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A Fast EEG Forecasting Algorithm for Phase-Locked Transcranial Electrical Stimulation of the Human Brain
by
Giacobbe, Peter
, Zariffa, José
, Downar, Jonathan
, Mansouri, Farrokh
, Dunlop, Katharine
in
Algorithms
/ Brain research
/ brain stimulation
/ closed-loop stimulation
/ EEG
/ EEG forecasting
/ Electrical stimuli
/ Electrodes
/ Electroencephalography
/ Frequency dependence
/ Health care networks
/ Mental disorders
/ Neuroscience
/ Oscillations
/ phase-locking
/ tACS
/ Therapeutic applications
2017
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A Fast EEG Forecasting Algorithm for Phase-Locked Transcranial Electrical Stimulation of the Human Brain
by
Giacobbe, Peter
, Zariffa, José
, Downar, Jonathan
, Mansouri, Farrokh
, Dunlop, Katharine
in
Algorithms
/ Brain research
/ brain stimulation
/ closed-loop stimulation
/ EEG
/ EEG forecasting
/ Electrical stimuli
/ Electrodes
/ Electroencephalography
/ Frequency dependence
/ Health care networks
/ Mental disorders
/ Neuroscience
/ Oscillations
/ phase-locking
/ tACS
/ Therapeutic applications
2017
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Do you wish to request the book?
A Fast EEG Forecasting Algorithm for Phase-Locked Transcranial Electrical Stimulation of the Human Brain
by
Giacobbe, Peter
, Zariffa, José
, Downar, Jonathan
, Mansouri, Farrokh
, Dunlop, Katharine
in
Algorithms
/ Brain research
/ brain stimulation
/ closed-loop stimulation
/ EEG
/ EEG forecasting
/ Electrical stimuli
/ Electrodes
/ Electroencephalography
/ Frequency dependence
/ Health care networks
/ Mental disorders
/ Neuroscience
/ Oscillations
/ phase-locking
/ tACS
/ Therapeutic applications
2017
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A Fast EEG Forecasting Algorithm for Phase-Locked Transcranial Electrical Stimulation of the Human Brain
Journal Article
A Fast EEG Forecasting Algorithm for Phase-Locked Transcranial Electrical Stimulation of the Human Brain
2017
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Overview
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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