A real-time data incremental saving method and system based on a microelectrode array

Abstract

The application provides a microelectrode array-based real-time data incremental saving method and system, the method comprising: a microelectrode array module acquiring target signal data and storing the target signal data to a microelectrode array cache queue; a data processing module synchronizing the target signal data in the microelectrode array cache queue to a pre-constructed synchronization cache queue according to a preset synchronization rule; and the data processing module incrementally saving the target signal data in the synchronization cache queue according to a preset format. The application synchronizes the data of the microelectrode array cache queue to the synchronization cache queue according to the preset synchronization rule, and incrementally saves the data of the synchronization cache queue according to the preset format, thereby realizing separation of data reading and use, saving storage space, and supporting long-time data saving.

Description

Technical Field

[0001] This invention relates to the field of artificial brain-intelligent complexes, and more particularly to a method and apparatus for real-time incremental data storage based on microelectrode arrays. Background Technology

[0002] The construction of artificial brain-intelligent complexes is a core foundation and important task for revealing the brain's functions, perception, and learning mechanisms. Artificial brain-intelligent complexes are created by integrating biotechnology and information technology, culturing specific cells (such as those in the cortex, hippocampus, or thalamus) in vitro, constructing neuron-electronic complexes, and then obtaining an "artificial brain" electronic complex with a certain level of intelligence through external neural regulation and learning.

[0003] Microelectrode arrays (MEAs) are powerful tools in electrophysiological research, capable of recording cellular neural signals extracellularly. They are a crucial foundational tool and device for constructing artificial brain-intelligent complexes. By implanting cells onto microelectrode array chips and culturing them discretely, neurons can gradually develop into synaptic-coupled neural networks. Researchers can then use conductive electrodes or other sensitive semiconductor devices to non-invasively record and simultaneously stimulate electrophysiological activities at multiple sites. Therefore, an information interaction platform for artificial brain-intelligent complexes based on microelectrode array devices can be constructed, enabling real-time recording and feedback of cell culture and neural signals.

[0004] Real-time reading of neural signals from cells using microelectrode array devices, along with real-time online and offline data analysis, is of great significance for research into the perception and learning mechanisms of artificial brains. Because microelectrode array devices have a large number of electrode channels, each channel collects a large amount of signals, resulting in a massive amount of data that computer memory cannot store for extended periods.

[0005] Therefore, existing technologies have shortcomings and need to be improved and developed. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a real-time incremental data storage method based on microelectrode arrays, which addresses the above-mentioned defects of the prior art. The aim is to solve the problem that the number of electrode channels in the microelectrode array device is large, the amount of data is huge, and the computer's memory capacity is insufficient to store long-term data.

[0007] The technical solution adopted by this invention to solve the technical problem is as follows:

[0008] A method for real-time incremental data storage based on a microelectrode array, wherein the method includes:

[0009] The microelectrode array module acquires target signal data and stores the target signal data in the microelectrode array buffer queue;

[0010] The data processing module synchronizes the target signal data in the microelectrode array buffer queue to the pre-constructed synchronization buffer queue according to the preset synchronization rules;

[0011] The data processing module incrementally saves the target signal data in the synchronization buffer queue according to a preset format.

[0012] In one implementation, the microelectrode array module acquires target signal data, including:

[0013] The microelectrode array module acquires raw neural signal data from each electrode channel, as well as raw stimulus labeling signal data.

[0014] The original stimulus identification signal data is obtained by converting a preset stimulus signal.

[0015] In one implementation, storing the target signal data in a microelectrode array buffer queue includes:

[0016] The microelectrode array module stores the acquired raw neural signal data in real time in the microelectrode array cache queue in the form of a floating-point two-dimensional array;

[0017] The first dimension of the raw neural signal data represents the electrode channel, and the second dimension represents the electrical signal data collected by each electrode channel that changes over time. The electrical signal data is in floating-point format.

[0018] The microelectrode array module stores the acquired raw stimulus identification signal data in the microelectrode array cache queue in real time in the form of a two-dimensional array;

[0019] In this context, the first dimension of the original stimulus identification signal data represents an additional channel, and the second dimension represents the stimulus state.

[0020] In one implementation, the preset synchronization rule is to synchronize the original neural signal data and the original stimulus identification signal data to the synchronization buffer queue according to a preset synchronization frequency;

[0021] The preset synchronization frequency is the same as the preset data acquisition frequency of the microelectrode array module.

