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Structural and functional connectivity in healthy aging: Associations for cognition and motor behavior
dc.contributor.authorHirsiger, Sarah
dc.contributor.authorKoppelmans, Vincent
dc.contributor.authorMérillat, Susan
dc.contributor.authorLiem, Franziskus
dc.contributor.authorErdeniz, Burak
dc.contributor.authorSeidler, Rachael D.
dc.contributor.authorJäncke, Lutz
dc.date.accessioned2017-06-16T20:10:40Z
dc.date.available2017-06-16T20:10:40Z
dc.date.issued2016-03
dc.identifier.citationHirsiger, Sarah; Koppelmans, Vincent; Mérillat, Susan ; Liem, Franziskus; Erdeniz, Burak; Seidler, Rachael D.; Jäncke, Lutz (2016). "Structural and functional connectivity in healthy aging: Associations for cognition and motor behavior." Human Brain Mapping 37(3): 855-867.
dc.identifier.issn1065-9471
dc.identifier.issn1097-0193
dc.identifier.urihttps://hdl.handle.net/2027.42/137343
dc.description.abstractAge‐related behavioral declines may be the result of deterioration of white matter tracts, affecting brain structural (SC) and functional connectivity (FC) during resting state. To date, it is not clear if the combination of SC and FC data could better predict cognitive/motor performance than each measure separately. We probed these relationships in the cingulum bundle, a major white matter pathway of the default mode network. We aimed to attain deeper knowledge about: (a) the relationship between age and the cingulum’s SC and FC strength, (b) the association between SC and FC, and particularly (c) how the cingulum’s SC and FC are related to cognitive/motor performance separately and combined. We examined these associations in a healthy and well‐educated sample of 165 older participants (aged 64‐85). SC and FC were acquired using probabilistic tractography to derive measures to capture white matter integrity within the cingulum bundle (fractional anisotropy, mean, axial and radial diffusivity) and a seed‐based resting‐state functional MRI correlation approach, respectively. Participants performed cognitive tests measuring processing speed, memory and executive functions, and motor tests measuring motor speed and grip force. Our data revealed that only SC but not resting state FC was significantly associated with age. Further, the cingulum’s SC and FC showed no relation. Different relationships between cognitive/motor performance and SC/FC separately were found, but no additive effect of the combined analysis of cingulum’s SC and FC for predicting cognitive/motor performance was apparent. Hum Brain Mapp 37:855–867, 2016. © 2015 Wiley Periodicals, Inc.
dc.publisherHogrefe
dc.publisherWiley Periodicals, Inc.
dc.subject.othermultimodal imaging
dc.subject.othertractography
dc.subject.othercognitive aging
dc.subject.othercingulum
dc.subject.otherfunctional connectivity
dc.titleStructural and functional connectivity in healthy aging: Associations for cognition and motor behavior
dc.typeArticleen_US
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelKinesiology and Sports
dc.subject.hlbsecondlevelNeurosciences
dc.subject.hlbtoplevelHealth Sciences
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/137343/1/hbm23067_am.pdf
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/137343/2/hbm23067.pdf
dc.identifier.doi10.1002/hbm.23067
dc.identifier.sourceHuman Brain Mapping
dc.identifier.citedreferenceSalami A, Eriksson J, Nilsson L‐G, Nyberg L ( 2011 ): Age‐related white matter microstructural differences partly mediate age‐related decline in processing speed but not cognition. BBA Mol Basis Disease: 1 – 8.
dc.identifier.citedreferenceNoble JW, Eng JJ, Kokotilo KJ, Boyd LA ( 2011 ): Aging effects on the control of grip force magnitude: an fMRI study. Exp Gerontol 46: 453 – 461.
dc.identifier.citedreferenceNoble KG, Korgaonkar MS, Grieve SM, Brickman AM ( 2013 ): Higher education is an age‐independent predictor of white matter integrity and cognitive control in late adolescence. Dev Sci 16: 653 – 664.
dc.identifier.citedreferenceO’Sullivan M, Jones DK, Summers PE, Morris RG, Williams SC, Markus HS ( 2001 ): Evidence for cortical “disconnection” as a mechanism of age‐related cognitive decline. Neurology 57: 632 – 638.
dc.identifier.citedreferenceOnoda K, Ishihara M, Yamaguchi S ( 2012 ): Decreased functional connectivity by aging is associated with cognitive decline. J Cogn Neurosci 24: 2186 – 2198.
dc.identifier.citedreferencePersson J, Pudas S, Nilsson L‐G, Nyberg L ( 2014 ): Longitudinal assessment of default‐mode brain function in aging. Neurobiol Aging 35: 2107 – 2117.
