline and Alzheimer's disease. Neurobiol. Aging 25, 5–18. 10.1016/j.neurobiolaging.2003.03.001
    1. Bartzokis G., Lu P. H., Tingus K., Mendez M. F., Richard A., Peters D. G., et al. . (2010). Lifespan trajectory of myelin integrity and maximum motor speed. Neurobiol. Aging 31, 1554–1562. 10.1016/j.neurobiolaging.2008.08.015
    1. Bartzokis G., Sultzer D., Lu P. H., Nuechterlein K. H., Mintz J., Cummings J. L. (2004). Heterogeneous age-related breakdown of white matter structural integrity: implications for cortical “disconnection” in aging and Alzheimer's disease. Neurobiol. Aging 25, 843–851. 10.1016/j.neurobiolaging.2003.09.005
    1. Basser P. J. (1995). Inferring microstructural features and the physiological state of tissues from diffusion-weighted images. NMR Biomed. 8, 333–344. 10.1002/nbm.1940080707
    1. Beaulieu C. (2002). The basis of anisotropic water diffusion in the nervous system - a technical review. NMR Biomed. 15, 435–455. 10.1002/nbm.782
    1. Beaulieu C., Does M. D., Snyder R. E., Allen P. S. (1996). Changes in water diffusion due to Wallerian degeneration in peripheral nerve. Magn. Reson. Med. 36, 627–631. 10.1002/mrm.1910360419
    1. Begg C. B., Iglewicz B. (1980). A treatment allocation procedure for sequential clinical trials. Biometrics 36, 81–90. 10.2307/2530497
    1. Bender A. R., Prindle J. J., Brandmaier A. M., Raz N. (2016a). White matter and memory in healthy adults: coupled changes over two years. Neuroimage 131, 193–204. 10.1016/j.neuroimage.2015.10.085
    1. Bender A. R., Völkle M. C., Raz N. (2016b). Differential aging of cerebral white matter in middle-aged and older adults: a seven-year follow-up. Neuroimage 125, 74–83. 10.1016/j.neuroimage.2015.10.030
    1. Bengtsson S. L., Nagy Z., Skare S., Forsman L., Forssberg H., Ullén F. (2005). Extensive piano practicing has regionally specific effects on white matter development. Nat. Neurosci. 8, 1148–1150. 10.1038/nn1516
    1. Black J. E., Isaacs K. R., Anderson B. J., Alcantara A. A., Greenough W. T. (1990). Learning causes synaptogenesis, whereas motor activity causes angiogenesis, in cerebellar cortex of adult rats. Proc. Natl. Acad. Sci. U.S.A. 87, 5568–5572. 10.1073/pnas.87.14.5568
    1. Bolandzadeh N., Tam R., Handy T. C., Nagamatsu L. S., Hsu C. L., Davis J. C., et al. . (2015). Resistance training and white matter lesion progression in older women: exploratory analysis of a 12-month randomized controlled trial. J. Am. Geriatr. Soc. 63, 2052–2060. 10.1111/jgs.13644
    1. Bullitt E., Rahman F. N., Smith J. K., Kim E., Zeng D., Katz L. M., et al. . (2009). The effect of exercise on the cerebral vasculature of healthy aged subjects as visualized by MR angiography. Am. J. Neuroradiol. 30, 1857–1863. 10.3174/ajnr.A1695
    1. Burzynska A. Z., Chaddock-Heyman L., Voss M. W., Wong C. N., Gothe N. P., Olson E. A., et al. . (2014). Physical activity and cardiorespiratory fitness are beneficial for white matter in low-fit older adults. PLoS ONE 9:e107413 10.1371/journal.pone.0107413
    1. Burzynska A. Z., Garrett D. D., Preuschhof C., Nagel I. E., Li S.-C., Bäckman L., et al. . (2013). A scaffold for efficiency in the human brain. J. Neurosci. 33, 17150–17159. 10.1523/jneurosci.1426-13.2013
    1. Burzynska A. Z., Preuschhof C., Bäckman L., Nyberg L., Li S. C., Lindenberger U., et al. . (2010). Age-related differences in white matter microstructure: region-specific patterns of diffusivity. Neuroimage 49, 2104–2112. 10.1016/j.neuroimage.2009.09.041
