An Object Oriented Approach to Multimodal Imaging Data in Neuroscience

  • Andrea Cappozzo
  • Federico FerraccioliEmail author
  • Marco Stefanucci
  • Piercesare Secchi
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 257)


We propose a methodological framework for exploring complex multimodal imaging data from a neuroscience study with the aim of identifying a data-driven group structure in the patients sample, possibly connected with the presence/absence of lifetime mental disorder. The functional covariances of fMRI signals are first considered as data objects. Appropriate clustering procedures and low dimensional representations are proposed. For inference, a Frechet estimator of both the covariance operator itself and the average covariance operator is used. A permutation procedure to test the equality of the covariance operators between two groups is also considered. We finally propose a method to incorporate spatial dependencies between different brain regions, merging the information from both the Structural Networks and the Dynamic functional activity.


Data objects Functional data analysis Principal components Multimodal Imaging Neuroscience 



We acknowledge Greg Kiar and Eric Bridgeford from NeuroData at Johns Hopkins University, who pre-processed the raw DTI and R-fMRI imaging data available at We would like to deeply thank the StartUp Research Scientific Committee for efficiently and flawlessly organizing such a motivating experience. We thank Professor Francesca Greselin and Doctor Mauro Ceroni for their support and help throughout the drafting of this manuscript.


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Andrea Cappozzo
    • 1
  • Federico Ferraccioli
    • 2
    Email author
  • Marco Stefanucci
    • 3
  • Piercesare Secchi
    • 4
  1. 1.Department of Statistics and Quantitative MethodsUniversity of Milano-BicoccaMilanItaly
  2. 2.Department of Statistical SciencesUniversity of PadovaPaduaItaly
  3. 3.Department of Statistical SciencesSapienza University of RomeRomeItaly
  4. 4.MOX Department of MathematicsPolitecnico di MilanoMilanItaly

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