A space-time two-dimensional firing map analysis method and system

Abstract

The application provides a space-time two-dimensional firing map analysis method and system. The method comprises the following steps: S1, data acquisition and preprocessing: acquiring neural activity data and behavioral data and preprocessing; S2, two-dimensional space-time firing map construction: calculating the firing rate of each neuron at the corresponding space position and time point, and constructing a two-dimensional space-time firing map; S3, space-time interaction analysis: based on the two-dimensional space-time firing map, analyzing the interaction between the space position information and the time information, quantifying the relationship between the space and the time through a statistical analysis method, and extracting the features in the two-dimensional space-time firing map; S4, visualization and interpretation of data results: visualizing the two-dimensional space-time firing map. The application combines the space information and the time information into the same map for quantitative analysis, thereby revealing the interaction relationship between the space and the time, and providing more comprehensive and accurate neural activity representation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of brain science and artificial intelligence, and particularly to a space-time two-dimensional firing map analysis method and system. BACKGROUND

[0002] The brain nervous system, especially the brain regions related to space and time information processing (such as hippocampus, prefrontal cortex, etc.), performs high-level cognitive tasks through complex neural circuits and activity patterns. In these brain regions, the firing rate of neurons often encodes information related to space and time. Especially in spatial cognitive tasks, such as place cells and direction cells, will change their firing patterns according to the spatial position and direction of the animal; while the encoding of time information is usually realized by time cells, whose activity is closely related to the elapsed time. Spatial information and temporal information are often the two main dimensions of animal behavior, and they are interrelated and occur in parallel in the actual behavior process.

[0003] However, existing neuroscience researches usually measure the spatial firing rate and the temporal firing rate separately when measuring the neural firing patterns of space and time information, without considering the interaction of the two dimensions comprehensively. For example, the classic spatial task (such as the study of place cells) usually focuses on the firing rate of neurons at different spatial positions, and constructs a spatial firing map based on it; while the temporal task (such as the study of time cells) focuses on how neurons fire at different time points, and establishes a time firing curve. Although these single-dimensional firing maps are important in space or time encoding research, they ignore the actual situation that spatial information and temporal information occur simultaneously and are associated with each other.

[0004] Therefore, the existing technology cannot measure the information of space and time simultaneously in the same map, resulting in the inability to fully reflect the common activity patterns of neurons in the time and space dimensions. SUMMARY

[0005] Therefore, the present application provides a space-time two-dimensional firing map analysis method and system to at least solve the above problems.

[0006] According to a first aspect of an embodiment of the present application, a spatial-temporal two-dimensional firing map analysis method is provided, comprising: S1, data acquisition and preprocessing: acquiring, in real time, neural activity data of neurons of a measured animal in a spatial navigation task through a neuroimaging technology, simultaneously acquiring behavioral data of the measured animal, and preprocessing the neural activity data and the behavioral data, the behavioral data comprising spatial position information and time information; S2, two-dimensional spatial-temporal firing map construction: calculating, according to the acquired spatial position information and time information, a firing rate of each neuron at a corresponding spatial position and time point, obtaining spatial-dimension firing rate data and time-dimension firing rate data, and constructing a two-dimensional spatial-temporal firing map according to the spatial-dimension firing rate data and the time-dimension firing rate data; S3, spatial-temporal interaction analysis: based on the two-dimensional spatial-temporal firing map, analyzing the interaction between the spatial position information and the time information, quantifying the relationship between the space and the time through a statistical analysis method, and extracting features in the two-dimensional spatial-temporal firing map; S4, visualization and interpretation of data results: visualizing the two-dimensional spatial-temporal firing map to visually display the activity characteristics of the neurons in the spatial dimension and the time dimension.

[0007] In an implementation manner, the neural activity data of the neurons of the measured animal in the spatial navigation task is acquired in real time through the neuroimaging technology in step S1, comprising: the neural activity data of the neurons of the measured animal in the spatial navigation task is acquired in real time through a calcium imaging technology and a whole-brain electrophysiological recording technology, and specific steps are as follows: in the calcium imaging technology, the activity of the neurons is recorded by using a calcium ion indicator, wherein a change in calcium ion concentration in the calcium ion indicator is used to reflect the firing activity of the neurons; in the whole-brain electrophysiological recording technology, the overall electrical activity of the brain region of the animal is recorded by implanting a microelectrode array.

[0008] In another implementation manner, the behavioral data of the measured animal is acquired in step S1, comprising: the spatial position and the movement time of the measured animal are recorded by a behavioral system to obtain the spatial position information and the time information, and the spatial position information and the time information are taken as the behavioral data of the measured animal.

[0009] In another implementation manner, the two-dimensional spatial-temporal firing map is constructed according to the spatial-dimension firing rate data and the time-dimension firing rate data in step S2, comprising: the two-dimensional spatial-temporal firing rate matrix is constructed according to the two-dimensional spatial-dimension firing rate data and the two-dimensional time-dimension firing rate data; the two-dimensional spatial-temporal firing rate matrix is smoothed through a Gaussian filter, and the two-dimensional spatial-temporal firing rate matrix after the smoothing operation is taken as the two-dimensional spatial-temporal firing map.

