A research paper by scientists from Tianjin University proposed a noninvasive method for locating and decoding intracranial endogenous signals with high spatiotemporal resolution.
The research paper, published on Apr. 9, 2025 in the journal Cyborg and Bionic Systems.
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, we 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." said the author Hao Zhang, a researcher at Tianjin University.
In this paper, a numerical simulation and experimental study of USMEEG was carried out based on an ultrasonic phased array using tFUS modulated conventional EEG. Previous studies ignored the complex structure of a real skull, and the experimental scenarios mainly focused on 2-dimensional simulations and experiments, using traditional envelope algorithms in data processing with unstable localization and decoding effects. In contrast, this study innovatively explored the effects of a skull and simulated brain tissues on acoustoelectric signals based on a real skull structure, realized precise transcranial ultrasound focusing using phased-array ultrasound, and extended the simulation and experiments to 3 dimensions in order to be close to the actual scene. The pulse repetition frequency (PRF) features of acoustoelectric signals were further introduced, and a PRF sideband algorithm was developed to realize high-temporaland-spatial-resolution noninvasive transcranial source signal localization and decoding.
Research 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. "Our study provides a reliable experimental basis and technical support for high-spatiotemporal-resolution noninvasive EEG signal acquisition and precise brain–computer manipulation." said Hao Zhang.
Authors of the paper include Hao Zhang, Xue Wang, Guowei Chen, Yanqiu Zhang, Xiqi Jian, Feng He, Minpeng Xu, and Dong Ming.
This work was supported by the National Key Research and Development Program of China (Nos. 2023YFF1204305 and 2023YFE0207800), the National Natural Science Foundation of China (Nos. 81925020, 62122059, and 82402430), the China Postdoctoral Science Foundation (Grant No. 2023M742605), the Postdoctoral Fellowship Program of CPSF (Grant No. GZB 20240528), the Autonomous Project of Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration (Grant No. 24HHNJSS00014), and the Tianjin University Science and Technology Leaders and Innovative Talents Cultivation Program (Grant No. 2024XQM-0022).
The paper, "Noninvasive Intracranial Source Signal Localization and Decoding with High Spatiotemporal Resolution" was published in the journal Cyborg and Bionic Systems on Apr. 9, 2025, at DOI: 10.34133/cbsystems.0206.