    1. Burzynska A. Z., Wong C. N., Voss M. W., Cooke G. E., Gothe N. P., Fanning J., et al. . (2015). Physical activity is linked to greater moment-to-moment variability in spontaneous brain activity in older adults. PLoS ONE 10:e0134819. 10.1371/journal.pone.0134819
    1. Carro E., Nuñez A., Busiguina S., Torres-Aleman I. (2000). Circulating insulin-like growth factor I mediates effects of exercise on the brain. J. Neurosci. 20, 2926–2933. 10.1016/j.tins.2006.06.011
    1. Ciccarelli O., Behrens T. E., Altmann D. R., Orrell R. W., Howard R. S., Johansen-Berg H., et al. . (2006). Probabilistic diffusion tractography: a potential tool to assess the rate of disease progression in amyotrophic lateral sclerosis. Brain 129, 1859–1871. 10.1093/brain/awl100
    1. Colby J. B., Van Horn J. D., Sowell E. R. (2011). Quantitative in vivo evidence for broad regional gradients in the timing of white matter maturation during adolescence. Neuroimage 54, 25–31. 10.1016/j.neuroimage.2010.08.014
    1. Colcombe S. J., Erickson K. I., Scalf P. E., Kim J. S., Prakash R., McAuley E., et al. . (2006). Aerobic exercise training increases brain volume in aging humans. J. Gerontol. A Biol. Sci. Med. Sci. 61, 1166–1170. 10.1093/gerona/61.11.1166
    1. Concha L., Gross D. W., Wheatley B. M., Beaulieu C. (2006). Diffusion tensor imaging of time-dependent axonal and myelin degradation after corpus callosotomy in epilepsy patients. Neuroimage 32, 1090–1099. 10.1016/j.neuroimage.2006.04.187
    1. Copeland J. L., Esliger D. W. (2009). Accelerometer assessment of physical activity in active, healthy older adults. J. Aging Phys. Act. 17, 17–30. 10.1123/japa.17.1.17
    1. Copenhaver B. R., Rabin L. A., Saykin A. J., Roth R. M., Wishart H. A., Flashman L. A., et al. . (2006). The fornix and mammillary bodies in older adults with Alzheimer's disease, mild cognitive impairment, and cognitive complaints: a volumetric MRI study. Psychiatry Res. Neuroimag. 147, 93–103. 10.1016/j.pscychresns.2006.01.015
    1. Cosottini M., Giannelli M., Siciliano G., Lazzarotti G., Michelassi M. C., del Corona A., et al. . (2005). Diffusion-tensor MR imaging of corticospinal tract in amyotrophic lateral sclerosis and progressive muscular atrophy. Radiology 237, 258–264. 10.1148/radiol.2371041506
    1. Demiot C., Dignat-George F., Fortrat J.-O., Sabatier F., Gharib C., Larina I., et al. . (2007). WISE 2005: chronic bed rest impairs microcirculatory endothelium in women. Am. J. Physiol. Heart Circ. Physiol. 293, H3159–H3164. 10.1152/ajpheart.00591.2007
    1. Dhami P., Moreno S., DeSouza J. F. X. (2015). New framework for rehabilitation-Fusion of cognitive and physical rehabilitation: the hope for dancing. Front. Psychol. 5:1478. 10.3389/fpsyg.2014.01478
    1. Douet V., Chang L. (2015). Fornix as an imaging marker for episodic memory deficits in healthy aging and in various neurological disorders. Front. Aging Neurosci. 7:343 10.3389/fnagi.2014.00343
    1. Etnier J. L., Caselli R. J., Reiman E. M., Alexander G. E., Sibley B. A., Tessier D., et al. . (2007). Cognitive performance in older women relative to ApoE-epsilon4 genotype and aerobic fitness. Med. Sci. Sports Exerc. 39, 199–207. 10.1249/01.mss.0000239399.85955.5e
    1. Fanning J., Porter G., Awick E. A., Ehlers D. K., Roberts S. A., Cooke G., et al. . (2016). Replacing sedentary time with sleep, light, or moderate-to-vigorous physical activity: effects on self-regulation and executive functioning. J. Behav. Med. 40, 1–11. 10.1007/s10865-016-9788-9
