Biology subjects

Rebollo, I.

Publications and source records attributed to Rebollo, I..

9 recordsLinked to original sources

bioRxiv2026

Spatiospectral signatures of stomach-brain synchrony

While cognitive neuroscience has increasingly recognized the brain-body connection, the temporal dynamics of how the stomachs intrinsic rhythm ([~]0.05 Hz) modulates human neural activity remain poorly understood. Leveraging high-resolution magneto-encephalography (MEG) and novel high-density electrogastrography (EGG), we provide the first comprehensive spatiotemporal mapping of human gastric-brain coupling at rest. Our circular-linear correlation approach revealed widespread, broadband phase-amplitude coupling between the gastric rhythm and spontaneous cortical oscillations across delta, theta, alpha, and beta bands. Using nonnegative matrix factorization, we identified distinct spatiospectral fingerprints that significantly overlap with the known fMRI-based gastric resting-state network. Crucially, we discovered a consistent preferred gastric phase for these modulations, i.e. during the transition between stomach waves, that was stable across brain regions, frequencies, and time. These findings suggest that the gastric rhythm - potentially in unison with other physiological signals - provides a stable, global scaffold for large-scale oscillatory brain organization. By unravelling these spectral signatures, our results establish the stomach as a critical driver of the temporal coordination of human brain dynamics.

neuroscience↗

bioRxiv2026

Slow breathing impacts inter-organ dynamics modulating brain function and risk behavior

Successful decision-making requires that external information be interpreted in the context of the bodys state. Within the framework of body-brain interaction, deliberately modifying ones autonomic state can shape how we evaluate the world, ultimately influencing choices. Yet, it remains unclear whether and how intentional autonomic regulation affects human decision-making. In this study, we tested instructed prolonged exhalation, a slow-breathing technique designed to boost parasympathetic activity during risky decision-making. Participants followed distinct breathing protocols while making risky choices, with neural and physiological activity measured using fMRI and multi-channel monitoring. Prolonged exhalation increased risky choices by enhancing reward sensitivity and elevating cardiac parasympathetic activity. Importantly, individuals with greater parasympathetic upregulation also showed stronger reward-related responses in the ventromedial prefrontal cortex and precuneus. Our work reveals a transformative role for breathing-based interventions, demonstrating that breathing-based autonomic regulation can shape value-based decision-making through neuro-cardiac pathways. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/698695v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@190293corg.highwire.dtl.DTLVardef@1835c63org.highwire.dtl.DTLVardef@1267ff3org.highwire.dtl.DTLVardef@9a583e_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTSO_LIProlonged exhalation increases risky decisions by increasing the reward sensitivity C_LIO_LIProlonged exhalation enhances cardiac parasympathetic activity without dampening sympathetic activities C_LIO_LIGreater cardiac parasympathetic activity under prolonged exhalation amplifies neural reward sensitivity in the ventromedial prefrontal cortex and precuneus C_LI

neuroscience↗

bioRxiv2025

Simultaneous stomach-brain electrophysiology reveals dynamic coupling in human sleep

Sleep involves coordinated interactions between the brain and body, yet whether and how peripheral physiology is organized during human sleep is poorly understood. Because gastric rhythms are strongly modulated by arousal states during wakefulness, we hypothesized that gastric electrical rhythms exhibit structured dynamics aligned with cortical oscillations during sleep. Using simultaneous high-density electroencephalography and electrogastrography, we find that gastric activity persists throughout sleep, increases during non-rapid eye movement (NREM), and exhibits infraslow fluctuations that are amplified during NREM. Moreover, gastric activity is synchronized with slow oscillations and sleep spindles, with gastric power tracking spindle occurrence and cortical infraslow cycles. Stomach-brain coupling predicted next-day memory recall beyond cortical measures, whereas gastric infraslow dynamics predicted subjective sleep quality beyond polysomnographic measures. Together, our findings show that even as the brain disconnects from the external world, it maintains structured communication with peripheral organs, reframing sleep as a coordinated, multi-organ physiological state.

neuroscience↗

bioRxiv2025

Accessible, realistic genome simulation with selection using stdpopsim

Selection is a fundamental evolutionary force that shapes patterns of genetic variation across species. However, simulations incorporating realistic selection along heterogeneous genomes in complex demographic histories are challenging, limiting our ability to benchmark statistical methods aimed at detecting selection and to explore theoretical predictions. stdpopsim is a community-maintained simulation library that already provides an extensive catalog of species-specific population genetic models. Here we present a major extension to the stdpopsim framework that enables simulation of various modes of selection, including background selection, selective sweeps, and arbitrary distributions of fitness effects (DFE) acting on annotated subsets of the genome (for instance, exons). This extension maintains stdpopsims core principles of reproducibility and accessibility while adding support for species-specific genomic annotations and published DFE estimates. We demonstrate the utility of this framework by comparing methods for demographic inference, DFE estimation, and selective sweep detection across several species and scenarios. Our results demonstrate the robustness of demographic inference methods to selection on linked sites, reveal the sensitivity of DFE-inference methods to model assumptions, and show how genomic features, like recombination rate and functional sequence density, influence power to detect selective sweeps. This extension to stdpopsim provides a powerful new resource for the population genetics community to explore the interplay between selection and other evolutionary forces in a reproducible, user-friendly framework.

evolutionary biology↗

bioRxiv2025

Leveraging ancestral recombination graphs for quantitative genetic analysis of rice yield in indica and japonica subspecies

