A method and system for evaluating GnRH neuron distribution patterns based on electrode arrays

Abstract

The present invention discloses a method and system for assessing the distribution pattern of GnRH neurons based on an electrode array. The electrode array collects electrical signals from the GnRH neuron region under the effects of a first induction drug and a second induction drug, respectively. The excitation rate corresponding to the first induction drug is calculated based on the discharge rate under the effect of the first induction drug, and the excitation rate corresponding to the second induction drug is calculated based on the discharge rate under the effect of the second induction drug. The excitation rates are used to identify GnRH neurons and regions. The electrode array has M rows and N columns, with the length of the electrode wires decreasing toward the center column, where M is a positive integer and N is a positive integer or a positive even number. The present invention can accurately assess the distribution pattern of GnRH neurons.

Description

Technical Field

[0001] The present invention relates to the field of biomedicine, and in particular to a method and system for evaluating the distribution pattern of GnRH neurons based on an electrode array. Background Art

[0002] GnRH neurons, also known as gonadotropin-releasing hormone (GnRH) neurons, are located in the hypothalamus of the brain. GnRH neurons are distributed from the rostral preoptic area to the caudal hypothalamus. GnRH neurons secrete GnRH, which is crucial for female reproductive activity and ovulation. Studying the secretion and mechanism of GnRH action can provide a better understanding of the causes of reproductive disorders such as infertility, hypogonadism, and polycystic ovary syndrome (PCOS), and can also aid in the diagnosis and treatment of conditions such as delayed puberty and precocious puberty. Studies have shown that GnRH neurons have a variety of firing patterns, including bursts, sustained activity, and silence. The firing patterns of GnRH neurons vary across the circadian cycle and in different regions, but their specific distribution patterns are unclear. Given their extremely dispersed and sparse distribution, accurately assessing their distribution patterns is crucial for GnRH research. Summary of the Invention

[0003] The purpose of the present invention is to provide a GnRH neuron distribution pattern evaluation method and system based on an electrode array, so as to accurately evaluate the GnRH neuron distribution pattern and the discharge pattern under different distribution patterns.

[0004] In order to achieve the above objectives, the present invention is implemented through the following technical solutions:

[0005] A method for evaluating the distribution pattern of GnRH neurons based on an electrode array comprises: collecting electrical signals of a GnRH neuron region under the action of a first induction drug and a second induction drug respectively through an electrode array, calculating the excitation rate corresponding to the first induction drug based on the discharge rate under the action of the first induction drug, calculating the excitation rate corresponding to the second induction drug based on the discharge rate under the action of the second induction drug, and determining the GnRH neurons and regions using the excitation rates; wherein the electrode array has M rows and N columns, and the length of the electrode wire is shorter the closer to the middle column, M is a positive integer, and N is a positive integer or a positive even number.

[0006] Optionally, the method further includes: collecting electrical signals of GnRH neurons at different stages through the electrode array, processing the electrical signals, and drawing activity distribution diagrams of GnRH neurons at different stages based on the processed electrical signals.

[0007] Optionally, the excitation rate corresponding to the first induction drug is calculated as follows:

[0008]

[0009] The calculation method of the excitation rate corresponding to the second induction drug is:

[0010]

[0011] Wherein, FR1 represents the discharge frequency of the electrode in the first preset time period under the action of the first induction drug, and FR2 represents the discharge frequency of the electrode in the first preset time period under the action of the second induction drug. It represents the discharge frequency of the electrode in a second preset time period without the effect of the inducing drug, and the length of the second preset time period is greater than the first preset time period.

[0012] Optionally, the step of determining the GnRH neurons and regions using the excitation rate includes:

[0013] The relative difference between the excitation rate corresponding to the first induction drug and the excitation rate corresponding to the second induction drug is calculated. If the difference is greater than a threshold, the electrode location is identified as the area of ​​the GnRH neuron.

[0014] Optionally, the discharge frequency of the electrode is obtained by calculating the ratio of the number of times the voltage signal collected by the electrode is greater than a set value within a preset time period to the preset time period.

