A dynamic closed-loop brain function topological map measurement and typing system with tactile perception

Abstract

The present application relates to a kind of dynamic closed-loop brain function topological map measurement and typing system of tactile perception, comprising: tactile device control module, image pre-processing module, brain function topological map construction module and brain function topological map measurement and typing module;Tactile device control module is used to collect nuclear magnetic image data file;Image pre-processing module is used to pre-process nuclear magnetic image data file;Brain function topological map construction module is used to construct quantitative tactile perception brain function normalization standard topological map by pre-processed nuclear magnetic image data file;Brain function topological map measurement and typing module is used to measure and typing to standard topological map, and tactile device control module is stimulated to correct feedback instruction, realizes the dynamic closed-loop control of stimulation prompt.The present application effectively improves the problem of low data processing efficiency, frequent switching between software is prone to misoperation, realizes the high-speed real-time brain function image analysis system of automated batch processing data.

Description

Technical Field

[0001] This invention relates to the field of brain mechanism research technology, and in particular to a dynamic closed-loop brain functional topology measurement and classification system for tactile perception. Background Technology

[0002] Brain function research is the origin of modern neuroscience, and its goal is to study the mapping relationship between brain function and external stimuli. Human fingers are the most sensitive tactile sensory organs and have the closest connection to the brain. However, in the field of neuroscience, due to the lag in the development of instruments for studying tactile brain function, research on tactile brain function is still in its early stages, lagging behind the development of research on other brain functions such as vision and spatial cognition. Currently, in research on tactile brain function, the tactile regions corresponding to the limbs, torso, and head in the somatosensory cortex of the brain have been identified, but the quantitative mapping relationship between tactile stimulation and activation of the somatosensory cortex remains undetermined. Current representative tactile brain atlas studies are often structural tactile brain function atlases obtained through anatomical analysis or through brain image structure and neural connectivity analysis. These atlases divide the cerebral cortex into four structurally different subregions, failing to reflect the quantitative mapping relationship between tactile stimulation and activation of the somatosensory cortex. Therefore, research on a quantitative topological map of tactile sensory brain function remains a blank.

[0003] In the study of tactile brain functional mapping, existing tactile stimulation control devices are generally still in the open-loop control stage, lacking a precise control feedback part, and therefore cannot achieve precise and quantitative closed-loop control stimulation, which also limits the research on tactile perception brain functional topology maps.

[0004] In the preprocessing and analysis of MRI data, researchers often need to use multiple processing software programs to complete the data processing and analysis tasks, and each step requires manual operation. This often leads to low data processing efficiency, an inability to achieve seamless integration between different software programs, and sometimes even incorrect analysis results due to operational errors. Therefore, there is an urgent need for high-speed, real-time brain functional image analysis software that can support automated batch processing of data. Summary of the Invention

[0005] The purpose of this invention is to provide a dynamic closed-loop brain functional topology map measurement and classification system for tactile perception, which supports real-time processing of MRI data, feedback on whether tactile points conform to brain atlases, and supports real-time modification of brain topography maps, thereby realizing dynamic closed-loop control of tactile stimulation and providing high-speed real-time brain functional image analysis software for more refined brain atlases, thus effectively improving the above-mentioned problems.

[0006] To achieve the above objectives, the present invention provides the following solution:

[0007] A dynamic closed-loop brain functional topology mapping measurement and classification system for tactile perception, comprising:

[0008] The system includes a tactile device control module, an image preprocessing module, a brain functional topology map construction module, and a brain functional topology map measurement and classification module.

[0009] The tactile device control module is used to control the tactile stimulation device to output stimulation and acquire MRI image data files in an NMR environment;

[0010] The image preprocessing module is used to preprocess the NMR image data file;

[0011] The brain function topology construction module is used to construct a standard topology map of quantitative tactile perception brain function normalization using the preprocessed MRI image data file.

[0012] The brain functional topology map measurement and classification module is used to measure and classify the standard topology map and send stimulation correction feedback commands to the tactile device control module to realize dynamic closed-loop control of stimulation prompts.

[0013] Preferably, the tactile device control module includes:

[0014] The experiment paradigm editing unit for tactile stimulation, the debugging unit for tactile stimulation equipment, and the operation unit for tactile stimulation experiment functions are all included.