    1. Fletcher E., Raman M., Huebner P., Liu A., Mungas D., Carmichael O., et al. . (2013). Loss of fornix white matter volume as a predictor of cognitive impairment in cognitively normal elderly individuals. JAMA Neurol. 70, 1389–1395. 10.1001/jamaneurol.2013.3263
    1. Gunning-Dixon F. M., Raz N. (2000). The cognitive correlates of white matter abnormalities in normal aging: a quantitative review. Neuropsychology 14, 224–232. 10.1037/0894-4105.14.2.224
    1. Haboush A., Floyd M., Caron J., LaSota M., Alvarez K. (2006). Ballroom dance lessons for geriatric depression: an exploratory study. Arts Psychother. 33, 89–97. 10.1016/j.aip.2005.10.001
    1. Hamburg N. M., McMackin C. J., Huang A. L., Shenouda S. M., Widlansky M. E., Schulz E., et al. . (2007). Physical inactivity rapidly induces insulin resistance and microvascular dysfunction in healthy volunteers. Arterioscler. Thromb. Vasc. Biol. 27, 2650–2656. 10.1161/ATVBAHA.107.153288
    1. Hamilton M. T., Hamilton D. G., Zderic T. W. (2004). Exercise physiology versus inactivity physiology: an essential concept for understanding lipoprotein lipase regulation. Exerc. Sport Sci. Rev. 32, 161–166. 10.1097/00003677-200410000-00007
    1. Hofer S., Frahm J. (2006). Topography of the human corpus callosum revisited—comprehensive fiber tractography using diffusion tensor magnetic resonance imaging. Neuroimage 32, 989–994. 10.1016/j.neuroimage.2006.05.044
    1. Jack C. R., Jr., Holtzman D. M. (2013). Biomarker modeling of Alzheimer's disease. Neuron 80, 1347–1358. 10.1016/j.neuron.2013.12.003
    1. Lauenroth A., Ioannidis A. E., Teichmann B. (2016). Influence of combined physical and cognitive training on cognition: a systematic review. BMC Geriatr. 16, 141. 10.1186/s12877-016-0315-1
    1. Law L. L. F., Barnett F., Yau M. K., Gray M. A. (2014). Effects of combined cognitive and exercise interventions on cognition in older adults with and without cognitive impairment: a systematic review. Ageing Res. Rev. 15, 61–75. 10.1016/j.arr.2014.02.008
    1. Lindquist S., Bodammer N., Kaufmann J., König F., Heinze H.-J., Brück W., et al. . (2007). Histopathology and serial, multimodal magnetic resonance imaging in a multiple sclerosis variant. Mult. Scler. 13, 471–482. 10.1177/1352458506071329
    1. Liu S., Rovine M. J., Molenaar P. C. M. (2012). Selecting a linear mixed model for longitudinal data: repeated measures analysis of variance, covariance pattern model, and growth curve approaches. Psychol. Methods 7, 15–30. 10.1037/a0026971
    1. Lövdén M., Köhncke Y., Laukka E. J., Kalpouzos G., Salami A., Li T. Q., et al. . (2014). Changes in perceptual speed and white matter microstructure in the corticospinal tract are associated in very old age. Neuroimage 102, 520–530. 10.1016/j.neuroimage.2014.08.020
    1. Madden D. J., Bennett I. J., Burzynska A., Potter G. G., Chen N.-K., Song A. W. (2012). Diffusion tensor imaging of cerebral white matter integrity in cognitive aging. Biochim. Biophys. Acta 1822, 386–400. 10.1016/j.bbadis.2011.08.003
    1. McKenzie I. A., Ohayon D., Li H., Paes de Faria J., Emery B., Tohyama K., et al. . (2014). Motor skill learning requires active central myelination. Science 346, 318–322. 10.1126/science.1254960
    1. McNeely M. E., Duncan R. P., Earhart G. M. (2015). A comparison of dance interventions in people with Parkinson disease and older adults. Maturitas 81, 10–16. 10.1016/j.maturitas.2015.02.007
