Synchronous function-structure brain imaging system based on acoustoelectric effect

Abstract

The invention relates to a synchronous function-structure brain imaging system based on an acoustoelectric effect. The synchronous function-structure brain imaging system comprises a transcranial ultrasonic multi-site focusing and synchronous scanning module, a nerve discharge function and brain tissue structure distribution detection module and a brain function-structure coupling module based on resistivity. Wherein the transcranial ultrasonic multi-site focusing and synchronous scanning module is used for performing multi-site ultrasonic focusing on a target brain region and implementing synchronous scanning so as to generate a nerve acoustoelectric signal based on an acoustoelectric effect; the nerve discharge function and brain tissue structure distribution detection module is used for detecting nerve acoustoelectric signals having a response relationship with original electroencephalogram and tissue resistivity, analyzing time-frequency change and amplitude-space distribution of the original electroencephalogram and mapping brain tissue structure distribution; and the resistivity-based brain function-structure coupling module is used for associating and coupling resistivity-based nerve discharge characteristics and tissue structure distribution to realize synchronous function-structure brain imaging.

Description

Technical Field

[0001] The invention relates to a synchronous function-structure brain imaging system based on acoustic-electric effect. Background Art

[0002] Neuroimaging generally refers to the technology that can directly or indirectly image the functional and structural characteristics of the nervous system (mainly the brain). According to the imaging mode, neuroimaging can be divided into functional imaging (EEG, MEG, etc.) and structural imaging (CT, MRI, etc.). Functional imaging is used to show the metabolic activity of the brain when performing certain tasks (including sensory, motor, cognitive and other functions). Structural imaging assists in the diagnosis of brain diseases by showing the structure of the brain. Synchronous detection of brain function and structure is of great significance for the efficient clinical diagnosis of neurological diseases.

[0003] Due to the difference in physical properties of detected biological signals, functional imaging and structural imaging are difficult to integrate, and multimodal imaging methods have the problem of highly matching different data types. Based on the electroacoustic effect, electroacoustic imaging can use focused ultrasound to target and change the local resistivity of the brain to achieve non-invasive high-resolution EEG detection. As a potential functional imaging method, electroacoustic imaging has a solid theoretical and experimental research foundation, and has shown important application value in the detection of biological currents such as EEG and ECG. The electroacoustic signal equation shows that the electroacoustic signal is closely related to the resistivity that affects the current density of biological tissues. Different brain tissues (such as cerebrospinal fluid, white matter, substantia nigra, etc.) have different resistivities, so the distribution of brain tissue structures can be located by detecting resistivity. Using the response relationship between electroacoustic signals and EEG and resistivity, it is expected to achieve synchronous functional-structural brain imaging by only detecting EEG signals under the electroacoustic effect. Therefore, the present invention proposes a synchronous functional-structural brain imaging system based on the electroacoustic effect, which provides technical support for direct, efficient and synchronous detection of brain functional structure. Summary of the invention

[0004] The present invention aims to utilize the direct response relationship between the acoustic-electric signal based on the acoustic-electric effect and the EEG and resistivity to analyze the original EEG characteristics and simultaneously map the resistivity distribution characteristics to achieve synchronous functional-structural brain imaging. Compared with the existing synchronous functional-structural neuroimaging methods, this system only needs to detect the scalp EEG signal under the acoustic-electric effect to directly reflect the brain nerve discharge function and structural distribution. It is expected to become a new type of synchronous functional-structural neuroimaging system. Further research and practice can achieve efficient and accurate clinical diagnosis effects and obtain considerable social and economic benefits.

