GnRH neuron distribution mode evaluation method and system based on electrode array

Abstract

The invention discloses a GnRH neuron distribution pattern evaluation method and system based on an electrode array, and the method comprises the steps: collecting electric signals of a GnRH neuron region under the action of a first induction drug and a second induction drug through the electrode array, and calculating the excitation rate corresponding to the first induction drug based on the discharge rate under the action of the first induction drug, calculating an excitation rate corresponding to the second induction drug based on the discharge rate under the action of the second induction drug, and determining a GnRH neuron and a region by using the excitation rate; wherein the electrode array is provided with M rows and N columns, the closer to the middle column, the shorter the length of the electrode wires is, M is a positive integer, and N is a positive integer or a positive even number. According to the method, the GnRH neuron distribution mode can be accurately evaluated.

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, or gonadotropin-releasing hormone neurons, are located in the hypothalamus of the brain. GnRH neurons are scattered from the rostral preoptic area to the caudal hypothalamus. GnRH neurons can secrete GnRH, which is essential for female reproductive cycle activity and ovulation. By studying the secretion and mechanism of action of GnRH, we can better understand the causes of reproductive disorders such as infertility, hypogonadism, polycystic ovary syndrome (PCOS), etc., and it is helpful for the diagnosis and treatment of puberty retardation or precocious puberty. Studies have shown that GnRH neurons have a variety of discharge modes, including bursts, continuous activity, and silence. The discharge patterns of GnRH neurons in different physiological cycles and distributed in different regions are different, but the specific distribution pattern is not clear. Since the distribution of GnRH neurons is extremely scattered and sparse, how to accurately evaluate the distribution pattern of GnRH neurons is of great significance to the study of GnRH. Summary of the invention

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

[0004] In order to achieve the above objectives, the present invention is implemented by 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 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.

[0006] Optionally, it also 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, 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 a region of GnRH neurons.

[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 of 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 of 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 the matrix is ​​smoothed and the signal value after the set is smoothed. 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 value 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 the activity of GnRH neurons at different stages based on the processed electrical signals comprises:

[0018] Each stage is divided into multiple time slices, and the changes in the excitation rate and 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;

[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] Determine to display a GnRH neuron activity graph according to the selection result, wherein 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 of the excitation rate and the change of 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, and then the change of the activity of the GnRH neurons in each stage is obtained;

[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] On the other hand, the present invention also provides a GnRH neuron distribution pattern assessment system based on an electrode array, comprising:

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

[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 determine the GnRH neurons and regions using the excitation rates.

[0029] Optionally, the data processing device further comprises: a distribution pattern evaluation module, which 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;

[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 view of the situation that the electrode array and the GnRH neuron distribution area do not completely match when using the 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 according to the discharge frequency of the GnRH neurons under the first induction drug and the second induction drug, and then the relevant information of the GnRH neurons is collected at different stages to obtain the pattern of the GnRH neurons at different stages, and displayed in the form of a dynamic graph, so as to accurately evaluate the distribution pattern of the GnRH neurons 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 the noise caused by movement and the like. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 A flow chart of a method for evaluating the distribution pattern of GnRH neurons based on an electrode array provided in one embodiment of the present invention;

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

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

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

[0040] Figure 7 A structural block diagram of a GnRH neuron distribution pattern assessment 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 be 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 for people familiar with this technology to understand and read, and are not used to limit the limiting conditions for the implementation of the present invention, so they have no technical substantive significance. Any structural modification, change in proportional relationship or adjustment of size, without affecting the effects that the present invention can produce and the purposes that can be achieved, should still fall within the scope of the technical content disclosed 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 upstream and downstream neurons, making it impossible to accurately evaluate the specific distribution pattern of current GnRH neurons. 2. In addition, due to the special morphology of GnRH neuron distribution and 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 vivo 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 in different situations, 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 by 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 area and the distribution of GnRH neurons, so as to solve the problem that the electrode array and the GnRH neuron distribution area do not completely match when using the electrode array to evaluate the GnRH neuron distribution pattern. When evaluating the distribution of GnRH neurons, the area of ​​GnRH neurons is first determined, that is, the GnRH neurons are determined according to the discharge frequency of GnRH neurons under the first induction drug and the second induction drug, so as to accurately evaluate the distribution pattern of GnRH neurons.