[0015] Optionally, the electrical signal values ​​collected by all electrodes at the same time are placed into a matrix according to the position distribution of the electrodes, and the electrical signal value collected by each electrode is placed into a set corresponding to the electrode, the matrix is ​​split into two sub-matrices with M rows and N / 2 columns from the middle of the matrix, the two sub-matrices are smoothed separately and then merged into a matrix with M rows and N columns, and then each set is smoothed; wherein N is a positive even number;

[0016] Determine the difference between the signal value of the same electrical signal value after matrix smoothing and the signal value after set smoothing. If the difference is greater than a preset value, perform a convolution operation on the electrical signal value in the matrix of the originally collected electrical signal values ​​using a 3D convolution kernel, and use the convolution result as the new value of the electrical signal value; if the difference is not greater than the preset value, use the average of the signal value in the matrix and the signal value in the set as the new value of the electrical signal value.

[0017] Optionally, the step of drawing a distribution diagram of GnRH neuron activities at different stages based on the processed electrical signals includes:

[0018] Each stage is divided into multiple time slices, and the changes in the excitation rate and the average voltage signal of the electrodes in each time slice are obtained;

[0019] Select the stage to be displayed and the content to be observed, wherein the content to be observed is the excitation rate or the average value of the voltage signal;

[0020] Determining to display a GnRH neuron activity graph according to the selection result, the GnRH neuron activity graph dynamically displays changes in the excitation rate or voltage signal in a stage;

[0021] Alternatively, each stage is divided into multiple time slices, and the change in the excitation rate and the change in the average voltage signal in one stage are obtained based on the excitation rate and the average voltage signal corresponding to the electrode in each time slice;

[0022] The activity of the GnRH neurons in each time slice is calculated based on the excitation rate and the average value of the voltage signal, thereby obtaining the change in the activity of the GnRH neurons in each stage;

[0023] The dynamic graph shows the changes in the activity of GnRH neurons at each stage;

[0024] Among them, the activity status of the GnRH neurons in each time slice is obtained based on the excitation rate and the average value of the voltage signal as follows: the excitation rate and the average value of the voltage signal are normalized, the weighted result of the normalized excitation rate and the average value of the voltage signal is calculated, and the weighted result is used as the activity status.

[0025] In another aspect, the present invention further provides a GnRH neuron distribution pattern assessment system based on an electrode array, comprising:

[0026] An electrode array having M rows and N columns, wherein the electrode wires are shorter toward the middle column, M being a positive integer, and N being a positive integer or a positive even number; the electrode array is used to respectively collect electrical signals from a GnRH neuron region under the action of a first induction drug and a second induction drug;

[0027] The data processing device comprises:

[0028] The GnRH neuron determination module is used to calculate the excitation rate corresponding to the first induction drug based on the discharge rate under the action of the first induction drug, calculate the excitation rate corresponding to the second induction drug based on the discharge rate under the action of the second induction drug, and use the excitation rate to determine the GnRH neurons and areas.

[0029] Optionally, the data processing device further comprises: a distribution pattern evaluation module, configured to collect electrical signals of GnRH neurons at different stages through the electrode array, process the electrical signals, and draw activity distribution diagrams of GnRH neurons at different stages based on the processed electrical signals;

[0030] The display device is used to display the activity distribution diagram.

[0031] In other aspects, the present invention further provides a readable storage medium, wherein the readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described above is implemented.

[0032] The present invention has at least the following technical effects:

[0033] In response to the situation where the electrode array and the GnRH neuron distribution area do not completely match when using an electrode array to evaluate the GnRH neuron distribution pattern, the present invention improves the electrode array and uses electrode wires of different lengths to better cover the range of brain areas. When evaluating the distribution of GnRH neurons, the area of ​​the GnRH neurons is first determined, that is, the GnRH neurons are determined based on the GnRH neuron discharge frequency under the first induction drug and the second induction drug. Then, relevant information about the GnRH neurons is collected at different stages to obtain the GnRH neuron pattern at different stages. The pattern is displayed in the form of a dynamic graph, achieving accurate evaluation of the GnRH neuron distribution pattern and the discharge pattern under different distribution patterns. In addition, the data processing process is improved according to the arrangement of the electrode array to reduce noise caused by movement and the like. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 A flowchart of a method for evaluating the distribution pattern of GnRH neurons based on an electrode array according to one embodiment of the present invention;

[0035] Figure 2 Schematic diagram of the hypothalamus region; the red circle is the distribution of the rPOA brain region where the GnRH neuron cell bodies are located.

