Images-based suppression of unwanted global signals in resting-state functional connectivity studies

Federico Giove, Tommaso Gili, Vittorio Iacovella, Emiliano Macaluso, Bruno Maraviglia

Research output: Contribution to journalArticlepeer-review


Correlated fluctuations of low-frequency fMRI signal have been suggested to reflect functional connectivity among the involved regions. However, large-scale correlations are especially prone to spurious global modulations induced by coherent physiological noise. Cardiac and respiratory rhythms are the most offending component, and a tailored preprocessing is needed in order to reduce their impact. Several approaches have been proposed in the literature, generally based on the use of physiological recordings acquired during the functional scans, or on the extraction of the relevant information directly from the images. In this paper, the performances of the denoising approach based on general linear fitting of global signals of noninterest extracted from the functional scans were assessed. Results suggested that this approach is sufficiently accurate for the preprocessing of functional connectivity data.

Original languageEnglish
Pages (from-to)1058-1064
Number of pages7
JournalMagnetic Resonance Imaging
Issue number8
Publication statusPublished - Oct 2009


  • fMRI
  • Functional connectivity
  • Global signals
  • Physiological noise
  • Resting state

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging
  • Biomedical Engineering


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