bioRxivNeurosciencePreprint
Methodological considerations in analyzing synchronization of resting-state brain networks with the intrinsic electrical rhythm of the stomach: Advantages of weighted phase-locking
Ann S. ChoeiD, Bohao TangiD, Kimberly SmithiD, Hamed HonariiD, Martin A. LindquistiD, Brian S. CaffoiD, James J. PekariD
Abstract
PurposeTo evaluate the amplitude-weighted phase-locking value (awPLV) as a measure of synchronization of brain resting-state networks (RSNs) with the gastric basal electrical rhythm (BER). MethodsA recent study combined rsfMRI with concurrent cutaneous electrogastrography (EGG), in a highly-sampled individual who underwent 22 scanning sessions (two 15-minute runs per session) at 3.0 Tesla. After excluding three sessions due to weak EGG signals, 9.5 hours of data remained, from which 18 RSNs were estimated using spatial independent component analysis. Previously, using the phase-locking value (PLV), three of the 18 RSNs were determined to be synchronized with the BER. However, RSN power fluctuations in the gastric frequency band could reduce sensitivity of PLV. Accordingly, the current reanalysis used awPLV to unweight contributions from low power epochs. Mismatched EGG and rsfMRI data (from different days) served as surrogate data; for each RSN, empirical awPLV was compared with chance-level awPLV using a Wilcoxon rank test. P-values were adjusted using with a false discovery rate of 0.05. Additionally, simulations were performed to compare PLV and awPLV error rates under settings with a known ground truth. ResultsSimulations show high false-negative rates when using PLV, but not awPLV. Reanalysis of the highly-sampled individual data using awPLV indicates that 11 of the 18 RSNs were synchronized with the BER. ConclusionSimulations indicate that awPLV is a more sensitive measure of stomach/brain synchronization than PLV. Reanalysis results imply communication between the enteric nervous system and brain circuits not typically considered responsive to gastric state or function.
- organism: human
- assay: bulk RNA-seq
- assay: imaging
- research focus: differential expression
- research focus: benchmarking
- approach: statistical model
- Citations
- 1
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