Space-time two-dimensional distribution map analysis method and system

Abstract

The invention provides a space-time two-dimensional distribution map analysis method and system. The method comprises the following steps: S1, data acquisition and preprocessing: acquiring and preprocessing neural activity data and behavioral data; s2, constructing a two-dimensional space-time distribution map: calculating the distribution rate of each neuron at the corresponding spatial position and time point, and constructing the two-dimensional space-time distribution map; s3, space-time interaction analysis: based on the two-dimensional space-time distribution 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 features in the two-dimensional space-time distribution map; and S4, visualization and interpretation of a data result: carrying out visualization processing on the two-dimensional space-time distribution graph. According to the method, the spatial information and the time information are combined into the same atlas for quantitative analysis, so that the interaction relationship between the space and the time is revealed, and more comprehensive and accurate neural activity characterization is provided.

Description

Technical Field

[0001] The present invention relates to the field of brain science and artificial intelligence technology, and specifically to a space-time two-dimensional emission spectrum analysis method and system. Background Art

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

[0003] However, existing neuroscience research usually measures spatial firing rate and temporal firing rate separately when measuring neural firing patterns of spatial and temporal information, and fails to comprehensively consider the interaction between these two dimensions. For example, classic spatial tasks (such as the study of place cells) usually focus on the firing rate of neurons at different spatial locations and use this to construct spatial firing maps; while temporal tasks (such as the study of time cells) focus on how neurons fire at different time points and establish temporal firing curves. Although these single-dimensional firing maps are of great significance in the study of spatial or temporal coding, they ignore the fact that spatial information and temporal information occur simultaneously and are interrelated.

[0004] Therefore, existing technologies are unable to simultaneously measure spatial and temporal information in the same atlas, resulting in the inability to fully reflect the common activity patterns of neurons in both temporal and spatial dimensions. Summary of the invention

[0005] In view of this, the present invention provides a space-time two-dimensional emission spectrum analysis method and system to at least solve the above-mentioned problems.

[0006] According to a first aspect of an embodiment of the present invention, a method for analyzing a space-time two-dimensional firing map is provided, comprising: S1, data acquisition and preprocessing: using neuroimaging technology to acquire the neural activity data of neurons of a tested animal in a spatial navigation task in real time, and at the same time acquiring the behavioral data of the tested animal, and preprocessing the neural activity data and the behavioral data, wherein the behavioral data comprises spatial position information and time information; S2, construction of a two-dimensional space-time firing map: according to the acquired spatial position information and time information, calculating the firing rate of each neuron at the corresponding spatial position and time point, obtaining the firing rate data of the spatial dimension and the firing rate data of the time dimension, and constructing a two-dimensional space-time firing map according to the firing rate data of the spatial dimension and the firing rate data of the time dimension; S3, space-time interaction analysis: based on the two-dimensional space-time firing map, analyzing the interaction between the spatial position information and the time information, quantifying the relationship between space and time by 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 to intuitively display the activity characteristics of neurons in the spatial dimension and the time dimension.

[0007] In one implementation, in step S1, neural activity data of neurons of the tested animal in a spatial navigation task are collected in real time by neuroimaging technology, including: neural activity data of neurons of the tested animal in a spatial navigation task are collected in real time by calcium imaging technology and whole-brain electrophysiological recording technology, and the specific steps are as follows: calcium imaging technology records the activity of neurons by using calcium ion indicators, wherein changes in calcium ion concentration in the calcium ion indicator are used to reflect the firing activity of neurons; whole-brain electrophysiological recording technology records the overall electrical activity of the animal's brain area by implanting a microelectrode array.

[0008] In another implementation, collecting behavioral data of the tested animal in step S1 includes: recording the spatial position and movement time of the tested animal through a behavioral system to obtain spatial position information and time information, and using the spatial position information and time information as the behavioral data of the tested animal.

[0009] In another implementation, in step S2, a two-dimensional space-time emission map is constructed according to the spatial dimension emission rate data and the time dimension emission rate data, including: constructing a two-dimensional space-time emission frequency matrix and a two-dimensional space-time total time length matrix according to the spatial dimension emission rate data and the time dimension emission rate data; constructing a two-dimensional space-time emission rate matrix based on the two-dimensional space-time emission frequency matrix and the two-dimensional space-time total time length matrix; smoothing the two-dimensional space-time emission rate matrix through a Gaussian filter, and using the two-dimensional space-time emission rate matrix after the smoothing operation as a two-dimensional space-time emission map.

