Resting State Functional MR Imaging of Language Function

Published:October 30, 2020DOI:https://doi.org/10.1016/j.nic.2020.09.005

      Keywords

      To read this article in full you will need to make a payment
      Purchase one-time access
      Subscribers receive full online access to your subscription and archive of back issues up to and including 2002.
      Content published before 2002 is available via pay-per-view purchase only.
      Subscribe to Neuroimaging Clinics
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Petrella J.R.
        • Shah L.M.
        • Harris K.M.
        • et al.
        Preoperative functional MR imaging localization of language and motor areas: effect on therapeutic decision making in patients with potentially resectable brain tumors.
        Radiology. 2006; 240: 793-802
        • Benjamin C.F.
        • Walshaw P.D.
        • Hale K.
        • et al.
        Presurgical language fMRI: mapping of six critical regions: fMRI mapping of six language-critical regions.
        Hum Brain Mapp. 2017; 38: 4239-4255
        • McGirt M.J.
        • Mukherjee D.
        • Chaichana K.L.
        • et al.
        -Hinojosa A. Association of surgically acquired motor and language deficits on overall survival after resection of glioblastoma multiforme.
        Neurosurgery. 2009; 65: 463-470
        • Lacroix M.
        • Abi-Said D.
        • Fourney D.R.
        • et al.
        A multivariate analysis of 416 patients with glioblastoma multiforme: prognosis, extent of resection, and survival.
        J Neurosurg. 2001; 95: 190-198
        • Gulati S.
        • Jakola A.S.
        • Nerland U.S.
        • et al.
        The risk of getting worse: surgically acquired deficits, perioperative complications, and functional outcomes after primary resection of glioblastoma.
        World Neurosurg. 2011; 76: 572-579
        • Vassal M.
        • Charroud C.
        • Deverdun J.
        • et al.
        Recovery of functional connectivity of the sensorimotor network after surgery for diffuse low-grade gliomas involving the supplementary motor area.
        J Neurosurg. 2017; 126: 1181-1190
        • Rutten G.J.M.
        • Ramsey N.F.
        • Van Rijen P.C.
        • et al.
        Development of a functional magnetic resonance imaging protocol for intraoperative localization of critical temporoparietal language areas.
        Ann Neurol. 2002; 51: 350-360
        • Zacà D.
        • Jarso S.
        • Pillai J.J.
        Role of semantic paradigms for optimization of language mapping in clinical fMRI studies.
        AJNR Am J Neuroradiol. 2013; 34: 1966-1971
        • Black D.F.
        • Vachha B.
        • Mian A.
        • et al.
        American society of functional neuroradiology–recommended fmri paradigm algorithms for presurgical language assessment.
        AJNR Am J Neuroradiol. 2017; 38: E65-E73
        • Brennan N.P.
        • Peck K.K.
        • Holodny A.
        Language mapping using fmri and direct cortical stimulation for brain tumor surgery: the good, the bad, and the questionable.
        Top Magn Reson Imaging. 2016; 25: 1-10
        • Hacker C.D.
        • Laumann T.O.
        • Szrama N.P.
        • et al.
        Resting state network estimation in individual subjects.
        NeuroImage. 2013; 82: 616-633
        • Leuthardt E.C.
        • Guzman G.
        • Bandt S.K.
        • et al.
        Integration of resting state functional MRI into clinical practice - A large single institution experience.
        PLOS ONE. 2018; 13: e0198349
        • Dierker D.
        • Roland J.L.
        • Kamran M.
        • et al.
        Resting-state functional magnetic resonance imaging in presurgical functional mapping.
        Neuroimaging Clin N Am. 2017; 27: 621-633
        • Sair H.I.
        • Yahyavi-Firouz-Abadi N.
        • Calhoun V.D.
        • et al.
        Presurgical brain mapping of the language network in patients with brain tumors using resting-state fMRI: comparison with task fMRI.
        Hum Brain Mapp. 2016; 37: 913-923
        • Grabner G.
        • Janke A.L.
        • Budge M.M.
        • et al.
        Symmetric atlasing and model based segmentation: an application to the hippocampus in older adults.
        in: Larsen R. Nielsen M. Sporring J. Medical image computing and computer-assisted intervention – MICCAI 2006. Lecture notes in computer science. Springer, 2006: 58-66https://doi.org/10.1007/11866763_8
        • Desikan R.S.
        • Ségonne F.
        • Fischl B.
        • et al.
        An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.
        NeuroImage. 2006; 31: 968-980
        • Yarkoni T.
        • Poldrack R.A.
        • Nichols T.E.
        • et al.
        Large-scale automated synthesis of human functional neuroimaging data.
        Nat Methods. 2011; 8: 665-670
        • Nielsen F.Å.
        • Hansen L.K.
        • Balslev D.
        Mining for associations between text and brain activation in a functional neuroimaging database.
        Neuroinformatics. 2004; 2: 369-379
        • Wager T.D.
        • Lindquist M.A.
        • Nichols T.E.
        • et al.
        Evaluating the consistency and specificity of neuroimaging data using meta-analysis.
        NeuroImage. 2009; 45: S210-S221
        • Blei D.M.
        Latent dirichlet allocation.
        J Mach Learn Res. 2003; 3: 993-1022
      1. Manning C, Raghavan P, Schuetze H. Introduction to information retrieval. Cambridge University Press; 2008.

