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Updated: Jan 20, 2026

Brain State-dependent Brain Stimulation with Real-time Electroencephalography-Triggered Transcranial Magnetic Stimulation
Published on: August 20, 2019
Awakening: Predicting external stimulation to force transitions between different brain states
Gustavo Deco1,2,3,4,5, Josephine Cruzat6,2, Joana Cabral7,8,9
1Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, 08018 Barcelona, Spain; gustavo.deco@upf.edu nklmpg@stanford.edu morten.kringelbach@psych.ox.ac.uk.
Researchers defined brain states as metastable substates, enabling in silico whole-brain modeling to identify optimal stimulation targets for transitioning between states, like awakening from sleep.
Area of Science:
- Systems Neuroscience
- Computational Neuroscience
Background:
- Defining brain states is crucial for understanding transitions, particularly for external stimulation applications.
- Current definitions lack the quantitative robustness needed for predictive modeling.
Purpose of the Study:
- To provide a quantitative definition of brain states based on metastable substates.
- To develop and apply whole-brain modeling for simulating brain stimulation effects in humans.
- To identify optimal stimulation targets for inducing state transitions, such as awakening from sleep.
Main Methods:
- Defined brain states as ensembles of metastable substates with probabilistic stability and occurrence frequencies.
- Utilized whole-brain modeling, fine-tuned with human sleep neuroimaging data and effective connectivity.
- Simulated in silico direct electrical stimulation (DES) to investigate state transition induction.
Main Results:
- Successfully defined brain states based on metastable substates and their dynamics.
- Demonstrated the capability of whole-brain models to simulate and predict state transitions.
- Identified specific brain regions and connectivity patterns for forcing transitions, including awakening from sleep.
Conclusions:
- A novel, quantitative definition of brain states as metastable substates facilitates robust modeling.
- Whole-brain modeling offers a powerful in silico tool for exploring brain state transitions and stimulation effects.
- Findings pave the way for discovering targeted stimulation strategies for neurological conditions and brain injury recovery.
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