[0010] In another implementation, in step S3, the interaction between the spatial position information and the time information is analyzed based on the two-dimensional space-time firing map, the relationship between the space and the time is quantified by a statistical analysis method, and the features in the two-dimensional space-time firing map are extracted, including: finding a space-time firing field in the two-dimensional space-time firing map, specifically: setting a peak firing threshold, and taking a continuous region greater than or equal to the peak firing threshold as a space-time firing field; sampling a specified sampling speed on the two-dimensional space-time firing map according to a specified gradient to obtain a space-time firing trajectory under the sampling speed; obtaining a space-time centroid on a line segment of the space-time firing trajectory under the sampling speed according to the size of the space-time firing rate corresponding to each point on the line segment; and extracting the features in the two-dimensional space-time firing map based on the space-time centroids obtained under different speeds.

[0011] In another implementation, the statistical analysis method includes at least one of correlation analysis and interaction strength calculation.

[0012] In another implementation, the features in the two-dimensional space-time firing map include at least one of firing rate distribution, interaction mode, and competition-integration mechanism.

[0013] In another implementation, in step S4, the two-dimensional space-time firing map is visualized, including: converting the two-dimensional space-time firing map into a heat map by a data visualization display and interpretation tool to realize the visualization of the two-dimensional space-time firing map.

[0014] According to a second aspect of an embodiment of the present application, a space-time two-dimensional firing map analysis system is provided, including: a neural data acquisition module for acquiring neural activity data of a measured animal, the neural data acquisition module including a calcium imaging device and an electrophysiological recording device; a behavior recording module for synchronously acquiring behavior data of the measured animal, the behavior data including spatial position information and time information; a data processing and analysis module for realizing the synchronization of the neural activity data and the behavior data, the construction of a two-dimensional space-time firing map, the analysis of space-time interaction, and the statistical analysis of results; a visualization and interpretation module for providing a data visualization display and interpretation tool, the data visualization display and interpretation tool being used to convert the two-dimensional space-time firing map into a heat map to realize the visualization of the two-dimensional space-time firing map; and a computing platform including a high-performance computing workstation, the high-performance computing workstation being used for real-time or offline data analysis; wherein the neural data acquisition module, the behavior recording module, the data processing and analysis module, the visualization and interpretation module, and the computing platform are in communication connection.

[0015] In summary, compared with the prior art, the biggest advantage of the scheme of the present application is to measure and fuse spatial and temporal information simultaneously. The present application can more accurately reveal how neurons process complex spatial and temporal information and their interaction through spatial-temporal firing map and interaction analysis technology. In addition, the present application also improves experimental efficiency and data processing accuracy by simultaneously processing spatial and temporal information, providing a more accurate and comprehensive analysis tool for neuroscience research and clinical application. These advantages make the present application have broad application prospects in the fields of neural coding research and treatment of neurodegenerative diseases. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 is a step flow chart of the method of the present application;

[0017] Figure 2 is a corresponding overall flow chart of the method of the present application; Figure 1

[0018] Figure 3 is a two-dimensional spatial-temporal firing map schematic diagram of a neuron of the method of the present application;

[0019] Figure 4 is a spatial-temporal firing field and different speed sampling schematic diagram of the method of the present application;

[0020] Figure 5 is a spatial-temporal centroid distribution schematic diagram of a certain neuron of the method of the present application;

[0021] Figure 6 is a velocity and spatial centroid and velocity and temporal centroid relationship schematic diagram on the two-dimensional spatial-temporal map of the method of the present application;

[0022] Figure 7 is a two-dimensional field size and position distribution schematic diagram of all neurons with significant spatial-temporal firing field in a certain task of the method of the present application;

[0023] Figure 8 is a structure schematic diagram of the system of the present application;

[0024] Figure 9 is a distribution schematic diagram of the spatial-temporal centroid fitting slope corresponding to the two-dimensional spatial-temporal firing map of neurons under multiple tasks of the method of the present application;

[0025] Figure 10 is a drift schematic diagram of the two-dimensional spatial-temporal firing map of five hippocampal neurons of the method of the present application over time without visual input. DETAILED DESCRIPTION

[0026] ​With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of the present application.

[0027] In order to facilitate understanding, before the specific embodiments of the present application are described in detail, the prior art of the present application is exemplarily described.

[0028] The prior art mainly includes the following research schemes related to the present application:

[0029] Single-dimensional firing rate measurement method: At present, most of the neuroscientific experiments still use the method of measuring spatial firing rate and temporal firing rate respectively. For example, the position cell research often records the firing rate of neurons during the movement of animals to construct a spatial firing map. This method takes the position of the animal as the horizontal coordinate and the firing frequency of the neuron as the vertical coordinate to show the neural firing characteristics of different position points. In the time cell research, researchers construct a time firing curve by tracking the firing frequency of neurons in time progression, with time as the horizontal coordinate and the firing rate of neurons as the vertical coordinate. However, these technical methods process spatial and temporal information separately and cannot reflect the interaction between them. In animal behavior, the interaction between spatial information and temporal information is ubiquitous, and the existing single-dimensional analysis method cannot reveal how neurons process and integrate these two kinds of information at the same time.

[0030] Research on the interaction between space and time: Recent research has found that there is a certain competition-integration relationship between spatial information and temporal information. For example, the processing of spatial information may affect the encoding of temporal information, and vice versa. However, existing researches mostly focus on the degree to which the firing of neurons in one dimension (such as spatial dimension or temporal dimension) is affected by the other dimension, without systematically analyzing the interaction between spatial and temporal information as a whole. The limitation of such researches is that the interaction between spatial information and temporal information is dynamically changing, and the interaction between the two is not simply linear influence, but more complex mutual restriction and integration. Therefore, the existing techniques and methods cannot effectively capture this dynamic interaction.

