Optimal use of EEG recordings to target active brain areas with transcranial electrical stimulation

NeuroImage

Laurent Koessler¹  Anthony M. Norcia²  Lucas C. Parra³  Jacek P. Dmochowski⁴  Marom Bikson⁵ 

[1] Corresponding author.;CNRS - University of Lorraine, France;City College of New York, USA;Department of Biomedical Engineering, Steinman Hall 460 City College of New York, New York, NY 10031, USA;Stanford University, USA;

关键词: EEG;    Transcranial direct current stimulation;    Transcranial electrical stimulation;    Reciprocity;    Closed-loop stimulation;    Source localization;   

DOI  :  

来源: DOAJ

【 摘 要 】

To demonstrate causal relationships between brain and behavior, investigators would like to guide brain stimulation using measurements of neural activity. Particularly promising in this context are electroencephalography (EEG) and transcranial electrical stimulation (TES), as they are linked by a reciprocity principle which, despite being known for decades, has not led to a formalism for relating EEG recordings to optimal stimulation parameters. Here we derive a closed-form expression for the TES configuration that optimally stimulates (i.e., targets) the sources of recorded EEG, without making assumptions about source location or distribution. We also derive a duality between TES targeting and EEG source localization, and demonstrate that in cases where source localization fails, so does the proposed targeting. Numerical simulations with multiple head models confirm these theoretical predictions and quantify the achieved stimulation in terms of focality and intensity. We show that constraining the stimulation currents automatically selects optimal montages that involve only a few (4−7) electrodes, with only incremental loss in performance when targeting focal activations. The proposed technique allows brain scientists and clinicians to rationally target the sources of observed EEG and thus overcomes a major obstacle to the realization of individualized or closed-loop brain stimulation.

【 授权许可】

Unknown