dc.identifier.citedreferenceRantanen T, Harris T, Leveille SG, Visser M, Foley D, Masaki K, Guralnik JM ( 2000a ): Muscle strength and body mass index as long‐term predictors of mortality in initially healthy men. J Gerontol A Biol Sci Med Sci 55: M168 – M173.
dc.identifier.citedreferenceRantanen T, Penninx BW, Masaki K, Lintunen T, Foley D, Guralnik JM ( 2000b ): Depressed mood and body mass index as predictors of muscle strength decline in old men. J Am Geriatr Soc 48: 613 – 617.
dc.identifier.citedreferenceRaz N, Rodrigue KM ( 2006 ): Differential aging of the brain: Patterns, cognitive correlates and modifiers. Neurosci Biobehav Rev 30: 730 – 748.
dc.identifier.citedreferenceReitan RM, Wolfson D ( 1985 ): The Halstead‐Reitan neuropsychological test battery. Tucson, AZ: Neuropsychological Press.
dc.identifier.citedreferenceRey A ( 1964 ): L’examen clinique en psychologie. Paris: Presses Universitaires de France.
dc.identifier.citedreferenceSalthouse TA ( 1996 ): The processing‐speed theory of adult age differences in cognition. Psychol Rev 103: 403 – 428.
dc.identifier.citedreferenceSalthouse TA, Atkinson TM, Berish DE ( 2003 ): Executive functioning as a potential mediator of age‐related cognitive decline in normal adults. J Exp Psychol Gen 132: 566 – 594.
dc.identifier.citedreferenceSeidler RD, Bernard JA, Burutolu TB, Fling BW, Gordon MT, Gwin JT, Kwak Y, Lipps DB ( 2010 ): Motor control and aging: links to age‐related brain structural, functional, and biochemical effects. Neurosci Biobehav Rev 34: 721 – 733.
dc.identifier.citedreferenceSeidler R, Erdeniz B, Koppelmans V, Hirsiger S, Mérillat S, Jäncke L ( 2015 ): Associations between age, motor function, and resting state sensorimotor network connectivity in healthy older adults. NeuroImage 108: 47 – 59.
dc.identifier.citedreferenceSmith SM, Jenkinson M, Woolrich MW, Beckmann CF, Behrens TEJ, Johansen‐Berg H, Bannister PR, De Luca M, Drobnjak I, Flitney DE, Niazy RK, Saunders J, Vickers J, Zhang Y, De Stefano N, Brady JM, Matthews PM ( 2004 ): Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage 23: S208 – S219.
dc.identifier.citedreferenceSong S‐K, Sun S‐W, Ju W‐K, Lin S‐J, Cross AH, Neufeld AH ( 2003 ): Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia. NeuroImage 20: 1714 – 1722.
dc.identifier.citedreferenceSong S‐K, Sun S‐W, Ramsbottom MJ, Chang C, Russell J, Cross AH ( 2002 ): Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water. NeuroImage 17: 1429 – 1436.
dc.identifier.citedreferenceSong X‐W, Dong Z‐Y, Long X‐Y, Li S‐F, Zuo X‐N, Zhu C‐Z, He Y, Yan C‐G, Zang Y‐F ( 2011 ): REST: a toolkit for resting‐state functional magnetic resonance imaging data processing. PLoS One 6: e25031
dc.identifier.citedreferenceSyddall H, Cooper C, Martin F, Briggs R, Aihie Sayer A ( 2003 ): Is grip strength a useful single marker of frailty? Age Ageing 32: 650 – 656.
dc.identifier.citedreferenceTeipel SJ, Bokde ALW, Meindl T, Amaro E, Soldner J, Reiser MF, Herpertz SC, Möller H‐J, Hampel H ( 2010 ): White matter microstructure underlying default mode network connectivity in the human brain. NeuroImage 49: 2021 – 2032.
dc.identifier.citedreferenceTustison NJ, Avants BB, Cook PA, Zheng Y, Egan A, Yushkevich PA, Gee JC ( 2010 ): N4ITK: improved N3 bias correction. IEEE Trans Med Imaging 29: 1310 – 1320.
dc.identifier.citedreferencevan den Heuvel M, Mandl R, Luigjes J, Hulshoff Pol H ( 2008 ): Microstructural organization of the cingulum tract and the level of default mode functional connectivity. J Neurosci 28: 10844 – 10851.
dc.identifier.citedreferenceVan Dijk KRA, Hedden T, Venkataraman A, Evans KC, Lazar SW, Buckner RL ( 2010 ): Intrinsic functional connectivity as a tool for human connectomics: theory, properties, and optimization. J Neurophysiol 103: 297 – 321.
dc.identifier.citedreferenceWakana S, Caprihan A, Panzenboeck MM, Fallon JH, Perry M, Gollub RL, Hua K, Zhang J, Jiang H, Dubey P, Blitz A, van Zijl P, Mori S ( 2007 ): Reproducibility of quantitative tractography methods applied to cerebral white matter. NeuroImage 36: 630 – 644.
