Method and device for measuring brain information transmission path

Abstract

The invention provides a method and device for measuring a brain information propagation path, and the method comprises the steps: mapping brain information recorded by a sensor into brain source activities of whole brain voxels in a source space, and obtaining a source map; the source space is determined based on a cerebral cortex region and a subcutaneous nucleus region of an individual subject, and the source map comprises a plurality of regions of brain source activity intensity; detecting active regions from a plurality of brain source activity intensity regions, and connecting the active regions at different time points in series to obtain a propagation path of brain information; calculating dynamic propagation characteristics according to the propagation path, and tracking a propagation area of the brain information in the cerebral cortex according to the dynamic propagation characteristics; wherein the dynamic propagation characteristics comprise at least one of propagation displacement, propagation time and propagation speed. According to the method disclosed by the invention, the propagation path of the brain information is visualized on the brain structure image, and the propagation characteristics of the information are calculated, so that the refined calculation and visualization of the brain information communication process are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of electroencephalogram (EEG) signal processing, and in particular to a method and device for measuring brain information propagation paths. Background Art

[0002] As a complex network system, the brain encodes, transmits, and decodes information through electrical and chemical signals, enabling responses to external stimuli and regulating internal states. From a microscopic perspective, the brain's most basic and primitive information transmission relies primarily on the exchange of electrical and chemical signals between individual neurons. However, macroscopic information, such as emotions and sensory-motor conversion, relies primarily on the intercommunication of neuronal clusters across brain regions.

[0003] In the study of information transmission in the brain, even if the electrical signals of single neurons at the microscopic scale can be recorded, it is difficult to decode their biological meaning. Therefore, the information that can generally be recorded is the electrical activity of neuronal clusters (containing hundreds of thousands of neurons) at the macroscopic scale, which can be decoded or interpreted as information with practical significance, such as sensory-motor conversion information: the human eye sees a basketball thrown at it, so it reaches out to catch the ball. In this process, visual information is transmitted from the primary visual cortex to the higher visual cortex, and then through some brain areas involved in decision-making. The final decision of "catching the ball" is transmitted to the motor cortex. The nerves in the limb muscles receive the instructions, and the muscles move to complete the action. In this process, functional magnetic resonance imaging (fMRI) studies have found that the sensory cortex is excited first and the motor cortex is excited later, thus deriving a vague transmission direction from the sensory cortex to the motor cortex. However, the specific transmission path of brain information and some transmission characteristics during the transmission process are still unknown.

[0004] Medical imaging technologies such as magnetic resonance imaging (MRI) and polarization optical computed tomography (PSOCT) provide detailed images of the brain's structure. Taking the commonly used MRI brain structural image as an example, its resolution can usually reach the millimeter level. The basic unit of imaging is called a voxel. For example, the structural image of the brain is composed of millions of voxels with a size of 1mm×1mm×1mm. At the millimeter scale, "information transmission from the sensory cortex to the motor cortex" does not meet the requirements of accuracy and specificity. Summary of the Invention

[0005] The present invention provides a method and device for measuring the brain information propagation path, which is used to solve the problem that the existing technology cannot characterize the specific spatial information of brain information during propagation, and simply describes the propagation of brain information in the cerebral cortex as "information is transmitted from the sensory cortex to the motor cortex", resulting in the inability to perform fine calculation and visualization of the brain information communication process. The method realizes the fine calculation and visualization of the brain information communication process.

[0006] The present invention provides a method for measuring brain information propagation paths, comprising: Mapping the brain information recorded by the sensor into brain source activity of whole-brain voxels in a source space to obtain a source map; the source space is determined based on the cerebral cortex area and subcortical nucleus area of the individual subject, and the source map includes multiple regions of brain source activity intensity; Detecting activation areas from the multiple brain source activity intensity regions, and connecting the activation areas at different time points in series to obtain the propagation path of the brain information; Dynamic propagation characteristics are calculated according to the propagation path, and the propagation area of the brain information in the cerebral cortex is tracked according to the dynamic propagation characteristics; wherein the dynamic propagation characteristics include at least one of propagation displacement, propagation time and propagation speed.

[0007] According to a method for measuring a brain information propagation path provided by the present invention, the source space is obtained by the following steps: performing tissue layer segmentation on the magnetic resonance imaging data of the individual subject to obtain segmentation data, and segmenting subcutaneous nucleus region data from the magnetic resonance imaging data; wherein different layers of the segmentation data include different tissue information, and the different tissue information includes a head envelope, an extracranial bone envelope, an intracranial bone envelope, and a cerebral cortex; The regional data is fused with the cerebral cortex in the segmented data to obtain the source space.

