Song Xizi, Huang Peishan, Chen Xinrui, Xu Minpeng, Ming Dong
Academy of Medical Engineering and Translational Medicine, Tianjin International Joint Research Centre for Neural Engineering, and Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, People's Republic of China.
Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, People's Republic of China.
J Neural Eng. 2022 Sep 9;19(5). doi: 10.1088/1741-2552/ac8e33.
Acoustoelectric brain imaging (ABI) is a potential noninvasive electrophysiological neuroimaging method with high spatiotemporal resolution. At the focal spot of the focused ultrasound, with the couple of acoustic and electric fields, high-frequency acoustoelectric (HF AE) signal is generated. Because the brain is a volume conductor, HF AE signal can be detected in other brain cortex. The processing of HF AE signal is critical for improving decoding precision, further improving the spatial resolution performance of ABI. This study investigates the processing network of HF AE signal in the living rat brain.When HF AE generated on the left primary visual cortex (V1-L), low-frequency (LF) electroencephalography and HF AE signals on different cortex were recorded at the same time. Firstly, AE signal on different sides of the brain cortex were compared, including prefrontal cortex (FrA) and primary somatosensory cortex (S1FL). Then, we constructed and analyzed functional networks of two signals.In the same cortex, HF AE signal on the right side had stronger intensity. And compared with LF networks, HF AE network had larger global efficiency and shorter characteristic path length, denoting the stronger processing and transmission of AE signal. Additionally, in HF AE network, the node had significantly increased local properties and the connection were concentrated in the occipital lobe, reflecting the occipital lobe plays an important role in the processing.Experiment results demonstrate that, compared with LF network, HF AE network is more efficient and had stronger transmission capabilities. And the connection of HF AE network is concentrated in the occipital lobe. This work preliminarily reveals the HF AE signal processing, which is significant for improving the ABI quality and provides a new insight for understanding the brain HF signal.
声电脑成像（ABI）是一种具有高时空分辨率的潜在无创电生理神经成像方法。在聚焦超声的焦点处，伴随着声场和电场的耦合，会产生高频声电（HF AE）信号。由于大脑是一个容积导体，在其他脑皮质中可以检测到HF AE信号。HF AE信号的处理对于提高解码精度、进一步提升ABI的空间分辨率性能至关重要。本研究调查了活体大鼠脑中HF AE信号的处理网络。当在左侧初级视觉皮层（V1-L）产生HF AE时，同时记录不同皮层上的低频（LF）脑电图和HF AE信号。首先，比较大脑皮层不同侧的AE信号，包括前额叶皮层（FrA）和初级体感皮层（S1FL）。然后，构建并分析两种信号的功能网络。在同一皮层中，右侧的HF AE信号强度更强。与LF网络相比，HF AE网络具有更高的全局效率和更短的特征路径长度，表明AE信号具有更强的处理和传输能力。此外，在HF AE网络中，节点的局部属性显著增加，连接集中在枕叶，这反映出枕叶在处理过程中起重要作用。实验结果表明，与LF网络相比，HF AE网络更高效且具有更强的传输能力。并且HF AE网络的连接集中在枕叶。这项工作初步揭示了HF AE信号的处理过程，这对于提高ABI质量具有重要意义，并为理解脑HF信号提供了新的视角。
