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Brain Topography

, Volume 29, Issue 6, pp 814–823 | Cite as

Combined DTI–fMRI Analysis for a Quantitative Assessment of Connections Between WM Bundles and Their Peripheral Cortical Fields in Verbal Fluency

  • Elisa Scaccianoce
  • Maria Marcella Laganà
  • Francesca Baglio
  • Maria Giulia Preti
  • Niels Bergsland
  • Pietro Cecconi
  • Mario Clerici
  • Giuseppe Baselli
  • George Papadimitriou
  • Nikos Makris
Original Paper

Abstract

Diffusion tensor imaging (DTI) tractography and functional magnetic resonance imaging (fMRI) are powerful techniques to elucidate the anatomical and functional aspects of brain connectivity. However, integrating these approaches to describe the precise link between structure and function within specific brain circuits remains challenging. In this study, a novel DTI–fMRI integration method is proposed, to provide the topographical characterization and the volumetric assessment of the functional and anatomical connections within the language circuit. In a group of 21 healthy elderly subjects (mean age 68.5 ± 5.8 years), the volume of connection between the cortical activity elicited by a verbal fluency task and the cortico-cortical fiber tracts associated with this function are mapped and quantified. An application of the method to a case study in neuro-rehabilitation context is also presented. Integrating structural and functional data within the same framework, this approach provides an overall view of white and gray matter when studying specific brain circuits.

Keywords

Diffusion tensor imaging (DTI) Functional magnetic resonance imaging (fMRI) Mapping brain connectivity Language Multimodal imaging 

Notes

Acknowledgments

This work was supported by 2014–2015 Ricerca Corrente (Italian Ministry of Health) (ES, MML, MGP, NB, PC, MC) and by the following funds: R21NS077059, R21NS079905, R01AG042512, R21EB016449 (NM).

Compliance with Ethical Standards

Conflicts of Interest

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Elisa Scaccianoce
    • 1
    • 2
  • Maria Marcella Laganà
    • 1
  • Francesca Baglio
    • 1
  • Maria Giulia Preti
    • 3
    • 4
  • Niels Bergsland
    • 1
    • 2
    • 5
  • Pietro Cecconi
    • 1
  • Mario Clerici
    • 1
    • 6
  • Giuseppe Baselli
    • 2
  • George Papadimitriou
    • 7
  • Nikos Makris
    • 7
  1. 1.Magnetic Resonance LaboratoryFondazione Don Carlo Gnocchi ONLUS, IRCCS S. Maria NascenteMilanItaly
  2. 2.Department of Electronics, Information and BioengineeringPolitecnico di MilanoMilanItaly
  3. 3.Institute of BioengineeringEcole Polytechnique Fédérale de LausanneLausanneSwitzerland
  4. 4.Department of Radiology and Medical InformaticsUniversity of GenevaGenevaSwitzerland
  5. 5.Buffalo Neuroimaging Analysis Center, Department of Neurology, School of Medicine and Biomedical SciencesUniversity at Buffalo, State University of New YorkBuffaloUSA
  6. 6.Università degli Studi di MilanoMilanItaly
  7. 7.Department of Psychiatry, Neurology and Radiology Services, Center for Morphometric AnalysisA. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolBostonUSA

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