A high robustness decoding technique for ultrasound modulated electroencephalogram

Ultrasound-modulated electroencephalography (USMEEG) has become a vital tool in neuroscience because it integrates millimeter-level spatial resolution with millisecond-level temporal resolution. However, under extremely complex scenarios, excessively strong or weak acoustoelectric signal coupling leads to severe distortion in USMEEG decoded signals. To address this, we developed a highly robust decoding algorithm based on the ultrasound pulse repetition frequency and introduced the acoustoelectric modulation ratio (AMR) to quantify different modulation scenarios. Across numerical simulations, phantoms, and validation using human steady-state visual evoked potential signals with data-level acoustoelectric coupling across 10 volunteers, the focused ultrasound phased array achieved an encoding spatial resolution of 0.79 millimeters. The proposed algorithm significantly outperformed four traditional methods, exhibiting higher precision under weak modulation (0 < AMR ≤ 0.6), moderate modulation (0.6 < AMR ≤ 1), and over modulation (AMR > 1) conditions, with average decoding correlations reaching 0.84, 0.90, and 0.89. This highly robust technique expands USMEEG applications and provides a technical foundation for high-performance noninvasive brain-computer interfaces.