[0036] Figure 3 The fluorescence-verified GnRH neuronal distribution and co-labeling with related viral expression provided in one embodiment of the present invention;

[0037] Figure 4 A schematic diagram of an improved electrode array provided in one embodiment of the present invention;

[0038] Figure 5 A schematic diagram of the connection of electrodes of the improved electrode array in the rPOA region provided by one embodiment of the present invention;

[0039] Figure 6A schematic diagram of the coverage of the electrodes of the improved electrode array in the rPOA region provided by one embodiment of the present invention;

[0040] Figure 7 This is a structural block diagram of a GnRH neuron distribution pattern evaluation system based on an electrode array provided in one embodiment of the present invention. DETAILED DESCRIPTION

[0041] The following is a further detailed description of a method and system for evaluating the distribution pattern of GnRH neurons based on an electrode array proposed by the present invention, in conjunction with the accompanying drawings and specific embodiments. According to the following description, the advantages and features of the present invention will become clearer. It should be noted that the drawings are in a very simplified form and use non-precise proportions, which are only used to conveniently and clearly assist in explaining the purpose of the embodiments of the present invention. In order to make the purposes, features and advantages of the present invention more obvious and easy to understand, please refer to the accompanying drawings. It should be noted that the structures, proportions, sizes, etc. illustrated in the drawings of this specification are only used to match the contents disclosed in the specification, so that people familiar with this technology can understand and read them, and are not used to limit the conditions for the implementation of the present invention, so they have no technical significance. Any modification of the structure, change in the proportional relationship or adjustment of the size should still fall within the scope of the technical content disclosed by the present invention without affecting the efficacy and purpose that can be achieved by the present invention.

[0042] As described in the background art, the specific distribution pattern of GnRH neurons is not clear. Since the discharge patterns of GnRH neurons in vivo and in vitro are different, previous studies were all in vitro studies, and there are currently no in vivo studies.

[0043] However, in vitro studies have the following defects: 1. In vitro studies destroy the morphological structure of GnRH neurons and the connection between them and upstream and downstream neurons, making it impossible to accurately evaluate the specific distribution pattern of the current GnRH neurons. 2. In addition, due to the special morphology of the distribution of GnRH neurons and their sparse and dispersed distribution, it is also very difficult to evaluate the specific distribution pattern of GnRH neurons.

[0044] In view of this, in order to accurately record the GnRH neurons in the body and evaluate their distribution and discharge patterns, the present invention designs an electrode array that conforms to the distribution morphology of GnRH neuron cell bodies in the rPOA brain region, thereby accurately evaluating the distribution and discharge patterns of GnRH neurons based on this electrode array.

[0045] like Figure 1 As shown, in order to understand the distribution of GnRH in the rostral preoptic area (rPOA) and its pattern under different conditions, this embodiment provides a method for evaluating the distribution pattern of GnRH neurons based on an electrode array, the method comprising the following steps:

[0046] S1: The electrical signals of the GnRH neuron area under the action of the first induction drug and the second induction drug are respectively collected through the electrode array, the excitation rate corresponding to the first induction drug is calculated based on the discharge rate under the action of the first induction drug, and the excitation rate corresponding to the second induction drug is calculated based on the discharge rate under the action of the second induction drug, and the GnRH neurons and areas are determined using the excitation rates; wherein the electrode array has M rows and N columns, and the closer to the middle column, the shorter the length of the electrode wire, M is a positive integer, and N is a positive integer or a positive even number.

[0047] This embodiment improves the electrode array and uses electrode wires of different lengths to better cover the brain region and match the distribution of GnRH neurons. This solves the problem of incomplete matching between the electrode array and the GnRH neuron distribution area when using the electrode array to assess the GnRH neuron distribution pattern. When assessing the GnRH neuron distribution, the area of ​​the GnRH neurons is first determined. Specifically, the GnRH neurons are determined based on the GnRH neuron discharge frequency under the first and second induction drugs, thereby accurately assessing the GnRH neuron distribution pattern.

[0048] GnRH neurons are mainly distributed in the rPOA region and are symmetrical. Figure 2 As shown, it shows the GnRH neuron area distributed in the rPOA region under fluorescence verification.

[0049] Figure 4 It is a schematic diagram of the length of the electrode wire of the electrode array. The electrode array has many electrode wires ( Figure 3 The electrode wires are composed of the electrodes (shown in the middle numbers 1 to 8), and the electrical signals of the brain regions (for example, the rPOA region) can be acquired through these electrode wires.

[0050] In a specific embodiment, the electrode array consists of 4 rows and 8 columns of electrodes, with 0.0014 cm nickel-chromium electrode wires arranged in a 4x8 pattern, each with a spacing of 300 um, 8 columns with a span of 2.1 mm, and 4 rows with a span of 0.9 mm. The direction of the 8 columns of electrodes is consistent with the side-opening direction.