[0015] The tactile stimulation experiment paradigm editing unit is used to edit the tactile stimulation experiment paradigm, realize the experimental conditions through the tactile stimulation experiment paradigm, and receive feedback information from the brain functional topology map measurement and classification module to correct the tactile stimulation experiment paradigm.

[0016] The tactile stimulation device debugging unit is used to initialize the tactile stimulation device and check the device status;

[0017] The tactile stimulation experiment function operation unit is used to save the content of the tactile stimulation experiment paradigm as a configuration file. When it is necessary to repeatedly edit the tactile stimulation experiment paradigm, the configuration file can be imported or exported.

[0018] Preferably, the tactile stimulation experimental paradigm includes: selection of stimulation channels, setting of stimulation frequency, and setting of stimulation duration.

[0019] Preferably, the tactile device control module further includes:

[0020] The experiment start or stop unit, the channel display unit, and the tactile stimulation experiment prompt unit;

[0021] The start or stop experiment unit is used to start or stop the output stimulation of the tactile stimulation device according to the tactile stimulation experiment paradigm and to acquire the MRI image data file; wherein, the MRI image data file includes: T1 structural image raw data file and functional image raw data file;

[0022] The channel display unit is used to select the channel to be stimulated and to display the channel being stimulated in progress on the channel display unit, allowing the operator to monitor the experimental progress and stimulation position in real time.

[0023] The tactile stimulation experiment prompting unit is used to display the progress of the stimulation experiment for the operator's reference, and to display operation instructions to guide the operator in using the tactile perception dynamic closed-loop brain function topology map measurement and classification system to prevent misoperation.

[0024] Preferably, the image preprocessing module includes:

[0025] The system includes a raw data file format conversion unit, a time-interlayer correction unit, a rearrangement header dynamic correction unit, and a standard spatial registration unit.

[0026] The raw data file format conversion unit is used to convert the T1 structural image raw data file and the functional image raw data file format into NIfTI format structural magnetic resonance imaging file and functional magnetic resonance imaging file;

[0027] The time-slice correction unit is used to correct the temporal differences between layers of the functional magnetic resonance imaging file by inputting the number of slices, repetition time, and slice order.

[0028] The rearranged head motion correction unit is used to perform rearranged head motion correction processing on the time-corrected functional magnetic resonance imaging file to correct the image shift caused by the subject's head movement, and to acquire the head movement and plot the head motion curve.

[0029] The standard spatial registration unit is used to align the rearranged functional magnetic resonance imaging (fMRI) files and the structural magnetic resonance imaging (SMRI) files.

[0030] Preferably, the image preprocessing module further includes:

[0031] Spatial normalization unit, spatial smoothing unit, image segmentation unit, and preprocessed image export unit;

[0032] The spatial normalization unit is used to perform spatial normalization processing on the aligned functional magnetic resonance imaging file.

[0033] The spatial smoothing processing unit is used to perform Gaussian smoothing on the functional magnetic resonance imaging file after spatial normalization.

[0034] The image segmentation unit is used to divide the gray and white matter of the image according to the differences in the intensity of the image signal in the structural magnetic resonance imaging file.

[0035] The preprocessed image export unit is used to export the segmented structural magnetic resonance imaging file and the head motion curve.

[0036] Preferably, spatial normalization of the aligned functional magnetic resonance imaging (fMRI) file includes:

[0037] The aligned functional magnetic resonance imaging (fMRI) files and anatomical images are matched to the same coordinate system. The average image from the time-corrected fMRI files or the matched anatomical images are registered with a pre-designed standard anatomical space template image to eliminate individual differences between fMRI files from different subjects.

[0038] Preferably, the brain functional topology map construction module includes:

[0039] GLM model estimation unit, voxel extraction domain unit, brain functional topology mapping unit;

[0040] The GLM model estimation unit is used to perform statistical analysis on the Gaussian-smoothed functional magnetic resonance imaging file by inputting repetition time parameters and reference slice position parameters, establish a GLM model, perform restricted maximum likelihood estimation and statistical comparison test on the GLM model, and obtain significantly activated brain regions.

[0041] The voxel extraction domain unit is used to select and extract voxel time series from the significantly activated brain regions and construct a receptive field model based on experimental conditions to obtain artificially fitted neural response signals. The receptive field analysis of the voxel time series is performed using the artificially fitted neural response signals to determine the hand region corresponding to the voxel.