Rice (Oryza sativa L.) has two main subspecies, indica and japonica, which coexist in many regions but are often treated separately during breeding. Combining both subspecies in quantitative genetic analyses could enhance genetic improvement, however, this requires appropriately modelling their genetic history. The ancestral recombination graph (ARG) is an effective population genetics tool that comprehensively and succinctly represents a species genetic history. This study evaluated the use of an ARG, encoded as a tree sequence, to improve quantitative genetic analyses of indica and japonica rice. Using data from Uruguays National Rice Breeding Program, we inferred ancestral alleles, constructed and dated an ARG, and examined its application in genomic prediction and genome-wide association studies. We compared the predictive ability of a branch-based relationship matrix (BRM) built from an ARG against conventional relationship matrices from pedigree and single nucleotide polymorphism (SNP) site data. We then estimated BRMs SNP site effects to identify potential sites of interest and better understand how these map onto the tree sequence branches. The results showed that the ARG captured key biological signals, encoded genomic data more efficiently than conventional formats, and resulted in the highest predictive ability when combining both subspecies. Although the ARG-based approach did not substantially outperform conventional approaches for between-species prediction, this approach holds promise for plant breeding with larger datasets and could enhance genome-wide association studies by elucidating haplotype ancestry and the evolution of their value. Overall, our results demonstrated the potential of ARGs for the quantitative genetic analysis of diverse populations.

genetics↗

bioRxiv2024

Increased stomach-brain coupling indexes a dimensional signature of negative mental health symptoms.

Visceral rhythms orchestrate the physiological states underlying human emotion. Chronic aberrations in these brain-body interactions are implicated in a broad spectrum of mental health disorders. However, the relationship of gastric-brain coupling to affective symptoms remains poorly understood. We investigated the relationship between this novel interoceptive axis and mental health in 243 participants, using a cross validated machine learning approach. We find that increased fronto-parietal brain coupling to the gastric rhythm indexes a dimensional signature of worse mental health, spanning anxiety, depression, stress, and well-being. Control analyses confirm the specificity of these interactions to the gastric-brain axis. Our study proposes coupling between the stomach and brain as a factor in mental health and offers potential new targets for interventions remediating aberrant brain-body coupling.

neuroscience↗

bioRxiv2021

Vagus nerve stimulation increases stomach-brain coupling via a vagal afferent pathway

Maintaining energy homeostasis is vital and supported by vagal signaling between digestive organs and the brain. Previous research has established a gastric network in the brain that is phase synchronized with the rhythm of the stomach, but tools to perturb its function were lacking. Here, we investigated the effect of acute right-sided transcutaneous auricular vagus nerve stimulation (taVNS) versus sham stimulation (randomized crossover-design) on stomach-brain coupling. In line with preclinical research, taVNS increased stomach-brain coupling in the nucleus of the solitary tract (NTS) and the midbrain while boosting coupling across the brain. Crucially, in the cortex, taVNS-induced changes in coupling occurred primarily in transmodal regions and were associated with changes in hunger ratings as indicators of the subjective metabolic state. Hence, taVNS alters stomach-brain coupling via an NTS-midbrain pathway that signals gut-induced reward, potentially paving the way for novel treatments in disorders such as Parkinsons disease or depression. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=160 SRC="FIGDIR/small/463517v1_ufig1.gif" ALT="Figure 1"> View larger version (53K): org.highwire.dtl.DTLVardef@39c673org.highwire.dtl.DTLVardef@113b785org.highwire.dtl.DTLVardef@175af94org.highwire.dtl.DTLVardef@15a2fbc_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LITranscutaneous vagus nerve stimulation (taVNS) can emulate interoceptive signals C_LIO_LItaVNS boosts stomach-brain coupling in the brainstem, midbrain, and transmodal cortex C_LIO_LItaVNS-induced changes in stomach-brain coupling mirror subjective hunger ratings C_LI

neuroscience↗

bioRxiv2021

The sensory and motor components of the cortical hierarchy are coupled to the rhythm of the stomach during rest

Bodily rhythms appear as novel scaffolding mechanisms orchestrating the spatio-temporal organization of spontaneous brain activity. Here, we follow up on the discovery of the gastric resting-state network (Rebollo et al, 2018), composed of brain regions in which the fMRI signal is phase-synchronized to the slow (0.05 Hz) electrical rhythm of the stomach. Using a larger sample size (n=63 human participants), we further characterize the anatomy and effect sizes of gastric-brain coupling across resting-state networks, a fine grained cortical parcellation, as well as along the main gradients of cortical organization. Most (67%) of the gastric network is included in the somato-motor-auditory (38%) and visual (29%) resting state networks. Gastric brain coupling also occurs in the granular insula and, to a lesser extent, in the piriform cortex. Thus, all sensory and motor cortices corresponding to both exteroceptive and interoceptive modalities are coupled to the gastric rhythm during rest. Conversely, little gastric-brain coupling occurs in cognitive networks and transmodal regions. These results suggest not only that gastric rhythm and sensory-motor processes are likely to interact, but also that gastric-brain coupling might be a mechanism of sensory and motor integration that mostly bypasses cognition, complementing the classical hierarchical organization of the human brain. Significance statementWhile there is growing interest for brain-body communication in general and brain-viscera communication in particular, little is known about how the brain interacts with the gastric rhythm, the slow electrical rhythm continuously produced in the stomach. Here, we show in human participants at rest that the gastric network, composed of brain regions synchronized with delays to the gastric rhythm, includes all motor and sensory (vision, audition, touch and interoception, olfaction) regions, but only few of the transmodal regions associated with higher-level cognition. Such results prompt for a reconsideration of the classical view of cortical organization, where the different sensory modalities are considered as relatively independent modules.

neuroscience↗

bioRxiv2017

Stomach-brain synchrony binds neural representations of the body in a novel, delayed-connectivity resting-state network

Resting-state networks offer a unique window into the brains 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 little 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.

neuroscience↗