dc.identifier.citedreferenceWu J‐T, Wu H‐Z, Yan C‐G, Chen W‐X, Zhang H‐Y, He Y, Yang H‐S ( 2011 ): Aging‐related changes in the default mode network and its anti‐correlated networks: a resting‐state fMRI study. Neurosci Lett 504: 62 – 67.
dc.identifier.citedreferenceZahr NM, Rohlfing T, Pfefferbaum A, Sullivan EV ( 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.
dc.identifier.citedreferenceZöllig J, Mérillat S, Eschen A, Röcke C, Martin M, Jäncke L ( 2011 ): Plasticity and imaging research in healthy aging: core ideas and profile of the International Normal Aging and Plasticity Imaging Center (INAPIC). Gerontology 57: 190 – 192.
dc.identifier.citedreferenceAlley D, Suthers K, Crimmins E ( 2007 ): Education and cognitive decline in older Americans: results from the AHEAD sample. Res Aging 29: 73 – 94.
dc.identifier.citedreferenceAndrews‐Hanna JR, Snyder AZ, Vincent JL, Lustig C, Head D, Raichle ME, Buckner RL ( 2007 ): Disruption of large‐scale brain systems in advanced aging. Neuron 56: 924 – 935.
dc.identifier.citedreferenceAschenbrenner S, Tucha O, Lange KW. ( 2000 ): RWT. Regensburger Wortflüssigkeits‐Test. Göttingen: Hogrefe.
dc.identifier.citedreferenceAoki T, Fukuoka Y ( 2010 ): Finger tapping ability in healthy elderly and young adults. Med Sci Sports Exercise 42: 449 – 455.
dc.identifier.citedreferenceAster Von M, Neubauer A, Horn R ( 2006 ): Hamburg‐Wechsler‐Intelligenz‐Test für Erwachsene III. Frankfurt: Harcourt.
dc.identifier.citedreferenceBarrick TR, Charlton RA, Clark CA, Markus HS ( 2010 ): White matter structural decline in normal ageing: a prospective longitudinal study using tract‐based spatial statistics. NeuroImage 51: 565 – 577.
dc.identifier.citedreferenceBartzokis G, Lu PH, Tingus K, Mendez MF, Richard A, Peters DG, Oluwadara B, Barrall KA, Finn JP, Villablanca P, Thompson PM, Mintz J ( 2010 ): Lifespan trajectory of myelin integrity and maximum motor speed. Neurobiol Aging 31: 1554 – 1562.
dc.identifier.citedreferenceBeauchet O, Celle S, Roche F, Bartha R, Montero‐Odasso M, Allali G, Annweiler C ( 2013 ): Blood pressure levels and brain volume reduction: a systematic review and meta‐analysis. J Hypertens 31: 1502 – 1516.
dc.identifier.citedreferenceBennett IJ, Madden DJ ( 2014 ): Disconnected aging: Cerebral white matter integrity and age‐related differences in cognition. Neuroscience 276:187–205.
dc.identifier.citedreferenceBennett IJ, Madden DJ, Vaidya CJ, Howard JH, Howard DV ( 2011 ): White matter integrity correlates of implicit sequence learning in healthy aging. Neurobiol Aging 32: 2317.e1 – 2312.
dc.identifier.citedreferenceBennett IJ, Rypma B ( 2013 ): Advances in functional neuroanatomy: a review of combined DTI and fMRI studies in healthy younger and older adults. Neurosci Biobehav Rev 37: 1201 – 1210.
dc.identifier.citedreferenceBorghesani PR, Madhyastha TM, Aylward EH, Reiter MA, Swarny BR, Schaie KW, Willis SL ( 2013 ): The association between higher order abilities, processing speed, and age are variably mediated by white matter integrity during typical aging. Neuropsychologia 51: 1435 – 1444.
dc.identifier.citedreferenceBuckner RL, Andrews‐Hanna JR, Schacter DL ( 2008 ): The brain’s default network: anatomy, function, and relevance to disease. Ann NY Acad Sci 1124: 1 – 38.
dc.identifier.citedreferenceChao‐Gan Y, Yu‐Feng Z ( 2010 ): DPARSF: A MATLAB Toolbox for “Pipeline” data analysis of resting‐state fMRI. Front Syst Neurosci 4: 13
dc.identifier.citedreferenceDamoiseaux JS, Beckmann CF, Arigita EJS, Barkhof F, Scheltens P, Stam CJ, Smith SM, Rombouts SARB ( 2008 ): Reduced resting‐state brain activity in the “default network” in normal aging. Cereb Cortex 18: 1856 – 1864.
