Impact of signal-to-noise on functional MRI.
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 ( approximately 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.
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Related Subject Headings
- Time Factors
- Sensitivity and Specificity
- Parietal Lobe
- Occipital Lobe
- Nuclear Medicine & Medical Imaging
- Models, Neurological
- Magnetic Resonance Imaging
- Humans
- Hemangioma, Cavernous, Central Nervous System
- Computer Simulation
Citation
Published In
DOI
EISSN
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Time Factors
- Sensitivity and Specificity
- Parietal Lobe
- Occipital Lobe
- Nuclear Medicine & Medical Imaging
- Models, Neurological
- Magnetic Resonance Imaging
- Humans
- Hemangioma, Cavernous, Central Nervous System
- Computer Simulation