[0022] In one implementation, the data processing module incrementally saves the target signal data in the synchronization buffer queue according to a preset format, including:

[0023] The data processing module reads the raw neural signal data and the raw stimulus identification signal data from the synchronous cache queue at a preset reading frequency;

[0024] The raw neural signal data is processed to obtain neural signal data to be saved;

[0025] The neural signal data to be saved and the original stimulus identification signal data are incrementally saved in a preset data storage file according to a preset format;

[0026] The preset format is an integer two-dimensional array, and the data storage file is an HDF5 file.

[0027] In one implementation, processing the original neural signal data to obtain neural signal data to be saved includes:

[0028] The data processing module acquires a preset multiplier factor and obtains the neural signal data to be saved based on the original neural signal data and the preset multiplier factor.

[0029] The preset multiplier factor is of floating-point type, and the neural signal data to be saved is an integer two-dimensional array.

[0030] In one implementation, the neural signal data to be saved is represented as: D = λR;

[0031] Where D represents the neural signal data to be saved, R represents the original neural signal data, and λ represents the preset multiplier factor.

[0032] In one implementation, after the data processing module incrementally saves the target signal data in the synchronization buffer queue according to a preset format, it further includes:

[0033] The data processing module reads the raw neural signal data and the raw stimulus identification signal data from the synchronization buffer queue;

[0034] Real-time online analysis is performed based on the raw neural signal data and the raw stimulus identification signal data.

[0035] This invention also discloses a real-time incremental data storage system based on a microelectrode array, wherein the system comprises:

[0036] The microelectrode array module is used to acquire target signal data and store the target signal data in the microelectrode array buffer queue;

[0037] The data processing module is used to synchronize the target signal data in the microelectrode array buffer queue to a pre-constructed synchronization buffer queue according to a preset synchronization rule, and to incrementally save the target signal data in the synchronization buffer queue according to a preset format.

[0038] The present invention also discloses a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program that can be executed to implement the real-time incremental data storage method based on microelectrode array as described above.

[0039] This invention provides a real-time incremental data storage method and system based on a microelectrode array. The method includes: a microelectrode array module acquiring target signal data and storing the target signal data in a microelectrode array buffer queue; a data processing module synchronizing the target signal data in the microelectrode array buffer queue to a pre-constructed synchronization buffer queue according to a preset synchronization rule; and the data processing module incrementally storing the target signal data in the synchronization buffer queue according to a preset format. This invention synchronizes data from the microelectrode array buffer queue to the synchronization buffer queue according to a preset synchronization rule and incrementally stores data from the synchronization buffer queue according to a preset format, achieving separation of data reading and usage, saving storage space, and supporting long-term data storage. Attached Figure Description

[0040] Figure 1 This is a schematic diagram of the real-time incremental data storage process based on microelectrode array in this invention.

[0041] Figure 2 This is a flowchart of a preferred embodiment of the real-time incremental data storage method based on microelectrode array in this invention.

[0042] Figure 3 This is a functional principle block diagram of a preferred embodiment of the real-time incremental data storage system based on microelectrode array in this invention. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of this invention clearer and more explicit, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0044] The construction of artificial brain-intelligent complexes is a core foundation and important task for revealing the brain's functions, perception, and learning mechanisms. Artificial brain-intelligent complexes are created by integrating biotechnology and information technology, culturing specific cells (such as those in the cortex, hippocampus, or thalamus) in vitro, constructing neuron-electronic complexes, and then obtaining an "artificial brain" electronic complex with a certain level of intelligence through external neural regulation and learning.

[0045] Microelectrode arrays (MEAs) are powerful tools in electrophysiological research, capable of recording cellular neural signals extracellularly. They are a crucial foundational tool and device for constructing artificial brain-intelligent complexes. By implanting cells onto microelectrode array chips and culturing them discretely, neurons can gradually develop into synaptic-coupled neural networks. Researchers can then use conductive electrodes or other sensitive semiconductor devices to non-invasively record and simultaneously stimulate electrophysiological activities at multiple sites. Therefore, an information interaction platform for artificial brain-intelligent complexes based on microelectrode array devices can be constructed, enabling real-time recording and feedback of cell culture and neural signals.