[0008] According to a method for measuring brain information propagation paths provided by the present invention, mapping brain information recorded by sensors into brain source activity of whole-brain voxels in source space to obtain a source map includes: A forward head model of the individual subject is constructed according to the spatial coordinates of all source points in the source space and the spatial coordinates of all recording sensors using a traceability method; An electrical activity mapping from a target grid point to a target channel is calculated based on the forward head model to obtain a gain matrix, and the gain matrix is determined to be the source map; wherein the target grid point belongs to the grid point of the source space for generating power source imaging according to the target spatial resolution, and the target channel belongs to the channel of the electrode contact implanted corresponding to the brain information.

[0009] According to a method for measuring brain information propagation paths provided by the present invention, calculating the electrical activity mapping from the target grid point to the target channel based on the forward head model to obtain a gain matrix includes: calculating a physical mapping of each source point to a sensor based on the forward head model; Using a minimum norm imaging method to calculate the current density of each source point according to the physical mapping, and setting the spatial direction of the current density in the source space to be unconstrained; The current density of each source point is mapped to the source space to obtain a visual source map.

[0010] According to a method for measuring brain information propagation paths provided by the present invention, detecting activation areas from the regions of the multiple brain source activity intensities includes: Performing global Z-score processing on the source map to obtain a new source map; The new source map is traversed using a sliding window, and within each time window, an area that meets a target condition is determined as the activation area; wherein the target condition includes that each source point within the time window is a peak point within the neighborhood, and the Z-score value of the area is greater than a first threshold.

[0011] According to a method for measuring brain information propagation paths provided by the present invention, after detecting activation areas from the multiple areas with different brain source activity intensities, the method further includes: A deduplication operation is performed on the source points in the activation area to obtain a deduplicated activation area.

[0012] The present invention also provides a device for measuring brain information propagation paths, comprising: a mapping module for mapping the brain information recorded by the sensor into brain source activity of whole-brain voxels in a source space to obtain a source map; the source space is determined based on the cerebral cortex area and subcortical nucleus area of the individual subject, and the source map includes multiple regions of brain source activity intensity; a detection module, configured to detect activation areas from the multiple brain source activity intensity regions, and connect the activation areas at different time points in series to obtain a propagation path of the brain information; A tracking module is used to calculate dynamic propagation characteristics based on the propagation path, and track the propagation area of the brain information in the cerebral cortex based on the dynamic propagation characteristics; wherein the dynamic propagation characteristics include at least one of propagation displacement, propagation time and propagation speed.

[0013] The present invention also provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for measuring the brain information propagation path as described above is implemented.

[0014] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-described methods for measuring brain information propagation paths.

[0015] The present invention also provides a computer program product, comprising a computer program, which, when executed by a processor, implements any of the above-described methods for measuring brain information propagation paths.

[0016] The method and device for measuring the brain information propagation path provided by the present invention maps the recorded brain information into the brain source activity of the whole-brain voxels in the source space to obtain a source map, then detects the activation areas from multiple regions of brain source activity intensity and connects them in series to obtain the propagation path of the brain information, finally calculates the dynamic propagation characteristics based on the propagation path, and tracks the propagation area of the brain information in the cerebral cortex based on the dynamic propagation characteristics, thereby realizing the visualization of the brain information propagation path on the brain structure image and calculating the information propagation characteristics, thereby realizing the refined calculation and visualization of the brain information exchange process. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 This is one of the flow charts of the method for measuring brain information propagation paths provided by the present invention.

[0019] Figure 2 It is a structural diagram of the activation zone propagation relationship model provided by the present invention.

[0020] Figure 3 It is a schematic diagram of the construction process of the forward head model provided by the present invention.

[0021] Figure 4 It is a regional schematic diagram of the activation area provided by the present invention under different threshold screening conditions.

[0022] Figure 5 This is a schematic diagram of visualization of epileptic discharge propagation paths and division of propagation areas provided by the present invention.

[0023] Figure 6 This is the second flow chart of the method for measuring brain information propagation paths provided by the present invention.

[0024] Figure 7 It is a structural schematic diagram of the device for measuring brain information propagation path provided by the present invention.

[0025] Figure 8 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0026] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0027] The following combination Figure 1-Figure 7 The present invention describes the method and device for measuring brain information propagation paths.