[0051] Preferably, the length of the electrode wires in the 4th and 5th columns is 4.6 mm, the length of the electrode wires in the 3rd and 6th columns is 4.9 mm, the length of the electrode wires in the 2nd and 7th columns is 5.1 mm, and the length of the electrode wires in the 1st and 8th columns is 5.4 mm. Each electrode wire covers an area of ​​the brain of 0.9 mm anteriorly and 2.1 mm laterally, but the present invention is not limited thereto.

[0052] like Figure 5 and Figure 6 As shown, Figure 5The figure shows the situation of measuring the rPOA region with one row of electrode wires of the electrode array. Thus, the improved electrode array is arranged in a symmetrical distribution form according to the GnRH neurons in the rPOA region. The specific distribution of the electrode wires of the electrode array in the rPOA region can be referred to Figure 6 The position of the star in the middle. This shows that the improved electrode wire can better match the rPOA area or the GnRH neuron area.

[0053] It is understood that before administering the induction drug, the GnRH neurons need to be transfected with an inhibitory or activating virus, wherein the virus is used to inhibit or activate the activity of the GnRH neurons; Figure 3 As shown, Figure 3 The green fluorescent area in a shows the distribution of GnRH neurons. Figure 3 The red fluorescent area in b shows the expression of the commonly used inhibitory virus (AAV2 / 9hSyn-DIO-hM4D(Gi)-EYFP-WPRE-hGH.polyA); Figure 3 The yellow fluorescent area in c shows good co-labeling between the red inhibitory virus and the green GnRH neurons. This indicates that the inhibitory virus binds well to the GnRH neurons to be tested. Subsequently, we examined changes in the electrical activity and distribution of GnRH neurons under the influence of different inducing drugs.

[0054] GnRH neurons respond differently to different inducing drugs. In a more specific embodiment, the first inducing drug is Kiss 10 (kisspeptin-10) and the second inducing drug is Kiss 10 + CNO (clozapine-N-oxide). After drug administration, the discharge frequency of each electrode under the action of the inducing drug is measured. Specifically, the discharge frequency within 10 minutes from the start of drug administration is calculated. The excitation rate corresponding to the different inducing drugs is then calculated based on the discharge frequency. In one embodiment, the excitation rate corresponding to the first inducing drug is calculated as follows:

[0055]

[0056] The calculation method of the excitation rate corresponding to the second induction drug is:

[0057]

[0058] Wherein, FR1 represents the discharge frequency of the electrode in the first preset time period under the action of the first induction drug, and FR2 represents the discharge frequency of the electrode in the first preset time period under the action of the second induction drug. Indicates the discharge frequency of the electrode in the second preset time period without the effect of the inducing drug, and the length of the second preset time period is longer than the first preset time period. Due to the different activities of GnRH at different positions, each electrode corresponds to a discharge frequency in the absence of the inducing drug.

[0059] In one embodiment, the discharge frequency is calculated by calculating the ratio of the number of times the voltage signal collected by the electrode is greater than a set value within a preset time period to the preset time period. If the voltage signal is greater than the preset value, it is considered a discharge of the GnRH neuron, for example, the preset value is 10mV or 20mV.

[0060] After obtaining the excitation rates corresponding to different induction drugs, the location or area of ​​the GnRH neurons is further determined. Specifically, the relative difference between the excitation rate corresponding to the first induction drug and the excitation rate corresponding to the second induction drug is calculated. If the difference is greater than a threshold, the location of the electrode is identified as the GnRH neuron area. The relative difference is calculated as |ER2-ER1| / ER2 or |ER2-ER1| / ER1. When the relative difference is greater than a threshold, the location of the electrode is identified as the GnRH neuron or area. In a preferred embodiment, the threshold is 0.4. The distribution areas of GnRH neurons in different individuals are not exactly the same. The distribution of GnRH neurons can be determined by S1.

[0061] Please continue to refer to Figure 1 As shown, this embodiment also includes: S2, collecting electrical signals of GnRH neurons at different stages through the electrode array, processing the electrical signals, and drawing activity distribution diagrams of GnRH neurons at different stages based on the processed electrical signals.

