Coding Biological Current Source With Pulsed Ultrasound for Acoustoelectric Brain Imaging: Application to Vivo Rat Brain

Zhou, Yijie; Song, Xizi; Wang, Zhongpeng; Zhao, Xue; Chen, Xinrui; Ming, Dong

doi:10.1109/access.2020.2972589

Cited by 13 publications

(12 citation statements)

References 25 publications

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“…This encoding mechanism was further validated in vivo rat experiments with different PRFs including 500 Hz, 1 kHz, and 2 kHz. Both the AE signal envelope and the decoded AE signal showed a significant correlation with low-frequency EEG (Zhou et al, 2020b ). Next, Zhou evaluated and validated multi-source ABI with different current source functions.…”

Section: Research Progressmentioning

confidence: 99%

Biological current source imaging method based on acoustoelectric effect: A systematic review

Zhang

Liu

et al. 2022

Front. Neurosci.

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Neuroimaging can help reveal the spatial and temporal diversity of neural activity, which is of utmost importance for understanding the brain. However, conventional non-invasive neuroimaging methods do not have the advantage of high temporal and spatial resolution, which greatly hinders clinical and basic research. The acoustoelectric (AE) effect is a fundamental physical phenomenon based on the change of dielectric conductivity that has recently received much attention in the field of biomedical imaging. Based on the AE effect, a new imaging method for the biological current source has been proposed, combining the advantages of high temporal resolution of electrical measurements and high spatial resolution of focused ultrasound. This paper first describes the mechanism of the AE effect and the principle of the current source imaging method based on the AE effect. The second part summarizes the research progress of this current source imaging method in brain neurons, guided brain therapy, and heart. Finally, we discuss the problems and future directions of this biological current source imaging method. This review explores the relevant research literature and provides an informative reference for this potential non-invasive neuroimaging method.

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Section: Research Progressmentioning

confidence: 99%

Biological current source imaging method based on acoustoelectric effect: A systematic review

Zhang

Liu

et al. 2022

Front. Neurosci.

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“…In the research of ABI, the Decoding Algorithm with Envelope is frequently utilized (Qin et al, 2012;Qin et al, 2015;Berthon et al, 2017;Preston et al, 2018;Berthon et al, 2019;Zhou et al, 2020;Zhou et al, 2021). The theory (Zhou et al, 2019) stipulates that the AE signal is first converted into an analytical signal.…”

Section: Decoding Algorithm With Envelopementioning

confidence: 99%

“…The basic work of early AE imaging decoded with envelope algorithm (Song et al, 2019;Zhou et al, 2019). Zhou et al, in 2020, conducted the first multi-source acoustoelectric imaging experiment (Zhou et al, 2020), which adopted algorithm based on the envelope function to decode the AE signal. For the first time, ABI decoded the Steady state visual evoked signal in the brain of a living mouse and also exploited the envelope algorithm to decode the AE signal (Song et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

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An adaptive acoustoelectric signal decoding algorithm based on Fourier fitting for brain function imaging

Song

Wang

et al. 2022

Front. Physiol.

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Acousticelectric brain imaging (ABI), which is based on the acoustoelectric (AE) effect, is a potential brain function imaging method for mapping brain electrical activity with high temporal and spatial resolution. To further enhance the quality of the decoded signal and the resolution of the ABI, the decoding accuracy of the AE signal is essential. An adaptive decoding algorithm based on Fourier fitting (aDAF) is suggested to increase the AE signal decoding precision. The envelope of the AE signal is first split into a number of harmonics by Fourier fitting in the suggested aDAF. The least square method is then utilized to adaptively select the greatest harmonic component. Several phantom experiments are implemented to assess the performance of the aDAF, including 1-source with various frequencies, multiple-source with various frequencies and amplitudes, and multiple-source with various distributions. Imaging resolution and decoded signal quality are quantitatively evaluated. According to the results of the decoding experiments, the decoded signal amplitude accuracy has risen by 11.39% when compared to the decoding algorithm with envelope (DAE). The correlation coefficient between the source signal and the decoded timing signal of aDAF is, on average, 34.76% better than it was for DAE. Finally, the results of the imaging experiment show that aDAF has superior imaging quality than DAE, with signal-to noise ratio (SNR) improved by 23.32% and spatial resolution increased by 50%. According to the experiments, the proposed aDAF increased AE signal decoding accuracy, which is vital for future research and applications related to ABI.

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“…Immediately following, Barragan et al used an ex vivo human skull to localize time-varying monopoles and dipoles (two platinum electrodes spaced 10 mm apart) that simulate epileptic discharges at depths greater than 60 mm with a spatial resolution of 1-4 mm [16]. In the same year, Song et al demonstrated the source signal modulation mechanism of pulse repetition frequency (PRF) of FUS by saline and rat brain experiments [17], and the results showed that decoding EEG signals from the modulated AE signals is feasible [18]. In addition, the feasibility of AE effect-based localization of physiological discharge sources in living organisms such as the heart of living rabbits [19,20] and the brain of living rats [21] has been verified in previous studies.…”

Section: Introductionmentioning

confidence: 99%

Experimental and simulation studies of localization and decoding of single and double dipoles

Zhang¹,

Xu²,

Zhang³

et al. 2022

J. Neural Eng.

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Electroencephalography (EEG) is a technique for measuring normal or abnormal neuronal activity in the human brain, but its low spatial resolution makes it difficult to locate the precise locations of neurons due to the volume conduction effect of brain tissue. The acoustoelectric (AE) effect has the advantage of detecting electrical signals with high temporal resolution and focused ultrasound with high spatial resolution. In this paper, we use dipoles to simulate real single and double neurons, and further investigate the localization and decoding of single and double dipoles based on AE effects from numerical simulations, brain tissue phantom experiments, and fresh porcine brain tissue experiments. The results show that the localization error of a single dipole is less than 0.3 mm, the decoding signal is highly correlated with the source signal, and the decoding accuracy is greater than 0.94; the location of double dipoles with an interval of 0.4 mm or more can be localized, the localization error tends to increase as the interval of dipoles decreases, and the decoding accuracy tends to decrease as the frequency of dipoles decreases. This study localizes and decodes dipole signals with high accuracy, and provides a technical method for the development of EEG.

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Coding Biological Current Source With Pulsed Ultrasound for Acoustoelectric Brain Imaging: Application to Vivo Rat Brain

Cited by 13 publications

References 25 publications

Biological current source imaging method based on acoustoelectric effect: A systematic review

Biological current source imaging method based on acoustoelectric effect: A systematic review

An adaptive acoustoelectric signal decoding algorithm based on Fourier fitting for brain function imaging

Experimental and simulation studies of localization and decoding of single and double dipoles

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