[0005] A synchronous function-structure brain imaging system based on electroacoustic effect comprises a transcranial ultrasound multi-site focusing and synchronous scanning module, a neural discharge function and brain tissue structure distribution detection module, and a resistivity-based brain function-structure coupling module; wherein the transcranial ultrasound multi-site focusing and synchronous scanning module is used to perform multi-site ultrasonic focusing on the target brain area and implement synchronous scanning to generate neural electroacoustic signals based on electroacoustic effect; the neural discharge function and brain tissue structure distribution detection module is used to detect neural electroacoustic signals having a response relationship with the original electroencephalogram and tissue resistivity, analyze the time-frequency changes and amplitude-space distribution of the original electroencephalogram, and map the brain tissue structure distribution; the resistivity-based brain function-structure coupling module is used to correlate and couple the neural discharge characteristics based on resistivity with the tissue structure distribution to achieve synchronous function-structure brain imaging.

[0006] Furthermore, the transcranial ultrasound multi-site focusing and synchronous scanning module includes:

[0007] Transcranial ultrasound multi-site focusing unit: The transcranial ultrasound multi-site focusing unit includes a multi-element phased array and its transducer, which is used to simultaneously transmit focused ultrasound at multiple locations in the target brain area;

[0008] Transcranial ultrasound synchronous scanning unit: The transcranial ultrasound synchronous scanning unit is used to focus multiple sites for programmable dynamic synchronous scanning; according to the location, size, and distribution of the target brain area, the number of sites is selected and the scanning strategy is designed, and the site starting position, scanning step, scanning block, scanning order, and scanning time parameters are controlled by programming and executing scripts to achieve transcranial ultrasound scanning.

[0009] Furthermore, the transcranial ultrasound multi-site focusing unit can preset the number of sites = total number of array elements / number of single-focus array elements, select the array element spacing and emission angle parameters according to actual needs, and control the distance and angle between each site.

[0010] Furthermore, the neural discharge function and brain tissue structure distribution detection module includes:

[0011] Neural discharge function analysis unit: reconstruct the current density distribution from the measured voltage at each scanning position; obtain the analytical acoustic and electrical signals reflecting the original EEG characteristics; perform windowing and Fourier transformation on the analytical acoustic and electrical signals reflecting the original EEG characteristics to extract the frequency domain information within the time window; slide the window forward along the time axis to analyze the time-frequency variation information of each time window; calculate the power spectral density integral within a certain frequency band and map it to the corresponding spatial position to characterize its functional amplitude-space distribution;

[0012] Brain tissue structure distribution mapping unit: establish a positive correlation response relationship between the measured voltage and current density distribution at each scanning position, and obtain the mathematical relationship between the measured voltage and resistivity based on the mapping relationship between current density and resistivity; according to the specific resistivity of different structures of cranial brain tissue, the mapping relationship between the measured voltage and brain tissue structure is established through resistivity.

[0013] Furthermore, the neural discharge function analysis unit includes: reconstructing the current density distribution J from the measured voltage V(x,y,z) at each scanning position (x,y,z) i (x,y,z); extract the acoustic-electric signal s from the measured voltage V(x,y,z) at each scanning position (x,y,z) according to the ultrasonic frequency AE (x, y, z, t), take its envelope to get the analytical acoustic signal s reflecting the original EEG characteristics AE-EEG (x, y, z, t), t represents time; for s AE-EEG (x, y, z, t) is windowed and Fourier transformed to extract the frequency domain information in the time window; the window is slid forward along the time axis to analyze the time-frequency variation information of each time window; the acoustic and electrical signal s is analyzed AE-EEG (x,y,z,t) calculates the integral of the power spectral density within a certain frequency band and maps it to the corresponding spatial position to characterize its functional amplitude-space distribution.

[0014] Furthermore, the brain tissue structure distribution mapping unit includes: the measured voltage V(x, y, z) and the current density J at each scanning position (x, y, z) i (ρ, x, y, z) satisfies the following positive correlation response relationship, where N represents N lead fields J L , K represents the action coefficient:

[0015]

[0016] According to the current density J i The mapping relationship between (ρ, x, y, z) and resistivity ρ(x, y, z) is obtained from equation (2) to obtain the mathematical relationship between the measured voltage V(x, y, z) and resistivity:

[0017] |J i (ρ,x,y,z)|=1.809×10 -8 ×ρ(x,y,z) -0.3196 -8.623×10 -9 (2)

[0018]

[0019] According to the specific resistivity of brain tissues with different structures, the mapping relationship between the measured voltage and the brain tissue structure is established through the resistivity ρ(x, y, z).