[0028] Figure 1 This is one of the flow charts of the method for measuring brain information propagation paths provided by the present invention, such as Figure 1 As shown, the method includes the following: Step 110: Map the brain information recorded by the sensor into brain source activity of all brain voxels in the source space to obtain a source map; the source space is determined based on the cerebral cortex area and subcortical nucleus area of the individual subject, and the source map includes multiple areas of brain source activity intensity.

[0029] In this step, brain information includes but is not limited to various signals such as the target object's EEG, MEG, and intracranial EEG.

[0030] In this step, the target objects of individual subjects include living beings with cerebral cortex structures such as humans or animals.

[0031] In this step, for brain signals, non-invasive devices can be used to record scalp electroencephalogram (EEG) and magnetoencephalogram (MEG); invasive devices can also be used to record intracranial EEG signals: stereotactic electroencephalogram (SEEG) and electrocortical electrogram (ECoG).

[0032] In this embodiment, the coordinates of the electromagnetic signals recorded by the sensors in the above-mentioned device are known, and the electromagnetic signals recorded by the sensors can be reversely projected into the activity intensity of the neuronal clusters (also called sources) contained in each voxel in the whole brain space through the dynamic statistical parametric mapping (dSPM) or beamforming algorithm in a traceable manner.

[0033] Taking brain information as SEEG signals as an example, assuming that there are C electrode contacts (also called channels) recording the electrical activity of neurons in the brain, and the number of source points in the brain is N, the electrical signals of N sources are calculated based on the electrical signals recorded by C contacts.

[0034] In this embodiment, to estimate the current of brain voxels, two different modeling problems can be designed: modeling the electromagnetic properties of the head and sensor array (also known as head model or forward model), and estimating the brain sources that generate electrophysiological data based on the head model.

[0035] Specifically, the forward modeling of head tissue and sensor characteristics is completed first; for example, since tracing relies on accurate forward head model solution, the conductance parameters of the scalp, skull and cortex can be set according to the segmentation results of individual anatomical images, and the three tissues can be fused into a more detailed forward head model based on the BEM boundary element method. Then, the brain information is mapped into brain source activity of the whole-brain voxels in the source space through the forward head model to obtain the corresponding source map; the source map indicates that at any sampling point at any time, there is an image representing the intensity of the whole-brain source activity, that is, a visual display of the source map.

[0036] It should be noted that, since the propagation process of SEEG signals does not involve the skull and scalp, this embodiment uses a dedicated head model for SEEG to perform subsequent traceability analysis.

[0037] Step 120: Detect activation areas from multiple regions of brain source activity intensity, and connect the activation areas at different time points in series to obtain the propagation path of brain information.

[0038] In this step, information propagation within the brain is defined as follows: if the same waveform appears in more than three non-adjacent channels (non-adjacent electrode contacts in SEEG), it is considered a propagation event.

[0039] It should be noted that at any point in time during the process of brain information transmission, the activity intensity of some source points is much higher than that of other brain areas, which are called volume regions of activation (VRA). The activation area is the main area of information transmission. By connecting the activation areas at each time point in series, the information transmission path is formed.

[0040] In this embodiment, the activation zone can be demarcated by setting a simple threshold, for example, 70% of the maximum intensity. However, different intensity thresholds result in different activation zone sizes. The unified threshold setting used in this embodiment is not suitable for multiple subjects. A unified activation zone detection rule needs to be established for group-level analysis.

[0041] In a feasible embodiment, detecting activation areas from multiple regions of brain source activity intensity includes: performing global Z-score processing on the source map to obtain a new source map; traversing the new source map using a sliding window, and determining, within each time window, areas that meet target conditions as activation areas; wherein the target conditions include that each source point within the time window is a peak point within a neighborhood, and the Z-score value of the area is greater than a first threshold.

[0042] In this embodiment, the first threshold value can be set according to user needs. For example, the first threshold value can be 10.

[0043] In this embodiment, the unified activation zone detection rule common to all test subjects is as follows: (1) The matrix is processed by global Zscore. Since global Zscore is a linear transformation, it will not change the matrix characteristics. (2) Use a 4ms sliding window to The matrix is traversed, and in each time window, the activation area is detected using the following rules: 1. Each source point in the time window is detected to see if it is a peak in the neighborhood; 2. If it is a peak, its Zscore value is detected to see if it is greater than 10; If there are m source points among N source points that meet the above conditions (1) and (2), then the m source points are confirmed to be activated, and the area they form in space is the activation area VRA. The center position of the activation area is the seed point (seed). After traversing the S_map matrix through the sliding window, an activation area sequence is obtained, and the corresponding brain information propagation path is obtained.