[0062] After determining the distribution of GnRH neurons, the electrode array is used to collect electrical signals from GnRH neurons at different stages, and further analyze the patterns of GnRH neurons at different stages. The different stages can include different growth stages, different stages of animal estrus, or different stages of the human menstrual cycle. In one embodiment, the different stages include pre-estrus, estrus, and post-estrus, and the activity of GnRH neurons is burst, sustained activity, and silence, respectively. However, the present invention is not limited to this.

[0063] Since people or animals may constantly walk or move during the process of collecting signals by the electrode array, this may cause noise in the collected signals. In one embodiment, the processing of the electrical signals is specifically as follows:

[0064] According to the position distribution of the electrodes, the electrical signal values ​​collected by all electrodes at the same time are placed in a matrix, and the electrical signal value collected by each electrode is placed in the set corresponding to the electrode. The matrix is ​​split into two sub-matrices with M rows and N / 2 columns in the middle of the matrix. The two sub-matrices are smoothed separately and then merged into a matrix with M rows and N columns. Then, each set is smoothed; where N is a positive even number.

[0065] Determine the difference between the signal value of the same electrical signal value after matrix smoothing and the signal value after set smoothing. If the difference is greater than a preset value, convolve the electrical signal value with a 3D convolution kernel in the matrix of the originally collected electrical signal values, and use the convolution result as the new value of the electrical signal value.

[0066] Each electrode corresponds to a region and continuously collects electrical signals, such as voltage values, from that region. The signals collected by each electrode are placed into the corresponding set, which represents the time series of the signals collected by that electrode. At each moment, all electrodes simultaneously collect a set of data, representing the data collected by all electrodes at that specific moment. To reduce noise in the collected data, in this embodiment, smoothing is performed from two perspectives. The first perspective is to smooth the data in each matrix, where the matrix stores the signals collected by all electrodes at a specific moment. For example, the signal collected by electrode (0,0) is at position (0,0) in the matrix. Because the distribution of GnRH neurons is approximately symmetrical, the matrix is ​​divided into two sub-matrices. Assuming the matrix is ​​4×8, it is split into two 4×4 sub-matrices, specifically splitting from the middle of the matrix columns. After smoothing each sub-matrix, it is merged into a 4×8 matrix. The second perspective is to smooth each set. The signals collected by the same electrode will not undergo significant mutations in a very short period of time. Smoothing the sets can prevent signal mutations caused by noise.

[0067] After obtaining each matrix and each set after smoothing, the difference between the value of the signal of the same electrode in the smoothed matrix and the value in the set at the same time is determined. If the difference is large, a 3D convolution kernel is used to perform a convolution operation on the signal with the large difference. The 3D convolution kernel acts on the multi-channel composed of multiple matrices composed of the original acquisition signal. For example, the spatiotemporal position of a signal is (4, 3, 10), that is, the value of the electrode at position (4, 3) on the 10th matrix. If the 3D convolution kernel is 3×3×3 in size, it will act on the 9th, 10th, and 11th matrices, and the core of the convolution kernel coincides with the position (4, 3) of the 10th matrix. The 3D convolution preferably uses a 3D Gaussian kernel, and the convolution result is used as the new value of the electrical signal value. If it is not greater than the preset value, the average value of the signal value in the matrix and the signal value in the set is used as the new value of the electrical signal value. For example, if the spatiotemporal position of a signal is (4, 3, 10), its value in the matrix is ​​1, and its value in the set is 3, then the average value is 2, and 2 is used as the new value of the spatiotemporal position (4, 3, 10).

[0068] After processing the electrical signals, the noise generated in the electrode array acquisition signal can be reduced. In order to facilitate people to observe the activity or pattern of GnRH at different stages, in one embodiment, the activity distribution diagram of GnRH neurons at different stages is drawn based on the processed electrical signals, specifically:

[0069] Each stage is divided into multiple time slices, and the changes in the excitation rate and the average voltage signal of the electrodes in each time slice are obtained.

[0070] The user selects the stage to be displayed and the content to be observed, wherein the content to be observed is the excitation rate or the average value of the voltage signal.

[0071] The GnRH neuron activity graph is displayed according to the user's selection, and the GnRH neuron activity graph dynamically displays the changes in the excitation rate or voltage signal in a stage.

