Stomach-brain synchrony reveals a novel, delayed-connectivity resting-state network in humans
Abstract
Resting-state networks offer a unique window into the brain's functional architecture, but their characterization remains limited to instantaneous connectivity thus far. Here, we describe a novel resting-state network based on the delayed connectivity between the brain and the slow electrical rhythm (0.05 Hz) generated in the stomach. The gastric network cuts across classical resting-state networks with partial overlap with autonomic regulation areas. This network is composed of regions with convergent functional properties involved in mapping bodily space through touch, action or vision, as well as mapping external space in bodily coordinates. The network is characterized by a precise temporal sequence of activations within a gastric cycle, beginning with somato-motor cortices and ending with the extrastriate body area and dorsal precuneus. Our results demonstrate that canonical resting-state networks based on instantaneous connectivity represent only one of the possible partitions of the brain into coherent networks based on temporal dynamics.
Article and author information
Author details
Funding
H2020 European Research Council (670325)
- Catherine Tallon-Baudry
Agence Nationale de la Recherche (ANR-10-LABX-0087 IEC)
- Catherine Tallon-Baudry
DIM cerveau et pensee
- Ignacio Rebollo
Fondation Bettencourt Schueller
- Ignacio Rebollo
Agence Nationale de la Recherche (ANR-10-IDEX-0001-02 PSL*)
- Catherine Tallon-Baudry
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: Participants received provided written informed consent for participation in the experiment. The study was approved by the ethics committee Comité de Protection des Personnes Ile de France III
Copyright
© 2018, Rebollo et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 8,789
- views
-
- 1,156
- downloads
-
- 142
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Citations by DOI
-
- 142
- citations for umbrella DOI https://doi.org/10.7554/eLife.33321