[0010] In another implementation, in step S3, based on the two-dimensional space-time emission spectrum, the interaction between spatial position information and time information is analyzed, the relationship between space and time is quantified by statistical analysis methods, and features in the two-dimensional space-time emission spectrum are extracted, including: finding the space-time emission field in the two-dimensional space-time emission spectrum, specifically: setting a peak emission threshold, and taking a continuous area greater than or equal to the peak emission threshold as the space-time emission field; performing speed sampling on the two-dimensional space-time emission spectrum at a specified sampling speed according to a specified gradient to obtain a space-time emission trajectory at the sampling speed; obtaining the space-time centroid on the line segment of the space-time emission trajectory at the sampling speed according to the size of the space-time emission rate corresponding to each point on the line segment of the space-time emission trajectory at the sampling speed; and extracting features in the two-dimensional space-time emission spectrum based on the space-time centroid obtained at 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 spatial-temporal firing map include at least one of a firing rate distribution, an interaction pattern, and a competition-integration mechanism.

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

[0014] According to a second aspect of an embodiment of the present invention, a space-time two-dimensional discharge map analysis system is provided, comprising: a neural data acquisition module for collecting neural activity data of a tested animal, the neural data acquisition module comprising a calcium imaging device and an electrophysiological recording device; a behavioral recording module for synchronously collecting behavioral data of the tested animal, the behavioral data comprising spatial position information and time information; a data processing and analysis module for realizing synchronization of neural activity data and behavioral data, construction of a two-dimensional space-time discharge map, space-time interaction analysis and 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 is used to convert the two-dimensional space-time discharge map into a heat map to realize visualization processing of the two-dimensional space-time discharge map; a computing platform, comprising a high-performance computing workstation, the high-performance computing workstation is used for real-time or offline data analysis; wherein the neural data acquisition module, the behavioral recording module, the data processing and analysis module, the visualization and interpretation module and the computing platform are communicatively connected.

[0015] In summary, compared with the prior art, the greatest advantage of the solution of the present invention is that it simultaneously measures and fuses spatial and temporal information. The present invention can more accurately reveal how neurons process complex spatial and temporal information and their interactions through space-time emission maps and interaction analysis techniques. In addition, the present invention 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 applications. These advantages make the present invention have broad application prospects in the fields of neural coding research and neurodegenerative disease treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a flow chart of the steps of the method of the present invention;

[0017] Figure 2 For Figure 1 The corresponding overall flow chart of the method of the present invention;

[0018] Figure 3 A schematic diagram of a two-dimensional spatial-temporal firing spectrum of a neuron in the method of the present invention;

[0019] Figure 4 It is a schematic diagram of the space-time release field and different speed sampling of the method of the present invention;

[0020] Figure 5 Schematic diagram of the spatial-temporal centroid distribution of a neuron in the method of the present invention;

[0021] Figure 6 It is a schematic diagram of the relationship between the speed and the spatial centroid and the speed and the temporal centroid on the two-dimensional space-time spectrum of the method of the present invention;

[0022] Figure 7 A schematic diagram of the size and position distribution of the two-dimensional field of all neurons with significant space-time firing fields in a certain task of the method of the present invention;

[0023] Figure 8 It is a structural schematic diagram of the system of the present invention;

[0024] Fig. 9 It is a schematic diagram of the distribution of the spatial-temporal centroid fitting slope corresponding to the two-dimensional spatial-temporal firing map of neurons under various tasks of the method of the present invention;

[0025] Fig.10 It is a schematic diagram of the drift of the two-dimensional space-time firing maps of five hippocampal neurons with task time when there is no visual input in the method of the present invention. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] For the sake of ease of understanding, before describing the specific embodiments of the present invention in detail, the prior art of the present invention is first exemplarily described.

[0028] The prior art mainly includes the following types of research solutions related to the present invention:

[0029] Single-dimensional firing rate measurement method: Currently, the vast majority of neuroscience experiments still use methods that measure spatial firing rate and temporal firing rate separately. For example, place cell research often constructs a spatial firing map by recording the firing rate of neurons during animal movement. This method uses the animal's position as the horizontal coordinate and the firing frequency of neurons as the vertical coordinate to display the characteristics of neural firing at different positions. In time cell research, researchers construct a temporal firing curve by tracking the firing frequency of neurons as time advances. The horizontal coordinate is time and the vertical coordinate is the firing rate of neurons. However, these technical methods process spatial and temporal information separately and cannot reflect the interaction between them. In animal behavior, the interaction between spatial and temporal information is ubiquitous, and existing single-dimensional analysis methods cannot reveal how neurons process and integrate these two types of information simultaneously.

[0030] Research on the mutual influence of space and time: Recent studies have 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, most existing studies focus on the extent to which the firing of neurons in one dimension (such as the spatial dimension or the temporal dimension) is affected by another dimension, without systematically analyzing the interaction of spatial and temporal information as a whole. The limitation of this type of research is that the interaction between spatial information and temporal information is dynamic, and the interactive relationship between the two is not a simple linear influence, but a more complex mutual constraint and integration. Therefore, existing technologies and methods cannot effectively capture this dynamic interaction.

