Impact of signal-to-noise on functional MRI

Todd B. Parrish*, Darren R. Gitelman, Kevin S. LaBar, M. Marsel Mesulam

*Corresponding author for this work

Research output: Contribution to journalArticle

162 Scopus citations

Abstract

Functional magnetic resonance imaging (fMRI) has recently been adopted as an investigational tool in the field of neuroscience. The signal changes induced by brain activations are small (~1-2%) at 1.5T. Therefore, the signal-to-noise ratio (SNR) of the time series used to calculate the functional maps is critical. In this study, the minimum SNR required to detect an expected MR signal change is determined using computer simulations for typical fMRI experimental designs. These SNR results are independent of manufacturer, site environment, field strength, coil type, or type of cognitive task used. Sensitivity maps depicting the minimum detectable signal change can be constructed. These sensitivity maps can be used as a mask of the activation map to help remove false positive activations as well as identify regions of the brain where it is not possible to confidently reject the null hypothesis due to a low SNR. (C) 2000 Wiley-Liss, Inc.

Original languageEnglish (US)
Pages (from-to)925-932
Number of pages8
JournalMagnetic resonance in medicine
Volume44
Issue number6
DOIs
StatePublished - 2000

Keywords

  • Functional MRI
  • SNR
  • fMRI
  • fMRI statistics

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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