[0044] Step 130: Calculate dynamic propagation characteristics based on the propagation path, and track the propagation area of brain information in the cerebral cortex based on the dynamic propagation characteristics; wherein the dynamic propagation characteristics include at least one of propagation displacement, propagation time and propagation speed.

[0045] In this step, when the propagation path of brain information is the detected activation area VRA sequence, the starting area, early propagation area and late propagation area of information propagation are divided according to the time point of appearance of each activation area. For example, the VRA before the propagation time constitutes the starting area of information propagation, 10%-30% of the VRA constitutes the early propagation area of information propagation, and the last 70% is the late propagation area of information propagation.

[0046] In this embodiment, the dynamic propagation characteristics (propagation displacement, propagation time or propagation speed) are calculated in the following manner: Figure 2 This is a schematic diagram of the structure of the activation area propagation relationship model provided by the present invention. Figure 2In the illustrated embodiment, the activation area propagation relationship model uses the nearest neighbor propagation as the basic principle to calculate the previous propagation node and the next propagation node of each VRA: for VRA(n), the distance between the seed point seed(n) and all the seed points seed(1) to seed(n-1) in the previous VRA sequence is calculated (n=2, 3, 4, 5, 6, 7), the nearest neighbor distance is recorded as dp (corresponding to Min_distance, in cm), the corresponding VRA index is p, then the propagation displacement of the information between the two VRAs is dp; the propagation speed of the information is dp divided by the time interval between the two VRAs; by accumulating the propagation displacement of the VRA sequence, the total propagation displacement (Displacement) of the information propagation event is obtained, and then the propagation speed of the VRA sequence is averaged to obtain the average speed (Velocity) of the information propagation event; and the time interval from the first VRA to the last VRA is the duration (Duration) of the information propagation event.

[0047] In some embodiments, the propagation displacement, propagation time, and propagation speed of the activation area obtained through the above calculations can be used to measure the propagation state of brain information in the cerebral cortex, so as to provide reliable data support for the quantitative analysis and monitoring of brain information exchange.

[0048] The method for measuring the brain information propagation path provided by an embodiment of the present invention maps the recorded brain information into brain source activity of whole-brain voxels in the source space to obtain a source map, then detects activation areas from multiple regions of brain source activity intensity and connects them in series to obtain the propagation path of the brain information, finally calculates the dynamic propagation characteristics based on the propagation path, and tracks the propagation area of the brain information in the cerebral cortex based on the dynamic propagation characteristics, thereby realizing the visualization of the brain information propagation path on the brain structure image and calculating the information propagation characteristics, thereby realizing the refined calculation and visualization of the brain information exchange process.

[0049] In some embodiments, the source space is acquired through the following steps: performing tissue layer segmentation on the magnetic resonance imaging data of the individual subject to obtain segmentation data, and segmenting the subcutaneous nucleus region data from the magnetic resonance imaging data; wherein different layers of the segmentation data include different tissue information, and the different tissue information includes the head envelope, the extracranial bone envelope, the intracranial bone envelope and the cerebral cortex; the regional data is fused with the cerebral cortex in the segmentation data to obtain the source space.

[0050] In this embodiment, the source space belongs to the spatial constraint area of the traceability solution. From a physiological perspective, the source space is a set of spaces where neuronal electrical activities may exist, and the source space includes the cerebral cortex and subcutaneous nuclei.

[0051] In this embodiment, the Brainstorm toolbox, the SPM toolbox, or Freesurfer software can be used to separate the MRI space into the head envelope (outermost layer, head), the outer skull envelope (the second layer, outer kull), the inner skull envelope (the third layer, inner skull), and the cerebral cortex; then the subcutaneous nuclei are separately segmented, and then the subcutaneous nuclei are merged with the cerebral cortex to form a customized source space.