[0046] Real-time reading of neural signals from cells using microelectrode array devices, and subsequent real-time, online, and offline data analysis, is crucial for research into the perception and learning mechanisms of artificial brains. However, due to the large number of electrode channels in microelectrode array devices, each channel collects a vast amount of signals, resulting in massive data volumes that computer memory cannot store for extended periods. Therefore, achieving real-time data storage for microelectrode array devices is a critical fundamental challenge that urgently needs to be addressed.

[0047] The basic functions of a microelectrode array device are: to generate real physical stimulation to each electrode channel in response to input external stimuli, and to acquire the corresponding neural signals generated by cells at each electrode in real time. Specifically, the microelectrode array can be connected to a stimulator, which then generates real-time stimulation signals to each electrode channel. Due to the unique nature of the electronic components in the physical device, after the external stimulation signal is received by the stimulator, it does not immediately act on the electrodes of the microelectrode array chip. Instead, it undergoes necessary signal transmission, signal amplification, and other signal processing processes, resulting in a certain system delay between the theoretical stimulation moment and the actual stimulation moment. Accurately identifying and preserving the actual stimulation moment is crucial for the analysis of neural signals.

[0048] Furthermore, considering the flexibility and scalability requirements of microelectrode array devices for external experiments and applications, the reading process of neural signals from each electrode should not depend on or be controlled by external connection devices or systems. In other words, the data reading process of the microelectrode array device should be relatively independent. The external systems or devices connected to the microelectrode array should be able to read the corresponding data on demand, thereby achieving real-time online data analysis and data storage.

[0049] To meet the above-mentioned important data requirements, this invention proposes a real-time incremental data storage method based on microelectrode array devices. This method can save the signals collected by the microelectrode array devices in real time, so as to facilitate online neural modulation experiments and offline data analysis. This method is of great significance and value for the research of artificial brain intelligent complexes.

[0050] like Figure 1 As shown, this invention mainly comprises two parts: a microelectrode array module and a data processing module. The microelectrode array module is primarily used for the acquisition and transmission of neural signals. The microelectrode array device is required to acquire the neural signals corresponding to each electrode in real time and output them to the microelectrode array buffer queue. The data processing module is mainly used for online data analysis and real-time incremental saving. The data processing module requires the construction of a synchronous buffer queue for temporarily storing the data transmitted from the microelectrode array buffer queue. In this invention, the microelectrode array module can be a microelectrode array device.

[0051] Please see Figure 2 , Figure 2 This is a flowchart of a preferred embodiment of the real-time incremental data storage method based on a microelectrode array in this invention. For example... Figure 2 As shown in the embodiment of the present invention, the real-time incremental data storage method based on microelectrode array includes:

[0052] Step S100: The microelectrode array module acquires the target signal data and stores the target signal data in the microelectrode array buffer queue.

[0053] Specifically, the microelectrode array module is mainly used for the acquisition and transmission of neural signals. The microelectrode array device is required to be able to acquire the neural signals corresponding to each electrode in real time, obtain target signal data, and output the target signal data to the microelectrode array buffer queue for storage.

[0054] In one implementation, step S100 specifically includes:

[0055] Step S110: The microelectrode array module acquires the raw neural signal data of each electrode channel and obtains the raw stimulus label signal data.

[0056] The original stimulus identification signal data is obtained by converting a preset stimulus signal.

[0057] Specifically, microelectrode array devices mainly consist of an electrophysiological signal acquisition system, a signal amplifier, and an A / D converter, and are primarily used to record the in vitro electrophysiological activities of cells. Some models of microelectrode array devices integrate a stimulator, meaning the stimulator is inside the microelectrode array, forming a single unit; other stimulators are separate devices that need to be connected separately to the microelectrode array device to be used.

[0058] In one embodiment, a preset stimulation signal and a target electrode channel are input into the software of a terminal device. This terminal device can be on the same terminal as the data processing module or on a different terminal. Simultaneously, the preset stimulation signal is sent to the stimulator, and an original stimulation identification signal is generated based on this signal. This original stimulation identification signal serves as a synchronization signal with the preset stimulation signal and is then sent to the microelectrode array module. Simultaneously, the preset stimulation signal is processed by the stimulator to generate a physical stimulation signal, which is then applied to the target electrode channel.