[0042] The brain functional topology mapping unit is used to classify the voxels through the hand region, obtain classification results, draw the brain functional topology map based on the classification results, and calculate the spatial center coordinates of different categories of voxels.

[0043] Preferably, the brain functional topology measurement and classification module includes:

[0044] Brain functional topology mapping measurement unit and brain functional topology mapping classification unit;

[0045] The brain functional topology measurement unit is used to establish a brain spatial matrix based on the spatial center coordinates. The brain spatial matrix is ​​linearly fitted with a pre-established hand matrix to obtain a measurement matrix and a residual matrix. The measurement of the brain functional topology is realized based on the measurement matrix and the residual matrix.

[0046] The brain functional topology mapping classification unit is used to analyze the measurement matrix, predict the degree of abnormality of the brain functional topology map, identify abnormally activated brain regions, obtain the corresponding hand stimulation areas based on the abnormally activated brain regions, and issue stimulation correction feedback commands to the tactile device control module through the hand stimulation areas.

[0047] The beneficial effects of this invention are as follows:

[0048] This invention integrates functions such as MRI image preprocessing, brain atlas construction, and brain functional topology measurement and classification. The process summarizes the objective workflow of MRI image preprocessing and brain atlas calculation, and incorporates user preferences and feedback from experienced clinicians and researchers. This effectively improves upon problems such as low data processing efficiency, frequent software switching leading to misoperation and data parsing errors, and achieves a high-speed, real-time brain functional image analysis system capable of automated batch data processing.

[0049] This invention supports the control of NMR-compatible tactile stimulation devices for tactile stimulation experiments in an NMR environment. The tactile device control module can achieve highly accurate and low-latency tactile stimulation command transmission in a high magnetic field environment; at the same time, the interface is user-friendly, making it easy for operators to input and implement experimental paradigms.

[0050] This invention realizes dynamic closed-loop tactile control, and achieves precise quantification of stimulation through tactile stimulation feedback instructions, thereby dynamically forming a brain map that is more refined, effectively promoting the research of tactile perception brain functional topology map. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 This is a flowchart illustrating a dynamic closed-loop brain functional topology measurement and classification system for tactile perception, according to an embodiment of the present invention.

[0053] Figure 2 This is a schematic diagram of the tactile device control module according to an embodiment of the present invention;

[0054] Figure 3 This is a schematic diagram of the image preprocessing module according to an embodiment of the present invention;

[0055] Figure 4 This is a schematic diagram of the brain functional topology map construction module according to an embodiment of the present invention;

[0056] Figure 5 This is a schematic diagram of the brain functional topology measurement and classification module according to an embodiment of the present invention. Detailed Implementation

[0057] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0058] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0059] like Figure 1 As shown, a dynamic closed-loop brain functional topology map measurement and classification system for tactile perception includes:

[0060] Tactile Device Control Module: Used to control the output of tactile stimulation devices in an MRI environment. It supports customized tactile stimulation experimental paradigms and their outputs, enabling low-latency, high-precision tactile control stimulation in high magnetic field environments in conjunction with tactile stimulation hardware. It can accept stimulation correction feedback commands from the brain functional topography measurement and classification module, assisting in real-time changes to the brain topography map, thereby achieving dynamic closed-loop control of stimulation cues in high magnetic fields. This module includes a tactile stimulation device debugging area, a tactile stimulation experimental paradigm editing area, a tactile stimulation experimental function operation area, a channel display area, and a tactile stimulation experimental prompt area. The tactile stimulation device debugging area allows operators to perform initialization operations such as resetting the device before starting the experiment. The tactile stimulation experimental paradigm editing area allows users to edit tactile stimulation experimental paradigms according to their needs, including selecting stimulation channels (single / multiple selection), setting stimulation frequency, and setting stimulation duration. Operators can sequentially edit the experimental conditions for each trial according to the established experimental paradigm. The tactile stimulation experiment operation area provides import and export functions for experimental protocols. The contents of the aforementioned experimental paradigm can be saved as an INI format configuration file. When repeated editing of experimental conditions is required, the corresponding configuration file can be imported. Once the experiment is ready, clicking the "Start Experiment" button will sequentially stimulate the subject according to the experimental steps in the "Tactile Stimulation Experiment Paradigm Editing Area." If it is necessary to terminate the experiment early, clicking the "End Experiment" function will automatically generate a log file to record the current information for the operator's reference. The channel display area allows the operator to easily select the channel to be stimulated during the experimental paradigm editing stage. During the experiment, the channel being stimulated can also be displayed in real-time in this area, facilitating real-time monitoring of the experimental progress and stimulation location. The tactile stimulation experiment prompt area displays the experimental progress for the operator's reference, and another part displays operation instructions to guide the operator in using the software and prevent misoperation. This module can receive feedback information from the brain functional topology measurement and classification module, assisting in correcting the tactile stimulation experimental paradigm, realizing feedback control of tactile stimulation, and thus achieving real-time dynamic closed-loop modification of the brain topography, making the brain atlas more refined.

