Simulation model construction method for stimulating deep brain area by electromagnetic waves

Abstract

The invention relates to the technical field of computer simulation, and provides a simulation model construction method for stimulating a deep brain area by electromagnetic waves, which comprises the following steps: constructing a brain finite element model, a semi-ellipsoid reflection structure and an electromagnetic wave emission source based on a COMSOL simulation software radio frequency module; the semi-ellipsoid reflection structure is located in the external space of the brain and comprises two semi-ellipsoid reflection surfaces with the same major semi-axis and the same minor semi-axis. The second focuses of the two semi-ellipsoid reflecting surfaces coincide in a deep brain region; the electromagnetic wave emission source comprises a lumped power supply port, a first patch antenna and a second patch antenna, wherein the first patch antenna and the second patch antenna are located at first focuses of the two semi-ellipsoid reflecting surfaces respectively. The first patch antenna and the second patch antenna respectively emit two beams of high-frequency carrier electromagnetic waves, and a preset tiny frequency difference exists between the frequencies of the two beams of high-frequency carrier electromagnetic waves. Through the method, a superficial brain region is bypassed, simulation modeling is performed on a deep brain region non-invasive electrical stimulation scheme, and model parameters are optimized.

Description

A method for constructing a simulation model of electromagnetic wave stimulation of deep brain regions Technical Field

[0001] This invention relates to the field of computer simulation technology, specifically to a method for constructing a simulation model of electromagnetic wave stimulation of deep brain regions. Background Technology

[0002] Electrical stimulation neuromodulation (ESN) is a method that uses external devices to apply electrical stimulation to the brain to regulate neural activity. It has been proven effective in pain management and in treating various brain disorders, including epilepsy and depression. Furthermore, by modulating cortical excitability, this technique can influence cognitive neural networks, potentially improving cognitive function. The basic principle of ESN is to modify the membrane potential of neurons through electrical current, thereby regulating neuronal excitability. It can be broadly classified into invasive and non-invasive methods. Non-invasive ESN is non-invasive and safe, making it more acceptable to patients than invasive methods.

[0003] Current mainstream non-invasive electrical stimulation techniques generate weak direct current or alternating current (typically 1-2 mA) by placing two or more electrodes on the scalp to modulate neural activity in brain regions. However, current methods suffer from difficulties in circumventing superficial brain regions to stimulate deeper brain regions and insufficient focus in stimulating deeper brain regions. Summary of the Invention

[0004] The technical problem to be solved by this invention is how to bypass the superficial brain regions, simulate and model non-invasive electrical stimulation schemes for deep brain regions, and optimize the model parameters.

[0005] This invention solves the above-mentioned technical problems through the following technical means: This invention provides a method for constructing a simulation model of electromagnetic wave stimulation of deep brain regions, including: constructing a finite element model of the brain, a semi-ellipsoidal reflective structure, and an electromagnetic wave emission source based on the radio frequency module of COMSOL simulation software; the semi-ellipsoidal reflective structure is located in the external space of the brain and includes two semi-ellipsoidal reflective surfaces with identical major and minor semi-axes; and the second foci of the two semi-ellipsoidal reflective surfaces coincide in the deep brain region; the electromagnetic wave emission source includes a lumped power supply port and a first patch antenna and a second patch antenna located at the first foci of the two semi-ellipsoidal reflective surfaces respectively; the first patch antenna and the second patch antenna respectively emit two high-frequency carrier electromagnetic waves, and the frequencies of the two high-frequency carrier electromagnetic waves have a preset typical frequency difference suitable for deep brain region stimulation.

[0006] Furthermore, the aforementioned finite element model of the brain is obtained through MRI scanning or by importing a standardized brain template for modeling.

[0007] Furthermore, the parameters of the finite element model of the brain include the magnetic permeability of different brain regions. Relative permittivity Electrical conductivity and electromagnetic wave angular frequency .

[0008] Furthermore, the rotation angles of the two hemispherical reflective surfaces are adjustable, and by adjusting the rotation angles, the position of the second focal point overlap in the deep brain region can be changed.

