Acoustoelectric brain imaging with different conductivities and acoustic distributions.

Objective: Acoustoelectric brain imaging (AEBI) is a promising imaging method for mapping brain biological current densities with high spatiotemporal resolution. Currently, it is still challenging to achieve human AEBI with an unclear acoustoelectric (AE) signal response of medium characteristics, particularly in conductivity and acoustic distribution. This study introduces different conductivities and acoustic distributions into the AEBI experiment, and clarifies the response interaction between medium characteristics and AEBI performance to address these key challenges. Approach: AEBI with different conductivities is explored by the imaging experiment, potential measurement, and simulation on a pig's fat, muscle, and brain tissue. AEBI with different acoustic distributions is evaluated on the imaging experiment and acoustic field measurement through a deep and surface transmitting model built on a human skullcap and pig brain tissue. Main results: The results show that conductivity is not only inversely proportional to the AE signal amplitude but also leads to a higher AEBI spatial resolution as it increases. In addition, the current source and sulcus can be located simultaneously with a strong AE signal intensity. The transcranial focal zone enlargement, pressure attenuation in the deep-transmitting model, and ultrasound echo enhancement in the surface-transmitting model cause a reduced spatial resolution, FFT-SNR, and timing correlation of AEBI. Under the comprehensive effect of conductivity and acoustics, AEBI with skull finally shows reduced imaging performance for both models compared with no-skull AEBI. On the contrary, the AE signal amplitude decreases in the deep-transmitting model and increases in the surface-transmitting model. Significance: This study reveals the response interaction between medium characteristics and AEBI performance, and makes an essential step toward developing AEBI as a practical neuroimaging technique.

Living Rat SSVEP Mapping With Acoustoelectric Brain Imaging.

OBJECTIVE: Acoustoelectric Brain Imaging (ABI) is a potential method for mapping brain electrical activity with high spatial resolution (millimeter). To resolve the key issue for eventual realization of ABI, testing that recorded acoustoelectric (AE) signal can be used to decode intrinsic brain electrical activity, the experiment of living rat SSVEP measurement with ABI is implemented. METHOD: A 1-MHz ultrasound transducer is focused on the visual cortex of anesthetized rat. With visual stimulus, the electroencephalogram and AE signal are simultaneously recorded with Pt electrode. Besides, with FUS transducer scanning at the visual cortex, corresponding AE signals at different spatial positions are decoded and imaged. RESULTS: Consistent with the directly measured SSVEP, decoded AE signal presents a clear event-related spectral perturbation (ERSP). And, decoded AE signal is of high amplitude response at the base and harmonics of the visual stimulus frequency. What's more, for timing signal, a significant positive amplitude correlation is observed between decoded AE signal and simultaneously measured SSVEP. In addition, the mean SNRs of SSVEP and decoded AE signal are both significantly higher than that of background EEG. Finally, with one fixed recording electrode, the active area with an inner diameter of 1mm is located within the 4 mm×4 mm measurement region. CONCLUSION: Experimental results demonstrate that the millimeter-level spatial resolution SSVEP measurement of living rat is achieved through ABI for the first time. SIGNIFICANCE: This study confirms that ABI should shed light on high spatiotemporal resolution neuroimaging.

Mathematical Model of Ultrasound Attenuation With Skull Thickness for Transcranial-Focused Ultrasound.

Transcranial-focused ultrasound (tFUS) has potential for both neuromodulation and neuroimaging. Due to the influence of head tissue, especially the skull, its attenuation is a key issue affecting precise focusing. The objective of the present study was to construct a mathematical model of ultrasound attenuation inclusive of skull thickness. First, combined with real skull phantom experiments and simulation experiments, tFUS attenuation of different head tissues was investigated. Furthermore, based on the system identification method, a mathematical model of ultrasound attenuation was constructed taking skull thickness into account. Finally, the performance of the mathematical model was tested, and its potential applications were investigated. For different head tissues, including scalp, skull, and brain tissue, the skull was found to be the biggest influencing factor for ultrasound attenuation, the attenuation caused by it being 4.70 times and 7.06 times that of attenuation caused by the brain and scalp, respectively. Consistent with the results of both the simulation and phantom experiments, the attenuation of the mathematical model increased as the skull thickness increased. The average error of the mathematical model was 1.87% in the phantom experiment. In addition, the experimental results show that the devised mathematical model is suitable for different initial pressures and different skulls with correlation coefficients higher than 0.99. Both simulation and phantom experiments validated the effectiveness of the proposed mathematical model. It can be concluded from this experiment that the proposed mathematical model can accurately calculate the tFUS attenuation and can significantly contribute to further research and application of tFUS.