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Journal Article Epublish 6 citations

PubMed: 39810817 DOI: 10.1162/imag_a_00270

Evaluating the effect of denoising submillimeter auditory fMRI data with NORDIC.

Imaging Neurosci (Camb) 2:1-18

Authors: Lonike K Faes, Agustin Lage-Castellanos, Giancarlo Valente, Zidan Yu, Martijn A Cloos, Luca Vizioli, Steen Moeller, Essa Yacoub, Federico De Martino

Affiliations

  • Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands.
  • Department of Neuroinformatics, Cuban Neuroscience Center, Havana City, Cuba.
  • Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, NY, United States.
  • Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, United States.
  • MRI Research Center, University of Hawaii, Honolulu, HI, United States.
  • Australian Institute for Bioengineering and Nanotechnology, University of Queensland, St. Lucia, Australia.
  • Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, United States.

Abstract

Functional magnetic resonance imaging (fMRI) has emerged as an essential tool for exploring human brain function. Submillimeter fMRI, in particular, has emerged as a tool to study mesoscopic computations. The inherently low signal-to-noise ratio (SNR) at submillimeter resolutions warrants the use of denoising approaches tailored at reducing thermal noise-the dominant contributing noise component in high-resolution fMRI. NOise Reduction with DIstribution Corrected Principal Component Analysis (NORDIC PCA) is one of such approaches, and has been benchmarked against other approaches in several applications. Here, we investigate the effects that two versions of NORDIC denoising have on auditory submillimeter data. While investigating auditory functional responses poses unique challenges, we anticipated NORDIC to have a positive impact on the data on the basis of previous applications. Our results show that NORDIC denoising improves the detection sensitivity and the reliability of estimates in submillimeter auditory fMRI data. These effects can be explained by the reduction of the noise-induced signal variability. However, we did observe a reduction in the average response amplitude (percent signal change) within regions of interest, which may suggest that a portion of the signal of interest, which could not be distinguished from general i.i.d. noise, was also removed. We conclude that, while evaluating the effects of the signal reduction induced by NORDIC may be necessary for each application, using NORDIC in high-resolution auditory fMRI studies may be advantageous because of the large reduction in variability of the estimated responses.

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