[0020] Furthermore, the resistivity-based brain function-structure coupling module identifies the brain structure to which each scanning position belongs point by point according to the mapping relationship between the resistivity value output by the brain tissue structure distribution mapping unit and the cranial brain tissue structure, and associates and couples it with the neural discharge function of the corresponding position to achieve synchronous function-structure brain imaging.

[0021] Furthermore, the resistivity-based brain function-structure coupling module includes:

[0022] Structural current reconstruction resistivity unit: Based on the mapping relationship between measured voltage and resistivity established by the brain tissue structure distribution mapping unit, the reconstructed resistivity of each scanning position is obtained by analyzing the measured voltage;

[0023] Resistivity-based brain structure discrimination unit: According to the approximate relationship between the reconstructed resistivity and the reference value of the brain tissue resistivity, the brain structure to which each scanning position belongs is determined;

[0024] Brain function-structure coupling unit: maps the analytical acoustic and electrical signals to the coupled tissue structures through position coordinates to achieve synchronous functional-structural brain imaging.

[0025] Furthermore, the specific process of the structural current reconstruction resistivity unit is as follows:

[0026] According to the mapping relationship between the measured voltage and resistivity established by the brain tissue structure distribution mapping unit, the reconstructed resistivity ρ of each scanning position (x, y, z) is obtained by analyzing the measured voltage V(x, y, z) J-AE (x,y,z) and satisfy the following mathematical relationship:

[0027]

[0028] Furthermore, the specific process of the brain structure discrimination unit based on resistivity is as follows:

[0029] Calculate and reconstruct the resistivity ρ point by point J-AE The absolute value of the difference between (x,y,z) and various reference values ​​of brain tissue resistivity Δ i (x,y,z) is as follows:

[0030]

[0031] i = scalp, skull, cerebrospinal fluid, gray matter, white matter

[0032] Take Δ i The minimum value of (x,y,z) min{Δ i(x,y,z)} as the decision value, and its corresponding brain structure i is the judgment result I(x,y,z,i) of the scanning position (x,y,z).

[0033] The synchronous functional-structural brain imaging system based on the acoustic-electric effect designed by the present invention utilizes the direct response relationship between the acoustic-electric signal based on the acoustic-electric effect and the EEG and resistivity to comprehensively analyze the original EEG characteristics and simultaneously map the resistivity distribution characteristics to achieve synchronous functional-structural brain imaging. Compared with the existing synchronous functional-structural neuroimaging system, the synchronous functional-structural brain imaging system based on the acoustic-electric effect has the following advantages:

[0034] (1) Simply by detecting the scalp EEG signal under the acoustic-electric effect, the function and structural distribution of brain nerve discharge can be directly reflected.

[0035] (2) Non-invasive, highly focused transcranial focused ultrasound is used to detect EEG signals in the target brain area, with both high temporal and high spatial resolution.

[0036] (3) It is expected that a new type of synchronous functional-structural brain imaging system will be established to provide technical support for efficient and rapid clinical diagnosis and neuroscience research. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a schematic diagram of the system structure of the present invention;

[0038] Figure 2 It is a work flow chart of the present invention;

[0039] Figure 3 This is a working flow diagram of the neural discharge function and brain tissue structure distribution detection module of the present invention;

[0040] Figure 4 This is a workflow diagram of the resistivity-based brain function-structure coupling module of the present invention. DETAILED DESCRIPTION