[0009] Furthermore, the major and minor axes of the two hemispherical reflective surfaces are adjustable, thereby adjusting the depth of their second focal point overlap position in the deep brain region.

[0010] Furthermore, the lumped power supply port controls the electric field strength of the two high-frequency carrier electromagnetic waves through the output voltage.

[0011] Preferably, the frequency range of the high-frequency carrier electromagnetic wave is 1GHz to 3GHz; the preset typical frequency difference range suitable for deep brain region stimulation is 70Hz to 185Hz.

[0012] Furthermore, the simulation model also includes a low-frequency electric field coupling model, including: (1) based on the parameters of the brain finite element model, the electric field modeling of the propagation of electromagnetic waves in brain tissue is performed, and the distribution of the electric field intensity E satisfies the wave equation, as follows:

[0013] The unit of electric field strength E is V / M. For gradient operators, For wave number, (1) The dielectric constant in a vacuum; (2) Based on the principle of overlapping coupling of two high-frequency electromagnetic waves in the deep brain region, a calculation model of the low-frequency electric field is constructed; Low-frequency electric field The calculation is as follows:

[0014] in, , These represent the electric field strengths of two high-frequency carrier electromagnetic waves in the deep brain region.

[0015] This invention also provides a method for optimizing the parameters of a simulation model for electromagnetic wave stimulation of deep brain regions. Based on the aforementioned simulation model, the method includes the following steps: S1, inputting initial parameters into the simulation model, performing N parameterized scans on the lumped power supply port voltage, the rotation angle of the semi-ellipsoidal reflector, and other parameters to determine the coordinate range of the target deep brain region; S2, performing parameterized scans using two high-frequency carrier electromagnetic waves respectively to obtain... There are N electric fields, where N is the number of rotation angle traversals of the semi-ellipsoidal reflector. Each set of data corresponds to the electric field propagation and distribution characteristics under different antenna positions and reflection angles. S3: Configure the core parameters of the genetic algorithm, including the initial population size, crossover probability, mutation probability, and maximum number of iterations. S4: With the optimal focusing of the stimulation region as the objective function, input the N pairs of electric field data obtained by parameterized scanning as the initial population into the genetic algorithm. Through selection, crossover, and mutation evolutionary operations, iteratively select the optimal parameter combination, including the lumped power supply port voltage and the positions of a pair of patch antennas. S5: Simulate and verify the optimal parameter combination obtained by the genetic algorithm, output the corresponding low-frequency electric field distribution, and provide a theoretical basis for the design of actual electromagnetic wave stimulation schemes.

[0016] Furthermore, the optimal focus of the stimulation region specifically means: maximizing the difference in electric field intensity between the target region and other brain regions, provided that the electric field intensity of the target region is higher than a set threshold, as expressed in the following formula:

[0017] in, This indicates the intensity of the low-frequency electric field in the target deep brain region. This represents the average electric field strength in other brain regions. The threshold is determined by the activation electric field intensity of different brain regions.

[0018] The advantages of this invention are: (1) This invention uses the COMSOL simulation software radio frequency module to simulate and construct a simulation environment including a semi-ellipsoidal reflection structure, a brain finite element model, a lumped power supply port and a high-frequency electromagnetic wave emission source. With the help of the geometric focusing characteristics of the ellipsoid, the electromagnetic waves can be accurately focused on the deep brain region. At the same time, the two high-frequency electromagnetic waves are coupled in the deep brain region to form a low-frequency electric field that can activate neurons, effectively bypassing the superficial area of ​​the brain and realizing the specific activation of neurons in the deep brain region, avoiding non-specific stimulation of the superficial brain region.

[0019] (2) This invention optimizes the parameters of the simulation model by combining parametric scanning and genetic algorithm on the basis of the constructed simulation model, thereby improving the focus of the brain stimulation area; and then simulates the optimal deep brain stimulation scheme, providing a theoretical basis for the design of actual electromagnetic wave stimulation scheme; the computer simulation method does not require a large number of physical experiments, effectively reducing research costs and shortening the research cycle.

