ArticleFrontiers in neuroscience2017
A Fast EEG Forecasting Algorithm for Phase-Locked Transcranial Electrical Stimulation of the Human Brain.
Article in Frontiers in neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Oscillatory brain state-dependent stimulation with transcranial magnetic stimulation combined with electroencephalography.Nature protocols · 2026Review
- Bayesian Temporal Prediction: A Robust Algorithm for Real-Time EEG Phase-Dependent Brain Stimulation.IEEE transactions on bio-medical engineering · 2026Article
- Lightweight EEG Phase Prediction Based on Channel Attention and Spatio-Temporal Parallel Processing.Brain sciences · 2025Article
- Optimizing real-time phase detection in diverse rhythmic biological signals for phase-specific neurostimulation.Journal of neural engineering · 2025Article
- Real-time TMS-EEG for brain state-controlled research and precision treatment: a narrative review and guide.Journal of neural engineering · 2024Review
- Leveraging Artificial Intelligence to Optimize Transcranial Direct Current Stimulation for Long COVID Management: A Forward-Looking Perspective.Brain sciences · 2024Article
- Article
- Closing the loop between brain and electrical stimulation: towards precision neuromodulation treatments.Translational psychiatry · 2023Review
- The Effect of the Peristimulus α Phase on Visual Perception through Real-Time Phase-Locked Stimulus Presentation.eNeuro · 2023Article
- Can vibrotactile stimulation and tDCS help inefficient BCI users?Journal of neuroengineering and rehabilitation · 2023Article
- Advanced Modeling and Signal Processing Methods in Brain-Computer Interfaces Based on a Vector of Cyclic Rhythmically Connected Random Processes.Sensors (Basel, Switzerland) · 2023Article
- Brain stimulation competes with ongoing oscillations for control of spike timing in the primate brain.PLoS biology · 2022Article
- Article
- Temporally Targeted Interactions With Pathologic Oscillations as Therapeutical Targets in Epilepsy and Beyond.Frontiers in neural circuits · 2021Review
- Closed-Loop Phase-Dependent Vibration Stimulation Improves Motor Imagery-Based Brain-Computer Interface Performance.Frontiers in neuroscience · 2021Article
- A user-friendly algorithm for adaptive closed-loop phase-locked stimulation.Journal of neuroscience methods · 2021Article
- Collective almost synchronization-based model to extract and predict features of EEG signals.Scientific reports · 2020Article
- Experimental evaluation of methods for real-time EEG phase-specific transcranial magnetic stimulation.Journal of neural engineering · 2020Article
- The shaky ground truth of real-time phase estimation.NeuroImage · 2020Article
- Large-scale cortical travelling waves predict localized future cortical signals.PLoS computational biology · 2019Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A growing body of research suggests that non-invasive electrical brain stimulation can more effectively modulate neural activity when phase-locked to the underlying brain rhythms. Transcranial alternating current stimulation (tACS) can potentially stimulate the brain in-phase to its natural oscillations as recorded by electroencephalography (EEG), but matching these oscillations is a challenging problem due to the complex and time-varying nature of the EEG signals. Here we address this challenge by developing and testing a novel approach intended to deliver tACS phase-locked to the activity of the underlying brain region in real-time. This novel approach extracts phase and frequency from a segment of EEG, then forecasts the signal to control the stimulation. A careful tuning of the EEG segment length and prediction horizon is required and has been investigated here for different EEG frequency bands. The algorithm was tested on EEG data from 5 healthy volunteers. Algorithm performance was quantified in terms of phase-locking values across a variety of EEG frequency bands. Phase-locking performance was found to be consistent across individuals and recording locations. With current parameters, the algorithm performs best when tracking oscillations in the alpha band (8-13 Hz), with a phase-locking value of 0.77 ± 0.08. Performance was maximized when the frequency band of interest had a dominant frequency that was stable over time. The algorithm performs faster, and provides better phase-locked stimulation, compared to other recently published algorithms devised for this purpose. The algorithm is suitable for use in future studies of phase-locked tACS in preclinical and clinical applications.
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