[0031] Multi-dimensional neural activity recording: In the field of neuroimaging technology, in recent years, calcium imaging technology (such as two-photon calcium imaging) and electrophysiological technology (such as multi-channel electrode array) have been widely used to record the activity of neurons. These technologies can simultaneously record the firing patterns of multiple neurons, providing potential experimental basis for the integration of spatial and temporal information. Although these technologies can record high-dimensional data, current analysis methods are still limited to extracting spatial and temporal firing features separately, lacking tools for simultaneously integrating spatial and temporal information.

[0032] Research scheme based on spatial-temporal interaction: Although existing research gradually recognizes the interaction between space and time, studies that truly integrate the two are still rare. A few attempts have simply conducted parallel experiments on spatial and temporal tasks, attempting to analyze their effects in independent tasks, but have not comprehensively considered the interaction of spatial and temporal information in the same experimental framework.

[0033] In addition, recent research has found that the spatial firing measured on a one-dimensional linear track is affected by the task period (time), and the temporal firing is affected by the task distance (space), but it has not directly measured the interaction of simultaneous spatial and temporal coding.

[0034] In existing technologies, for the hippocampal region and other related brain areas (such as neurons encoding spatial or temporal information), research usually measures the firing rate curves of spatial information and temporal information separately. This means that the encoding of spatial information (such as the firing rate of position cells) and the encoding of temporal information (such as the firing rate of time cells) are calculated independently. In this method, spatial information (such as the firing rate of position cells on a 200 cm long track) and temporal information (such as the firing rate of time cells within a certain time during movement) are studied separately. Although this separate measurement method can reveal the activity patterns of neurons in a specific spatial or temporal dimension, it ignores the interaction and coupling relationship between spatial and temporal information in the process of neuronal firing.

[0035] More importantly, separate measurement of spatial and temporal information does not fully reflect the joint action of space and time in animal behavior. In the process of animal movement and cognition in natural environments, spatial information and temporal information often occur simultaneously and influence each other. For example, during spatial navigation, the interwoven action of space and time cannot be ignored, and spatial and temporal information are integrated and compete with each other. This phenomenon has not been fully quantitatively analyzed, leading to an insufficient understanding of the interaction mechanism of temporal and spatial information in neural activity by existing methods.

[0036] In addition, existing spatial firing rates and temporal firing rates are usually analyzed separately in one dimension (such as time or space), without considering the interaction of spatial and temporal dimensions and their comprehensive regulatory effects on neural activity. The limitations of these existing methods prevent researchers from considering the overall regulatory effects of spatial-temporal information when analyzing the function of neural circuits, and thus fail to deeply understand the fine mechanisms of the brain in processing complex spatial-temporal tasks.

[0037] To solve the problem of independence of spatial information and temporal information measurement in the prior art, the present application provides a spatial-temporal two-dimensional firing map analysis method, which can simultaneously measure the firing rate of neurons in the spatial and temporal dimensions. Through this technology, the present application combines spatial information and temporal information into the same map for quantitative analysis, thereby revealing the interaction between space and time, providing a more comprehensive and accurate characterization of neural activity, and enabling a more accurate understanding of how the brain processes spatial and temporal information.

[0038] The present application is mainly applied in the field of neuroscience, particularly for the analysis of neuronal activity in the hippocampal region and other brain regions related to spatial or temporal information coding. It can be applied to animal behavior experiments, especially tasks involving spatial navigation and time perception (such as spatial positioning, path planning, time-dependent tasks, etc.).

[0039] Referring to Figure 1 , 2 The spatial-temporal two-dimensional firing map analysis method provided by the present application comprises:

[0040] S1, data acquisition and preprocessing: real-time acquisition of neural activity data of neurons of the measured animal in a spatial navigation task through a neural imaging technique, simultaneous acquisition of behavioral data of the measured animal, and preprocessing of the neural activity data and the behavioral data, the behavioral data including spatial position information and temporal information;

[0041] S2, two-dimensional spatial-temporal firing map construction: according to the acquired spatial position information and temporal information, the firing rate of each neuron at the corresponding spatial position and time point is calculated to obtain spatial dimension firing rate data and temporal dimension firing rate data, and a two-dimensional spatial-temporal firing map is constructed according to the spatial dimension firing rate data and the temporal dimension firing rate data;

[0042] S3, spatial-temporal interaction analysis: based on the two-dimensional spatial-temporal firing map, the interaction between the spatial position information and the temporal information is analyzed, the relationship between the space and the time is quantified by statistical analysis method, and the features in the two-dimensional spatial-temporal firing map are extracted;

[0043] S4, visualization and interpretation of data results: the two-dimensional space-time firing map is visualized to intuitively show the activity characteristics of neurons in the spatial dimension and the time dimension.

[0044] The space-time two-dimensional firing map analysis method of the application integrates spatial and temporal information, creates a unified firing map, and directly measures the interaction between spatial and temporal information. This method breaks through the limitation of separately processing spatial and temporal information in the prior art, can comprehensively reflect the firing mode of neurons in multidimensional information, and reveals the competition and integration mechanism of spatial and temporal information in neural activity.

[0045] Through the method of the application, it can be more accurately understood how neurons jointly encode information in space and time, and how they interact with each other.

[0046] Further, the method of the application can provide a new idea for exploring how the brain processes complex spatial and temporal information, and provide an effective tool for multidimensional data analysis in neuroscience research.

