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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
  • IRCCS Fondazione Don Carlo Gnocchi - Milano
  • Polytechnic University of Milan
  • Swiss Federal Institute of Technology Lausanne
  • University of Geneva
  • University of Milan
  • Massachusetts General Hospital

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

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.

Original languageEnglish
Pages (from-to)814-823
Number of pages10
JournalBrain Topography
Volume29
Issue number6
DOIs
StatePublished - Nov 1 2016

Keywords

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

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