[0061] Image Preprocessing Module: Used for preprocessing raw data files. It supports efficient real-time processing of 7T high-field MRI data, automating batch operations and integrating complex tasks such as image format conversion and data parsing, significantly improving data preprocessing efficiency and providing effective support for subsequent brain functional topology mapping and result analysis. This module's functions include DICOM raw data file format conversion, SliceTiming temporal correction, Realign head movement correction, Coregister standard spatial registration, Normalise spatial normalization, Smooth spatial smoothing, Segment image segmentation, and preprocessed image export. The DICOM raw data file format conversion supports converting T1 structural and functional image raw data files acquired during tactile stimulation experiments from DICOM format to NIfTI format for preprocessing. SliceTiming temporal correction processes functional image NIfTI data, correcting for differences in acquisition time between layers due to fMRI layer-by-layer or interlayer scanning, ensuring consistent time points between layers. Realigning the head movement correction data rearranges the functional NIfTI images to correct image shifts caused by subject head movements and captures the subject's head movements during the experiment. Coregister standard spatial registration aligns structural and functional images, providing a basis for subsequent brain functional topology mapping. Normalize spatial standardization registers functional and anatomical images to the same coordinate system by applying the corrected mean image or registered anatomical image to a pre-designed template image in the standard anatomical space within each slice image, thus eliminating differences between MRI files from different subjects. Smooth spatial smoothing performs Gaussian smoothing on the functional image data. Segment image segmentation processes T1 structural image data, dividing the image into gray and white matter based on differences in signal strength. Preprocessed image export displays the processed structural images and head movement curves in the UI. The processed functional image files are then used in the brain functional topology mapping module.

[0062] The brain functional topology map construction module is used to construct a normalized standard topology map of quantitative tactile perception brain function. By testing the precise distribution map of tactile perception thresholds, it determines the cortical amplification model of tactile perception, further resolving the normalization problem between tactile perception and cortical amplification, thus constructing a normalized standard topology map of quantitative tactile perception brain function. Based on preprocessed functional image files and partial temporal scan information, a GLM (generalized linear model) is established. After restricted maximum likelihood estimation of the GLM, statistical test conditions are designed according to experimental conditions, and statistical comparison tests are performed to obtain statistical results, i.e., significantly activated brain regions. Voxels within the VOI (volume of interest) are selected and extracted for receptive field analysis. A receptive field model is established according to experimental conditions, and the model determines the hand region corresponding to the voxels. Voxels within the VOI are classified, and the classification results are visualized to draw a brain functional topology map, thus realizing the construction of the brain functional topology map. After classification, the spatial center coordinates of different voxel groups are calculated, providing a basis for the measurement and classification of the brain functional topology map.

[0063] The Brain Functional Topology Mapping Measurement and Classification Module is used to accurately measure and classify tactile perception brain functional topology maps. Through spatial multi-voxel analysis technology of brain functional data, the precise correspondence between tactile perception thresholds and brain functional topology maps is determined, further enabling the measurement and accurate classification of tactile perception brain functional topology maps. This can provide a reliable normalization standard for the early diagnosis of neurological diseases. Based on the spatial center coordinates of different voxel groups obtained in the brain functional topology map construction module, a brain spatial matrix is ​​established and linearly fitted with a pre-established hand matrix to calculate the measurement matrix and residual matrix, thereby achieving the measurement of the brain functional topology map. The measurement matrix is ​​the main basis for brain functional topology map classification, used to determine whether the data comes from healthy subjects or subjects with neurological diseases. The measurement matrix is ​​analyzed and combined with the information in the brain functional topology map construction module to identify abnormally activated brain regions, locate the corresponding hand stimulation areas, and then send tactile stimulation correction commands to the tactile device control module to assist it in correcting the tactile stimulation experimental paradigm and realize feedback control of tactile stimulation. Through stepwise feedback, the brain map is made more refined, thereby realizing real-time dynamic closed-loop correction of the brain functional topology map.

