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Schoeters R, Tarnaud T, Martens L, Tanghe E. Simulation study on high spatio-temporal resolution acousto-electrophysiological neuroimaging. J Neural Eng 2024; 20:066039. [PMID: 38109769 DOI: 10.1088/1741-2552/ad169c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 12/18/2023] [Indexed: 12/20/2023]
Abstract
Objective.Acousto-electrophysiological neuroimaging (AENI) is a technique hypothesized to record electrophysiological activity of the brain with millimeter spatial and sub-millisecond temporal resolution. This improvement is obtained by tagging areas with focused ultrasound (fUS). Due to mechanical vibration with respect to the measuring electrodes, the electrical activity of the marked region will be modulated onto the ultrasonic frequency. The region's electrical activity can subsequently be retrieved via demodulation of the measured signal. In this study, the feasibility of this hypothesized technique is tested.Approach.This is done by calculating the forward electroencephalography response under quasi-static assumptions. The head is simplified as a set of concentric spheres. Two sizes are evaluated representing human and mouse brains. Moreover, feasibility is assessed for wet and dry transcranial, and for cortically placed electrodes. The activity sources are modeled by dipoles, with their current intensity profile drawn from a power-law power spectral density.Results.It is shown that mechanical vibration modulates the endogenous activity onto the ultrasonic frequency. The signal strength depends non-linearly on the alignment between dipole orientation, vibration direction and recording point. The strongest signal is measured when these three dependencies are perfectly aligned. The signal strengths are in the pV-range for a dipole moment of 5 nAm and ultrasonic pressures within Food and Drug Administration (FDA)-limits. The endogenous activity can then be accurately reconstructed via demodulation. Two interference types are investigated: vibrational and static. Depending on the vibrational interference, it is shown that millimeter resolution signal detection is possible also for deep brain regions. Subsequently, successful demodulation depends on the static interference, that at MHz-range has to be sub-picovolt.Significance.Our results show that mechanical vibration is a possible underlying mechanism of acousto-electrophyisological neuroimaging. This paper is a first step towards improved understanding of the conditions under which AENI is feasible.
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Affiliation(s)
- Ruben Schoeters
- Department of Information Technology (INTEC-WAVES/IMEC), Ghent University/IMEC, Technologypark 126, 9052 Zwijnaarde, Belgium
| | - Thomas Tarnaud
- Department of Information Technology (INTEC-WAVES/IMEC), Ghent University/IMEC, Technologypark 126, 9052 Zwijnaarde, Belgium
| | - Luc Martens
- Department of Information Technology (INTEC-WAVES/IMEC), Ghent University/IMEC, Technologypark 126, 9052 Zwijnaarde, Belgium
| | - Emmeric Tanghe
- Department of Information Technology (INTEC-WAVES/IMEC), Ghent University/IMEC, Technologypark 126, 9052 Zwijnaarde, Belgium
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Zhang H, Zhang Y, Wang X, Chen G, Jian X, Xu M, Ming D. Transcranial dipole localization and decoding study based on ultrasonic phased array for acoustoelectric brain imaging. J Neural Eng 2023; 20:066001. [PMID: 37918024 DOI: 10.1088/1741-2552/ad08f5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 11/02/2023] [Indexed: 11/04/2023]
Abstract
Objective. Neuroimaging is one of the effective tools to understand the functional activities of the brain, but traditional non-invasive neuroimaging techniques are difficult to combine both high temporal and spatial resolution to satisfy clinical needs. Acoustoelectric brain imaging (ABI) can combine the millimeter spatial resolution advantage of focused ultrasound with the millisecond temporal resolution advantage of electroencephalogram signals.Approach. In this study, we first explored the transcranial modulated acoustic field distribution based on ABI, and further localized and decoded single and double dipoles signals.Main results. The results show that the simulation-guided acoustic field modulation results are significantly better than those of self-focusing, which can realize precise modulation focusing of intracranial target focusing. The single dipole transcranial localization error is less than 0.4 mm and the decoding accuracy is greater than 0.93. The double dipoles transcranial localization error is less than 0.2 mm and the decoding accuracy is greater than 0.89.Significance. This study enables precise focusing of transcranial acoustic field modulation, high-precision localization of source signals and decoding of their waveforms, which provides a technical method for ABI in localizing evoked excitatory neuron areas and epileptic focus.
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Affiliation(s)
- Hao Zhang
- 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
- Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration, Tianjin 300392, People's Republic of China
| | - Yanqiu Zhang
- School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin 300070, People's Republic of China
| | - Xue Wang
- 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
| | - Guowei Chen
- 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
| | - Xiqi Jian
- School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin 300070, People's Republic of China
| | - Minpeng Xu
- 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
- Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration, Tianjin 300392, People's Republic of China
| | - Dong Ming
- 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
- Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration, Tianjin 300392, People's Republic of China
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Zhou Y, Song X, Song Y, Guo J, Han G, Liu X, He F, Ming D. Acoustoelectric brain imaging with different conductivities and acoustic distributions. Front Physiol 2023; 14:1241640. [PMID: 38028773 PMCID: PMC10644821 DOI: 10.3389/fphys.2023.1241640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 10/16/2023] [Indexed: 12/01/2023] Open
Abstract
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.
