Spinal fMRI during proprioceptive and tactile tasks in healthy subjects: Activity detected using cross-correlation, general linear model and independent component analysis

P. Valsasina, F. Agosta, D. Caputo, P. W. Stroman, M. Filippi

Research output: Contribution to journalArticle

Abstract

Introduction: Functional MRI (fMRI) of the spinal cord is able to provide maps of neuronal activity. Spinal fMRI data have been analyzed in previous studies by calculating the cross-correlation (CC) between the stimulus and the time course of every voxel and, more recently, by using the general linear model (GLM). The aim of this study was to compare three different approaches (CC analysis, GLM and independent component analysis (ICA)) for analyzing fMRI scans of the cervical spinal cord. Methods: We analyzed spinal fMRI data from healthy subjects during a proprioceptive and a tactile stimulation by using two model-based approaches, i.e., CC analysis between the stimulus shape and the time course of every voxel, and the GLM. Moreover, we applied independent component analysis, a model-free approach which decomposes the data in a set of source signals. Results: All methods were able to detect cervical cord areas of activity corresponding to the expected regions of neuronal activations. Model-based approaches (CC and GLM) revealed similar patterns of activity. ICA could identify a component correlated to fMRI stimulation, although with a lower statistical threshold than model-based approaches, and many components, consistent across subjects, which are likely to be secondary to noise present in the data. Conclusions: Model-based approaches seem to be more robust for estimating task-related activity, whereas ICA seems to be useful for eliminating noise components from the data. Combined use of ICA and GLM might improve the reliability of spinal fMRI results.

Original languageEnglish
Pages (from-to)895-902
Number of pages8
JournalNeuroradiology
Volume50
Issue number10
DOIs
Publication statusPublished - Oct 2008

Keywords

  • Cervical cord
  • fMRI data analysis
  • Functional magnetic resonance imaging
  • General linear model
  • Independent component analysis

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Clinical Neurology
  • Cardiology and Cardiovascular Medicine

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