[0059] The microelectrode array acquires neural signals from each electrode channel in real time. When a target electrode channel receives a physical stimulation signal applied by the stimulator, the electrical signal data on the target electrode channel changes accordingly. The microelectrode array module records the original stimulation identification signal as a one-dimensional signal, the data length of which is the same as the length of the neural signal acquired by each electrode channel of the microelectrode array. The original stimulation identification signal is used to determine whether the stimulator has applied stimulation at each moment, facilitating subsequent selection and analysis of the signal data recorded by the microelectrode array device. When physical stimulation occurs, the value of this one-dimensional signal is a non-zero constant; when no stimulation occurs, the value of this one-dimensional signal is zero. Thus, by detecting the non-zero value of this signal, the corresponding stimulation moment can be obtained.

[0060] The microelectrode array module acquires raw neural signal data from each electrode channel according to a preset data acquisition frequency, and obtains raw stimulation label data.

[0061] Due to the unique nature of electronic components in physical devices, external stimulus signals, upon entering the stimulator, do not immediately act on the electrodes of the microelectrode array chip. Instead, they undergo necessary signal transmission, amplification, and other signal processing. This results in a system delay between the theoretical and actual stimulus moments. This invention, however, simultaneously transmits the original stimulus identification signal along with the stimulus signal. This allows for accurate identification and storage of the actual physical stimulus moment. During subsequent online data analysis, the original stimulus identification signal data is used to identify the location of the stimulus moment, enabling the extraction of signals within a specific time range after the stimulus.

[0062] In one implementation, step S100 further includes:

[0063] Step S120: The microelectrode array module stores the acquired raw neural signal data in the microelectrode array cache queue in real time as a floating-point two-dimensional array.

[0064] The first dimension of the raw neural signal data represents the electrode channel, and the second dimension represents the electrical signal data collected by each electrode channel that changes over time. The electrical signal data is in floating-point format.

[0065] The microelectrode array module stores the acquired raw stimulus identification signal data in the microelectrode array cache queue in real time in the form of a two-dimensional array;

[0066] In this context, the first dimension of the original stimulus identification signal data represents an additional channel, and the second dimension represents the stimulus state.

[0067] Specifically, the microelectrode array module acquires raw neural signal data from each electrode channel in real time, generating two-dimensional signal data, which is stored in the microelectrode array buffer queue in real time as a floating-point two-dimensional array. The first dimension represents different electrode channels, and the second dimension represents the time-varying electrical signal data acquired by each electrode channel; this electrical signal data is in floating-point format. This raw neural signal data is stored in the microelectrode array buffer queue in real time, and the queue length can be customized. The main purpose of setting up the microelectrode array buffer queue is to ensure that the signal reading process of the microelectrode array is not subject to external control or interference; that is, the microelectrode array device always reads data and stores it in the microelectrode array buffer queue. When the microelectrode array buffer queue is full, it can automatically release previously stored data, allowing newly acquired data to continue to be stored in the microelectrode array buffer queue. This enables the microelectrode array device to achieve real-time and constant data acquisition. Simultaneously, external devices or systems can also obtain the required data from the microelectrode array buffer queue on demand, achieving independence in data reading and usage, and improving the flexibility and scalability of the device.

[0068] Simultaneously, the microelectrode array stores the acquired raw stimulus identification signal data in real-time in the microelectrode array buffer queue in the form of a two-dimensional array; wherein, the raw stimulus identification signal data is stored in the data stream of the microelectrode array device and saved in the extra channel. The first dimension of the raw stimulus identification signal data represents the extra channel, which is a channel other than the electrode channels of the microelectrode array, used to store the raw stimulus identification signal. The second dimension represents the stimulus state. If the microelectrode array has a total of 60 electrode channels, and the electrode channel range is 0-59, then the raw stimulus identification signal corresponding to the target electrode channel can be stored in the 61st dimension channel, i.e., the extra channel. Assuming that all signals are stored in the two-dimensional array A, the stimulus identification signal when the target electrode channel receives stimulation at a certain moment is A[60, v], where v represents the stimulus state, v=1 indicates that the stimulator has stimulated the target electrode at that moment, and v=0 indicates that the stimulator has not stimulated the target electrode at that moment.

[0069] The target electrode channel refers to each electrode channel that receives stimulation. During stimulation, the stimulator will individually stimulate each electrode channel according to the electrode channels set by the terminal. Each stimulator corresponds to an additional channel; the stimulation states of different stimulators are independent and do not affect each other; each additional stimulator adds an extra channel to store the corresponding identification signal. This extra channel can also be understood as adding a row of data to the first dimension of a two-dimensional array to store the identification signal.

