Impact of signal-to-noise on functional MRI

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

doi:10.1002/1522-2594(200012)44:6<925::AID-MRM14>3.0.CO;2-M

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 journal › Article › peer-review

189 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 language	English (US)
Pages (from-to)	925-932
Number of pages	8
Journal	Magnetic resonance in medicine
Volume	44
Issue number	6
DOIs	https://doi.org/10.1002/1522-2594(200012)44:6<925::AID-MRM14>3.0.CO;2-M
State	Published - 2000

Keywords

Functional MRI
SNR
fMRI
fMRI statistics

ASJC Scopus subject areas

Radiology Nuclear Medicine and imaging

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10.1002/1522-2594(200012)44:6<925::AID-MRM14>3.0.CO;2-M

Cite this

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title = "Impact of signal-to-noise on functional MRI",

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.",

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author = "Parrish, {Todd B.} and Gitelman, {Darren R.} and LaBar, {Kevin S.} and Mesulam, {M. Marsel}",

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AU - Parrish, Todd B.

AU - Gitelman, Darren R.

AU - LaBar, Kevin S.

AU - Mesulam, M. Marsel

PY - 2000

Y1 - 2000

N2 - 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.

AB - 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.

KW - Functional MRI

KW - SNR

KW - fMRI

KW - fMRI statistics

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Impact of signal-to-noise on functional MRI

Abstract

Keywords

ASJC Scopus subject areas

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