[0064] A dynamic closed-loop brain functional topology map measurement and classification system for tactile perception, the specific implementation of which is as follows:

[0065] Specific implementation of the tactile device control module (reference) Figure 2 Tactile stimulation includes, but is not limited to, body parts such as the hands, upper arms, and torso.

[0066] Experimental Preparation Phase: Operators can click the "Add Step" button to set basic elements such as test channels, stimulation frequency, and stimulation duration for each experimental trial in the "Edit Paradigm" area on the right. Batch operations of experimental paradigms can be achieved through "Save Experimental Protocol" and "Import Experimental Protocol." Through these steps, operators can set up the experimental methods. After the experimental paradigm is entered, operators can use the "All Set" and "All Reset" functions to send initialization commands to the tactile stimulation device and check its availability.

[0067] Experimental Phase: Once the subjects, tactile stimulation devices, and MRI acquisition equipment are ready, the system issues a control command to simultaneously initiate MRI data acquisition and the tactile stimulation experiment. The operator can monitor the experimental progress in real time through the "Experiment Status" and "Channel Status" display areas. Simultaneously, MRI data processing is performed. After obtaining the genotyping results from the MRI data processing, a tactile stimulation feedback command is sent to the editing paradigm function area to correct the tactile stimulation paradigm in real time.

[0068] Specific implementation of NMR data processing:

[0069] like Figure 3 As shown, the image preprocessing module: First, the user inputs various parameters into the UI interface based on the information from the magnetic resonance scanning sequence in the NMR experiment, such as... Figure 3As shown. After confirming that all parameters are entered correctly, the user clicks the "Run" button. The UI passes the parameters to the underlying function code, which uses the received parameters as input to begin its work. The "Number of Subjects" parameter in the UI determines the number of data sets processed by the underlying code, as well as the number of folders generated to hold preprocessing intermediate files and result files. After the user selects the working directory and the file path for the raw data to be processed, the underlying code converts the DICOM raw data files in .dcm or .IMA format under each subject's data path into NIfTI files in .nii format, including structural magnetic resonance imaging (MRI) files and functional magnetic resonance imaging (fMRI) files. Based on the "number of slices," "repetition time (TR)," and "slice order" information from the MRI scan sequence input by the user into the UI, the previously converted .nii format functional image files undergo inter-tissue correction to eliminate the influence of MRI scans on the time series of brain functional activation. The time-corrected functional image files then undergo head movement correction to eliminate the influence of subject head movements during MRI scans on functional imaging, generating head movement data information and storing it in .txt format. The head movement-corrected functional image files are then registered with structural image files to ensure the accuracy of brain activation region localization. Following this, the functional image files are standardized using the universal standard brain template TPM (Tissue Probability Maps) to eliminate individual differences in brain images. The standardized functional image files undergo image smoothing to improve image quality. Finally, the structural image files are segmented for gray and white matter. For structural image files, the underlying code reads the .nii format structural image file and outputs it as a .png format image file, which is then displayed in the UI. In addition, the underlying code uses head motion information to draw head motion curves, generating .png format image files and outputting them to the UI. After the underlying function code completes its work, it returns the path name of the working directory, structural image scan information, and calculation parameters for time-inter-slice correction, which are then displayed on the UI. The above describes the specific implementation process of the functions included in the NMR data preprocessing module.

