Abstract
Brain white matter (WM) could be generally categorized into two types, deep and superficial WM. Studies combining these two types WM are important for a better understanding of brain plasticity induced by motor training. In this study, we applied both univariate and multivariate approaches to study gymnastic training-induced plasticity in brain WM. Specifically, we acquired diffusion tensor imaging data from 13 world class gymnasts and 14 non-athlete normal controls, reconstructed brain deep and superficial WM tracts, estimated and compared their fractional anisotropy (FA) difference between the two groups. Taking FA values as the features, we applied logistic regression and support vector machine to distinguish the gymnasts from the controls. Compared to the controls, the gymnasts showed lower FA in four regional deep WM tracts, including the occipital lobe portion of left inferior fronto-occipital fasciculus (IFOF.L), occipital and temporal lobe portion of right inferior longitudinal fasciculus (ILF.R), insular cortex portion of right uncinate fasciculus (UF.R), and parietal lobe portion of right arcuate fasciculus (AF.R). Meanwhile, we found lower FA in the superficial U-shaped tracts within the frontal lobe in the gymnasts compared to the controls. In addition, we detected that mean FA in either the AF.R or the U-shaped tracts connecting the left pars triangularis and superior frontal gyrus was negatively correlated with years of training in the gymnasts. Classification analyses indicated FA in deep WM hold higher potential to distinguish the gymnasts from the controls. Overall, our findings provide a more complete picture of training-induced plasticity in brain WM.
Similar content being viewed by others
Abbreviations
- ATR:
-
anterior thalamic radiation
- CST:
-
corticospinal tract
- CGC:
-
cingulum cingulate
- IFOF:
-
Inferior fronto-occipital fasciculus
- ILF:
-
Inferior longitudinal fasciculus
- SLF:
-
Superior longitudinal fasciculus
- UF:
-
Uncinate fasciculus
- AF:
-
Arcuate fasciculus
- Tr:
-
Pars triangularis
- SF:
-
Superior frontal
- RMF:
-
Rostral middle frontal
- Op:
-
Pars opercularis
- WCGs:
-
World class gymnasts
- NCs:
-
Non-athlete normal controls
- FA:
-
Fractional anisotropy
- WM:
-
Gray matter
- GM:
-
Gray matter
References
Alexander DC et al (2001) Spatial transformations of diffusion tensor magnetic resonance images. IEEE Trans Med Imaging 20(11):1131–1139
Anderson EJ et al (2012) Cortical network for gaze control in humans revealed using multimodal MRI. Cereb Cortex 22(4):765–775
Barkovich AJ (2000) Concepts of myelin and myelination in neuroradiology. Am J Neuroradiol 21(6):1099
Bartzokis G (2004) Age-related myelin breakdown: a developmental model of cognitive decline and Alzheimer’s disease. Neurobiol Aging 25(1):5
Behrens TE et al (2003) Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging. Nat Neurosci 6(7):750–757
Behrens TE et al (2007) Probabilistic diffusion tractography with multiple fibre orientations: what can we gain? Neuroimage 34(1):144–155
Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate—a practical and powerful approach to multiple testing. J Roy Stat Soc 57(1):289–300
Bennett EL et al (1964) Chemical and anatomical plasticity of brain. Science 146(3644):610–619
Bisley JW, Goldberg ME (2003) Neuronal activity in the lateral intraparietal area and spatial attention. Science 299(5603):81–86
Butt A, Berry M (2000) Oligodendrocytes and the control of myelination in vivo: new insights from the rat anterior medullary velum. J Neurosci Res 59(4):477–488
Button KS et al (2013) Power failure: Why small sample size undermines the reliability of neuroscience. Nat Rev Neurosci 14(5):365
Catani M et al (2012) Short frontal lobe connections of the human brain. Cortex 48(2):273–291
Chang CC, Lin CJ (2011) LIBSVM: A library for support vector machines. Acm Trans Intell Syst Technol 2(3):27
IBM Corp (2011) IBM SPSS Statistics for Windows, Version 20.0. IBM Corp, Armonk, NY
Demerens C, Lubetzki C (1996) Induction of myelination in the central nervous system by electrical activity. Proc Natl Acad Sci USA 93(18):9887–9892
Diedrichsen J, Kornysheva K (2015) Motor skill learning between selection and execution. Trends Cogn Sci 19(4):227–233
Draganski B et al (2004) Neuroplasticity: changes in grey matter induced by training. Nature 427(6972):311–312
Fan L et al (2014) Connectivity-based parcellation of the human temporal pole using diffusion tensor imaging. Cereb Cortex 24(12):3365–3378
Filippi M et al (2010) Motor learning in healthy humans is associated to gray matter changes: a tensor-based morphometry study. Plos One 5(4):e10198
Fogassi L, Luppino G (2005) Motor functions of the parietal lobe. Curr Opin Neurobiol 15(6):626–631