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Affiliation(s)
- Yijie Zhou
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Xizi Song
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Yibo Song
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Jiande Guo
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Gangnan Han
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Xiuyun Liu
- College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Feng He
- College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Dong Ming
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
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Song X, Huang P, Chen X, Xu M, Ming D. The frontooccipital interaction mechanism of high-frequency acoustoelectric signal. Cereb Cortex 2023; 33:10723-10735. [PMID: 37724433 DOI: 10.1093/cercor/bhad306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 07/13/2023] [Accepted: 07/15/2023] [Indexed: 09/20/2023] Open
Abstract
Based on acoustoelectric effect, acoustoelectric brain imaging has been proposed, which is a high spatiotemporal resolution neural imaging method. At the focal spot, brain electrical activity is encoded by focused ultrasound, and corresponding high-frequency acoustoelectric signal is generated. Previous studies have revealed that acoustoelectric signal can also be detected in other non-focal brain regions. However, the processing mechanism of acoustoelectric signal between different brain regions remains sparse. Here, with acoustoelectric signal generated in the left primary visual cortex, we investigated the spatial distribution characteristics and temporal propagation characteristics of acoustoelectric signal in the transmission. We observed a strongest transmission strength within the frontal lobe, and the global temporal statistics indicated that the frontal lobe features in acoustoelectric signal transmission. Then, cross-frequency phase-amplitude coupling was used to investigate the coordinated activity in the AE signal band range between frontal and occipital lobes. The results showed that intra-structural cross-frequency coupling and cross-structural coupling co-occurred between these two lobes, and, accordingly, high-frequency brain activity in the frontal lobe was effectively coordinated by distant occipital lobe. This study revealed the frontooccipital long-range interaction mechanism of acoustoelectric signal, which is the foundation of improving the performance of acoustoelectric brain imaging.
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Affiliation(s)
- Xizi Song
- Academy of Medical Engineering and Translation Medicine, Tianjin University, Tianjin 300072, China
| | - Peishan Huang
- Academy of Medical Engineering and Translation Medicine, Tianjin University, Tianjin 300072, China
| | - Xinrui Chen
- Academy of Medical Engineering and Translation Medicine, Tianjin University, Tianjin 300072, China
| | - Minpeng Xu
- Academy of Medical Engineering and Translation Medicine, Tianjin University, Tianjin 300072, China
- College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Dong Ming
- Academy of Medical Engineering and Translation Medicine, Tianjin University, Tianjin 300072, China
- College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
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Kang J, Huang C, Perkins C, Alvarez A, Kunyansky L, Witte RS, O'Donnell M. Current Source Density Imaging Using Regularized Inversion of Acoustoelectric Signals. IEEE TRANSACTIONS ON MEDICAL IMAGING 2023; 42:739-749. [PMID: 36260574 PMCID: PMC10081961 DOI: 10.1109/tmi.2022.3215748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Acoustoelectric (AE) imaging can potentially image biological currents at high spatial (~mm) and temporal (~ms) resolution. However, it does not directly map the current field distribution due to signal modulation by the acoustic field and electric lead fields. Here we present a new method for current source density (CSD) imaging. The fundamental AE equation is inverted using truncated singular value decomposition (TSVD) combined with Tikhonov regularization, where the optimal regularization parameter is found based on a modified L-curve criterion with TSVD. After deconvolution of acoustic fields, the current field can be directly reconstructed from lead field projections and the CSD image computed from the divergence of that field. A cube phantom model with a single dipole source was used for both simulation and bench-top phantom studies, where 2D AE signals generated by a 0.6 MHz 1.5D array transducer were recorded by orthogonal leads in a 3D Cartesian coordinate system. In simulations, the CSD reconstruction had significantly improved image quality and current source localization compared to AE images, and performance further improved as the fractional bandwidth (BW) increased. Similar results were obtained in the phantom with a time-varying current injected. Finally, a feasibility study using an in vivo swine heart model showed that optimally reconstructed CSD images better localized the current source than AE images over the cardiac cycle.
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Song X, Wang T, Su M, Chen X, Liu X, Ming D. An adaptive acoustoelectric signal decoding algorithm based on Fourier fitting for brain function imaging. Front Physiol 2022; 13:1054103. [PMID: 36569760 PMCID: PMC9772038 DOI: 10.3389/fphys.2022.1054103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 11/25/2022] [Indexed: 12/12/2022] Open
Abstract
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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Affiliation(s)
- Xizi Song
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Tong Wang
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Mengyue Su
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Xinrui Chen
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Xiuyun Liu
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China,Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Dong Ming
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China,Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China,*Correspondence: Dong Ming,
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Song X, Huang P, Chen X, Xu M, Ming D. The processing network of high-frequency acoustoelectric signal in the living rat brain. J Neural Eng 2022; 19:056013. [PMID: 36044882 DOI: 10.1088/1741-2552/ac8e33] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 08/31/2022] [Indexed: 11/11/2022]
Abstract
Objective.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.Approach.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.Main results.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.Significance.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.
