Sign in
NeuroscienceImaging Neuroscience
Peer-reviewed journal article

Lumbosacral spinal cord functional connectivity at rest: From feasibility to reliability

Ilaria RicchiiD, Nawal KinanyiD, Dimitri Van De VilleiD

Abstract

In the past decade, exploration of spontaneous blood-oxygen-level-dependent (BOLD) signal fluctuations has expanded beyond the brain to include the spinal cord. While most studies have predominantly focused on the cervical region, the lumbosacral segments play a crucial role in motor control and sensory processing of the lower limbs. Addressing this gap, the aims of the current study were two-fold: first, confirming the presence and nature of organized spontaneous BOLD signals in the human lumbosacral spinal cord; second, systematically assessing the impact of various denoising strategies on signal quality and functional connectivity (FC) patterns. Given the susceptibility of spinal cord fMRI to noise, this step is pivotal to ensure the robustness of intrinsic FC. Our findings uncovered bilateral FC between the ventral horns. Importantly, these patterns were consistently observed across denoising methods and demonstrating fair to excellent reliability. Conversely, no other significant connectivity patterns were identified across the remaining horns. Importantly, the evaluation of diverse denoising strategies highlighted the efficacy of PNM-based pipelines in cleaning the signal while preserving the strength and reliability of connectivity estimates. Together, our results provide evidence of robust FC patterns in the lumbosacral spinal cord, thereby paving the way for future studies probing caudal spinal activity.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISKaptan '23Eippert '16Kündig '24Kowalczyk '23Dabbagh '24Kowalczyk '26
80% semantic matchNeuroscience
Merve Kaptan, Ulrike Horn, S. Johanna Vannesjo+5 more·NeuroImage·May 2, 2023· 19 citations