[0072] Each stage can be divided into multiple time slices. Preferably, the length of the time slice is 1 minute, 5 minutes or 10 minutes. Of course, it can also be divided into shorter time slices. The excitation rate corresponding to each electrode in each time slice is calculated. The formula for calculating the excitation rate is:

[0073]

[0074] Among them, ER represents the excitation rate, FR represents the discharge frequency of GnRH neurons collected by electrodes in a time slice, is the GnRH neuron discharge frequency collected by the electrode when not in the stage. Similarly, each electrode corresponds to a GnRH neuron discharge frequency obtained when not in the stage. The voltage value reflects the intensity of GnRH neuron discharge and is also something to observe.

[0075] After the excitation rate and voltage average of each electrode in each time slice are calculated, they can be stored in the database, and the user can select the stage to view and the content to observe to generate a dynamic graph.

[0076] Both the frequency and voltage values ​​reflect the activity of the GnRH neurons. In another embodiment, the activity of the GnRH neurons is obtained based on the frequency and voltage values. The activity distribution of the GnRH neurons at different stages is drawn based on the processed electrical signals, specifically:

[0077] Each stage is divided into multiple time slices, and the changes in the excitation rate and the average voltage signal of the electrodes in each time slice are obtained.

[0078] The activity of the GnRH neurons in each time slice is calculated based on the excitation rate and the average value of the voltage signal, thereby obtaining the change in the activity of the GnRH neurons in each stage;

[0079] The dynamic graph shows the changes in the activity of GnRH neurons in each stage.

[0080] Among them, the activity status of the GnRH neurons in each time slice is obtained based on the excitation rate and the average value of the voltage signal as follows: the excitation rate and the average value of the voltage signal are normalized, the weighted result of the normalized excitation rate and the average value of the voltage signal is calculated, and the weighted result is used as the activity status.

[0081] In a second embodiment of the present invention, the present invention provides a GnRH neuron distribution pattern evaluation system based on an electrode array, such as Figure 7 As shown, the system at least includes an electrode array, a data processing device and a display device;

[0082] The electrode array is used to respectively collect electrical signals of the GnRH neuron region under the action of the first induction drug and the second induction drug.

[0083] The data processing device includes the following modules:

[0084] The GnRH neuron determination module calculates the excitation rate corresponding to the first induction drug based on the discharge rate under the action of the first induction drug, calculates the excitation rate corresponding to the second induction drug based on the discharge rate under the action of the second induction drug, and uses the excitation rates to determine the GnRH neurons and areas; wherein, the electrode array has M rows and N columns, and the length of the electrode wire is shorter the closer to the middle column, M is a positive integer, and N is a positive integer or a positive even number.

[0085] The distribution pattern evaluation module is used to collect electrical signals of GnRH neurons at different stages through the electrode array, process the electrical signals, and draw activity distribution diagrams of GnRH neurons at different stages based on the processed electrical signals.

[0086] In this embodiment, the excitation rate corresponding to the first induction drug is calculated based on the discharge rate under the action of the first induction drug, and the excitation rate corresponding to the second induction drug is calculated based on the discharge rate under the action of the second induction drug, specifically:

[0087] The calculation method of the excitation rate corresponding to the first induction drug is:

[0088]

[0089] The calculation method of the excitation rate corresponding to the second induction drug is:

[0090]

[0091] Wherein, FR1 represents the discharge frequency of the electrode in the first preset time period under the action of the first induction drug, and FR2 represents the discharge frequency of the electrode in the first preset time period under the action of the second induction drug. It represents the discharge frequency of the electrode in a second preset time period without the effect of the inducing drug, and the length of the second preset time period is greater than the first preset time period.

[0092] In this embodiment, the determination of GnRH neurons and regions using the excitation rate is specifically as follows:

[0093] The relative difference between the excitation rate corresponding to the first induction drug and the excitation rate corresponding to the second induction drug is calculated. If the difference is greater than a threshold, the location of the electrode is marked as the GnRH neuron area.

[0094] In this embodiment, the processing of the electrical signal is specifically:

[0095] According to the position distribution of the electrodes, the electrical signal values ​​collected by all electrodes at the same time are placed in a matrix, and the electrical signal value collected by each electrode is placed in the set corresponding to the electrode. The matrix is ​​split into two sub-matrices with M rows and N / 2 columns in the middle of the matrix. The two sub-matrices are smoothed separately and then merged into a matrix with M rows and N columns. Then, each set is smoothed; where N is a positive even number.

[0096] Determine the difference between the signal value of the same electrical signal value after matrix smoothing and the signal value after set smoothing. If the difference is greater than a preset value, convolve the electrical signal value with a 3D convolution kernel in the matrix of the originally collected electrical signal values, and use the convolution result as the new value of the electrical signal value.