[0070] like Figure 2 As shown, the real-time incremental data storage method based on microelectrode array described in this embodiment further includes:

[0071] Step S200: The data processing module synchronizes the target signal data in the microelectrode array buffer queue to the pre-constructed synchronization buffer queue according to the preset synchronization rules.

[0072] Specifically, the data processing module represents the data processing operation part of the external device or system connected to the microelectrode array device. It is mainly used to acquire signal data from the microelectrode array on demand and save the data in real time. A synchronous buffer queue periodically synchronizes the signal data of the microelectrode array buffer queue. The data processing module constructs a synchronous buffer queue to periodically read signal data from the microelectrode array buffer queue and temporarily store it in the synchronous buffer queue for subsequent online data analysis or data storage. The frequency of data reading is consistent with the frequency of data reading by the microelectrode array device, thus ensuring that the data in the synchronous buffer queue and the microelectrode array buffer queue remain relatively consistent. The purpose of constructing the synchronous buffer queue is to ensure the integrity of the read data: since the microelectrode array buffer queue is not controlled by external devices or systems, when data overflows in the microelectrode array buffer queue, the external system cannot read that part of the data in time, which can easily lead to data loss. By establishing a synchronous buffer queue, the data in the microelectrode array buffer queue can be completely synchronized with the synchronous buffer queue, thereby solving the data loss problem caused by "reading data on demand" and avoiding the situation where data is lost when data overflows, even if the data is only stored in the microelectrode array buffer queue. Meanwhile, the synchronous cache queue is used to support online analysis and subsequent real-time incremental data storage operations, which separates data acquisition and reading, and makes the data reading and usage processes independent, effectively avoiding system performance bottlenecks caused by the lack of independence between data reading and usage.

[0073] This invention considers the flexibility and scalability of microelectrode arrays. Based on actual needs, it establishes a microelectrode array cache queue and a data synchronization cache queue, which can effectively independently handle the two needs of reading data from microelectrode array devices and using data from external devices or systems. This improves the scalability of microelectrode array devices and facilitates the flexibility of external devices in using data.

[0074] In one implementation, the preset synchronization rule is to synchronize the original neural signal data and the original stimulus identification signal data to the synchronization buffer queue according to a preset synchronization frequency;

[0075] The preset synchronization frequency is the same as the preset data acquisition frequency of the microelectrode array module.

[0076] Specifically, the preset synchronization frequency is the same as the preset data acquisition frequency of the microelectrode array module, which effectively ensures that the data is synchronized to the synchronization buffer queue in real time.

[0077] like Figure 2 As shown, the real-time incremental data storage method based on microelectrode array described in this embodiment further includes:

[0078] Step S300: The data processing module incrementally saves the target signal data in the synchronization buffer queue according to a preset format.

[0079] Specifically, the data processing module incrementally saves the target signal data in the synchronization cache queue according to a preset format. In this invention, incrementally saving the target signal data according to a preset format ensures the integrity of data storage, effectively supports online analysis, saves storage space, and supports long-term data retention.

[0080] In one embodiment, step S300 specifically includes:

[0081] Step S310: The data processing module reads the original neural signal data and the original stimulus identification signal data from the synchronous cache queue at a preset reading frequency;

[0082] Step S320: Process the raw neural signal data to obtain neural signal data to be saved;

[0083] Step S330: The neural signal data to be saved and the original stimulus identification signal data are incrementally saved in a preset data storage file according to a preset format;

[0084] The preset format is an integer two-dimensional array, and the data storage file is an HDF5 file.

[0085] Specifically, data preservation is crucial for subsequent offline analysis and applications. In this invention, the data processing module reads signal data from the synchronous cache queue at a preset reading frequency. The signal data includes the original neural signal data and the original stimulus identification signal data. The preset reading frequency here is related to the acquisition frequency of the microelectrode array. If the acquisition frequency of the microelectrode array is 25,000 data points per second, the reading frequency can be set to read once every 100ms, reading 2,500 data points each time. Due to the massive amount of neural signal data, in order to minimize the data's demand on storage resources and reduce the size of the saved data file, this invention processes the original neural signal data, converting it from a floating-point two-dimensional array into an integer two-dimensional array. Simultaneously, to achieve real-time, incremental saving, this invention uses the "HDF5" (Hierarchical Data Format) data format to save the data. HDF5 is a common cross-platform data storage file that can store different types of images and digital data and can be transferred on different types of machines.