[0047] Optionally, in step S1, the neural activity data of the neurons of the measured animal in the spatial navigation task is collected in real time by a neural imaging technology, including: the neural activity data of the neurons of the measured animal in the spatial navigation task is collected in real time by a calcium imaging technology and a whole-brain electrophysiological recording technology, and the specific steps are as follows: in the calcium imaging technology, the activity of neurons is recorded by using a calcium ion indicator, wherein the change of the calcium ion concentration in the calcium ion indicator is used to reflect the firing activity of the neurons; in the whole-brain electrophysiological recording technology, the overall electrical activity of the brain region of the animal is recorded by implanting a microelectrode array.

[0048] Optionally, in step S1, the behavior data of the measured animal is collected, including: the spatial position and movement time of the measured animal are recorded by a behavior system to obtain spatial position information and time information, and the spatial position information and the time information are taken as the behavior data of the measured animal.

[0049] Optionally, in step S2, the two-dimensional space-time firing map is constructed according to the spatial dimension firing rate data and the time dimension firing rate data, including: the two-dimensional space-time firing number matrix and the two-dimensional space-time total time length matrix are constructed according to the spatial dimension firing rate data and the time dimension firing rate data; the two-dimensional space-time firing rate matrix is constructed based on the two-dimensional space-time firing number matrix and the two-dimensional space-time total time length matrix; the two-dimensional space-time firing rate matrix after the smoothing operation is taken as the two-dimensional space-time firing map by using a Gaussian filter to perform the smoothing operation on the two-dimensional space-time firing rate matrix.

[0050] Optionally, in step S3, the interaction between the spatial position information and the time information is analyzed based on the two-dimensional space-time firing map, the relationship between the space and the time is quantified by a statistical analysis method, and the features in the two-dimensional space-time firing map are extracted, including: finding a space-time firing field in the two-dimensional space-time firing map, specifically: setting a peak firing threshold, and taking a continuous region greater than or equal to the peak firing threshold as a space-time firing field; sampling the speed according to a specified gradient on the two-dimensional space-time firing map to obtain a space-time firing trajectory under the sampling speed; obtaining the space-time centroid on the line segment of the space-time firing trajectory under the sampling speed according to the size of the space-time firing rate corresponding to each point on the line segment; and extracting the features in the two-dimensional space-time firing map based on the space-time centroids obtained under different speeds.

[0051] Optionally, the statistical analysis method includes at least one of correlation analysis and interaction strength calculation.

[0052] Optionally, the features in the two-dimensional space-time firing map include at least one of firing rate distribution, interaction mode, and competition-integration mechanism.

[0053] Optionally, in step S4, the two-dimensional space-time firing map is visualized, including: converting the two-dimensional space-time firing map into a heat map through a data visualization display and interpretation tool to realize the visualization of the two-dimensional space-time firing map.

[0054] Specifically, the scheme of the application is further described according to the following examples:

[0055] The application aims to realize the two-dimensional joint measurement of the space and time firing rates of neurons and quantify the interaction between the space and time information through a new technical method. The scheme integrates the space information and the time information into a two-dimensional space-time firing map through a series of steps, and can accurately measure the space and time firing patterns of neurons in complex behavior tasks. The following is a detailed technical scheme description, see Figure 1 , 2 .

[0056] S1, data acquisition and preprocessing

[0057] In the implementation process of the application, data acquisition is a basic step. The application uses neuroimaging technology (such as calcium imaging and whole brain electrophysiological recording) to record the activity of neurons. These technologies can accurately capture the firing of each neuron in a spatial navigation task, thereby improving the comprehensiveness and accuracy of the data.

[0058] (1) Data acquisition of neural activity

[0059] Calcium imaging: By using calcium ion indicators (such as GCaMP series probes), the activity of neurons is recorded. Changes in calcium ion concentration directly reflect the firing activity of neurons. Calcium imaging technology can provide time-resolved activity maps of each neuron, and is widely used in monitoring neural activity in vivo.

[0060] Whole-brain electrophysiological recording technology: By implanting microelectrode arrays, the overall electrical activity of brain regions is recorded. Compared with calcium imaging, electrophysiological technology provides higher time resolution and can more accurately capture the transient activity of neurons.

[0061] (2) Behavior data synchronization

[0062] While collecting neural activity data, the spatial position (such as coordinate changes in one-dimensional space) and movement time (such as time markers from the start of the experiment to each time point) of the measured animal are recorded by the behavioral system. Through time-synchronized processing of behavioral data and neural activity data, consistent data pairing is ensured in both spatial and temporal dimensions, providing a foundation for subsequent two-dimensional firing map construction.

[0063] S2, Two-dimensional space-time firing map construction

[0064] This step is one of the core technologies of the present application, and the purpose is to integrate the firing rate of spatial information and time information into a two-dimensional firing map.

[0065] Two-dimensional matrix construction: The firing rate data of each neuron at different time and spatial coordinates are integrated into a two-dimensional matrix. The horizontal coordinate of the matrix represents the spatial coordinate (for example, the change in position in the spatial task), and the vertical coordinate represents the time coordinate (for example, the passage of time during the experiment); or take time as the horizontal coordinate and space as the vertical coordinate. The value in each matrix cell is the firing rate of the neuron at the corresponding time and spatial position.