        • LeCun Y.
        • Bengio Y.
        • Hinton G.
        Deep learning.
        Nature. 2015; 521: 436
        • Huang G.
        • Liu Z.
        • Pleiss G.
        • et al.
        Convolutional networks with dense connectivity.
        IEEE Trans Pattern Anal Mach Intell. 2019; (Published online): 1https://doi.org/10.1109/TPAMI.2019.2918284
        • Thomas Yeo B.T.
        • Krienen F.M.
        • Sepulcre J.
        • et al.
        The organization of the human cerebral cortex estimated by intrinsic functional connectivity.
        J Neurophysiol. 2011; 106: 1125-1165
        • Brier M.R.
        • Thomas J.B.
        • Snyder A.Z.
        • et al.
        Loss of intranetwork and internetwork resting state functional connections with Alzheimer’s disease progression.
        J Neurosci. 2012; 32: 8890-8899
        • Chhatwal J.P.
        • Schultz A.P.
        • Johnson K.A.
        • et al.
        Preferential degradation of cognitive networks differentiates Alzheimer’s disease from ageing.
        Brain. 2018; 141: 1486-1500
        • Thomas J.B.
        • Brier M.R.
        • Snyder A.Z.
        • et al.
        Pathways to neurodegeneration: effects of HIV and aging on resting-state functional connectivity.
        Neurology. 2013; 80: 1186-1193
        • Power J.D.
        • Mitra A.
        • Laumann T.O.
        • et al.
        Methods to detect, characterize, and remove motion artifact in resting state fMRI.
        NeuroImage. 2014; 84: 320-341
        • Power J.D.
        • Cohen A.L.
        • Nelson S.M.
        • et al.
        Functional network organization of the human brain.
        Neuron. 2011; 72: 665-678
        • Gordon E.M.
        • Laumann T.O.
        • Gilmore A.W.
        • et al.
        Precision functional mapping of individual human brains.
        Neuron. 2017; 95: 791-807.e7
        • Csurka G.
        • Larlus D.
        • Perronnin F.
        What is a good evaluation measure for semantic segmentation? In: Proceedings of the British machine vision conference 2013. British Machine Vision Association.
        Durham University, Durham (UK)2013: 32.1-32.11https://doi.org/10.5244/C.27.32
        • Martin D.R.
        • Fowlkes C.C.
        • Malik J.
        Learning to detect natural image boundaries using local brightness, color, and texture cues.
        IEEE Trans Pattern Anal Mach Intell. 2004; 26: 530-549
        • Rivest J.
        • Cabanagh P.
        Localizing contours defined by more than one attribute.
        Vision Res. 1996; 36: 53-66
        • Sanai N.
        • Mirzadeh Z.
        • Berger M.S.
        Functional outcome after language mapping for glioma resection.
        N Engl J Med. 2008; 358: 18-27
        • Agarwal S.
        • Hua J.
        • Sair H.I.
        • et al.
        Repeatability of language fMRI lateralization and localization metrics in brain tumor patients.
        Hum Brain Mapp. 2018; 39: 4733-4742