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Updated: May 15, 2025

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
Published on: June 30, 2018
Noninvasive Intracranial Source Signal Localization and Decoding with High Spatiotemporal Resolution
Hao Zhang1,2, Xue Wang1, Guowei Chen1
1Academy of Medical Engineering and Translational Medicine, State Key Laboratory of Advanced Medical Materials and Devices, Tianjin International Joint Research Centre for Neural Engineering, and Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin, China.
Abstract:
High spatiotemporal resolution of noninvasive electroencephalography (EEG) signals is an important prerequisite for fine brain-computer manipulation. However, conventional scalp EEG has a low spatial resolution due to the volume conductor effect, making it difficult to accurately identify the intent of brain-computer manipulation. In recent years, transcranial focused ultrasound modulated EEG technology has increasingly become a research hotspot, which is expected to acquire noninvasive acoustoelectric coupling signals with a high spatial and temporal resolution. In view of this, this study established a transcranial focused ultrasound numerical simulation model and experimental platform based on a real brain model and a 128-array phased array, further constructed a 3-dimensional transcranial multisource dipole localization and decoding numerical simulation model and experimental platform based on the acoustic field platform, and developed a high-precision localization and decoding algorithm. The results show that the simulation-guided phased-array acoustic field experimental platform can achieve accurate focusing in both pure water and transcranial conditions within a safe threshold, with a modulation range of 10 mm, and the focal acoustic pressure can be enhanced by more than 200% compared with that of transducer self-focusing. In terms of dipole localization decoding results, the proposed algorithm in this study has a localization signal-to-noise ratio of 24.18 dB, which is 50.59% higher than that of the traditional algorithm, and the source signal decoding accuracy is greater than 0.85. This study provides a reliable experimental basis and technical support for high-spatiotemporal-resolution noninvasive EEG signal acquisition and precise brain-computer manipulation.