Griswold MA et al (2002) Generalized autocalibrating partially parallel acquisitions (GRAPPA). Magn Reson Med 47(6):1202–1210
Grotegerd D et al (2014) MANIA-a pattern classification toolbox for neuroimaging data. Neuroinformatics 12(3):471–486
Halsband U, Lange RK (2006) Motor learning in man: a review of functional and clinical studies. J Physiol Paris 99(4):414–424
Hanggi J et al (2010) Structural neuroplasticity in the sensorimotor network of professional female ballet dancers. Hum Brain Mapp 31(8):(1196–1206)
Hänggi J et al (2015) Structural brain correlates associated with professional handball playing. Plos One 10(4):e0124222
Hartzell JF et al (2016) Brains of verbal memory specialists show anatomical differences in language, memory and visual systems. Neuroimage 131:181–192
Hoeft F et al (2007) More is not always better: increased fractional anisotropy of superior longitudinal fasciculus associated with poor visuospatial abilities in Williams syndrome. J Neurosci 27(44):11960–11965
Hua K et al (2008) Tract probability maps in stereotaxic spaces: analyses of white matter anatomy and tract-specific quantification. Neuroimage 39(1):336–347
Huang R et al (2015) Long-term intensive training induced brain structural changes in world class gymnasts. Brain Struct Funct 220(2):625–644
Ishibashi T et al (2006) Astrocytes Promote Myelination in Response to Electrical Impulses. Neuron 49(6):823–832
Jäncke L et al (2009) The Architecture of the Golfer’s Brain. Plos One 4(3):e4785
Jbabdi S, Johansen-Berg H (2011) Tractography: where do we go from here? Brain Connect 1(3):169
Jbabdi S et al (2015) Measuring macroscopic brain connections in vivo. Nat Neurosci 18(11):1546
Jenkinson M, Smith S (2001) A global optimisation method for robust affine registration of brain images. Med Image Anal 5(2):143–156
Jenkinson M et al (2012) Fsl. Neuroimage 62(2):782–790
Johansenberg H, Rushworth MF (2009) Using diffusion imaging to study human connectional anatomy. Annu Rev Neurosci 32(1):75
Johnson RT et al (2014) Diffusion properties of major white matter tracts in young, typically developing children. Neuroimage 88(2):143–154
Jones DK (2010) Diffusion MRI: Theory, Methods, and Applications. Springer, New York, p 371
Karnath HO et al (2004) The anatomy of spatial neglect based on voxelwise statistical analysis: a study of 140 patients. Cereb Cortex 14(10):1164
Keller TA, Just MA (2009) Altering cortical connectivity: Remediation-induced changes in the white matter of poor readers. Neuron 64(5):624–631
Konrad A, Winterer G (2008) Disturbed structural connectivity in schizophrenia—primary factor in pathology or epiphenomenon? Schizophr Bull 34(1):72–92
Landi SM, Baguear F, Della-Maggiore V (2011) One week of motor adaptation induces structural changes in primary motor cortex that predict long-term memory one year later. J Neurosci 31(33):11808–11813
Lebel C et al (2012) Diffusion tensor imaging of white matter tract evolution over the lifespan. Neuroimage 60(1):340
Lerch JP et al (2017) Studying neuroanatomy using MRI. Nat Neurosci 20(3):314
Liu M et al (2016) The superficial white matter in temporal lobe epilepsy: a key link between structural and functional network disruptions. Brain 139(9):2431
Makris N et al (2005) Segmentation of subcomponents within the superior longitudinal fascicle in humans: a quantitative, in vivo, DT-MRI study. Cereb Cortex 15(6):854–869
Maricich S et al (2007) Myelination as assessed by conventional MR imaging is normal in young children with idiopathic developmental delay. AJNR American journal of neuroradiology 28(8):1602–1605
Menon V, Uddin LQ (2010) Saliency, switching, attention and control: a network model of insula function. Brain Struct Funct 214(5):655–667
Nazeri A et al (2013) Alterations of superficial white matter in schizophrenia and relationship to cognitive performance. Neuropsychopharmacology 38(10):1954
Nazeri A et al (2015) Superficial white matter as a novel substrate of age-related cognitive decline. Neurobiol Aging 36(6):2094–2106
Nichols TE, Holmes AP (2002) Nonparametric Permutation Tests For Functional Neuroimaging: A Primer with Examples. Hum Brain Mapp 15(1):1
Oechslin MS et al (2009) The plasticity of the superior longitudinal fasciculus as a function of musical expertise: a diffusion tensor imaging study. Front Human Neurosci 3(1):76
Oishi K et al (2008) Human brain white matter atlas: Identification and assignment of common anatomical structures in superficial white matter. Neuroimage 43(3):447–457
Oishi K et al (2011) Superficially Located White Matter Structures Commonly Seen in the Human and the Macaque Brain with Diffusion Tensor Imaging. Brain Connect 1(1):37–47
Park IS et al (2015) White matter plasticity in the cerebellum of elite basketball athletes. Anatomy Cell Biol 48(4):262–267