[0041] The present invention designs a synchronous functional-structural brain imaging system based on the acoustic-electric effect. Brain imaging can detect the structural and functional changes of the living brain non-invasively or minimally invasively, and provide a reliable reference for studying the pathogenesis and diagnosis and treatment evaluation of diseases. The research and development of new technologies for synchronous functional-structural brain imaging plays a vital role in clinical disease diagnosis and neuroscience research. The acoustic-electric effect is a basic physical phenomenon of the mutual coupling of sound and electric fields, that is, ultrasound can cause changes in the local resistivity of the medium. Based on the acoustic-electric effect, focused ultrasound can be used to target and change the local resistivity of the brain to obtain high-resolution EEG information of the target brain area, and simultaneously map brain tissue structures with different resistivity distribution characteristics, which is expected to achieve synchronous functional-structural brain imaging through non-invasive detection of EEG signals under the acoustic-electric effect.

[0042] The technical process of the present invention is: using transcranial focused ultrasound scanning to detect brain areas in a directional target, and simultaneously collecting scalp EEG signals under the electroacoustic effect; preprocessing the collected EEG signals to obtain electroacoustic signals; analyzing the time-frequency-amplitude-space response of the original EEG of the target brain area from the electroacoustic signals to map its neural function changes; analyzing the resistivity characteristics of the scanned brain area tissue from the electroacoustic signals to depict its brain tissue structure distribution; correlating the functional changes and structural distribution analyzed by the coupled electroacoustic signals to achieve synchronous functional-structural brain imaging based on the electroacoustic effect.

[0043] The present invention is described below in conjunction with the accompanying drawings and embodiments.

[0044] 1. System design overall solution

[0045] The structural block diagram of the synchronous functional-structural brain imaging system based on the acoustic-electric effect is shown in Figure 1. Figure 1 As shown. The system mainly consists of a transcranial ultrasound multi-site focusing and synchronous scanning module, a neural discharge function and brain tissue structure distribution detection module, and a resistivity-based brain function-structure coupling module. Among them, the transcranial ultrasound multi-site focusing and synchronous scanning module is used to perform multi-site ultrasound focusing on the target brain area and implement synchronous scanning to generate neural acoustic-electric signals based on the acoustic-electric effect; the neural discharge function and brain tissue structure distribution detection module is used to detect neural acoustic-electric signals that have a response relationship with the original EEG and tissue resistivity, analyze the time-frequency changes and amplitude-space distribution of the original EEG, and map the distribution of brain tissue structures such as sulci, cortex, etc.; the resistivity-based brain function-structure coupling module is used to correlate and couple the neural discharge characteristics based on resistivity with the tissue structure distribution to achieve synchronous function-structure brain imaging.

[0046] The workflow of the synchronous functional-structural brain imaging system based on the acoustic-electric effect is shown in the figure below. Figure 2 As shown, the whole process can be divided into the following three steps: ① multi-site ultrasound focusing and synchronous scanning; ② detection of neural discharge function and brain tissue structure distribution; ③ correlation and coupling between neural discharge characteristics and tissue structure distribution.

[0047] 2Transcranial ultrasound multi-site focusing and synchronous scanning module

[0048] (1) Transcranial ultrasound multi-site focusing unit: The transcranial ultrasound multi-site focusing unit can be composed of a 512-element phased array and its transducer, which is used to simultaneously transmit focused ultrasound at multiple locations in the target brain area. The number of preset sites = total number of elements / number of single-focus elements. If 64 elements are selected to focus on 1 site, 8-site focusing can be achieved. It is expected that 1-8 sites can be selected, and the effective focal spot diameter is less than 1mm. Select parameters such as element spacing and emission angle according to actual needs to control the distance and angle between each site.

[0049] (2) Transcranial ultrasound synchronous scanning unit: The transcranial ultrasound synchronous scanning unit is used to focus multiple sites for programmable dynamic synchronous scanning. According to the location, size, and distribution of the target brain area, the number of sites is selected and the scanning strategy is designed. The starting position of the site, scanning step, scanning block, scanning order, scanning time and other parameters are controlled by programming and executing scripts to achieve fast, accurate, and comprehensive transcranial ultrasound scanning.

