Applied Microscopy

Korean Society of Microscopy (한국현미경학회)
권호 표지
DOI QR코드

DOI QR Code

Brain Mapping Using Neuroimaging

  • Tae, Woo-Suk (Brain Convergence Research Center, Korea University) ;
  • Kang, Shin-Hyuk (Brain Convergence Research Center, Korea University) ;
  • Ham, Byung-Joo (Brain Convergence Research Center, Korea University) ;
  • Kim, Byung-Jo (Brain Convergence Research Center, Korea University) ;
  • Pyun, Sung-Bom (Brain Convergence Research Center, Korea University)
  • Received : 2016.12.25
  • Accepted : 2016.12.28
  • Published : 2016.12.30
Download PDF
⟨ Previous Next ⟩

Abstract

Mapping brain structural and functional connections through the whole brain is essential for understanding brain mechanisms and the physiological bases of brain diseases. Although region specific structural or functional deficits cause brain diseases, the changes of interregional connections could also be important factors of brain diseases. This review will introduce common neuroimaging modalities, including structural magnetic resonance imaging (MRI), functional MRI (fMRI), diffusion tensor imaging, and other recent neuroimaging analyses methods, such as voxel-based morphometry, cortical thickness analysis, local gyrification index, and shape analysis for structural imaging. Tract-Based Spatial Statistics, TRActs Constrained by UnderLying Anatomy for diffusion MRI, and independent component analysis for fMRI also will also be introduced.