[0052] Specifically, through automatic or semi-automatic segmentation algorithms (such as those based on atlas registration or machine learning models), the head structure in the magnetic resonance imaging (MRI) data of individual subjects is decomposed layer by layer into the head envelope (skin and soft tissue), extracranial bone envelope (outer layer of the skull), intracranial bone envelope (inner layer of the skull), and cerebral cortex (the junction area between gray matter and white matter); the segmentation results are stored in the form of multi-layer masks to support subsequent conductivity modeling and electric field conduction calculations; then, ROI extraction based on a priori templates or data-driven independent component analysis (ICA) is used to separate subcutaneous nuclei such as the thalamus and basal ganglia from the MRI data to ensure that the anatomical boundaries are aligned with the functional subregions; finally, the subcutaneous nucleus region data is rigidly / nonlinearly aligned with the cerebral cortex segmentation results to obtain the corresponding source space, which can eliminate the displacement error caused by differences in the scanning sequence and ensure the anatomical consistency of the cortex and subcutaneous nuclei in three-dimensional space.

[0053] The method for measuring brain information propagation paths provided by an embodiment of the present invention obtains segmented data by performing tissue layer segmentation on the magnetic resonance imaging data of individual subjects, and then segments the subcutaneous nucleus area data from the magnetic resonance imaging data. The source space can then integrate individual anatomical and functional characteristics, providing a reliable spatial framework for brain information tracing.

[0054] In some embodiments, the brain information recorded by the sensor is mapped to the brain source activity of the whole brain voxels in the source space to obtain the source map, including: taking the source tracing method to construct a forward head model of the individual subject according to the spatial coordinates of all source points in the source space and the spatial coordinates of all recording sensors; calculating the electrical activity mapping from the target grid to the target channel according to the forward head model to obtain the gain matrix, and determining the gain matrix as the source map; wherein, the target grid belongs to the grid point of the source space for generating the power source imaging according to the target spatial resolution, and the target channel belongs to the channel of the electrode contact implanted corresponding to the brain information.

[0055] Figure 3 This is a schematic diagram of the construction process of the forward head model provided by the present invention. Figure 3In the embodiment shown, in the above-mentioned source space, grid points for power source imaging are generated with a spatial resolution of 3 mm, the number of grid points is recorded as N, and the target grid point can be one or more of the N grid points; the tracing grid points are divided according to the brain network group map, and the tracing points in the same brain area are set to the same color. After the implanted SEEG electrode is reconstructed, the corresponding electrode contact spatial coordinates are known, and the number (number of channels) is recorded as C; according to the relationship between the spatial coordinates of the SEEG electrode contacts and the source space, the forward head model (corresponding to the OpenMEEG Head Model) calculation method provided by OpenMEEG can be used to construct a forward head model of the subject, and then the forward head model is used to calculate the electrical activity mapping of N grid points (corresponding to N vertices) to C channels (C channels) to obtain an N×C gain matrix Gain Matrix, that is, the source map; wherein, g NC is the element value corresponding to the Nth row and the Cth column in the gain matrix.

[0056] In some embodiments, calculating the electrical activity mapping from the target grid to the target channel according to the forward head model to obtain the gain matrix includes: calculating the physical mapping of each source point to the sensor based on the forward head model; using the minimum norm imaging method to calculate the current density of each source point according to the physical mapping, and setting the spatial direction of the current density in the source space to be unconstrained; mapping the current density of each source point to the source space to obtain a visual source map.

[0057] In this embodiment, the forward head model calculated above can be used to calculate the activity mapping from all source points in the source space to the recording sensors, and tracing the source is the inverse problem of this process. This embodiment reversely solves the electrical activity of the source space points based on the electrical signals recorded by SEEG. By adopting the minimum norm imaging method, the current density map is solved in the source space, and the spatial direction is set to unconstrained, that is, the direction of the current density at the source point is set to the free direction, allowing the dipole to rotate freely in three-dimensional space, which is more in line with the multidirectional characteristics of real neural activity.

[0058] In this embodiment, setting the grid dipole direction to be unconstrained means that at each tracing point, the electric activity intensity includes source intensity in three spatial directions: X, Y, and Z.

[0059] Specifically, the electrical activity recorded by SEEG (C×t matrix) is mapped to the electrical activity of the whole brain's source points (3N×t matrix) through the source tracing method. 3N means that each source point has electrical activity intensities in three spatial directions. The vectors in the three directions are modulo-valued to obtain the activity intensity of each point, which is a matrix with a dimension of N×t. This matrix is called the source map (sourcemap, ), which can realize the visualization of brain source activity by providing an image representing the intensity of brain source activity at any sampling point at any time.