[0097] In this embodiment, the activity distribution diagram of GnRH neurons at different stages is drawn based on the processed electrical signals, specifically:

[0098] Each stage is divided into multiple time slices, and the changes in the excitation rate and the average voltage signal of the electrodes in each time slice are obtained.

[0099] The user selects the stage to be displayed and the content to be observed, wherein the content to be observed is the excitation rate or the average value of the voltage signal.

[0100] The GnRH neuron activity graph is displayed according to the user's selection, and the GnRH neuron activity graph dynamically displays the changes in the excitation rate or voltage signal in a stage.

[0101] In a third embodiment of the present invention, the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method described in the first embodiment is implemented.

[0102] In a fourth embodiment of the present invention, the present invention further provides a computer device, which includes at least a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the method described in the first embodiment is implemented.

[0103] Through the description of the above embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by adding the necessary general hardware platform, or of course, by combining hardware and software. Based on this understanding, the essence of the above technical solution or the portion that contributes to the prior art can be embodied in the form of a computer product. The present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0104] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply the existence of any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0105] It should be noted that the devices and methods disclosed in the embodiments of this document may also be implemented in other ways. The device embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of the devices, methods, and computer program products according to the various embodiments of this document. In this regard, each box in the flowchart or block diagram may represent a module, program, or portion of code, wherein the module, program segment, or portion of code contains one or more executable instructions for implementing a specified logical function, and the module, program segment, or portion of code contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the boxes may also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes may actually be executed substantially in parallel, or they may sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system for performing the specified function or action, or may be implemented by a combination of dedicated hardware and computer instructions.

[0106] In addition, the functional modules in the various embodiments of this document may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0107] Although the present invention has been described in detail through the above preferred embodiments, it should be understood that the above description is not intended to limit the present invention. After reading the above description, various modifications and substitutions of the present invention will become apparent to those skilled in the art. Therefore, the scope of protection of the present invention should be defined by the appended claims.

Claims

1. A method for evaluating the distribution pattern of GnRH neurons based on an electrode array, characterized in that: include: The electrical signals of the GnRH neuron region under the action of the first induction drug and the second induction drug are respectively collected by an electrode array, and the excitation rate corresponding to the first induction drug is calculated based on the discharge rate under the action of the first induction drug, and the excitation rate corresponding to the second induction drug is calculated based on the discharge rate under the action of the second induction drug. The calculation method of the excitation rate corresponding to the first induction drug is: The calculation method of the excitation rate corresponding to the second induction drug is: Wherein, FR1 represents the discharge frequency of the electrode in the first preset time period under the action of the first induction drug, and FR2 represents the discharge frequency of the electrode in the first preset time period under the action of the second induction drug. represents the discharge frequency of the electrode in a second preset time period without the effect of the inducing drug, wherein the length of the second preset time period is greater than that of the first preset time period; Determining the GnRH neurons and regions using the excitation rate, specifically, calculating a relative difference between the excitation rate corresponding to the first induction drug and the excitation rate corresponding to the second induction drug, and if the difference is greater than a threshold, identifying the electrode location as a GnRH neuron region; The electrode array has M rows and N columns, and the electrode wire length is shorter as it approaches the middle column, M is a positive integer, and N is a positive integer or a positive even number; The method further includes: collecting electrical signals of GnRH neurons at different stages through the electrode array, processing the electrical signals, and drawing activity distribution diagrams of GnRH neurons at different stages based on the processed electrical signals; The step of drawing a distribution diagram of GnRH neuron activity at different stages based on the processed electrical signals comprises: Each stage is divided into multiple time slices, and the changes in the excitation rate and the average voltage signal of the electrodes in each time slice are obtained; Select the stage to be displayed and the content to be observed, wherein the content to be observed is the excitation rate or the average value of the voltage signal; Determining to display a GnRH neuron activity graph according to the selection result, the GnRH neuron activity graph dynamically displays changes in the excitation rate or voltage signal in a stage; Alternatively, each stage is divided into multiple time slices, and the change in the excitation rate and the change in the average voltage signal in one stage are obtained based on the excitation rate and the average voltage signal corresponding to the electrode in each time slice; The activity of the GnRH neurons in each time slice is calculated based on the excitation rate and the average value of the voltage signal, thereby obtaining the change in the activity of the GnRH neurons in each stage; The dynamic graph shows the changes in the activity of GnRH neurons at each stage; Among them, the activity status of the GnRH neurons in each time slice is obtained based on the excitation rate and the average value of the voltage signal as follows: the excitation rate and the average value of the voltage signal are normalized, the weighted result of the normalized excitation rate and the average value of the voltage signal is calculated, and the weighted result is used as the activity status.