    1. Medina D., DeToledo-Morrell L., Urresta F., Gabrieli J. D. E., Moseley M., Fleischman D., et al. . (2006). White matter changes in mild cognitive impairment and AD: a diffusion tensor imaging study. Neurobiol. Aging 27, 663–672. 10.1016/j.neurobiolaging.2005.03.026
    1. Metzler-Baddeley C., Jones D. K., Belaroussi B., Aggleton J. P., O'Sullivan M. J. (2011). Frontotemporal connections in episodic memory and aging: a diffusion MRI tractography study. J. Neurosci. 31, 13236–13245. 10.1523/JNEUROSCI.2317-11.2011
    1. Mielke M. M., Okonkwo O. C., Oishi K., Mori S., Tighe S., Miller M. I., et al. . (2012). Fornix integrity and hippocampal volume predict memory decline and progression to Alzheimer's disease. Alzheimer's Dementia 8, 105–113. 10.1016/j.jalz.2011.05.2416
    1. Oberlin L. E., Verstynen T. D., Burzynska A. Z., Voss M. W., Prakash R. S., Chaddock-Heyman L., et al. . (2016). White matter microstructure mediates the relationship between cardiorespiratory fitness and spatial working memory in older adults. Neuroimage 131, 91–101. 10.1016/j.neuroimage.2015.09.053
    1. Oswald W. D., Gunzelmann T., Rupprecht R., Hagen B. (2006). Differential effects of single versus combined cognitive and physical training with older adults: the SimA study in a 5-year perspective. Eur. J. Ageing 3, 179–192. 10.1007/s10433-006-0035-z
    1. Peterson M. J., Morey M. C., Giuliani C., Pieper C. F., Evenson K. R., Mercer V., et al. . (2010). Walking in old age and development of metabolic syndrome: the health, aging, and body composition study. Metab. Syndr. Relat. Disord. 8, 317–322. 10.1089/met.2009.0090
    1. Pfefferbaum A., Rosenbloom M. J., Chu W., Sassoon S. A., Rohlfing T., Pohl K. M., et al. . (2014). White matter microstructural recovery with abstinence and decline with relapse in alcohol dependence interacts with normal ageing: a controlled longitudinal DTI study. Lancet Psychiatry 1, 202–212. 10.1016/S2215-0366(14)70301-3
    1. Pfefferbaum A., Sullivan E. V., Carmelli D. (2001). Genetic regulation of regional microstructure of the corpus callosum in late life. Neuroreport 12, 1677–1681. 10.1097/00001756-200106130-00032
    1. Rahe J., Becker J., Fink G. R., Kessler J., Kukolja J., Rahn A., et al. . (2015). Cognitive training with and without additional physical activity in healthy older adults: cognitive effects, neurobiological mechanisms, and prediction of training success. Front. Aging Neurosci. 7:187. 10.3389/fnagi.2015.00187
    1. Rasmussen P., Brassard P., Adser H., Pedersen M. V., Leick L., Hart E., et al. . (2009). Evidence for a release of brain-derived neurotrophic factor from the brain during exercise. Exp. Physiol. 94, 1062–1069. 10.1113/expphysiol.2009.048512
    1. Raz N., Lindenberger U., Rodrigue K. M., Kennedy K. M., Head D., Williamson A., et al. . (2005). Regional brain changes in aging healthy adults: general trends, individual differences and modifiers. Cereb. Cortex 15, 1676–1689. 10.1093/cercor/bhi044
    1. Raz N., Rodrigue K. M. (2006). Differential aging of the brain: patterns, cognitive correlates and modifiers. Neurosci. Biobehav. Rev. 30, 730–748. 10.1016/j.neubiorev.2006.07.001
    1. Reese T. G., Heid O., Weisskoff R. M., Wedeen V. J. (2003). Reduction of eddy-current-induced distortion in diffusion MRI using a twice-refocused spin echo. Magn. Reson. Med. 49, 177–182. 10.1002/mrm.10308