[0070] like Figure 4As shown, the brain functional topology map construction module works as follows: After the user inputs various parameters based on the MRI scan sequence information in the UI interface and clicks the "Run" button, the UI passes the parameters to the underlying function code. The function uses the received parameters as input and begins its operation. First, the user selects the working directory and the path to the data processing result file generated in the aforementioned image preprocessing module, and then begins the brain functional topology map construction process. First, based on the "TR (Repetition Time)" and "Reference Slice Order" parameters input in the UI, statistical analysis is performed on the preprocessed functional image data file, and a GLM model is established. Restricted maximum likelihood estimation is performed on the established GLM model. Statistical test conditions are pre-designed according to the experimental conditions, and comparative tests are conducted to obtain statistical results, identifying significantly activated brain regions. From these, VOIs are automatically selected, and voxel time series within the VOIs are extracted for receptive field analysis. Based on the experimental conditions, a receptive field model was established. This model provided artificially fitted neural response signals. Receptive field analysis was performed on the voxel time series using these artificial signals to determine if neuronal populations within the voxels tended to control the hand region. This analysis served as the basis for voxel classification. After classification, the spatial center coordinates of different voxel groups were calculated, and the classification and calculation results were stored in .mat format in the working directory. Based on the aforementioned comparative tests, a voxel activation distribution map was plotted and displayed on the UI. Additionally, based on the receptive field model analysis results, a receptive field map was plotted and also displayed on the UI. Combining the statistical tests and classification calculation results, a brain functional topology map was constructed, thus achieving the brain functional topology map construction. The above describes the specific implementation process of the functions included in the brain functional topology map construction module.

[0071] like Figure 5 As shown, the brain functional topology map measurement and classification module: Based on the results obtained after implementing the functions of the aforementioned brain functional topology map construction module, in-depth analysis is performed on statistically significant and categorized voxel data. First, the spatial center coordinates of various voxels are organized and used as multiple vectors to form the brain spatial matrix Y. The linear transformation relationship Y = AX + B between Y and the pre-defined hand spatial coordinate matrix X is calculated, yielding the measurement matrix A and the residual matrix B, thus realizing the measurement of the brain functional topology map. For data from different subjects, the calculated measurement matrices often differ, and the measurement matrices of subjects with neurological diseases may differ significantly from those of healthy subjects. This predicts the degree of topology map abnormality in patients, serving as the basis for brain functional topology map classification. After classification, based on the abnormal locations of the functional topology map discovered during the aforementioned analysis, the corresponding hand regions are located and fed back to the tactile device control module for corrective stimulation, thereby achieving closed-loop feedback throughout the entire implementation process.

[0072] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A dynamic closed-loop brain functional topology map measurement and classification system for tactile perception, characterized in that, include: The system includes a tactile device control module, an image preprocessing module, a brain functional topology map construction module, and a brain functional topology map measurement and classification module. The tactile device control module is used to control the tactile stimulation device to output stimulation and acquire MRI image data files in an NMR environment; The image preprocessing module is used to preprocess the NMR image data file; The brain function topology construction module is used to construct a standard topology map of quantitative tactile perception brain function normalization using the preprocessed MRI image data file. The brain functional topology map construction module includes: GLM model estimation unit, voxel extraction domain unit, brain functional topology mapping unit; The GLM model estimation unit is used to perform statistical analysis on the Gaussian-smoothed functional magnetic resonance imaging file by inputting repetition time parameters and reference slice position parameters, establish a GLM model, perform restricted maximum likelihood estimation and statistical comparison test on the GLM model, and obtain significantly activated brain regions. The voxel extraction domain unit is used to select and extract voxel time series from the significantly activated brain regions and construct a receptive field model based on experimental conditions to obtain artificially fitted neural response signals. The receptive field analysis of the voxel time series is performed using the artificially fitted neural response signals to determine the hand region corresponding to the voxel. The brain functional topology mapping unit is used to classify the voxels through the hand region, obtain classification results, and draw the brain functional topology map and calculate the spatial center coordinates of different categories of voxels based on the classification results. The brain functional topology map measurement and classification module is used to measure and classify the standard topology map and send stimulation correction feedback commands to the tactile device control module to realize dynamic closed-loop control of stimulation prompts.

2. The dynamic closed-loop brain functional topology map measurement and classification system for tactile perception according to claim 1, characterized in that, The tactile device control module includes: The experiment paradigm editing unit for tactile stimulation, the debugging unit for tactile stimulation equipment, and the operation unit for tactile stimulation experiment functions are all included. The tactile stimulation experiment paradigm editing unit is used to edit the tactile stimulation experiment paradigm, realize the experimental conditions through the tactile stimulation experiment paradigm, and receive feedback information from the brain functional topology map measurement and classification module to correct the tactile stimulation experiment paradigm. The tactile stimulation device debugging unit is used to initialize the tactile stimulation device and check the device status; The tactile stimulation experiment function operation unit is used to save the content of the tactile stimulation experiment paradigm as a configuration file. When it is necessary to repeatedly edit the tactile stimulation experiment paradigm, the configuration file can be imported or exported.