[0020] (3) The brain finite element model of the simulation model of the present invention supports MRI scan modeling or importing standardized brain templates, and is suitable for brain region stimulation research of different individuals; the parameterized design of the simulation process makes it flexible to be applied to the stimulation needs of various deep brain regions, and has broad scientific research and clinical translation potential. Attached Figure Description

[0021] Figure 1 is a schematic diagram of the simulation structure of a simulation model construction method for electromagnetic wave stimulation of deep brain regions according to an embodiment of the present invention; Figure 2 is a schematic diagram of the parameter optimization method for a simulation model of electromagnetic wave stimulation of deep brain regions according to an embodiment of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Example 1 This example aims to construct an accurate, feasible, and well-focused simulation model of electromagnetic wave stimulation of deep brain regions, thereby verifying the feasibility and reliability of the electromagnetic wave stimulation scheme at the theoretical and simulation levels, and thus shortening the research cycle and reducing research costs. This example provides a novel method for deep brain region stimulation based on the principle of electromagnetic wave propagation and coupling, to solve the problems of traditional non-invasive electrical stimulation modulation techniques, such as difficulty in accurately stimulating deep brain regions by bypassing superficial brain regions and insufficient stimulation focus. The structure of the simulation model is shown in Figure 1, specifically including: constructing a finite element model of the brain, a semi-ellipsoidal reflection structure, and an electromagnetic wave emission source based on the radio frequency module of the COMSOL simulation software; the radio frequency function module of the COMSOL simulation software can provide the basic parameter settings and finite element calculations required for electromagnetic wave simulation, as well as some automated functions, including setting parameters such as the simulation boundary coordinate system and the virtual domain.

[0024] The semi-ellipsoidal reflective structure is located in the external space of the brain and includes two semi-ellipsoidal reflective surfaces with identical major and minor axes; the second foci of the two semi-ellipsoidal reflective surfaces coincide in a deep brain region; in this embodiment, the major axis is set to 500 mm and the minor axis is set to 400 mm; in addition, the values ​​of the major and minor axes can be adjusted according to the depth of the target brain region, thereby adjusting the depth of the region of the second foci.

[0025] The electromagnetic wave transmitter includes a lumped power supply port and a first patch antenna and a second patch antenna located at the first foci of two hemispherical reflectors, respectively. The first and second patch antennas emit two high-frequency carrier electromagnetic waves, with a predetermined small frequency difference between them. After reflection by the ellipsoidal surfaces, the electromagnetic waves emitted by the antennas theoretically converge at the second foci of the ellipsoid, which is also the location of the target deep brain region in the finite element model of the brain, thus achieving focused transmission of electromagnetic waves to the deep brain region.

[0026] The aforementioned brain finite element model is obtained through MRI scans or by importing standardized brain templates. The modeling yields finite element models of the brain containing different tissues such as gray matter, white matter, and cerebrospinal fluid. Furthermore, this modeling method also supports the direct import of standardized brain templates, enhancing the model's versatility.

[0027] The parameters of the finite element model of the brain include the magnetic permeability of different brain regions. Relative permittivity Electrical conductivity and electromagnetic wave angular frequency .

[0028] The rotation angle of the two hemispherical reflective surfaces is adjustable, and by adjusting the rotation angle, the position of the second focal point overlap in the deep brain region can be changed.

[0029] The lumped power supply port controls the electric field strength of the two high-frequency carrier electromagnetic waves by outputting voltage.

[0030] In this embodiment, the frequency of the high-frequency carrier electromagnetic wave emitted by the first patch antenna is 1.5 GHz; the frequency of the high-frequency carrier electromagnetic wave emitted by the second patch antenna is 1.5 GHz + 100 Hz. Extensive experiments with various subjects have demonstrated that the applicable frequency range for high-frequency carrier electromagnetic waves is 1 GHz to 3 GHz, and the typical effective frequency range for deep brain region stimulation is 70 to 185 Hz. Therefore, in this embodiment, the frequency difference between the two high-frequency carrier electromagnetic waves is set to 100 Hz. Since the frequencies of the two high-frequency carrier electromagnetic waves exceed the response threshold of brain neurons, they will not directly activate neurons. Therefore, they can bypass the superficial layers of the brain and serve only as carrier waves for subsequent low-frequency electric field coupling in the second focal region.