[0086] In summary, through the above steps, this invention achieves real-time, incremental storage of all recorded signal data, including stimulation signal data. The microelectrode array device can achieve independent data reading, while external devices or systems can connect to the microelectrode array to realize real-time online signal analysis and a real-time and complete incremental data storage process, which is of great significance for experiments on the regulation of neural signals and downstream applications.

[0087] In one embodiment, step S320 specifically includes: a data processing module acquiring a preset multiplier factor, and obtaining neural signal data to be saved based on the original neural signal data and the preset multiplier factor. The preset multiplier factor is a floating-point type, and the neural signal data to be saved is an integer two-dimensional array. This invention can complete data type conversion simply by using a preset multiplier factor, simplifying the calculation and eliminating the need for extensive computational overhead.

[0088] In one embodiment, the neural signal data to be saved is represented as: D = λR; where D represents the signal data to be saved, R represents the original neural signal data, and λ represents a preset multiplier factor.

[0089] Specifically, this invention saves the original neural signal data as integers while simultaneously saving a preset multiplier factor λ, which is used for data conversion between D and R. This invention considers the massive volume of neural signal data and designs a real-time, incremental saving method, effectively solving the problem that computer memory cannot store all neural signal data. Furthermore, considering the storage resource consumption of data saving, this invention designs a data format conversion method, using integer data instead of floating-point data, significantly reducing the storage resource consumption of data saving.

[0090] In one embodiment, the step S300 is followed by:

[0091] A1. The data processing module reads the raw neural signal data and the raw stimulus identification signal data from the synchronization buffer queue;

[0092] A2. Perform real-time online analysis based on the original neural signal data and the original stimulus identification signal data.

[0093] Specifically, experiments on the regulation of neural signals and downstream applications require an external system to acquire neural signals from cells at irregular intervals from the microelectrode array. Based on the constructed synchronous buffer queue, the data processing module can read the corresponding data from the synchronous buffer queue at any time for real-time online data analysis. This invention, through the above steps, achieves the ability to read data from the buffer queue for online analysis according to data reading needs.

[0094] In one embodiment, such as Figure 3 As shown, based on the above-described real-time incremental data storage method based on microelectrode arrays, the present invention also provides a real-time incremental data storage system based on microelectrode arrays, comprising:

[0095] The microelectrode array module 100 is used to acquire target signal data and store the target signal data in the microelectrode array buffer queue;

[0096] The data processing module 200 is used to synchronize the target signal data in the microelectrode array buffer queue to a pre-constructed synchronization buffer queue according to a preset synchronization rule, and to incrementally save the target signal data in the synchronization buffer queue according to a preset format.

[0097] The present invention also provides a computer-readable storage medium storing a computer program that can be executed to implement the steps of the real-time incremental data saving method based on a microelectrode array as described above.

[0098] In summary, this invention provides a method and system for real-time incremental data storage in a microelectrode array. The method includes: a microelectrode array module acquiring target signal data and storing the target signal data in a microelectrode array buffer queue; a data processing module synchronizing the target signal data in the microelectrode array buffer queue to a pre-constructed synchronization buffer queue according to a preset synchronization rule; and the data processing module incrementally storing the target signal data in the synchronization buffer queue according to a preset format. This invention synchronizes the data in the microelectrode array buffer queue to the synchronization buffer queue according to a preset synchronization rule and incrementally stores the data in the synchronization buffer queue according to a preset format, achieving separation of data reading and use, saving storage space, and supporting long-term data storage.

[0099] It should be noted that the data storage method in this invention is not limited to the field of microelectronic array data storage, and can be easily applied to scenarios or devices with large data volumes that require real-time acquisition, storage, and application. Furthermore, the incremental data storage format in this invention can adopt any data format capable of incremental storage.