2. The method for evaluating the distribution pattern of GnRH neurons based on an electrode array according to claim 1, wherein: The discharge frequency of the electrode is obtained by calculating the ratio of the number of times the voltage signal collected by the electrode is greater than the set value within the preset time period to the preset time period.

3. The method for evaluating the distribution pattern of GnRH neurons based on an electrode array according to claim 1, wherein: The electrical signal values ​​collected by all electrodes at the same time are placed into a matrix according to the position distribution of the electrodes, and the electrical signal value collected by each electrode is placed into the set corresponding to the electrode. The matrix is ​​split into two sub-matrices with M rows and N / 2 columns in the middle of the matrix. The two sub-matrices are smoothed separately and then merged into a matrix with M rows and N columns. Then, each set is smoothed; where N is a positive even number; Determine the difference between the signal value of the same electrical signal value after matrix smoothing and the signal value after set smoothing. If the difference is greater than a preset value, perform a convolution operation on the electrical signal value in the matrix of the originally collected electrical signal values ​​using a 3D convolution kernel, and use the convolution result as the new value of the electrical signal value; if the difference is not greater than the preset value, use the average of the signal value in the matrix and the signal value in the set as the new value of the electrical signal value.

4. A GnRH neuron distribution pattern assessment system based on an electrode array, characterized in that: include: An electrode array having M rows and N columns, wherein the electrode wires are shorter toward the middle column, M being a positive integer, and N being a positive integer or a positive even number; the electrode array is used to respectively collect electrical signals from a GnRH neuron region under the action of a first induction drug and a second induction drug; Data processing equipment includes: a GnRH neuron determination module, configured to calculate an excitation rate corresponding to the first induction drug based on the discharge rate under the action of the first induction drug, calculate an excitation rate corresponding to the second induction drug based on the discharge rate under the action of the second induction drug, and determine the GnRH neurons and regions using the excitation rates; The GnRH neuron determination module specifically uses the following formula to calculate the excitation rate corresponding to the first induction drug: The excitation rate corresponding to the second induction drug is calculated using the following formula: Wherein, FR1 represents the discharge frequency of the electrode in the first preset time period under the action of the first induction drug, and FR2 represents the discharge frequency of the electrode in the first preset time period under the action of the second induction drug. indicating the discharge frequency of the electrode in a second preset time period in the absence of the inducing drug, the second preset time period being longer than the first preset time period; and calculating the relative difference between the excitation rate corresponding to the first inducing drug and the excitation rate corresponding to the second inducing drug, and if the difference is greater than a threshold, identifying the location of the electrode as a region of GnRH neurons; the data processing device further comprising: a distribution pattern evaluation module for collecting electrical signals of GnRH neurons at different stages through the electrode array, processing the electrical signals, and drawing an activity distribution diagram of GnRH neurons at different stages based on the processed electrical signals; The data processing device is specifically used to divide each stage into multiple time slices, and obtain the change of the excitation rate and the change of the voltage signal average value in one stage based on the excitation rate and the voltage signal average value corresponding to the electrode in each time slice; Select the stage to be displayed and the content to be observed, wherein the content to be observed is the excitation rate or the average value of the voltage signal; Determining to display a GnRH neuron activity graph according to the selection result, the GnRH neuron activity graph dynamically displays changes in the excitation rate or voltage signal in a stage; Alternatively, each stage is divided into multiple time slices, and the change in the excitation rate and the change in the average voltage signal in one stage are obtained based on the excitation rate and the average voltage signal corresponding to the electrode in each time slice; The activity of the GnRH neurons in each time slice is calculated based on the excitation rate and the average value of the voltage signal, thereby obtaining the change in the activity of the GnRH neurons in each stage; The dynamic graph shows the changes in the activity of GnRH neurons at each stage; The method of obtaining the activity of the GnRH neurons in each time slice based on the excitation rate and the average value of the voltage signal is as follows: normalizing the excitation rate and the average value of the voltage signal, calculating a weighted result of the normalized excitation rate and the average value of the voltage signal, and using the weighted result as the activity; A display device is used to display the activity distribution diagram.

5. A readable storage medium, characterized in that: The readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 3 is implemented.

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