[0050] 3. Neural discharge function and brain tissue structure distribution detection module

[0051] The acoustic and electrical signals under the acoustic and electrical effect are collected by conventional EEG amplifiers AE (t), the workflow of the neural discharge function and brain tissue structure distribution detection module is as follows Figure 3 shown.

[0052] (1) Neural discharge function analysis unit: First, the current density distribution J is reconstructed from the measured voltage V(x,y,z) at each scanning position (x,y,z) i (x, y, z), which can reflect the distribution of nerve discharge amplitude in space. The acoustic-electric signal s is extracted from the measured voltage V(x, y, z) at each scanning position (x, y, z) according to the ultrasonic frequency AE (x, y, z, t), take its envelope to get the analytical acoustic signal s that can reflect the original EEG characteristics AE-EEG (x,y,z,t), t represents time. AE-EEG (x, y, z, t) is windowed and Fourier transformed to extract the frequency domain information in the time window. The window is moved forward along the time axis, and the data in each time window is processed in the same way to analyze its time-frequency variation information; AE-EEG (x,y,z,t) calculates the integral of the power spectral density within a certain frequency band and maps it to the corresponding spatial position to characterize its functional amplitude-space distribution.

[0053] (2) Brain tissue structure distribution mapping unit: measured voltage V(x,y,z) and current density J at each scanning position (x,y,z) i (ρ, x, y, z) satisfies the following positive correlation response relationship, where N represents N lead fields J L , K represents the action coefficient

[0054]

[0055] According to the current density J iThe mapping relationship between (ρ, x, y, z) and resistivity ρ(x, y, z) is obtained from equation (2), and the mathematical relationship between the measured voltage V(x, y, z) and resistivity is shown in equation (3) (the model can be found in: Yijie Zhou, Yibo Song, Xizi Song, Minpeng Xu, Feng He, Dong Ming. Synchronous mapping of neural current source and sulcus with acoustoelectric brain imaging. IEEE Transactions on Instrumentation and Measurement, 2024, 73: 4507910).

[0056] |J i (ρ,x,y,z)|=1.809×10 -8 ×ρ(x,y,z) -0.3196 -8.623×10 -9 (2)

[0057]

[0058] Different structures of brain tissue have specific resistivity, and their reference values ​​are shown in Table 1. So far, the mapping relationship between the measured voltage and the brain tissue structure is established through the resistivity ρ(x, y, z).

[0059] Table 1. Cranial tissue resistivity parameters

[0060] Brain tissue name Resistivity (Ω·m) scalp 3.215 skull 50 Cerebrospinal fluid 0.500 Gray matter 9.346 White matter 15.152

[0061] 4. Resistivity-based brain function-structure coupling module

[0062] The workflow of the resistivity-based brain function-structure coupling module is as follows Figure 4 According to the mapping relationship between the output resistivity value of the brain tissue structure distribution mapping unit and the cranial brain tissue structure, the brain structure to which each scanning position belongs is identified point by point, and it is associated and coupled with the neural discharge function of the corresponding position.

[0063] (1) Structural current reconstruction resistivity unit: According to the mapping relationship between the measured voltage and the resistivity described in the brain tissue structure distribution mapping unit (3), the reconstructed resistivity ρ at each scanning position (x, y, z) can be obtained by analyzing the measured voltage V(x, y, z) J-AE (x,y,z) and satisfy the following mathematical relationship:

[0064]

[0065] (2) Resistivity-based brain structure discrimination unit: According to the reconstructed resistivity ρ J-AE The approximate relationship between (x, y, z) and the reference value of the resistivity of the brain tissue is used to determine the brain structure to which each scanning position (x, y, z) belongs. Specific process: First, the reconstructed resistivity ρ is calculated point by point J-AE The absolute value of the difference between (x,y,z) and various reference values ​​of brain tissue resistivity Δ i (x,y,z) is as follows:

[0066]

[0067] i = scalp, skull, cerebrospinal fluid, gray matter, white matter

[0068] Then, take Δ i The minimum value of (x,y,z) min{Δ i (x,y,z)} as the decision value, and its corresponding brain structure i is the judgment result I(x,y,z,i) of the scanning position (x,y,z).

