Volume 90, Issue 6 p. 2486-2499
RESEARCH ARTICLE

Spatial and Spectral Components of the BOLD Global Signal in Rat Resting-State Functional MRI

Nmachi Anumba

Nmachi Anumba

Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, USA

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Eric Maltbie

Eric Maltbie

Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, USA

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Wen-Ju Pan

Wen-Ju Pan

Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, USA

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Theodore J. LaGrow

Theodore J. LaGrow

School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA

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Nan Xu

Nan Xu

Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, USA

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Shella Keilholz

Corresponding Author

Shella Keilholz

Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, USA

Correspondence

Shella Keilholz, Department of Biomedical Engineering at Georgia Institute of Technology and Emory University, 1760 Haygood Dr NE, Suite W230, Atlanta, GA, USA.

Email: [email protected]

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First published: 15 August 2023

Abstract

Purpose

In resting-state fMRI (rs-fMRI), the global signal average captures widespread fluctuations related to unwanted sources of variance such as motion and respiration, as well as widespread neural activity; however, relative contributions of neural and non-neural sources to the global signal remain poorly understood. This study sought to tackle this problem through the comparison of the BOLD global signal to an adjacent non-brain tissue signal, where neural activity was absent, from the same rs-fMRI scan obtained from anesthetized rats. In this dataset, motion was minimal and ventilation was phase-locked to image acquisition to minimize respiratory fluctuations. Data were acquired using three different anesthetics: isoflurane, dexmedetomidine, and a combination of dexmedetomidine and light isoflurane.

Methods

A power spectral density estimate, a voxel-wise spatial correlation via Pearson's correlation, and a co-activation pattern analysis were performed using the global signal and the non-brain tissue signal. Functional connectivity was calculated using Pearson's linear correlation on default mode network (DMN) regions.

Results

We report differences in the spectral composition of the two signals and show spatial selectivity within DMN structures that show an increased correlation to the global signal and decreased intra-network connectivity after global signal regression. All of the observed differences between the global signal and the non-brain tissue signal were maintained across anesthetics.

Conclusion

These results show that the global signal is distinct from the noise contained in the tissue signal, as support for a neural contribution. This study provides a unique perspective to the contents of the global signal and their origins.

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