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Affiliation(s)
- Xizi Song
- 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
| | - Peishan Huang
- 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
| | - Xinrui Chen
- 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
| | - Minpeng Xu
- 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
| | - Dong Ming
- 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
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Song X, Su X, Chen X, Xu M, Ming D. In Vivo Transcranial Acoustoelectric Brain Imaging of Different Steady-State Visual Stimulation Paradigms. IEEE Trans Neural Syst Rehabil Eng 2022; 30:2233-2241. [PMID: 35930511 DOI: 10.1109/tnsre.2022.3196828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
OBJECTIVE Based on the acoustoelectric (AE) effect, transcranial acoustoelectric brain imaging (tABI) is of potential for brain functional imaging with high temporal and spatial resolution. With nonlinear and non-steady-state, brain electrical signal is microvolt level which makes the development of tABI more difficult. This study demonstrates for the first time in vivo tABI of different steady-state visual stimulation paradigms. METHOD To obtain different brain activation maps, we designed three steady-state visual stimulation paradigms, including binocular, left eye and right eye stimulations. Then, tABI was implemented with one fixed recording electrode. And, based on decoded signal power spectrum (tABI-power) and correlation coefficient between steady-state visual evoked potential (SSVEP) and decoded signal (tABI-cc) respectively, two imaging methods were investigated. To quantitatively evaluate tABI spatial resolution performance, ECoG was implemented at the same time. Finally, we explored the performance of tABI transient imaging. RESULTS Decoded AE signal of activation region is consistent with SSVEP in both time and frequency domains, while that of the nonactivated region is noise. Besides, with transcranial measurement, tABI has a millimeter-level spatial resolution (< 3mm). Meanwhile, it can achieve millisecond-level (125ms) transient brain activity imaging. CONCLUSION Experiment results validate tABI can realize brain functional imaging under complex paradigms and is expected to develop into a brain functional imaging method with high spatiotemporal resolution.
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Zhang H, Xu M, Zhang C, He F, Song X, Chen S, Jian X, Ming D. Experimental and simulation studies of localization and decoding of single and double dipoles. J Neural Eng 2022; 19. [PMID: 35468593 DOI: 10.1088/1741-2552/ac6a12] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 04/24/2022] [Indexed: 11/11/2022]
Abstract
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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Affiliation(s)
- Hao Zhang
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, No.92 Weijin Road, Nankai District, Tianjin, Tianjin, 300072, CHINA
| | - Minpeng Xu
- Biomedical Engineering, Tianjin University, No.92 Weijin Road, Nankai District, Tianjin, Tianjin, Tianjin, 300072, CHINA
| | - Chen Zhang
- Tianjin University, No.92 Weijin Road, Nankai District, Tianjin, Tianjin, 300072, CHINA
| | - Feng He
- Tianjin University, No.92 Weijin Road, Nankai District, Tianjin, Tianjin, Tianjin, 300072, CHINA
| | - Xizi Song
- Academy of Medical Engineering and Translation Medicine, Tianjin University, No.92 Weijin Road, Nankai District, Tianjin, Tianjin, Tianjin, 300072, CHINA
| | - Shanguang Chen
- Tianjin University, No.92 Weijin Road, Nankai District, Tianjin, Tianjin, Tianjin, 300072, CHINA
| | - Xiqi Jian
- School of biomedical and engineering, Tianjin Medical University, No.22, Qixiangtai Road, Heping District, Tianjin, 300070, CHINA
| | - Dong Ming
- Department of Biomedical Engineering, Tianjin University, No.92 Weijin Road, Nankai District, Tianjin, Tianjin, 300072, CHINA
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Guo J, Song X, Chen X, Xu M, Ming D. Mathematical Model of Ultrasound Attenuation With Skull Thickness for Transcranial-Focused Ultrasound. Front Neurosci 2022; 15:778616. [PMID: 35250434 PMCID: PMC8891811 DOI: 10.3389/fnins.2021.778616] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 12/16/2021] [Indexed: 11/23/2022] Open
Abstract
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.
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Affiliation(s)
- Jiande Guo
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Xizi Song
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Xinrui Chen
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Minpeng Xu
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Dong Ming
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
- *Correspondence: Dong Ming,
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Aristovich K. Opinion: the Future of Electrical Impedance Tomography. JOURNAL OF ELECTRICAL BIOIMPEDANCE 2022; 13:1-3. [PMID: 35432659 PMCID: PMC8975587 DOI: 10.2478/joeb-2022-0001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Affiliation(s)
- Kirill Aristovich
- Dept. of Med. Phys. & Biomedical Eng., Faculty of Engineering Science, University College London, LondonUnited Kingdom
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