[0031] The simulation model also includes a low-frequency electric field coupling model, including: (1) Based on the parameters of the brain finite element model, the electric field model is used to model the propagation of electromagnetic waves in brain tissue. The distribution of electric field intensity E satisfies the wave equation, as follows:

[0032] The unit of electric field strength E is V / M. For gradient operators, For wave number, ρ is the dielectric constant in a vacuum; this equation comprehensively describes the propagation characteristics of electromagnetic waves in a lossy medium (brain tissue).

[0033] (2) Based on the principle of overlapping coupling of two high-frequency electromagnetic waves in the deep brain region, a calculation model of the low-frequency electric field is constructed; low-frequency electric field The calculation is as follows:

[0034] in, , These represent the electric field strengths of two high-frequency carrier electromagnetic waves in the deep brain region. Through this coupling process, the resulting low-frequency electric field can effectively activate brain neurons, thereby achieving regulation of the deep brain region.

[0035] Example 2 requires further explanation. To select the optimal stimulation scheme for the target brain region from a massive number of parameter combinations, efficient optimization is achieved through parametric scanning combined with a genetic algorithm. This example provides a simulation model parameter optimization method for electromagnetic wave stimulation of deep brain regions. Based on the simulation model described in Example 1, the specific implementation process is shown in Figure 2, including the following steps: S1. Input initial parameters, including basic parameters such as ellipsoidal geometric parameters and initial antenna position, into the simulation model. Set the scanning range for key parameters such as lumped port voltage and rotation angle of the ellipsoidal reflection structure, and accurately calibrate the three-dimensional coordinate range of the target deep brain region (e.g., the coordinate range of the thalamus region) using medical imaging; S2. Perform parametric scanning at two frequencies, 1.5 GHz and 1.5 GHz + 100 Hz, respectively, to obtain... There are N electric fields, where N is the number of rotation angle traversals of the semi-ellipsoidal reflector. Each set of data corresponds to the electric field propagation and distribution characteristics under different antenna positions and reflection angles. S3: Configure the core parameters of the genetic algorithm, including the initial population size, crossover probability, mutation probability, and maximum number of iterations. S4: With the optimal focusing of the stimulation region as the objective function, input the N pairs of electric field data obtained by parameterized scanning as the initial population into the genetic algorithm. Through selection, crossover, and mutation evolutionary operations, iteratively select the optimal parameter combination, including the lumped power supply port voltage and the positions of a pair of patch antennas. S5: Simulate and verify the optimal parameter combination obtained by the genetic algorithm, output the corresponding low-frequency electric field distribution, and provide a theoretical basis for the design of actual electromagnetic wave stimulation schemes.

[0036] The optimal focus of the stimulation region is specifically achieved by maximizing the difference in electric field intensity between the target region and other brain regions, provided that the electric field intensity of the target region is higher than a set threshold. This can be expressed as follows:

[0037] in, This indicates the intensity of the low-frequency electric field in the target deep brain region. This represents the average electric field strength in other brain regions. The threshold is determined by the activation electric field intensity of different brain regions.

[0038] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for constructing a simulation model of electromagnetic wave stimulation of deep brain regions, characterized in that, include: Based on the radio frequency module of COMSOL simulation software, a finite element model of the brain, a semi-ellipsoidal reflection structure, and an electromagnetic wave emission source were constructed. The semi-ellipsoidal reflective structure is located in the external space of the brain and includes two semi-ellipsoidal reflective surfaces with identical major and minor axes; the second foci of the two semi-ellipsoidal reflective surfaces coincide in the deep brain region; the electromagnetic wave emission source includes a lumped power supply port and a first patch antenna and a second patch antenna located at the first foci of the two semi-ellipsoidal reflective surfaces respectively; the first patch antenna and the second patch antenna respectively emit two high-frequency carrier electromagnetic waves, and the frequencies of the two high-frequency carrier electromagnetic waves have a preset typical frequency difference suitable for deep brain region stimulation.

