From oscillatory transcranial current stimulation to scalp EEG changes: a biophysical and physiological modeling...

Area of Science:

• Neuroscience
• Computational Modeling
• Biophysics

Background:

• Assessing transcranial current stimulation (tCS) effects on EEG requires considering biophysical and neurophysiological factors.
• Existing models often lack integration of realistic head geometry and neuronal population dynamics.

Purpose of the Study:

• To develop a global computational model for simulating scalp EEG signals under tCS.
• To investigate the impact of tCS on cortical activity and subsequent EEG.
• To predict changes in EEG based on stimulation parameters.

Main Methods:

• Constructed realistic head and electrode meshes to map electric field distribution.
• Generated cortical neuronal population activity simulating 10 Hz alpha rhythms.
• Incorporated electric field effects on neuronal populations based on biophysical models.
• Simulated EEG signals using a realistic head model and forward problem solution.

Main Results:

• Simulated 10 Hz tACS significantly increased alpha power in scalp EEG compared to no stimulation.
• The alpha power increase was widespread, more pronounced on posterior electrodes, and frequency-dependent (8-12 Hz).
• Model predictions aligned with previously reported post-tACS effects in real subjects.

Conclusions:

• The integrated modeling approach successfully simulates EEG responses to tCS.
• The model can interpret and predict EEG changes based on tCS parameters.
• This approach offers a valuable tool for optimizing tCS protocols and understanding brain responses.