From Rest to Digest: A Large-Sample fMRI Exploration of Brain-Stomach Coupling
Poster No:
1776
Submission Type:
Abstract Submission
Authors:
Ignacio Rebollo1, Leah Banellis2, Niia Nikolova3, Micah Allen4
Institutions:
1German Institute of Human Nutrition, Potsdam-Rebrücke, Nuthetal, 2Aarhus University, Aarhus C, Midtjylland, 3Aarhus University, Aarhus, DK, 4Aarhus University, Lystrup, Denmark
First Author:
Co-Author(s):
Introduction:
Signals from the gastro-intestinal tract are constantly relayed to subcortical, cortical and neuromodulatory structures, interacting with spontaneous brain activity and its underlying organization into resting state networks (Azzalini et al., 2019). The stomach, produces its own slow electrical rhythm (~0.05 Hz, i.e., every 20 seconds), and multiple studies have shown that fMRI activity continuously waxes and wanes with the pace of this gastric rhythm (Levakov et al., 2023; Müller et al., 2021; Rebollo et al., 2018; Rebollo & Tallon-Baudry, 2022), albeit with sample sizes limited to 30-60 participants. In this study, we aimed to replicate, compare and extend these findings in a larger sample, while performing strict control for cardiac and physiological artifacts.
Methods:
We simultaneously recorded brain activity with fMRI (3 Tesla, TR=1.4 secs, 600 volumes), stomach activity with the electrogastrogram (EGG, (Wolpert et al., 2020)) in 247 human participants at rest with eyes open. fMRI preprocessing included fMRIPrep minimal pipeline, spatial smoothing with a 3mm FWHM kernel, and regressing out six motion parameters, six aCompCor parameters, as well as 12 RETROICOR components reflecting cardiac and respiratory physiological noise. After bandpass filtering the EGG and BOLD time series at individual EGG peak frequencies, we measured the phase coupling between the two (Lachaux et al., 1999). Each voxel coupling was compared to a chance level, estimated by shifting in time the EGG time series. We used FSL randomize algorithm to extract significant coupled voxels at the group level, correcting for multiple comparisons by using the null distribution of the max cluster mass (Strict threshold t = 5.4 , liberal threshold = 2.7).
Results:
We found an extended network of cortical and subcortical regions significantly coupled to the stomach at the group level. Using a more liberal threshold as in previous studies, we found that significant gastric coupling spans virtually the whole cortex. Using a more stringent threshold, the so-called gastric network (Figure 1) is more salient in sensory motor as well as transmodal regions, with largest overlap with the sensory-motor network followed by the default mode network, in line with previous studies using smaller sample sizes.
·Figure 1: Gastric network and resting state networks
Conclusions:
We found that coupling between the brain and the stomach during resting state is pervasive across the cortex, despite strict corrections for physiological noise from the heart and respiration. The large sample size of the current study allowed thus to reveal the full extent of the gastric network, which is in line with the multiple neuromodulatory pathways that are recruited by afferents from the stomach.
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 2
fMRI Connectivity and Network Modeling 1
Keywords:
Other - gastric
1|2Indicates the priority used for review
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Lachaux, J.-P., Rodriguez, E., Martinerie, J., Varela, F. J., & others. (1999). Measuring phase synchrony in brain signals. Human Brain Mapping, 8(4), 194–208.
Levakov, G., Ganor, S., & Avidan, G. (2023). Reliability and validity of brain-gastric phase synchronization. Human Brain Mapping, 44(14), 4956–4966. https://doi.org/10.1002/hbm.26436
Müller, S., Teckentrup, V., Rebollo, I., Hallschmid, M., & Kroemer, N. B. (2021). Vagus nerve stimulation increases stomach-brain coupling via a vagal afferent pathway (p. 2021.10.07.463517). https://doi.org/10.1101/2021.10.07.463517
Rebollo, I., Devauchelle, A.-D., Béranger, B., & Tallon-Baudry, C. (2018). Stomach-brain synchrony reveals a novel, delayed-connectivity resting-state network in humans. eLife, 7, e33321. https://doi.org/10.7554/eLife.33321
Rebollo, I., & Tallon-Baudry, C. (2022). The sensory and motor components of the cortical hierarchy are coupled to the rhythm of the stomach during rest. Journal of Neuroscience. https://doi.org/10.1523/JNEUROSCI.1285-21.2021
Wolpert, N., Rebollo, I., & Tallon‐Baudry, C. (2020). Electrogastrography for psychophysiological research: Practical considerations, analysis pipeline, and normative data in a large sample. Psychophysiology, e13599. https://doi.org/10.1111/psyp.13599