    1. Rejeski W. J., Marsh A. P., Brubaker P. H., Buman M., Fielding R. A., Hire D., et al. . (2016). Analysis and interpretation of accelerometry data in older adults: the LIFE study. J. Gerontol. A Biol. Sci. Med. Sci. 71, 521–528. 10.1093/gerona/glv204
    1. Rémy F., Vayssière N., Saint-Aubert L., Barbeau E., Pariente J. (2015). White matter disruption at the prodromal stage of Alzheimer's disease: relationships with hippocampal atrophy and episodic memory performance. Neuroimage Clin. 7, 482–492. 10.1016/j.nicl.2015.01.014
    1. Rieckmann A., Van Dijk K. R. A., Sperling R. A., Johnson K. A., Buckner R. L., Hedden T. (2016). Accelerated decline in white matter integrity in clinically normal individuals at risk for Alzheimer's disease. Neurobiol. Aging 42, 177–188. 10.1016/j.neurobiolaging.2016.03.016
    1. Ringman J. M., O'Neill J., Geschwind D., Medina L., Apostolova L. G., Rodriguez Y., et al. . (2007). Diffusion tensor imaging in preclinical and presymptomatic carriers of familial Alzheimer's disease mutations. Brain 130, 1767–1776. 10.1093/brain/awm102
    1. Ritchie S. J., Bastin M. E., Tucker-Drob E. M., Mu-oz Maniega S., Engelhardt L. E., Cox S. R., et al. . (2015). Coupled changes in brain white matter microstructure and fluid intelligence in later life. J. Neurosci. 35, 8672–8682. 10.1523/JNEUROSCI.0862-15.2015
    1. Rueckert D., Sonoda L. I., Hayes C., Hill D. L. G., Leach M. O., Hawkes D. J. (1999). Nonrigid registration using free-form deformations: application to breast MR images. IEEE Trans. Med. Imaging 18, 712–721. 10.1109/42.796284
    1. Salthouse T. A. (2004). Localizing age-related individual differences in a hierarchical structure. Intelligence 32, 541–561. 10.1016/j.intell.2004.07.003
    1. Salthouse T. A. (2005). Relations between cognitive abilities and measures of executive functioning. Neuropsychology 19, 532–545. 10.1037/0894-4105.19.4.532
    1. Salthouse T. A. (2010). Influence of age on practice effects in longitudinal neurocognitive change. Neuropsychology 24, 563–572. 10.1037/a0019026
    1. Salthouse T. A., Ferrer-Caja E. (2003). What needs to be explained to account for age-related effects on multiple cognitive variables? Psychol. Aging 18, 91–110. 10.1037/0882-7974.18.1.91
    1. Sampaio-Baptista C., Khrapitchev A. A., Foxley S., Schlagheck T., Scholz J., Jbabdi S., et al. . (2013). Motor skill learning induces changes in white matter microstructure and myelination. J. Neurosci. 33, 19499–19503. 10.1523/jneurosci.3048-13.2013
    1. Scholz J., Klein M. C., Behrens T. E. J., Johansen-Berg H. (2009). Training induces changes in white-matter architecture. Nat. Neurosci. 12, 1370–1371. 10.1038/nn.2412
    1. Sen P. N., Basser P. J. (2005). A model for diffusion in white matter in the brain. Biophys. J. 89, 2927–2938. 10.1529/biophysj.105.063016
    1. Sexton C. E., Betts J. F., Demnitz N., Dawes H., Ebmeier K. P., Johansen-Berg H. (2016). A systematic review of MRI studies examining the relationship between physical fitness and activity and the white matter of the ageing brain. NeuroImage 131, 81–90. 10.1016/j.neuroimage.2015.09.071
    1. Sexton C. E., Walhovd K., Storsve A. B., Tamnes C. K., Westlye L. T., Johansen-Berg H., et al. (2014). Accelerated changes in white matter microstructure during ageing: a longitudinal diffusion tensor imaging study. J. Neurosci. 34, 15425–15436. 10.1523/JNEUROSCI.0203-14.2014