[0100] It should be understood that the application of the present invention is not limited to the examples above. Those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. A method for real-time incremental data storage based on a microelectrode array, characterized in that, include: The microelectrode array module acquires target signal data and stores the target signal data in the microelectrode array buffer queue; The data processing module synchronizes the target signal data in the microelectrode array buffer queue to the pre-constructed synchronization buffer queue according to the preset synchronization rules; The data processing module incrementally saves the target signal data in the synchronization buffer queue according to a preset format; The microelectrode array module acquires target signal data, including: the microelectrode array module acquires raw neural signal data from each electrode channel, and acquires raw stimulus label signal data; the raw stimulus label signal data is obtained by converting a preset stimulus signal. The step of storing the target signal data in the microelectrode array cache queue includes: the microelectrode array module storing the acquired raw neural signal data in real time in the microelectrode array cache queue as a floating-point two-dimensional array; wherein, the first dimension of the raw neural signal data represents the electrode channel, and the second dimension represents the electrical signal data acquired by each electrode channel that changes over time, and the electrical signal data is floating-point type; the microelectrode array module storing the acquired raw stimulus identification signal data in real time in the microelectrode array cache queue as a two-dimensional array; wherein, the first dimension of the raw stimulus identification signal data represents the additional channel, and the second dimension represents the stimulus state; The preset synchronization rule is to synchronize the original neural signal data and the original stimulus identification signal data to the synchronization buffer queue according to a preset synchronization frequency; wherein, the preset synchronization frequency is the same as the preset data acquisition frequency of the microelectrode array module.

2. The real-time incremental data storage method based on microelectrode array according to claim 1, characterized in that, The data processing module incrementally saves the target signal data in the synchronization buffer queue according to a preset format, including: The data processing module reads the raw neural signal data and the raw stimulus identification signal data from the synchronous cache queue at a preset reading frequency; The raw neural signal data is processed to obtain neural signal data to be saved; The neural signal data to be saved and the original stimulus identification signal data are incrementally saved in a preset data storage file according to a preset format; The preset format is an integer two-dimensional array, and the data storage file is an HDF5 file.

3. The real-time incremental data storage method based on microelectrode array according to claim 2, characterized in that, The process of processing the original neural signal data to obtain neural signal data to be saved includes: The data processing module acquires a preset multiplier factor and obtains the neural signal data to be saved based on the original neural signal data and the preset multiplier factor. The preset multiplier factor is of floating-point type, and the neural signal data to be saved is an integer two-dimensional array.

4. The real-time incremental data storage method based on microelectrode array according to claim 3, characterized in that, The neural signal data to be saved is represented as follows: ; Where D represents the neural signal data to be saved, and R represents the original neural signal data. This indicates the preset multiplier factor.

5. The real-time incremental data storage method based on microelectrode array according to claim 1, characterized in that, After the data processing module incrementally saves the target signal data in the synchronization buffer queue according to a preset format, it also includes: The data processing module reads the raw neural signal data and the raw stimulus identification signal data from the synchronization buffer queue; Real-time online analysis is performed based on the raw neural signal data and the raw stimulus identification signal data.

6. A real-time incremental data storage system based on a microelectrode array, characterized in that, include: The microelectrode array module is used to acquire target signal data and store the target signal data in the microelectrode array buffer queue; The data processing module is used to synchronize the target signal data in the microelectrode array buffer queue to a pre-constructed synchronization buffer queue according to a preset synchronization rule, and to incrementally save the target signal data in the synchronization buffer queue according to a preset format. The microelectrode array module acquires target signal data, including: the microelectrode array module acquires raw neural signal data from each electrode channel, and acquires raw stimulus label signal data; the raw stimulus label signal data is obtained by converting a preset stimulus signal. The step of storing the target signal data in the microelectrode array cache queue includes: the microelectrode array module storing the acquired raw neural signal data in real time in the microelectrode array cache queue as a floating-point two-dimensional array; wherein, the first dimension of the raw neural signal data represents the electrode channel, and the second dimension represents the electrical signal data acquired by each electrode channel that changes over time, and the electrical signal data is floating-point type; the microelectrode array module storing the acquired raw stimulus identification signal data in real time in the microelectrode array cache queue as a two-dimensional array; wherein, the first dimension of the raw stimulus identification signal data represents the additional channel, and the second dimension represents the stimulus state; The preset synchronization rule is to synchronize the original neural signal data and the original stimulus identification signal data to the synchronization buffer queue according to a preset synchronization frequency; wherein, the preset synchronization frequency is the same as the preset data acquisition frequency of the microelectrode array module.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that can be executed to implement the steps of the real-time incremental data saving method based on a microelectrode array as described in any one of claims 1 to 5.

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