[0066] Specifically for a neuron, first construct a two-dimensional space-time firing number matrix, find the corresponding spatial position and movement time when the neuron fires in a certain experiment, then the firing number of the corresponding matrix position is +1;

[0067] Then construct a two-dimensional space-time total time length matrix, each element represents the total time length that meets the corresponding spatial position and time node at the same time during movement;

[0068] Then the two-dimensional space-time firing rate matrix is the quotient matrix (divide the corresponding elements) of the two-dimensional space-time firing number matrix divided by the two-dimensional space-time total time length matrix.

[0069] Obviously, the unit of the firing rate matrix is: times / second, or Hertz (Hz).

[0070] Referring to Figure 3 The two-dimensional space-time firing rate matrix can be smoothed using a Gaussian filter, and the smoothed two-dimensional space-time firing rate matrix is taken as a two-dimensional space-time firing map.

[0071] S3, space-time interaction analysis

[0072] This step is one of the core technologies of the present application. After obtaining the two-dimensional space-time firing map, the next step of the present application is to analyze the interaction between the space information and the time information in the map.

[0073] It should be noted that, instead of directly measuring the correlation or mutual information of the space-time field on the two-dimensional space-time firing map, the interaction of the space-time centroids at different speeds is measured.

[0074] Specifically, first, find the space-time firing field in the two-dimensional space-time firing map. For example, take 30% of the peak firing as the peak firing threshold, and the continuous region equal to or greater than 30% of the peak firing can be taken as the space-time firing field, referring to the left graph in Figure 4 The left graph is the (two-dimensional) space-time firing field.

[0075] Second, according to the actual motion in a certain experiment, estimate the possible range of the motion speed, and then sample the speed at certain intervals, such as from 5 cm / s to 30 cm / s, every 2.5 cm / s. For a certain sampling speed, the space-time relationship at that speed will be a ray starting from the origin (the origin of the two-dimensional space-time map). The ray will intersect with the space-time firing field (the continuous region equal to or greater than 30% of the peak firing) to obtain a line segment, representing the space-time firing trajectory at that speed, referring to the right graph in Figure 4 The right graph is the sampling of different speeds.

[0076] According to the size of the space-time firing rate corresponding to each point on the line segment, the space-time centroid on the speed line segment can be obtained, referring to Figure 5 The space-time centroid distribution diagram of a certain neuron, in which the white points are negative correlations.

[0077] Finally, according to the space-time centroids obtained at different speeds, the competition and integration mechanism is quantified, referring to Figure 5Specifically, the relationship between the space-time centroids can be measured by Pearson correlation analysis or the like, or the effect of the space centroid on the time centroid (i.e., the size of the fitting slope) can be measured by linear fitting, or the effect of the time centroid on the space centroid can be measured by linear fitting.

[0078] In addition, the relationship between the space centroid and the velocity or the relationship between the time centroid and the velocity can also be measured, see Figure 6 These analyses help to understand how neurons integrate and process multiple information in complex spatial and temporal tasks.

[0079] S4, visualization and interpretation of data results

[0080] In order to more intuitively show the analysis results, the two-dimensional space-time firing map is converted into a heat map, see Figure 3 , which intuitively shows the activity of neurons in the spatial and temporal dimensions. The color depth in the heat map can represent the firing rate of the neurons, and the horizontal and vertical axes of the map correspond to the spatial and temporal coordinates.

[0081] In addition, for a neuron population, the total centroid position and field size of all cells with significant space-time fields can be marked in the space-time total time length matrix, see Figure 7 It can be seen that different neurons have different two-dimensional firing field sizes and positions, and the two-dimensional firing field of the cell close to the space-time boundary is smaller.

[0082] Through the map and the analysis results, it is revealed how neurons process spatial and temporal information simultaneously, and further explored their roles in neural circuits.

[0083] See Figure 8 The present application also provides a space-time two-dimensional firing map analysis system for implementing the corresponding methods in the foregoing method embodiments and having the beneficial effects of the corresponding method embodiments, and the system comprises:

[0084] A neural data acquisition module for acquiring neural activity data of a measured animal, the neural data acquisition module comprising a calcium imaging device and an electrophysiological recording device;

[0085] A behavioral recording module for synchronously acquiring behavioral data of the measured animal, the behavioral data comprising spatial position information and temporal information;

[0086] A data processing and analysis module for implementing the synchronization of the neural activity data and the behavioral data, the construction of the two-dimensional space-time firing map, the space-time interaction analysis, and the statistical analysis of the results;

[0087] a visualization and interpretation module for providing visualization and interpretation tools for the data, which are used to convert the two-dimensional space-time firing map into a heat map to realize the visualization processing of the two-dimensional space-time firing map;

[0088] a computing platform, including a high-performance computing workstation, which is used for real-time or offline data analysis;

[0089] The neural data acquisition module, the behavior recording module, the data processing and analysis module, the visualization and interpretation module, and the computing platform are in communication connection.

[0090] It should be understood that the computing platform of the present application supports large-scale data processing and real-time / offline data analysis.

