Delay Analysis in Closed-Loop EEG Phase-Triggered Transcranial Magnetic Stimulation.

Area of Science:

• Neuroscience
• Biomedical Engineering
• Signal Processing

Background:

• Closed-loop EEG phase-triggered TMS enables adaptive neuromodulation by synchronizing stimulation to brain activity.
• System transport delay is a critical, yet often overlooked, factor affecting EEG phase prediction accuracy.

Purpose of the Study:

• To propose and validate a delay analysis framework for closed-loop EEG phase-triggered TMS systems.
• To assess the impact of system delay on the performance of EEG phase prediction algorithms.

Main Methods:

• Development of a delay analysis framework for closed-loop TMS.
• In-silico validation using real EEG data to compare common phase prediction algorithms.
• Evaluation of algorithm performance across varying system delay levels.

Main Results:

• System delay significantly influences the performance of EEG phase prediction algorithms.
• The relative performance ranking of algorithms changes depending on the level of system delay.
• Algorithm accuracy is demonstrably affected by the total system transport delay.

Conclusions:

• A delay analysis framework is essential for the robust design and validation of closed-loop TMS systems.
• Understanding and accounting for system delay is critical for optimizing adaptive neuromodulation.
• Future research should incorporate delay analysis into the development of EEG phase prediction algorithms.