2. The method for constructing a simulation model of electromagnetic wave stimulation of deep brain regions according to claim 1, characterized in that, The brain finite element model was obtained through MRI scans or by importing a standardized brain template.

3. The method for constructing a simulation model of electromagnetic wave stimulation of deep brain regions according to claim 2, characterized in that, The parameters of the finite element model of the brain include the magnetic permeability of different brain regions. Relative permittivity Electrical conductivity and electromagnetic wave angular frequency 。 4. The method for constructing a simulation model of electromagnetic wave stimulation of deep brain regions according to claim 1, characterized in that, The rotation angle of the two hemispherical reflective surfaces is adjustable, and by adjusting the rotation angle, the position of the second focal point overlap in the deep brain region can be changed.

5. The method for constructing a simulation model of electromagnetic wave stimulation of deep brain regions according to claim 1, characterized in that, The major and minor axes of the two hemispherical reflective surfaces are adjustable, thereby adjusting the depth of their second focal point overlap position in the deep brain region.

6. The method for constructing a simulation model of electromagnetic wave stimulation of deep brain regions according to claim 1, characterized in that, The lumped power supply port controls the electric field strength of the two high-frequency carrier electromagnetic waves by outputting voltage.

7. The method for constructing a simulation model of electromagnetic wave stimulation of deep brain regions according to claim 1, characterized in that, The frequency range of the high-frequency carrier electromagnetic wave is 1GHz to 3GHz; the preset typical frequency difference range suitable for deep brain region stimulation is 70Hz to 185Hz.

8. The method for constructing a simulation model of electromagnetic wave stimulation of deep brain regions according to claim 3, characterized in that, The simulation model also includes a low-frequency electric field coupling model, including: (1) Based on the parameters of the brain finite element model, the electric field model is used to model the propagation of electromagnetic waves in brain tissue. The distribution of electric field intensity E satisfies the wave equation, as follows: The unit of electric field strength E is V / M. For gradient operators, For wave number, (1) The dielectric constant in a vacuum; (2) Based on the principle of overlapping coupling of two high-frequency electromagnetic waves in the deep brain region, a calculation model of the low-frequency electric field is constructed; Low-frequency electric field The calculation is as follows: in, 、 These represent the electric field strengths of two high-frequency carrier electromagnetic waves in the deep brain region.

9. A method for optimizing parameters of a simulation model of electromagnetic wave stimulation of deep brain regions, characterized in that, Based on the simulation model described in claims 1-8, the method includes the following steps: S1, inputting initial parameters into the simulation model, performing N parametric scans on the lumped power supply port voltage, the rotation angle of the semi-ellipsoidal reflector, and clarifying the coordinate range of the target deep brain region; S2, performing parametric scans using two high-frequency carrier electromagnetic waves respectively, to obtain... There are N electric fields, where N is the number of rotation angle traversals of the semi-ellipsoidal reflector. Each set of data corresponds to the electric field propagation and distribution characteristics under different antenna positions and reflection angles. S3: Configure the core parameters of the genetic algorithm, including the initial population size, crossover probability, mutation probability, and maximum number of iterations. S4: With the optimal focusing of the stimulation region as the objective function, input the N pairs of electric field data obtained by parameterized scanning as the initial population into the genetic algorithm. Through selection, crossover, and mutation evolutionary operations, iteratively select the optimal parameter combination, including the lumped power supply port voltage and the positions of a pair of patch antennas. S5: Simulate and verify the optimal parameter combination obtained by the genetic algorithm, output the corresponding low-frequency electric field distribution, and provide a theoretical basis for the design of actual electromagnetic wave stimulation schemes.

10. The method for optimizing the parameters of a simulation model of electromagnetic wave stimulation of deep brain regions according to claim 9, characterized in that, The optimal focus of the stimulation region is specifically achieved by maximizing the difference in electric field intensity between the target region and other brain regions, provided that the electric field intensity of the target region is higher than a set threshold. This can be expressed as follows: in, This indicates the intensity of the low-frequency electric field in the target deep brain region. This represents the average electric field strength in other brain regions. The threshold is determined by the activation electric field intensity of different brain regions.

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