[0069] (3) Brain function-structure coupling unit: The analytical acoustic-electrical signal s is converted into AE-EEG (x, y, z, t) is mapped to the coupled associated tissue structure I(x, y, z, i) to achieve synchronous functional-structural brain imaging, and its expression is shown in formula (6).

[0070]

[0071] i = scalp, skull, cerebrospinal fluid, gray matter, white matter.

Claims

1. A synchronous function-structure brain imaging system based on acoustic-electric effect, comprising a transcranial ultrasound multi-site focusing and synchronous scanning module, a neural discharge function and brain tissue structure distribution detection module, and a brain function-structure coupling module based on resistivity; wherein, The transcranial ultrasound multi-site focusing and synchronous scanning module is used to perform multi-site ultrasound focusing on the target brain area and implement synchronous scanning to generate neural acoustic-electric signals based on the acoustic-electric effect; The neural discharge function and brain tissue structure distribution detection module is used to detect neural acoustic-electrical signals that have a response relationship with the original EEG and tissue resistivity, analyze the time-frequency changes and amplitude-space distribution of the original EEG, and map the brain tissue structure distribution; the resistivity-based brain function-structure coupling module is used to correlate and couple the neural discharge characteristics based on resistivity with the tissue structure distribution to achieve synchronous function-structure brain imaging.

2. The synchronous functional-structural brain imaging system based on the electroacoustic effect according to claim 1, characterized in that: The transcranial ultrasound multi-site focusing and synchronous scanning module includes: Transcranial ultrasound multi-site focusing unit: The transcranial ultrasound multi-site focusing unit includes a multi-element phased array and its transducer, which is used to simultaneously transmit focused ultrasound at multiple locations in the target brain area; Transcranial ultrasound synchronous scanning unit: The transcranial ultrasound synchronous scanning unit is used to focus multiple sites for programmable dynamic synchronous scanning; according to the location, size, and distribution of the target brain area, the number of sites is selected and the scanning strategy is designed, and the site starting position, scanning step, scanning block, scanning order, and scanning time parameters are controlled by programming and executing scripts to achieve transcranial ultrasound scanning.

3. The synchronous functional-structural brain imaging system based on the electroacoustic effect according to claim 2, characterized in that: The transcranial ultrasound multi-site focusing unit can preset the number of sites = total number of array elements / number of single-focus array elements, select the array element spacing and emission angle parameters according to actual needs, and control the distance and angle between each site.

4. The synchronous functional-structural brain imaging system based on the electroacoustic effect according to claim 1, characterized in that: The neural discharge function and brain tissue structure distribution detection module includes: Neural discharge function analysis unit: reconstruct the current density distribution from the measured voltage at each scanning position; obtain the analytical acoustic and electrical signals reflecting the original EEG characteristics; perform windowing and Fourier transformation on the analytical acoustic and electrical signals reflecting the original EEG characteristics to extract the frequency domain information within the time window; slide the window forward along the time axis to analyze the time-frequency variation information of each time window; calculate the power spectral density integral within a certain frequency band and map it to the corresponding spatial position to characterize its functional amplitude-space distribution; Brain tissue structure distribution mapping unit: establish a positive correlation response relationship between the measured voltage and current density distribution at each scanning position, and obtain the mathematical relationship between the measured voltage and resistivity based on the mapping relationship between current density and resistivity; according to the specific resistivity of different structures of cranial brain tissue, the mapping relationship between the measured voltage and brain tissue structure is established through resistivity.