[0060] The method for measuring brain information propagation paths provided in an embodiment of the present invention uses a tracing method to construct a forward head model of an individual subject based on the spatial coordinates of all source points in the source space and the spatial coordinates of all recording sensors. The electrical activity mapping from the target grid point to the target channel is then calculated based on the forward head model to obtain a gain matrix. This method can detect the intensity of source activity across the entire brain and realize a visual display of tracing.

[0061] In some embodiments, after detecting activation areas from multiple regions with different brain source activity intensities, the method for measuring brain information propagation paths further includes: performing a deduplication operation on source points in the activation areas to obtain deduplicated activation areas.

[0062] In an information propagation event, the propagation path of brain information is the detected activation area VRA sequence {VRA(1), VRA(2), … VRA(end)}. In this embodiment, the deduplication operation of the source space points contained in the VRA sequence is set as follows: If an activation point in VRA(n) exists in VRA(1) to VRA(n-1), then this point will be removed; if all source points contained in the last VRA have been activated in the previous VRA, then the VRA sequence will no longer contain this VRA after deduplication.

[0063] In this embodiment, in addition, the length of the VRA sequence after deduplication may be reduced, and the seed point seed of each VRA needs to be recalculated.

[0064] The method for measuring brain information propagation paths provided by the embodiment of the present invention can balance computational efficiency and physiological rationality by deduplicating activation area source points, providing high signal-to-noise ratio input for subsequent functional network analysis and clinical diagnosis.

[0065] In one embodiment, for pathological brain information such as epileptic spikes, spike wave propagation is defined as follows: if the same waveform appears in more than three non-adjacent channels (non-adjacent electrode contacts of SEEG), it is considered a propagation event. This embodiment selects the period from -50 ms of the first peak to +50 ms of the last peak, extracts the SEEG signal within this period, and traces the source to obtain S_map, whose dimension is N×t, representing the activity intensity sequence of N source points within t sampling times.

[0066] Figure 4 This is a schematic diagram of the activation area provided by the present invention under different threshold screening conditions. Figure 4 In the embodiment shown, at any time point during the spike wave propagation process, the activity intensity of the source point of the activated area is much higher than that of other brain areas. The activated area can be divided by a simple threshold setting, for example, set to 70% of the highest intensity; Figure 4 When different intensity thresholds are set in the image, the size of the activation area is also different (the activation area is the bright area in the central area of the brain, and the range of the activation area decreases from left to right) It should be noted that the size of the VRA is very sensitive to the threshold setting. In fact, the activity intensity of the source map is directly determined by the amplitude of the spike wave itself, and the spike wave amplitude varies greatly among different individuals. For subjects with extremely large spike wave peaks in some channels (>2000uV), the threshold needs to be lowered as much as possible to detect other activated areas. For subjects with spike wave peaks in all channels close to the baseline level (<100uV), the threshold needs to be raised as much as possible to filter out non-activated areas. Therefore, the unified threshold setting method used in this embodiment is not suitable for multiple subjects, and a unified activation area detection rule needs to be established for subject group-level analysis.

[0067] Figure 5 This is a schematic diagram of the visualization of the epileptic discharge propagation path and the division of the propagation area provided by the present invention. Figure 5In the embodiment shown, in this spike wave propagation event, the spike wave appears in the right hippocampus during the 4–8 ms period (onset zone, ESI_onset_zone); the spike wave begins to propagate across the hemisphere to the left hemisphere during the 8–23 ms period (early propagation zone, ESI_early_spread_zone); after 23 ms, the spike wave mainly appears in the left hippocampus (spread zone, ESI_spread_zone); the entire propagation process lasts about 66 ms, and the early propagation zones are A01–A03, D01–D03, and E01–E0 3 contacts, and the late propagation area is near the L01–L04 and K01–K05 contacts. For this embodiment, the diagnosis report issued by the clinical expert is described as "ictal period, A1–8, D1–5, E1–5→K1–4, L1–4". The embodiment of the present invention basically captures the epileptic discharge propagation relationship diagnosed by the clinician. The propagation area is consistent with the SEEG contact position in terms of scope, and the propagation order is consistent with the overall propagation position of epilepsy in terms of propagation order, which is consistent with the description in the clinical diagnosis report, indicating the effectiveness of the brain information propagation path measurement method adopted in this embodiment.

[0068] In addition, the brain information propagation path measurement method adopted in this embodiment calculated that the displacement of spike wave propagation was 5.2 cm, the propagation process lasted 66 ms, and the propagation speed was 78.7 cm / s. The spike wave propagation speed index was consistent with the previous research range (10–150 cm / s), which illustrates the reliability of the method of calculating brain information propagation characteristics of the present invention.