[0091] Compared with the prior art, the greatest advantage of the present application is that it simultaneously measures and integrates spatial and temporal information, and through the space-time firing map and interaction analysis technology, it can more accurately reveal how neurons process complex spatial and temporal information and their interaction. In addition, by simultaneously processing spatial and temporal information, the present application improves experimental efficiency and data processing accuracy, providing a more accurate and comprehensive analysis tool for neuroscience research and clinical applications. These advantages make the present application have broad application prospects in the fields of neural coding research and treatment of neurodegenerative diseases. Compared with the prior art, the present application has significant technical advantages, especially in the following aspects:

[0092] (1) Joint measurement of spatial and temporal information

[0093] Disadvantages of the prior art: Current research usually measures spatial and temporal information separately, and evaluates the spatial dimension (such as position cell firing rate) or the temporal dimension (such as time cell firing rate) separately. This separate processing method cannot fully reflect the interaction of spatial and temporal information, and ignores their synchronicity and synergy in actual neural activity.

[0094] Advantages of the present application: The present application simultaneously measures and combines spatial and temporal information in the same map through the construction of a two-dimensional space-time firing map, which can fully capture the activity characteristics of neurons in the spatial and temporal dimensions. This method breaks through the limitations of traditional technology and can better reveal how neurons simultaneously process spatial and temporal information in actual tasks, thereby providing a more accurate neural coding model.

[0095] (2) Quantitative analysis of spatial and temporal interaction

[0096] Limitations of existing technologies: While some studies have indicated an interaction between spatial and temporal information, these studies primarily focus on the impact of a single dimension, lacking in-depth quantitative analysis of spatial-temporal interactions. Traditional research methods have not integrated spatial and temporal information into a holistic analysis, nor have they quantified their mutual influence.

[0097] Advantages of this invention: Based on a two-dimensional space-time firing map, this invention uses statistical analysis methods (such as correlation analysis and interaction strength calculation) to quantify the interaction relationship between spatial and temporal information, directly revealing their competition-integration mechanism in neural circuits. This method clarifies the interaction patterns of spatial and temporal information, thus providing a deeper understanding of neural coding mechanisms.

[0098] (3) Visualization of the space-time distribution map

[0099] The drawbacks of existing technologies: In traditional research, the firing patterns of neurons are usually presented in a single temporal or spatial dimension, failing to intuitively demonstrate how neurons fire under the interaction of space and time. This single-dimensional analysis method makes it difficult for researchers to fully understand the complexity of neural circuits.

[0100] Advantages of this invention: This invention provides a visualization method for spatial-temporal firing maps, which can intuitively display the firing characteristics of neurons in the spatial and temporal dimensions, facilitating researchers to quickly analyze and understand how neurons process both types of information simultaneously. This visualization not only improves the intuitiveness of data analysis but also promotes in-depth exploration of neural activity patterns.

[0101] (4) Wider range of application scenarios

[0102] Limitations of existing technologies: Although existing technologies have made progress in analyzing neuronal firing patterns, most studies are limited to a specific type of neuron or a specific experimental task, making it difficult to apply them broadly to the study of other types of neural circuits or neurodegenerative diseases.

[0103] Advantages of this invention: The two-dimensional space-time firing atlas of this invention is not only applicable to basic research in the field of neuroscience, but also has broad application prospects. It can be extended to the study of neurodegenerative diseases (such as Parkinson's disease and Alzheimer's disease), and helps to explore the functional impairment of neural circuits and their recovery mechanisms in these diseases. Furthermore, the universality and scalability of the method of this invention provide theoretical support for future neurorehabilitation technologies.

[0104] (5) Improve experimental efficiency and accuracy

[0105] Disadvantages of the prior art: In traditional neuroscience experiments, the analysis of spatial and temporal information often requires multiple independent steps, including separate recording and analysis of behavioral data and neural activity, which can lead to inconsistent data or missing important interaction information during the experiment.

[0106] Advantages of the present application: The present application simplifies the experimental process by using a two-dimensional spatial-temporal map for unified measurement and analysis, reducing errors and inconsistencies that may occur in multi-step analysis, and improving the efficiency and accuracy of the experiment. Through automated data processing and analysis, the present application can obtain more accurate results in a shorter time, improving experimental output and research progress.

[0107] Experimental verification

[0108] The present application has been verified by experiments of various one-dimensional linear behavioral paradigms, proving its feasibility, and the experimental results show that the method has significant effectiveness and practicality. The following are specific experimental and simulation results:

[0109] (1) Experimental verification and application

[0110] The method of the present application has been applied in multiple experimental tasks, especially in spontaneous running tasks in virtual reality environments, driven running tasks, and spontaneous movement on circular reality tracks. In the experiment, the firing patterns of neurons were recorded when the animal moved at different spatial positions and time points. By constructing a two-dimensional spatial-temporal firing map, we found that most hippocampal neurons showed obvious spatial-temporal firing fields, which could encode the spatial position and movement time of the animal simultaneously. In the experiment, we analyzed the spatial-temporal centroids at different speeds and measured the strength of the time variable on the space variable through the slope of the linear fitting of the spatial-temporal centroid, and found that most of the slopes were negative, as shown in Figure 9 , the abscissa represents the slope of the spatial-temporal centroid fitting, i.e. spatial centroid = slope x time centroid + intercept; the ordinate represents the significance level of the fitting (log p value, points above the black dotted line represent p < 0.05, i.e. neurons with significant spatial-temporal fitting); Figure 9 , left graph: virtual reality spontaneous running task; Figure 9 , middle graph: virtual reality driven running task; Figure 9 , right graph: spontaneous movement on a circular reality track. Blue represents neurons with significant speed-time fitting; green represents neurons with significant speed-space fitting; red represents neurons with significant speed-time and speed-space fitting.