[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 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 following: (as 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 is composed of 4 rows and 8 columns of electrodes, 4x8 arranged 0.0014 cm nickel-chromium electrode wires, each with a spacing of 300 um, 8 columns with a span of 2.1 mm, 4 rows with a span of 0.9 mm, and 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. The brain range covered by each electrode wire is: 0.9 mm front and back, 2.1 mm sideways, but the present invention is not limited thereto.

[0052] like Figure 5 and Figure 6 As shown, Figure 5FIG. 1 shows a situation where a row of electrode wires of the electrode array measures the rPOA region. Thus, the improved electrode array is used to achieve a symmetrical distribution of 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. It can be seen 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 that the red inhibitory virus and the green GnRH neurons are well co-labeled, indicating that the inhibitory virus is well bound to the GnRH neurons to be detected. Then, under the action of different induction drugs, we detected the changes in the electrical activity and distribution of GnRH neurons.

[0054] For different induction drugs, the response of GnRH neurons is different. In a more specific embodiment, the first induction drug is Kiss 10 (kisspeptin-10), and the second induction drug is Kiss10+CNO (Clozapine-N-oxide). After the drug is administered, the discharge frequency of each electrode under the action of the induction drug is measured. Specifically, the discharge frequency within 10 minutes is calculated from the start of drug administration. Then, the excitation rate corresponding to different induction drugs is calculated based on the discharge frequency. In one embodiment, the excitation rate corresponding to the first induction 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, 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 the 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. Due to the different activities of GnRH at different positions, each electrode corresponds to a discharge frequency of the electrode 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 to be 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 position 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 the threshold, the position of the electrode is marked 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 the threshold, the position of the electrode is marked 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 an activity distribution diagram of GnRH neurons at different stages based on the processed electrical signals.

[0062] After determining the distribution of GnRH neurons, the electrical signals of GnRH neurons at different stages are collected through the electrode array, and the patterns of GnRH neurons at different stages are further analyzed. The different stages are different growth stages or different stages of animal estrus or human menstrual cycle, etc. In one embodiment, the different stages include pre-estrus, estrus, and post-estrus, and the activities of GnRH neurons are burst, continuous activity, and silence, respectively. However, the present invention is not limited to this.

[0063] Since people or animals will keep walking or moving during the process of collecting signals by the electrode array, this will 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, and 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, and then each set is smoothed; wherein N is a positive even number.

[0065] Determine the difference between the signal value of the same electrical signal value after the matrix is ​​smoothed and the signal value after the set is smoothed. If the difference is greater than a preset value, convolve the electrical signal value using 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 an area, and the electrode will continuously collect electrical signals such as voltage values ​​in this area, and put the signals collected by each electrode into the set corresponding to the electrode. This set is the time series of the signals collected by this electrode. At each moment, all electrodes will collect a set of data at the same time. This set of data is the data collected by all electrodes at a specific moment. In order to reduce the noise of the collected data, in this embodiment, smoothing is performed from two directions. The first direction is to smooth the data of each matrix, wherein the matrix stores the signals collected by all electrodes at a certain moment, such as the signal collected by electrode (0,0) at the (0,0) position of the matrix. Since the distribution of GnRH neurons has the characteristic of approximate symmetry, the matrix is ​​divided into two sub-matrices. Assuming that the matrix is ​​4×8, it is split into two 4×4 sub-matrices after splitting, and the splitting method is specifically splitting from the middle of the column of the matrix. After smoothing each sub-matrix, it is merged into a 4×8 matrix. The second direction is to smooth each set. The signal collected by the same electrode will not undergo a large mutation in a very short time. By smoothing the set, the signal mutation caused by noise can be prevented.

[0067] After obtaining each matrix and each set after smoothing, determine the difference between the value of the signal of the same electrode at the same time in the matrix after smoothing and the value in the set. If the difference is large, use a 3D convolution kernel to perform a convolution operation on the signal with a 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 space-time position of a signal is (4,3,10), the value in the matrix is ​​1, and the value in the set is 3, then the average value is 2, and 2 is used as the new value of the space-time position (4,3,10).

[0068] After processing the electrical signal, 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 signal, specifically:

[0069] Each stage is divided into multiple time slices, and the changes in the excitation rate and 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.