    1. Sidaros A., Engberg A. W., Sidaros K., Liptrot M. G., Herning M., Petersen P., et al. . (2008). Diffusion tensor imaging during recovery from severe traumatic brain injury and relation to clinical outcome: a longitudinal study. Brain 131, 559–572. 10.1093/brain/awm294
    1. Smith J. C., Nielson K. A., Antuono P., Lyons J.-A., Hanson R. J., Butts A. M., et al. . (2013). Semantic memory functional MRI and cognitive function after exercise intervention in mild cognitive impairment. J. Alzheimer's Dis. 37, 197–215. 10.3233/JAD-130467
    1. Smith S. M. (2002). Fast robust automated brain extraction. Hum. Brain Mapp. 17, 143–155. 10.1002/hbm.10062
    1. Smith S. M., Jenkinson M., Johansen-Berg H., Rueckert D., Nichols T. E., Mackay C. E., et al. . (2006). Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 31, 1487–1505. 10.1016/j.neuroimage.2006.02.024
    1. Smith S. M., Jenkinson M., Woolrich M. W., Beckmann C. F., Behrens T. E., Johansen-Berg H., et al. . (2004). Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 23(Suppl 1), S208–S219. 10.1016/j.neuroimage.2004.07.051
    1. Smith S. M., Johansen-Berg H., Jenkinson M., Rueckert D., Nichols T. E., Miller K. L., et al. . (2007). Acquisition and voxelwise analysis of multi-subject diffusion data with tract-based spatial statistics. Nat. Protoc. 2, 499–503. 10.1038/nprot.2007.45
    1. Song S.-K., Sun S.-W., Ju W.-K., Lin S.-J., Cross A. H., Neufeld A. H. (2003). Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia. Neuroimage 20, 1714–1722. 10.1016/j.neuroimage.2003.07.005
    1. Song S.-K., Sun S.-W., Ramsbottom M. J., Chang C., Russell J., Cross A. H. (2002). Dysmyelination revealed through MRI as increased radial (but Unchanged Axial) diffusion of water. Neuroimage 17, 1429–1436. 10.1006/nimg.2002.1267
    1. Song S.-K., Yoshino J., Le T. Q., Lin S.-J., Sun S.-W., Cross A. H., et al. . (2005). Demyelination increases radial diffusivity in corpus callosum of mouse brain. Neuroimage 26, 132–140. 10.1016/j.neuroimage.2005.01.028
    1. Storsve A. B., Fjell A. M., Yendiki A., Walhovd K. B. (2016). Longitudinal changes in white matter tract integrity across the adult lifespan and its relation to cortical thinning. PLoS ONE 11:e0156770. 10.1371/journal.pone.0156770
    1. Sullivan E. V., Rohlfing T., Pfefferbaum A. (2010a). Quantitative fiber tracking of lateral and interhemispheric white matter systems in normal aging: relations to timed performance. Neurobiol. Aging 31, 464–481. 10.1016/j.neurobiolaging.2008.04.007
    1. Sullivan E. V., Rohlfing T., Pfefferbaum A. (2010b). Longitudinal study of callosal microstructure in the normal adult aging brain using quantitative DTI fiber tracking. Dev. Neuropsychol. 35, 233–256. 10.1080/87565641003689556
    1. Sun S.-W., Liang H.-F., Cross A. H., Song S.-K. (2008). Evolving Wallerian degeneration after transient retinal ischemia in mice characterized by diffusion tensor imaging. Neuroimage 40, 1–10. 10.1016/j.neuroimage.2007.11.049
    1. Thomalla G., Glauche V., Koch M. A., Beaulieu C., Weiller C., Röther J. (2004). Diffusion tensor imaging detects early Wallerian degeneration of the pyramidal tract after ischemic stroke. Neuroimage 22, 1767–1774. 10.1016/j.neuroimage.2004.03.041
    1. Thomas A. G., Koumellis P., Dineen R. A. (2011). The fornix in health and disease: an imaging review. Radiographics 31, 1107–1121. 10.1148/rg.314105729
    1. Thomas C., Baker C. I. (2013). Teaching an adult brain new tricks: a critical review of evidence for training-dependent structural plasticity in humans. Neuroimage 73, 225–236. 10.1016/j.neuroimage.2012.03.069