Pereira F, Botvinick MM (2009) Machine learning classifiers and fMRI: A tutorial overview. Neuroimage 45(1):S199-S209
Petrides M, Pandya DN (1984) Projections to the frontal cortex from the posterior parietal region in the rhesus monkey. J Comp Neurol 228(1):105–116
Petrides M, Pandya DN (1988) Association fiber pathways to the frontal cortex from the superior temporal region in the rhesus monkey. J Comp Neurol 273(1):52
Phillips OR et al (2013) Superficial white matter: effects of age, sex, and hemisphere. Brain Connect 3(2):146
Pierpaoli C et al (2001) Diffusion tensor MR imaging of the human brain. Radiology 201(3):637
Reveley C et al (2015) Superficial white matter fiber systems impede detection of long-range cortical connections in diffusion MR tractography. Proc Natl Acad Sci USA 112(21):E2820
Schmahmann JD et al (2007) Association fibre pathways of the brain: parallel observations from diffusion spectrum imaging and autoradiography. Brain 130(3):630
Scholz J et al (2009) Training induces changes in white-matter architecture. Nat Neurosci 12(11):1370–1371
Schüz A, Braitenberg V, Miller R (2002) The human cortical white matter: quantitative aspects of cortico-cortical long-range connectivity. In: Schüz A, Miller R (eds) Cortical areas: unity and diversity. Taylor Francis, London, UK, pp 377–385
Sexton CE et al (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
Smith SM et al (2006) Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data. Neuroimage 31(4):1487–1505
Specht K, Reul J (2003) Functional segregation of the temporal lobes into highly differentiated subsystems for auditory perception: an auditory rapid event-related fMRI-task. Acta Pol Pharm 20(4):1944
Stuss DT, Alexander MP, Floden D, Binns MA, Levine B, Mcintosh AR et al (2002) Fractionation and localization of distinct frontal lobe processes: evidence from focal lesions in humans. In: Stuss DT, Knight RT (eds) Principles of Frontal Lobe Function. pp 392–407
Szeszko PR, Kingsley PB (2010) MRI atlas of human white matter. Concepts Magn Resonan Part A 28A(2):180–181
Taubert M et al (2010) Dynamic properties of human brain structure: learning-related changes in cortical areas and associated fiber connections. J Neurosci 30(35):11670–11677
Umarova RM et al (2010) Structural connectivity for visuospatial attention: significance of ventral pathways. Cereb Cortex 20(1):121–129
Von Der Heide RJ et al (2013) Dissecting the uncinate fasciculus: disorders, controversies and a hypothesis. Brain 136(6):1692
Wakana S et al (2007) Reproducibility of quantitative tractography methods applied to cerebral white matter. Neuroimage 36(3):630–644
Wang B et al (2013) Brain anatomical networks in world class gymnasts: a DTI tractography study. Neuroimage 65(1):476
Wang X et al (2014) White matter microstructure changes induced by motor skill learning utilizing a body machine interface. Neuroimage 88(3):32–40
Wu M et al (2014) Development of superficial white matter and its structural interplay with cortical gray matter in children and adolescents. Hum Brain Mapp 35(6):2806
Wu M, Kumar A, Yang S (2016) Development and aging of superficial white matter myelin from young adulthood to old age: Mapping by vertex-based surface statistics (VBSS). Hum Brain Mapp 37(5):1759
Yeatman JD et al (2012) Tract profiles of white matter properties: automating fiber-tract quantification. PLoS One 7(11):e49790
Yeatman JD, Wandell BA, Mezer AA (2014) Lifespan maturation and degeneration of human brain white matter. Nat Commun 5(5):4932
Zatorre RJ, Fields RD, Johansen-Berg H (2012) Plasticity in gray and white: neuroimaging changes in brain structure during learning. Nat Neurosci 15(4):528–536
Acknowledgements
This work was supported by funding from the National Natural Science Foundation of China (Grant Numbers: 81371535, 81271548, 81428013, and 81471654).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
We declare that we have no competing financial interests.
Ethical approval
All procedures performed in studies involving human participants were in accordance with the ethical standards of the Institutional Review Board of the State Key Laboratory of Cognitive Neuroscience and Learning at Beijing Normal University (BNU) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent
Informed consent was obtained from all individual participants included in the study.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Deng, F., Zhao, L., Liu, C. et al. Plasticity in deep and superficial white matter: a DTI study in world class gymnasts. Brain Struct Funct 223, 1849–1862 (2018). https://doi.org/10.1007/s00429-017-1594-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00429-017-1594-9