dc.identifier.citedreferenceDavis SW, Dennis NA, Buchler NG, White LE, Madden DJ, Cabeza R ( 2009 ): Assessing the effects of age on long white matter tracts using diffusion tensor tractography. NeuroImage 46: 530 – 541.
dc.identifier.citedreferenceDennis EL, Thompson PM ( 2014 ): Functional brain connectivity using fMRI in aging and Alzheimer’s disease. Neuropsychol Rev 24: 49 – 62.
dc.identifier.citedreferenceFerreira LK, Busatto GF ( 2013 ): Resting‐state functional connectivity in normal brain aging. Neurosci Biobehav Rev 37: 384 – 400.
dc.identifier.citedreferenceFjell AM, Walhovd KB ( 2010 ): Structural brain changes in aging: courses, causes and cognitive consequences. Rev Neurosci 21: 187 – 221.
dc.identifier.citedreferenceFolstein MF, Folstein SE, McHugh PR ( 1975 ): “Mini‐mental state”: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 12: 189 – 198.
dc.identifier.citedreferenceFox MD, Raichle ME ( 2007 ): Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci 8: 700 – 711.
dc.identifier.citedreferenceFrederiksen H, Hjelmborg J, Mortensen J, McGue M, Vaupel JW, Christensen K ( 2006 ): Age trajectories of grip strength: cross‐sectional and longitudinal data among 8,342 Danes aged 46 to 102. Ann Epidemiol 16: 554 – 562.
dc.identifier.citedreferenceGeschwind N ( 1965 ): Disconnexion syndromes in animals and man. Brain 88: 237 – 294, 585–564.
dc.identifier.citedreferenceGrady C ( 2012 ): The cognitive neuroscience of ageing. Nat Rev Neurosci 13: 491 – 505.
dc.identifier.citedreferenceGreicius MD, Supekar K, Menon V, Dougherty RF ( 2009 ): Resting‐state functional connectivity reflects structural connectivity in the default mode network. Cereb Cortex 19: 72 – 78.
dc.identifier.citedreferenceHelmstaedter C, Lendt M, Lux S ( 2001 ): Verbaler Lern‐ und Merkfähigkeitstest [Verbal Learning and Memory Test]. Beltz.
dc.identifier.citedreferenceHolm S ( 1979 ): A simple sequentially rejective multiple test procedure. Scandinavian journal of statistics.
dc.identifier.citedreferenceHsu J‐L, Leemans A, Bai C‐H, Lee C‐H, Tsai Y‐F, Chiu H‐C, Chen W‐H ( 2008 ): Gender differences and age‐related white matter changes of the human brain: A diffusion tensor imaging study. NeuroImage 39: 566 – 577.
dc.identifier.citedreferenceInano S, Takao H, Hayashi N, Yoshioka N, Mori H, Kunimatsu A, Abe O, Ohtomo K ( 2012 ): Effects of age and gender on neuroanatomical volumes. J Magn Reson Imaging 2013:1072–1076.
dc.identifier.citedreferenceKhalsa S, Mayhew SD, Chechlacz M, Bagary M, Bagshaw AP ( 2013 ): The structural and functional connectivity of the posterior cingulate cortex: Comparison between deterministic and probabilistic tractography for the investigation of structure–function relationships. NeuroImage 102:118–127.
dc.identifier.citedreferenceMadden DJ, Bennett IJ, Burzynska A, Potter GG, Chen N‐K, Song AW ( 2012 ): Diffusion tensor imaging of cerebral white matter integrity in cognitive aging. Biochim Biophys Acta 1822: 386 – 400.
dc.identifier.citedreferenceMarcus J, Gardener H, Rundek T, Elkind MSV, Sacco RL, Decarli C, Wright CB ( 2011 ): Baseline and longitudinal increases in diastolic blood pressure are associated with greater white matter hyperintensity volume: the northern Manhattan study. Stroke 42: 2639 – 2641.
dc.identifier.citedreferenceMaylor EA, Reimers S, Choi J, Collaer ML, Peters M, Silverman I ( 2007 ): Gender and sexual orientation differences in cognition across adulthood: age is kinder to women than to men regardless of sexual orientation. Arch Sex Behav 36: 235 – 249.
dc.identifier.citedreferenceMetzler‐Baddeley C, Jones DK, Steventon J, Westacott L, Aggleton JP, O’Sullivan MJ ( 2012 ): Cingulum microstructure predicts cognitive control in older age and mild cognitive impairment. J Neurosci 32: 17612 – 17619.
dc.identifier.citedreferenceMevel K, Landeau B, Fouquet M, La Joie R, Villain N, Mézenge F, Perrotin A, Eustache F, Desgranges B, Chételat G ( 2013 ): Age effect on the default mode network, inner thoughts, and cognitive abilities. Neurobiol Aging 34: 1292 – 1301.
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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