[0111] (2) Spatial-temporal interaction drift without visual input

[0112] In further experiments, the spatiotemporal firing map of the present application was applied under the condition of no visual input to investigate the changes in the spatiotemporal interaction in the absence of visual information, see Figure 10 where each row is a neuron, and each column from left to right is a different task time in chronological order. The experimental results show that in this case, the spatiotemporal firing field exhibits a significant drift, especially the spatial information and temporal information present a more independent or loose interaction mode in the absence of visual feedback. However, despite this, the negative correlation between the spatiotemporal centroids is still maintained, further verifying that the present application can still effectively quantify the rules of spatial and temporal interaction in the absence of external visual input. This indicates that as the animal's movement speed changes, the interaction of spatial and temporal information in the spatiotemporal firing map exhibits a synergistic and competitive mechanism.

[0113] In summary, under multiple experimental conditions, the present application not only reveals how spatial information and temporal information interact in neuronal firing, but also further verifies the existence of competitive and integrated mechanisms. Understanding these mechanisms provides a new perspective on how spatial and temporal information jointly regulate behavior in neural networks in neuroscience, and also provides a new theoretical basis for treatment options for neurodegenerative diseases such as Parkinson's disease and Alzheimer's disease.

[0114] In addition, it should be noted that:

[0115] (1) The core of the present application is to construct a two-dimensional spatiotemporal firing map, but in some specific experiments, the following modified designs can be used as alternative solutions:

[0116] Multi-dimensional spatiotemporal map. If the experiment involves higher-dimensional spatial tasks (such as 3D spatial exploration tasks), the two-dimensional map can be extended to a three-dimensional or more dimensional spatiotemporal map. In this case, the construction method of the map can be adapted to different dimensional spatial requirements by adding additional dimensional information (such as height or depth, etc.).

[0117] Multi-channel data fusion map. If the experiment involves multiple neural regions (such as the hippocampus and different regions of the cortex participating in spatial tasks simultaneously), a more complex spatiotemporal firing map can be generated through multi-channel data fusion technology to better reveal the collaborative working mode between multiple brain regions.

[0118] (2) The present application can not only be used in neuroscience research to analyze the neural mechanisms of spatial and temporal coding, but also has the following potential uses:

[0119] Early diagnosis and intervention of cognitive disorders. By using the two-dimensional spatio-temporal firing pattern analysis of the present invention, it can be used for early detection and diagnosis of cognitive disorders (such as Alzheimer's disease or Parkinson's disease). By identifying abnormal firing patterns of neurons in spatial and temporal tasks, new ideas can be provided for early intervention of diseases.

[0120] Motor control and neurorehabilitation. The present invention can quantify the interaction of space and time in motor tasks, providing new techniques for the rehabilitation of motor disorders. For example, in the rehabilitation process of Parkinson's disease patients, by analyzing the spatio-temporal firing patterns of motor-visual feedback, personalized neurorehabilitation training programs can be designed.

[0121] Neural networks and artificial intelligence. The spatio-temporal interaction analysis method proposed by the present invention can provide a theoretical basis for the construction of neural network models. By drawing on the spatio-temporal information processing mechanism in biological neural networks, it can provide a reference for developing more efficient and intelligent artificial neural network models.

[0122] Education and virtual reality training. Using the analysis techniques of the present invention, more effective virtual reality (VR) or augmented reality (AR) training systems can be designed, especially in the application of spatial navigation and cognitive training. By tracking the spatio-temporal performance of learners in the VR environment in real time, personalized training optimization can be performed.

[0123] It should be noted that the present invention can be a method, a system, an apparatus and / or a computer program product. The computer program product can include a computer readable storage medium having computer readable program instructions stored therein for implementing various aspects of the present invention by a processor.

[0124] The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium can be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the above. More specific examples (a non-exhaustive list) of the computer readable storage medium include a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a hole in a raised structure, and any suitable combination of the above. The computer readable storage medium used here is not to be interpreted as a transitory signal per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (for example, optical pulses through an optical fiber cable), or electrical signals transmitted through a wire.

[0125] Computer readable program instructions described herein can be downloaded to respective computing / processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and / or a wireless network. The network can comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and / or edge servers. A network adapter card or network interface in each computing / processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing / processing device.

[0126] Computer readable program instructions for carrying out operations of the present application can be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer readable program instructions can execute entirely on the user's computing / processing device, partly on the user's computing / processing device, as a stand-alone software package, partly on the user's computing / processing device and partly on a remote computing / processing device or entirely on the remote computing / processing device or server. In the latter scenario, the remote computing / processing device can be connected to the user's computing / processing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computing / processing device, for example, through the Internet using an Internet Service Provider. In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) can execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present application.

[0127] The computer readable program instructions can also be loaded onto a computing / processing device, other programmable data processing apparatus, or other device to cause a series of operations to be performed on the computing / processing device, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computing / processing device, other programmable apparatus, or other device implement the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0128] These computer readable program instructions can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks. These computer readable program instructions can also be stored in a computer readable storage medium that can include a non-transitory computer readable storage medium that can be a computer- readable storage medium having no data, programs, program modules, e.g., instructions for operation, or digital content stored thereon or therein for a short time or not at all. The computer readable storage medium can also have instructions stored thereon or therein which may

[0129] The computer readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable data processing apparatus, or other device implement the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0130] The flow diagrams and block diagrams in the attached Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flow diagrams and block diagrams can represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical functions (‘instructions’). In some alternative implementations, the functions noted in the block can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks can sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and / or flowchart illustrations, and combinations thereof, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and

[0131] Having described various embodiments of the application, it is to be understood that the above description is meant to be illustrative only and not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art, without departing from the scope and spirit of the described embodiments. The selection of terms to be used in the description is intended to best explain the principles of the embodiments, the practical application, or technical improvement over the prior art, or to enable others skilled in the art to understand the embodiments disclosed herein. The scope of the application is defined by the claims appended hereto.