[0069] Figure 6 This is the second flow chart of the method for measuring the brain information propagation path provided by the present invention. Figure 6 In the embodiment shown, the steps for implementing a method for measuring the propagation path of brain information include: (1) mapping the signals recorded by the device into source activities of voxels in the whole brain using a traceability method; (2) setting a unified detection rule to detect activation areas with high activity intensity in the source space to form the propagation path of brain information; (3) determining the activation areas with propagation relationships and calculating the propagation displacement, propagation time and propagation speed of the information.

[0070] The following describes the measurement device for the brain information propagation path provided by the present invention. The measurement device for the brain information propagation path described below and the measurement method for the brain information propagation path described above can refer to each other.

[0071] Figure 7 This is a schematic diagram of the structure of the device for measuring the brain information propagation path provided by the present invention. Figure 7 As shown, the device for measuring the brain information propagation path includes: a mapping module 710, a detection module 720 and a tracking module 730.

[0072] A mapping module 710 is configured to map the brain information recorded by the sensors into brain source activity of voxels throughout the brain in a source space to obtain a source map. The source space is determined based on the cerebral cortex and subcortical nuclei of the individual subject, and the source map includes multiple regions of brain source activity intensity. Detection module 720, for detecting activation areas from multiple regions of brain source activity intensity, and connecting activation areas at different time points in series to obtain the propagation path of brain information; The tracking module 730 is used to calculate the dynamic propagation characteristics according to the propagation path, and track the propagation area of brain information in the cerebral cortex according to the dynamic propagation characteristics; wherein the dynamic propagation characteristics include at least one of the propagation displacement, propagation time and propagation speed.

[0073] The device for measuring the brain information propagation path provided by an embodiment of the present invention maps the recorded brain information into brain source activity of whole-brain voxels in the source space to obtain a source map, then detects activation areas from multiple regions of brain source activity intensity and connects them in series to obtain the propagation path of the brain information, finally calculates the dynamic propagation characteristics based on the propagation path, and tracks the propagation area of the brain information in the cerebral cortex based on the dynamic propagation characteristics, thereby realizing the visualization of the brain information propagation path on the brain structure image and the calculation of the information propagation characteristics, thereby realizing the refined calculation and visualization of the brain information exchange process.

[0074] Figure 8 An example of a physical structure diagram of an electronic device is shown below. Figure 8 As shown, the electronic device may include: a processor 810, a communications interface 820, a memory 830, and a communications bus 840. The processor 810, the communications interface 820, and the memory 830 communicate with each other via the communications bus 840. The processor 810 may invoke logic instructions in the memory 830 to execute a method for measuring brain information propagation paths. The method includes: mapping brain information recorded by sensors into brain source activity of voxels throughout the brain in a source space to obtain a source map; the source space is determined based on the cerebral cortex and subcortical nuclei of an individual subject, and the source map includes multiple regions of brain source activity intensity; detecting activation regions from the multiple regions of brain source activity intensity, and concatenating the activation regions at different time points to obtain a brain information propagation path; calculating dynamic propagation characteristics based on the propagation path, and tracking the propagation region of brain information in the cerebral cortex based on the dynamic propagation characteristics; wherein the dynamic propagation characteristics include at least one of propagation displacement, propagation time, and propagation speed.

[0075] Furthermore, the logic instructions in the aforementioned memory 830 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product, stored in a storage medium, includes instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0076] On the other hand, the present invention also provides a computer program product, which includes a computer program, which can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the measurement method of the brain information propagation path provided by the above methods, the method including: mapping the brain information recorded by the sensor into brain source activity of whole-brain voxels in the source space to obtain a source map; the source space is determined based on the cerebral cortex area and subcortical nucleus area of the individual subject, and the source map includes multiple areas of brain source activity intensity; activation areas are detected from the areas of multiple brain source activity intensities, and the activation areas at different time points are connected in series to obtain the propagation path of brain information; dynamic propagation characteristics are calculated according to the propagation path, and the propagation area of brain information in the cerebral cortex is tracked according to the dynamic propagation characteristics; wherein the dynamic propagation characteristics include at least one of propagation displacement, propagation time and propagation speed.