[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 1min, 5min or 10min, and of course it can also be divided into shorter time slices. Calculate the excitation rate corresponding to each electrode in each time slice, and 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 firing frequency collected by the electrode when not in the stage. Similarly, each electrode corresponds to a GnRH neuron firing 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, and the activity distribution diagram 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 in one stage are obtained based on the excitation rate and the average voltage signal corresponding to the electrode in each time slice.

[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, and then the change of the activity of the GnRH neurons in each stage is obtained;

[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 assessment 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 comprises 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 determines the GnRH neurons and areas 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.

[0085] The distribution pattern evaluation module is used to collect the 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, 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 a 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, and 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, and then each set is smoothed; wherein N is a positive even number.

[0096] Determine the difference between the signal value of the same electrical signal value after the matrix is ​​smoothed and the signal value after the set is smoothed. If the difference is greater than a preset value, convolve the electrical signal value using 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 in one stage are obtained based on the excitation rate and the average voltage signal corresponding to the electrode in each time slice.

[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 implementation methods, technicians in this field can clearly understand that each implementation method can be implemented by adding a necessary general hardware platform, and of course can also be implemented by combining hardware and software. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a computer product, and the present invention can be in 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 codes.

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

[0105] It should be noted that the devices and methods disclosed in the embodiments of this article can also be implemented in other ways. The device implementation described above is only schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of this article. In this regard, each box in the flowchart or block diagram can represent a part of a module, program or code, and the module, program segment or part of the code contains one or more executable instructions for implementing the specified logical function, and the module, program segment or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can 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 can be implemented by a dedicated hardware-based system for performing a specified function or action, or can 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 content of the present invention has been described in detail through the above preferred embodiments, it should be appreciated that the above description should not be considered as a limitation of the present invention. After reading the above content, it will be apparent to those skilled in the art that various modifications and substitutions of the present invention will occur. Therefore, the protection scope of the present invention should be limited 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 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.

2. The method for evaluating the distribution pattern of GnRH neurons based on an electrode array according to claim 1, characterized in that: Also includes: The electrode array is used to collect electrical signals of GnRH neurons at different stages, and the electrical signals are processed. Based on the processed electrical signals, a distribution diagram of the activities of GnRH neurons at different stages is drawn.

3. The method for evaluating the distribution pattern of GnRH neurons based on an electrode array according to claim 1, characterized in that: 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, 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.

4. The method for evaluating the distribution pattern of GnRH neurons based on an electrode array according to claim 1, wherein: The step of determining the GnRH neurons and regions using the excitation rate comprises: 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 a region of GnRH neurons.

5. The method for evaluating the distribution pattern of GnRH neurons based on an electrode array according to claim 3, characterized in that: 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.

6. The method for evaluating the distribution pattern of GnRH neurons based on an electrode array according to claim 2, characterized in that: According to the position distribution of the electrodes, the electrical signal values ​​collected by all electrodes at the same time are placed into a matrix, 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; Determine the difference between the signal value of the same electrical signal value after the matrix is ​​smoothed and the signal value after the set is smoothed. 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 value of the signal value in the matrix and the signal value in the set as the new value of the electrical signal value.

7. The method for evaluating the distribution pattern of GnRH neurons based on an electrode array according to claim 1, characterized in that: The step of drawing a distribution diagram of the activity of GnRH neurons 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 in one stage are obtained based on the excitation rate and the average voltage signal 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; Determine to display a GnRH neuron activity graph according to the selection result, wherein 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 of the excitation rate and the change of 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, and then the change of the activity of the GnRH neurons in each stage is obtained; 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.

8. A GnRH neuron distribution pattern assessment system based on an electrode array, characterized in that: include: An electrode array, wherein the electrode array has M rows and N columns, and the electrode wires are shorter as they are closer to the middle column, M is a positive integer, and N is a positive integer or a positive even number; the electrode array is used to collect electrical signals of the GnRH neuron region under the action of the first induction drug and the second induction drug, respectively; The data processing device comprises: 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 determine the GnRH neurons and regions using the excitation rates.

9. The electrode array-based GnRH neuron distribution pattern assessment system according to claim 8, characterized in that: The data processing device further includes: a distribution pattern evaluation module, which 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; The display device is used to display the activity distribution diagram.

10. 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 7 is implemented.

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