5. The synchronous functional-structural brain imaging system based on the electroacoustic effect according to claim 4 is characterized in that: The neural discharge function analysis unit comprises: reconstructing the current density distribution J from the measured voltage V(x,y,z) at each scanning position (x,y,z) i (x,y,z); extract the acoustic-electric signal s from the measured voltage V(x,y,z) at each scanning position (x,y,z) according to the ultrasonic frequency AE (x, y, z, t), take its envelope to get the analytical acoustic signal s reflecting the original EEG characteristics AE-EEG (x, y, z, t), t represents time; for s AE-EEG (x, y, z, t) is windowed and Fourier transformed to extract the frequency domain information in the time window; the window is slid forward along the time axis to analyze the time-frequency variation information of each time window; the acoustic and electrical signal s is analyzed AE-EEG (x,y,z,t) calculates the integral of the power spectral density within a certain frequency band and maps it to the corresponding spatial position to characterize its functional amplitude-space distribution.

6. The synchronous functional-structural brain imaging system based on the electroacoustic effect according to claim 5, characterized in that: The brain tissue structure distribution mapping unit includes: the measured voltage V(x,y,z) and the current density J at each scanning position (x,y,z) i (ρ, x, y, z) satisfies the following positive correlation response relationship, where N represents N lead fields J L , K represents the action coefficient: According to the current density J i The mapping relationship between (ρ, x, y, z) and resistivity ρ(x, y, z) is obtained from equation (2) to obtain the mathematical relationship between the measured voltage V(x, y, z) and resistivity: |J i (ρ,x,y,z)|=1.809×10 -8 ×ρ(x,y,z) -0.3196 −8,623 × 10 -9 (2) According to the specific resistivity of brain tissues with different structures, the mapping relationship between the measured voltage and the brain tissue structure is established through the resistivity ρ(x, y, z).

7. The synchronous functional-structural brain imaging system based on the electroacoustic effect according to claim 1, characterized in that: The resistivity-based brain function-structure coupling module, according to the mapping relationship between the resistivity value output by the brain tissue structure distribution mapping unit and the cranial brain tissue structure, identifies the brain structure to which each scanning position belongs point by point, and associates and couples it with the neural discharge function of the corresponding position to achieve synchronous function-structure brain imaging.

8. The synchronous functional-structural brain imaging system based on the electroacoustic effect according to claim 7, characterized in that: The resistivity-based brain function-structure coupling module includes: Structural current reconstruction resistivity unit: Based on the mapping relationship between measured voltage and resistivity established by the brain tissue structure distribution mapping unit, the reconstructed resistivity of each scanning position is obtained by analyzing the measured voltage; Resistivity-based brain structure discrimination unit: According to the approximate relationship between the reconstructed resistivity and the reference value of the brain tissue resistivity, the brain structure to which each scanning position belongs is determined; Brain function-structure coupling unit: maps the analytical acoustic and electrical signals to the coupled tissue structures through position coordinates to achieve synchronous functional-structural brain imaging.

9. The synchronous functional-structural brain imaging system based on the electroacoustic effect according to claim 8, characterized in that: The specific process of the structural current reconstruction resistivity unit is as follows: According to the mapping relationship between the measured voltage and resistivity established by the brain tissue structure distribution mapping unit, the reconstructed resistivity ρ of each scanning position (x, y, z) is obtained by analyzing the measured voltage V(x, y, z) J-AE (x,y,z) and satisfy the following mathematical relationship:

10. The synchronous functional-structural brain imaging system based on the electroacoustic effect according to claim 9, characterized in that: The specific process of the brain structure discrimination unit based on resistivity is as follows: Calculate and reconstruct the resistivity ρ point by point J-AE The absolute value of the difference between (x,y,z) and various reference values ​​of brain tissue resistivity Δ i (x,y,z) is as follows: i = scalp, skull, cerebrospinal fluid, gray matter, white matter Take Δ i The minimum value of (x,y,z) min{Δ i (x,y,z)} as the decision value, and its corresponding brain structure i is the judgment result I(x,y,z,i) of the scanning position (x,y,z).

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