[0077] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for measuring the brain information propagation path provided by the above-mentioned methods, the method comprising: mapping the brain information recorded by the sensor into brain source activity of whole-brain voxels in the source space to obtain a source map; the source space is determined based on the cerebral cortex area and subcortical nucleus area of the individual subject, and the source map includes multiple areas of brain source activity intensity; activation areas are detected from the areas of multiple brain source activity intensities, and the activation areas at different time points are connected in series to obtain the propagation path of brain information; dynamic propagation characteristics are calculated based on the propagation path, and the propagation area of brain information in the cerebral cortex is tracked based on the dynamic propagation characteristics; wherein the dynamic propagation characteristics include at least one of propagation displacement, propagation time and propagation speed.

[0078] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0079] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0080] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for measuring brain information propagation paths, characterized in that: include: Map the brain information recorded by the sensor into the brain source activity of the whole brain voxels in the source space to obtain the source map; The source space is determined based on the cerebral cortex area and subcortical nucleus area of the individual subject, and the source map includes multiple areas of brain source activity intensity; Detecting activation areas from the multiple brain source activity intensity regions, and connecting the activation areas at different time points in series to obtain the propagation path of the brain information; Dynamic propagation characteristics are calculated according to the propagation path, and the propagation area of the brain information in the cerebral cortex is tracked according to the dynamic propagation characteristics; wherein the dynamic propagation characteristics include at least one of propagation displacement, propagation time and propagation speed.

2. The method for measuring brain information propagation paths according to claim 1, characterized in that: The source space is obtained by the following steps: performing tissue layer segmentation on the magnetic resonance imaging data of the individual subject to obtain segmentation data, and segmenting subcutaneous nucleus region data from the magnetic resonance imaging data; wherein different layers of the segmentation data include different tissue information, and the different tissue information includes a head envelope, an extracranial bone envelope, an intracranial bone envelope, and a cerebral cortex; The regional data is fused with the cerebral cortex in the segmented data to obtain the source space.

3. The method for measuring brain information propagation paths according to claim 1, characterized in that: Mapping the brain information recorded by the sensor into brain source activity of whole-brain voxels in the source space to obtain a source map includes: A forward head model of the individual subject is constructed according to the spatial coordinates of all source points in the source space and the spatial coordinates of all recording sensors using a traceability method; An electrical activity mapping from a target grid point to a target channel is calculated based on the forward head model to obtain a gain matrix, and the gain matrix is determined to be the source map; wherein the target grid point belongs to the grid point in the source space that generates power source imaging according to the target spatial resolution, and the target channel belongs to the channel of the contact between the brain information and the target grid point.

4. The method for measuring brain information propagation paths according to claim 3, characterized in that: Calculating the electrical activity mapping from the target grid point to the target channel according to the forward head model to obtain a gain matrix includes: calculating a physical mapping of each source point to a sensor based on the forward head model; The current density of each source point is calculated according to the physical mapping using a minimum norm imaging method, and the spatial direction of the current density in the source space is set to be unconstrained; The current density of each source point is mapped to the source space to obtain a visual source map.

5. The method for measuring brain information propagation paths according to claim 1, characterized in that: The detecting of the activation area from the regions of the plurality of brain source activity intensities comprises: Performing global Z-score processing on the source map to obtain a new source map; The new source map is traversed using a sliding window, and within each time window, an area that meets a target condition is determined as the activation area; wherein the target condition includes that each source point within the time window is a peak point within the neighborhood, and the Z-score value of the area is greater than a first threshold.

6. The method for measuring brain information propagation paths according to claim 1, characterized in that: After detecting the activation area from the multiple regions with different brain source activity intensities, the method further includes: A deduplication operation is performed on the source points in the activation area to obtain a deduplicated activation area.

7. A device for measuring brain information propagation paths, characterized in that: include: A mapping module is used to map the brain information recorded by the sensor into brain source activity of the whole brain voxels in the source space to obtain a source map; The source space is determined based on the cerebral cortex area and subcortical nucleus area of the individual subject, and the source map includes multiple areas of brain source activity intensity; a detection module, configured to detect activation areas from the multiple brain source activity intensity regions, and connect the activation areas at different time points in series to obtain a propagation path of the brain information; A tracking module is used to calculate dynamic propagation characteristics based on the propagation path, and track the propagation area of the brain information in the cerebral cortex based on the dynamic propagation characteristics; wherein the dynamic propagation characteristics include at least one of propagation displacement, propagation time and propagation speed.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the method for measuring the brain information propagation path according to any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for measuring the brain information propagation path according to any one of claims 1 to 6 is implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the method for measuring the brain information propagation path according to any one of claims 1 to 6 is implemented.

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