Exploration of SSVEP Classification Performance Based on Acousto-Electric Brain Imaging

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Abstract
Brain imaging technologies can reveal the neural basis behind thoughts, emotions, and behaviors. Acousto-electric brain imaging is an emerging neuroimaging technique with high spatiotemporal resolution. This study designed and implemented multi-frequency steady-state visual evoked stimuli in rats to explore the classification performance of acousto-electric imaging. Canonical correlation analysis was used to classify the signals, and results were compared with traditional scalp electroencephalography (EEG) methods. The findings indicate that acousto-electric brain imaging is less affected by electrode placement (n.s.) compared to traditional EEG(*). However, the classification performance of ABI signals still lags behind traditional EEG when averaging trials and placing electrode optimally(****).
Funding Information
  • National Natural Science Foundation of China (62276183)