Browse by author
Lookup NU author(s): Professor Marcus Kaiser
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Copyright: © 2025 Gatica et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Transcranial ultrasound stimulation (TUS) is an emerging non-invasive neuromodulation technique, offering a potential alternative to pharmacological treatments for psychiatric and neurological disorders. While functional analysis has been instrumental in characterizing the TUS effects, understanding its indirect influence across the network remains challenging. Here, we developed a whole-brain model to represent functional changes as measured by fMRI, enabling us to investigate how TUS-induced effects propagate throughout the brain with increasing stimulus intensity. We implemented two mechanisms: one based on anatomical distance and another on broadcasting dynamics, to explore plasticity-driven changes in specific brain regions. Finally, we highlighted the role of higher-order functional interactions in localizing spatial effects of off-line TUS at two target areas-the right thalamus and inferior frontal cortex-revealing distinct patterns of functional reorganization. This work lays the foundation for mechanistic insights and predictive models of TUS, advancing its potential clinical applications.
Author(s): Gatica M, Atkinson-Clement C, Coronel-Oliveros C, Alkhawashki M, Mediano PAM, Tagliazucchi E, Rosas FE, Kaiser M, Petri G
Publication type: Article
Publication status: Published
Journal: PLoS Computational Biology
Year: 2025
Volume: 21
Issue: 10
Online publication date: 06/10/2025
Acceptance date: 10/09/2025
Date deposited: 20/10/2025
ISSN (electronic): 1553-7358
Publisher: Public Library of Science
URL: https://doi.org/10.1371/journal.pcbi.1013514
DOI: 10.1371/journal.pcbi.1013514
Data Access Statement: The data analysis was conducted using MATLAB version 2022b. The MATLAB code for quantifying synergy and redundancy from integrated information decomposition of time series, utilizing the Gaussian MMI solver, is available at https://doi.org/10.1038/s41593-022-01070-0 We computed the communication models for weighted networks using the Brain Connectivity Toolbox: http://www.brain-connectivity-toolbox.net. We used the Python code to simulate the Hopf model, freely available at: https://github.com/ carlosmig/StarCraft-2-Modeling.git. Brain plot visualizations were generated using MRIcroGL: https://www.nitrc.org/projects/mricrogl/. A Python code to reproduce this work, along with the data necessary to run the code, is available at https://github.com/nplresearch/Modelling-TUS.
PubMed id: 41052135
Altmetrics provided by Altmetric