3. The dynamic closed-loop brain functional topology measurement and classification system for tactile perception according to claim 2, characterized in that, The experimental paradigm for tactile stimulation includes: selection of stimulation channels, setting of stimulation frequency, and setting of stimulation duration.

4. The dynamic closed-loop brain functional topology measurement and classification system for tactile perception according to claim 2, characterized in that, The tactile device control module also includes: The experiment start or stop unit, the channel display unit, and the tactile stimulation experiment prompt unit; The start or stop experiment unit is used to start or stop the output stimulation of the tactile stimulation device according to the tactile stimulation experiment paradigm and to acquire the MRI image data file; wherein, the MRI image data file includes: T1 structural image raw data file and functional image raw data file; The channel display unit is used to select the channel to be stimulated and to display the channel being stimulated in progress on the channel display unit, allowing the operator to monitor the experimental progress and stimulation position in real time. The tactile stimulation experiment prompting unit is used to display the progress of the stimulation experiment for the operator's reference, and to display operation instructions to guide the operator in using the tactile perception dynamic closed-loop brain function topology map measurement and classification system to prevent misoperation.

5. The dynamic closed-loop brain functional topology map measurement and classification system for tactile perception according to claim 4, characterized in that, The image preprocessing module includes: The system includes a raw data file format conversion unit, a time-interlayer correction unit, a rearrangement header dynamic correction unit, and a standard spatial registration unit. The raw data file format conversion unit is used to convert the T1 structural image raw data file and the functional image raw data file format into NIfTI format structural magnetic resonance imaging file and functional magnetic resonance imaging file; The time-slice correction unit is used to correct the temporal differences between layers of the functional magnetic resonance imaging file by inputting the number of slices, repetition time, and slice order. The rearranged head motion correction unit is used to perform rearranged head motion correction processing on the time-corrected functional magnetic resonance imaging file to correct the image shift caused by the subject's head movement, and to acquire the head movement and plot the head motion curve. The standard spatial registration unit is used to align the rearranged functional magnetic resonance imaging (fMRI) files and the structural magnetic resonance imaging (SMRI) files.

6. The dynamic closed-loop brain functional topology measurement and classification system for tactile perception according to claim 5, characterized in that, The image preprocessing module further includes: Spatial normalization unit, spatial smoothing unit, image segmentation unit, and preprocessed image export unit; The spatial normalization unit is used to perform spatial normalization processing on the aligned functional magnetic resonance imaging file. The spatial smoothing processing unit is used to perform Gaussian smoothing on the functional magnetic resonance imaging file after spatial normalization. The image segmentation unit is used to divide the gray and white matter of the image according to the differences in the intensity of the image signal in the structural magnetic resonance imaging file. The preprocessed image export unit is used to export the segmented structural magnetic resonance imaging file and the head motion curve.

7. The dynamic closed-loop brain functional topology measurement and classification system for tactile perception according to claim 6, characterized in that, Spatial normalization of the aligned functional magnetic resonance imaging (fMRI) files includes: The aligned functional magnetic resonance imaging (fMRI) files and anatomical images are matched to the same coordinate system. The average image from the time-corrected fMRI files or the matched anatomical images are registered with a pre-designed standard anatomical space template image to eliminate individual differences between fMRI files from different subjects.

8. The dynamic closed-loop brain functional topology measurement and classification system for tactile perception according to claim 1, characterized in that, The brain functional topology mapping and classification module includes: Brain functional topology mapping measurement unit and brain functional topology mapping classification unit; The brain functional topology measurement unit is used to establish a brain spatial matrix based on the spatial center coordinates. The brain spatial matrix is ​​linearly fitted with a pre-established hand matrix to obtain a measurement matrix and a residual matrix. The measurement of the brain functional topology is realized based on the measurement matrix and the residual matrix. The brain functional topology mapping classification unit is used to analyze the measurement matrix, predict the degree of abnormality of the brain functional topology map, identify abnormally activated brain regions, obtain the corresponding hand stimulation areas based on the abnormally activated brain regions, and issue stimulation correction feedback commands to the tactile device control module through the hand stimulation areas.

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