Curve Clustering for Brain Functional Activity and Synchronization

  • Gaia Bertarelli
  • Alice Corbella
  • Jacopo Di Iorio
  • Anastasia Gorshechnikova
  • Marian Scott
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 257)


Functional Magnetic Resonance Imaging (fMRI) has become one of the leading methods for brain mapping in neuroscience and it is an important tool in modern neuroscience investigation. Moreover, the recent advances in fMRI analysis are widely used to define the default state of brain activity, functional connectivity and basal activity. Signal processing schemes have been suggested to analyze the resting state Blood-Oxygenation-Level-Dependent (BOLD) signal from simple correlations to spectral decomposition. Our goal is to determine which brain areas behave similarly in the time domain. To address this question, we apply functional curve clustering methods. We carry out an exploratory study using classical functional clustering of fMRI time series. The analysis confirms the hypothesis of a possible spatial influence on the results and therefore suggests the development of spatial curve clustering methods for brain data.


Curve clustering fMRI Functional boxplot Smoothing 



We are grateful to Greg Kiar and Eric Bridgeford from NeuroData at Johns Hopkins University, who graciously pre-processed the raw DTI and R-fMRI imaging data available at, using the pipelines ndmg and C-PAC and to the reviewers and The Scientific Committee of StartUp Research for all the suggestions aimed at improving this paper.


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Gaia Bertarelli
    • 1
  • Alice Corbella
    • 2
  • Jacopo Di Iorio
    • 3
  • Anastasia Gorshechnikova
    • 4
  • Marian Scott
    • 5
  1. 1.Department of Economics and ManagementUniversity of PisaPisaItaly
  2. 2.MRC Biostatistics Unit, School of Clinical MedicineUniversity of CambridgeCambridgeUK
  3. 3.MOX, Department of MathematicsPolitecnico di MilanoMilanItaly
  4. 4.Department of Statistical SciencesUniversity of PadovaPaduaItaly
  5. 5.School of Mathematics and StatisticsUniversity of GlasgowGlasgowUK

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