Pre-stimulus brain states predict and control variability in stimulation responses
5 affiliations
- 1Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain. Electronic address: [email protected]
- 2Aix-Marseille Univ, INSERM, INS, Institut de Neurosciences des Systèmes, Marseille, France; Department of Motor Sciences and Wellness, University of Naples "Parthenope", Naples, Italy
- 3Okinawa Institute for Science and Technology, Okinawa, Japan
- 4Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain
- 5Brain Stimulation Lab, Stanford Psychiatry and Behavioral Sciences, 401 Quarry Rd, Stanford CA, 94304, United States of America; Department of Psychiatry and Human Behavior, UCI School of Medicine, Irvine, CA, United States of America; Noel Drury, M.D. Institute for Translational Depression Discoveries, University of California, Irvine, Irvine, CA, United States of America
Abstract
Does the ongoing brain state determine how it responds to localized electrical stimulation? This fundamental question has major implications for neuroscience and medicine, as stimulation outcomes remain highly variable even when identical parameters ("how") and target sites ("where") are used. Such unpredictability undermines reproducibility, limits clinical reliability, and forces current protocols to rely on empirical trial-and-error rather than principled, evidence-based strategies. Mounting evidence suggests that the brain's state prior to stimulation—a crucial "when" factor—shapes responses, yet the most reliable predictive markers remain unknown. Here, we systematically characterize the links between pre-stimulus (spontaneous) activity and post-stimulus (evoked) responses using simultaneous high-density EEG and stereotactic EEG from 36 epilepsy patients across ~320 sessions (>10,000 individual stimulations). We show that large-scale neural dynamics robustly predict stimulation outcomes, with a subset of measures—particularly network synchronization, functional connectivity, and spatiotemporal signal diversity—consistently forecasting responses across sessions. Whole-brain activity enhanced prediction compared to local assessments, and predictability varied across networks, being strongest in sensorimotor and visual regions. These findings establish a quantitative framework for state-dependent brain stimulation: by timing interventions to optimal pre-stimulus states, variability can be reduced and reproducibility enhanced. Our results directly address the fundamental question of where and when to stimulate, providing a pathway toward evidence-based protocols with improved therapeutic precision.
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BibTeX
@article{rabuffo2026prestimulus,
title = {{Pre-stimulus brain states predict and control variability in stimulation responses}},
author = {Giovanni Rabuffo and Marianna Angiolelli and Tomoki Fukai and Gustavo Deco and Pierpaolo Sorrentino and Davide Momi},
journal = {Brain stimulation},
year = {2026},
month = may,
doi = {10.1016/j.brs.2026.103118},
url = {https://doi.org/10.1016/j.brs.2026.103118},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Pre-stimulus brain states predict and control variability in stimulation responses
AU - Giovanni Rabuffo
AU - Marianna Angiolelli
AU - Tomoki Fukai
AU - Gustavo Deco
AU - Pierpaolo Sorrentino
AU - Davide Momi
PY - 2026
DA - 2026/05/16
JO - Brain stimulation
DO - 10.1016/j.brs.2026.103118
UR - https://doi.org/10.1016/j.brs.2026.103118
AB - Does the ongoing brain state determine how it responds to localized electrical stimulation? This fundamental question has major implications for neuroscience and medicine, as stimulation outcomes remain highly variable even when identical parameters ("how") and target sites ("where") are used. Such unpredictability undermines reproducibility, limits clinical reliability, and forces current protocols to rely on empirical trial-and-error rather than principled, evidence-based strategies. Mounting evidence suggests that the brain's state prior to stimulation—a crucial "when" factor—shapes responses, yet the most reliable predictive markers remain unknown. Here, we systematically characterize the links between pre-stimulus (spontaneous) activity and post-stimulus (evoked) responses using simultaneous high-density EEG and stereotactic EEG from 36 epilepsy patients across ~320 sessions (>10,000 individual stimulations). We show that large-scale neural dynamics robustly predict stimulation outcomes, with a subset of measures—particularly network synchronization, functional connectivity, and spatiotemporal signal diversity—consistently forecasting responses across sessions. Whole-brain activity enhanced prediction compared to local assessments, and predictability varied across networks, being strongest in sensorimotor and visual regions. These findings establish a quantitative framework for state-dependent brain stimulation: by timing interventions to optimal pre-stimulus states, variability can be reduced and reproducibility enhanced. Our results directly address the fundamental question of where and when to stimulate, providing a pathway toward evidence-based protocols with improved therapeutic precision.
SN - 1876-4754
SN - 1935-861X
ER -