Keywords

References

  1. Agosta F, Galantucci S, and Filippi M (2016) Advanced magnetic resonance imaging of neurodegenerative diseases. Neurol. Sci. doi: 10.1007/s10072-016-2764-x.
  2. Alexander A L, Lee J E, Lazar M, and Field A S (2007) Diffusion tensor imaging of the brain. Neurotherapeutics 4, 316-329. https://doi.org/10.1016/j.nurt.2007.05.011
  3. Ashburner J (2007) A fast diffeomorphic image registration algorithm. Neuroimage 38, 95-113. https://doi.org/10.1016/j.neuroimage.2007.07.007
  4. Christidi F, Karavasilis E, Samiotis K, Bisdas S, and Papanikolaou N (2016) Fiber tracking: a qualitative and quantitative comparison between four different software tools on the reconstruction of major white matter tracts. Eur. J. Radiol. Open. 3, 153-161. https://doi.org/10.1016/j.ejro.2016.06.002
  5. Good C D, Johnsrude I S, Ashburner J, Henson R N, Friston K J, and Frackowiak R S (2001) A voxel-based morphometric study of ageing in 465 normal adult human brains. Neuroimage 14, 21-36. https://doi.org/10.1006/nimg.2001.0786
  6. Hu M L, Zong X F, Mann J J, Zheng J J, Liao Y H, Li Z C, He Y, Chen X G, and Tang J S (2016) A review of the functional and anatomical default mode network in schizophrenia. Neurosci. Bull. doi: 10.1007/s12264-016-0090-1.
  7. Janssen J, Aleman-Gomez Y, Schnack H, Balaban E, Pina-Camacho L, Alfaro-Almagro F, Castro-Fornieles J, Otero S, Baeza I, Moreno D, Bargallo N, Parellada M, Arango C, and Desco M (2014) Cortical morphology of adolescents with bipolar disorder and with schizophrenia. Schizophr. Res. 158, 91-99. https://doi.org/10.1016/j.schres.2014.06.040
  8. Mak E, Gabel S, Mirette H, Su L, Williams G B, Waldman A, Wells K, Ritchie K, Ritchie C, and O'Brien J (2016) Structural neuroimaging in preclinical dementia: from microstructural deficits and grey matter atrophy to macroscale connectomic changes. Ageing Res. Rev. S1568-1637, 30062-30069.
  9. McKeown M J, Makeig S, Brown G G, Jung T P, Kindermann S S, Bell A J, and Sejnowski T J (1998) Analysis of fMRI data by blind separation into independent spatial components. Hum. Brain Mapp. 6, 160-188. https://doi.org/10.1002/(SICI)1097-0193(1998)6:3<160::AID-HBM5>3.0.CO;2-1
  10. McKeown M J and Sejnowski T J (1998) Independent component analysis of fMRI data: examining the assumptions. Hum. Brain Mapp. 6, 368-372. https://doi.org/10.1002/(SICI)1097-0193(1998)6:5/6<368::AID-HBM7>3.0.CO;2-E
  11. Nanda P, Tandon N, Mathew I T, Giakoumatos C I, Abhishekh H A, Clementz B A, Pearlson G D, Sweeney J, Tamminga C A, and Keshavan M S (2014) Local gyrification index in probands with psychotic disorders and their first-degree relatives. Biol. Psychiatry 76, 447-455. https://doi.org/10.1016/j.biopsych.2013.11.018
  12. Nenadic I, Maitra R, Dietzek M, Langbein K, Smesny S, Sauer H, and Gaser C (2015) Prefrontal gyrification in psychotic bipolar I disorder vs. schizophrenia. J. Affect Disord. 185, 104-107. https://doi.org/10.1016/j.jad.2015.06.014
  13. Nixon N L, Liddle P F, Nixon E, Worwood G, Liotti M, and Palaniyappan L (2014) Biological vulnerability to depression: linked structural and functional brain network findings. Br. J. Psychiatry 204, 283-289. https://doi.org/10.1192/bjp.bp.113.129965
  14. Ogawa S (2012) Finding the BOLD effect in brain images. Neuroimage 62, 608-609. https://doi.org/10.1016/j.neuroimage.2012.01.091
  15. Smith S M, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols T E, Mackay C E, Watkins K E, Ciccarelli O, Cader M Z, Matthews P M, and Behrens T E (2006) Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 31, 1487-1505. https://doi.org/10.1016/j.neuroimage.2006.02.024
  16. Tae W S, Yakunina N, Kim T S, Kim S S, and Nam E C (2014) Activation of auditory white matter tracts as revealed by functional magnetic resonance imaging. Neuroradiology 56, 597-605. https://doi.org/10.1007/s00234-014-1362-y