    1. Troiano R. P., Berrigan D., Dodd K. W., Mâsse L. C., Tilert T., McDowell M. (2008). Physical activity in the United States measured by accelerometer. Med. Sci. Sports Exerc. 40, 181–188. 10.1249/mss.0b013e31815a51b3
    1. Tseng B. Y., Uh J., Rossetti H. C., Cullum C. M., Diaz-Arrastia R. F., Levine B. D., et al. . (2013). Masters athletes exhibit larger regional brain volume and better cognitive performance than sedentary older adults. J. Magn. Reson. Imaging 38, 1169–1176. 10.1002/jmri.24085
    1. Verghese J., Lipton R. B., Katz M. J., Hall C. B., Derby C. A., Kuslansky G., et al. . (2003). Leisure activities and the risk of dementia in the elderly. N. Eng. J. Med. 348, 2508–2516. 10.1056/NEJMoa022252
    1. Vik A., Hodneland E., Haász J., Ystad M., Lundervold A. J., Lundervold A. (2015). Fractional anisotropy shows differential reduction in frontal-subcortical fiber bundles-A longitudinal MRI study of 76 middle-aged and older adults. Front. Aging Neurosci. 7:81. 10.3389/fnagi.2015.00081
    1. Voss M. W., Erickson K. I., Prakash R. S., Chaddock L., Kim J. S., Alves H., et al. . (2013a). Neurobiological markers of exercise-related brain plasticity in older adults. Brain Behav. Immun. 28, 90–99. 10.1016/j.bbi.2012.10.021
    1. Voss M. W., Heo S., Prakash R. S., Erickson K. I., Alves H., Chaddock L., et al. . (2013b). The influence of aerobic fitness on cerebral white matter integrity and cognitive function in older adults: results of a one-year exercise intervention. Hum. Brain Mapp. 34, 2972–2985. 10.1002/hbm.22119
    1. Voss M. W., Prakash R. S., Erickson K. I., Basak C., Chaddock L., Kim J. S., et al. . (2010). Plasticity of brain networks in a randomized intervention trial of exercise training in older adults. Front. Aging Neurosci. 2:32. 10.3389/fnagi.2010.00032
    1. Wang R., Fratiglioni L., Laukka E. J., Lövdén M., Kalpouzos G., Keller L., et al. . (2015). Effects of vascular risk factors and APOE ε4 on white matter integrity and cognitive decline. Neurology 84, 1128–1135. 10.1212/WNL.0000000000001379
    1. Yanagibori R., Kondo K., Suzuki Y., Kawakubo K., Iwamoto T., Itakura H. (1998). Effect of 20 days' bed rest on the reverse cholesterol transport system in healthy young subjects. J. Intern. Med. 243, 307–312. 10.1046/j.1365-2796.1998.00303.x
    1. Young J. C., Dowell N. G., Watt P. W., Tabet N., Rusted J. M. (2016). Long-term high-effort endurance exercise in older adults: diminishing returns for cognitive and brain aging. J. Aging Phys. Act. 24, 659–675. 10.1123/japa.2015-0039
    1. Zahr N. M., Rohlfing T., Pfefferbaum A., Sullivan E. V. (2009). Problem solving, working memory, and motor correlates of association and commissural fiber bundles in normal aging: a quantitative fiber tracking study. Neuroimage 44, 1050–1062. 10.1016/j.neuroimage.2008.09.046
    1. Zoeller R. F., Stout J. R., O'Kroy J. A., Torok D. J., Mielke M. (2007). Effects of 28 days of beta-alanine and creatine monohydrate supplementation on aerobic power, ventilatory and lactate thresholds, and time to exhaustion. Amino Acids 33, 505–510. 10.1007/s00726-006-0399-6
    1. Zoladz J. A., Pilc A., Majerczak J., Grandys M., Zapart-Bukowska J., Duda K. (2008). Endurance training increases plasma brain-derived neurotrophic factor concentration in young healthy men. J. Physiol. Pharmacol. 59(Suppl. 7), 119–132.

Source: PubMed

Patrocinadores y Colaboradores

Condiciones médicas

Intervenciones de drogas

3
Suscribir