Claims

1. A method for spatial-temporal two-dimensional firing map analysis, characterized in that, The method comprises the following steps: S1, data acquisition and preprocessing: real-time acquisition of the neural activity data of the neurons of the measured animal in the spatial navigation task through the neural imaging technology, acquisition of the behavioral data of the measured animal, and preprocessing of the neural activity data and the behavioral data, wherein the behavioral data comprises spatial position information and time information; S2, two-dimensional space-time firing map construction: according to the acquired spatial position information and time information, the firing rate of each neuron at the corresponding spatial position and time point is calculated to obtain spatial dimension firing rate data and time dimension firing rate data, and a two-dimensional space-time firing map is constructed according to the spatial dimension firing rate data and the time dimension firing rate data S3, space-time interaction analysis: based on the two-dimensional space-time firing map, the interaction between the spatial position information and the time information is analyzed, the relationship between the space and the time is quantified by a statistical analysis method, and the features in the two-dimensional space-time firing map are extracted; S4, visualization and interpretation of data results: the two-dimensional space-time firing map is visualized to directly show the activity characteristics of the neurons in the spatial dimension and the time dimension; In step S2, the two-dimensional space-time firing map is constructed according to the spatial dimension firing rate data and the time dimension firing rate data, comprising: According to the spatial dimension firing rate data and the time dimension firing rate data, a two-dimensional space-time firing frequency matrix and a two-dimensional space-time total time length matrix are constructed; Based on the two-dimensional space-time firing frequency matrix and the two-dimensional space-time total time length matrix, a two-dimensional space-time firing rate matrix is constructed; The two-dimensional space-time firing rate matrix after the smoothing operation is taken as the two-dimensional space-time firing map by using a Gaussian filter to perform the smoothing operation on the two-dimensional space-time firing rate matrix; In step S3, based on the two-dimensional space-time firing map, the interaction between the spatial position information and the time information is analyzed, the relationship between the space and the time is quantified by a statistical analysis method, and the features in the two-dimensional space-time firing map are extracted, comprising: Find the space-time firing field in the two-dimensional space-time firing map, specifically: set a peak firing threshold, and take the continuous region greater than or equal to the peak firing threshold as the space-time firing field; According to the specified gradient, the velocity sampling is performed on the specified sampling speed on the two-dimensional space-time firing map to obtain the space-time firing trajectory under the sampling speed; According to the size of the space-time firing rate corresponding to each point on the line segment of the space-time firing trajectory under the sampling speed, the space-time centroid on the line segment of the space-time firing trajectory under the sampling speed is obtained; Based on the space-time centroids obtained under different speeds, the features in the two-dimensional space-time firing map are extracted.

2. The method of claim 1, wherein, In step S1, the neural activity data of the neurons of the measured animal in the spatial navigation task is acquired in real time through the neural imaging technology, comprising: The neural activity data of the neurons of the measured animal in the spatial navigation task is acquired in real time through the calcium imaging technology and the whole brain electro-physiological recording technology, and the specific steps are as follows: In the calcium imaging technique, the activity of neurons is recorded by using calcium ion indicators, in which the change of calcium ion concentration is used to reflect the firing activity of neurons; in the whole brain electrophysiological recording technique, the overall electrical activity of the brain region of the animal is recorded by implanting a microelectrode array.

3. The method of claim 1, wherein, The behavior data of the measured animal in step S1 includes: The spatial position and motion time of the measured animal are recorded by the behavior system to obtain spatial position information and time information, and the spatial position information and time information are taken as the behavior data of the measured animal.

4. The method of claim 1, wherein, The statistical analysis method includes at least one of correlation analysis and interaction strength calculation.

5. The method of claim 1, wherein, The features in the two-dimensional space-time firing map include at least one of firing rate distribution, interaction mode, and competition-integration mechanism.

6. The method of claim 1, wherein, In step S4, the two-dimensional space-time firing map is visualized, including: converting the two-dimensional space-time firing map into a heat map by a data visualization display and interpretation tool to realize the visualization of the two-dimensional space-time firing map.

7. A spatio-temporal two-dimensional firing map analysis system for implementing the method according to any one of claims 1 to 6, characterized in that including: The neural data acquisition module is used to acquire the neural activity data of the measured animal, and the neural data acquisition module includes a calcium imaging device and an electrophysiological recording device; The behavior recording module is used to synchronously acquire the behavior data of the measured animal, and the behavior data includes spatial position information and time information; The data processing and analysis module is used to realize the synchronization of the neural activity data and the behavior data, the construction of the two-dimensional space-time firing map, the spatial-time interaction analysis, and the statistical analysis of the results; The visualization and interpretation module is used to provide a data visualization display and interpretation tool, which is used to convert the two-dimensional space-time firing map into a heat map to realize the visualization of the two-dimensional space-time firing map; The computing platform includes a high-performance computing workstation, which is used for real-time or offline data analysis; The neural data acquisition module, the behavior recording module, the data processing and analysis module, the visualization and interpretation module, and the computing platform are in communication connection.

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