  17. Thompson P M, Stein J L, Medland S E, Hibar D P, Vasquez A A, Renteria M E, Toro R, Jahanshad N, Schumann G, Franke B, Wright M J, Martin N G, Agartz I, Alda M, Alhusaini S, Almasy L, Almeida J, Alpert K, Andreasen N C, Andreassen O A, Apostolova L G, Appel K, Armstrong N J, Aribisala B, Bastin M E, Bauer M, Bearden C E, Bergmann O, Binder E B, Blangero J, Bockholt H J, Boen E, Bois C, Boomsma D I, Booth T, Bowman I J, Bralten J, Brouwer R M, Brunner H G, Brohawn D G, Buckner R L, Buitelaar J, Bulayeva K, Bustillo J R, Calhoun V D, Cannon D M, Cantor R M, Carless M A, Caseras X, Cavalleri G L, Chakravarty M M, Chang K D, Ching C R, Christoforou A, Cichon S, Clark V P, Conrod P, Coppola G, Crespo-Facorro B, Curran J E, Czisch M, Deary I J, de Geus E J, den Braber A, Delvecchio G, Depondt C, de Haan L, de Zubicaray G I, Dima D, Dimitrova R, Djurovic S, Dong H, Donohoe G, Duggirala R, Dyer T D, Ehrlich S, Ekman C J, Elvsashagen T, Emsell L, Erk S, Espeseth T, Fagerness J, Fears S, Fedko I, Fernandez G, Fisher S E, Foroud T, Fox P T, Francks C, Frangou S, Frey E M, Frodl T, Frouin V, Garavan H, Giddaluru S, Glahn D C, Godlewska B, Goldstein R Z, Gollub R L, Grabe H J, Grimm O, Gruber O, Guadalupe T, Gur R E, Gur R C, Goring H H, Hagenaars S, Hajek T, Hall G B, Hall J, Hardy J, Hartman C A, Hass J, Hatton S N, Haukvik U K, Hegenscheid K, Heinz A, Hickie I B, Ho B C, Hoehn D, Hoekstra P J, Hollinshead M, Holmes A J, Homuth G, Hoogman M, Hong L E, Hosten N, Hottenga J J, Hulshoff Pol H E, Hwang K S, Jack C R Jr, Jenkinson M, Johnston C, Jonsson E G, Kahn R S, Kasperaviciute D, Kelly S, Kim S, Kochunov P, Koenders L, Kramer B, Kwok J B, Lagopoulos J, Laje G, Landen M, Landman B A, Lauriello J, Lawrie S M, Lee P H, Le Hellard S, Lemaitre H, Leonardo C D, Li C S, Liberg B, Liewald D C, Liu X, Lopez L M, Loth E, Lourdusamy A, Luciano M, Macciardi F, Machielsen M W, Macqueen G M, Malt U F, Mandl R, Manoach D S, Martinot J L, Matarin M, Mather K A, Mattheisen M, Mattingsdal M, Meyer-Lindenberg A, McDonald C, McIntosh A M, McMahon F J, McMahon K L, Meisenzahl E, Melle I, Milaneschi Y, Mohnke S, Montgomery G W, Morris D W, Moses E K, Mueller B A, Munoz Maniega S, Muhleisen T W, Muller-Myhsok B, Mwangi B, Nauck M, Nho K, Nichols T E, Nilsson L G, Nugent A C, Nyberg L, Olvera R L, Oosterlaan J, Ophoff R A, Pandolfo M, Papalampropoulou-Tsiridou M, Papmeyer M, Paus T, Pausova Z, Pearlson G D, Penninx B W, Peterson C P, Pfennig A, Phillips M, Pike G B, Poline J B, Potkin S G, Putz B, Ramasamy A, Rasmussen J, Rietschel M, Rijpkema M, Risacher S L, Roffman J L, Roiz-Santianez R, Romanczuk-Seiferth N, Rose E J, Royle N A, Rujescu D, Ryten M, Sachdev P S, Salami A, Satterthwaite T D, Savitz J, Saykin A J, Scanlon C, Schmaal L, Schnack H G, Schork A J, Schulz S C, Schur R, Seidman L, Shen L, Shoemaker J M, Simmons A, Sisodiya S M, Smith C, Smoller J W, Soares J C, Sponheim S R, Sprooten E, Starr J M, Steen V M, Strakowski S, Strike L, Sussmann J, Samann P G, Teumer A, Toga A W, Tordesillas-Gutierrez D, Trabzuni D, Trost S, Turner J, Van den Heuvel M, van der Wee N J, van Eijk K, van Erp T G, van Haren N E, van't Ent D, van Tol M J, Valdes Hernandez M C, Veltman D J, Versace A, Volzke H, Walker R, Walter H, Wang L, Wardlaw J M, Weale M E, Weiner M W, Wen W, Westlye L T, Whalley H C, Whelan C D, White T, Winkler A M, Wittfeld K, Woldehawariat G, Wolf C, Zilles D, Zwiers M P, Thalamuthu A, Schofield P R, Freimer N B, Lawrence N S, Drevets W; Alzheimer's Disease Neuroimaging Initiative, EPIGEN Consortium, IMAGEN Consortium, Saguenay Youth Study (SYS) Group (2014) The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data. Brain Imaging Behav. 8, 153-182.
  18. Yendiki A, Panneck P, Srinivasan P, Stevens A, Zollei L, Augustinack J, Wang R, Salat D, Ehrlich S, Behrens T, Jbabdi S, Gollub R, and Fischl B (2011) Automated probabilistic reconstruction of white-matter pathways in health and disease using an atlas of the underlying anatomy. Front Neuroinform 5, 23.