[0031] Multi-dimensional neural activity recording: In terms of neural imaging technology, in recent years, calcium imaging technology (such as two-photon calcium imaging) and electrophysiological technology (such as multi-channel electrode arrays) have been widely used to record neuronal activity. These technologies can record the firing patterns of multiple neurons at the same time, providing a 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, and lack tools to integrate spatial and temporal information at the same time.

[0032] Research based on the spatial-temporal interaction: Although existing research has gradually recognized the interactive relationship between space and time, research that truly integrates the two is still relatively rare. The few attempts simply conduct parallel experiments on spatial tasks and temporal tasks, trying to analyze the impact of the two in independent tasks, but have not comprehensively considered the interaction of spatial and temporal information under the same experimental framework.

[0033] In addition, recent studies have found that the one-dimensional linear track measures the influence of spatial release on task period (time) and the influence of temporal release on task distance (space), but does not directly measure the interaction of simultaneous spatial and temporal encoding.

[0034] In the prior art, for the hippocampus and other related brain regions (such as neurons encoding spatial or temporal information), studies usually measure 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 place 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 place cells on a 200 cm long track) and temporal information (such as the firing rate of time cells within a certain period of time during movement) are studied separately. Although this separate measurement method can reveal the activity pattern 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, measuring spatial and temporal information separately does not fully reflect the interaction of space and time in animal behavior. In the natural environment, spatial and temporal information often occur synchronously and influence each other during the movement and cognition of animals. For example, when performing spatial navigation, the interweaving of time and space cannot be ignored, and spatial and temporal information integrate and compete with each other. This phenomenon has not been fully quantified, resulting in insufficient understanding of the interaction mechanism of temporal and spatial information in neural activities by existing methods.

[0036] In addition, existing spatial firing rates and temporal firing rates are usually analyzed in one dimension alone (such as time or space), without considering the impact of the interaction between spatial and temporal dimensions and their comprehensive regulatory effects on neural activity. The limitations of these existing methods have prevented researchers from considering the overall regulatory effects of spatial-temporal information when analyzing the functions of neural circuits, and from gaining a deep understanding of the brain's fine mechanisms in processing complex spatial-temporal tasks.

[0037] In order to solve the problem of independence of spatial information and temporal information measurement in the prior art, the present invention proposes a spatial-temporal two-dimensional firing graph analysis method, which can simultaneously measure the firing rate of neurons in the spatial and temporal dimensions. Through this technology, the present invention combines spatial information and temporal information into the same graph for quantitative analysis, thereby revealing the interactive relationship between space and time, providing a more comprehensive and accurate representation of neural activity, and more accurately understanding how the brain processes spatial and temporal information.

[0038] The invention is mainly used in the field of neuroscience, especially for the analysis of neuronal activity in the hippocampus and other brain regions related to the encoding of spatial or temporal information. 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] See also Figure 1 , 2 The present invention provides a space-time two-dimensional emission spectrum analysis method comprising:

[0040] S1. Data collection and preprocessing: The neural activity data of the neurons of the tested animals in the spatial navigation task are collected in real time through neuroimaging technology. At the same time, the behavioral data of the tested animals are collected, and the neural activity data and behavioral data are preprocessed. The behavioral data includes spatial position information and time information.

[0041] S2. Construction of a two-dimensional space-time firing map: Based on the collected spatial position information and time information, the firing rate of each neuron at the corresponding spatial position and time point is calculated to obtain the spatial dimension firing rate data and the time dimension firing rate data, and a two-dimensional space-time firing map is constructed based on the spatial dimension firing rate data and the time dimension firing rate data;

[0042] S3, space-time interaction analysis: Based on the two-dimensional space-time emission map, analyze the interaction between spatial position information and time information, quantify the relationship between space and time through statistical analysis methods, and extract features from the two-dimensional space-time emission map;

[0043] S4. Visualization and interpretation of data results: Visualize the two-dimensional space-time firing map to intuitively display the activity characteristics of neurons in the spatial and temporal dimensions.

[0044] The spatial-temporal two-dimensional firing pattern analysis method of the present invention integrates spatial and temporal information to create a unified firing pattern, directly measuring the interaction between spatial and temporal information. This method of the present invention breaks through the limitation of the prior art of processing spatial information and temporal information separately, and can fully reflect the firing pattern of neurons on multi-dimensional information, revealing the competition and integration mechanism of spatial and temporal information in neural activities.

[0045] The method of the present invention can more accurately understand how neurons jointly encode information in space and time, and how they interact with each other.

[0046] Furthermore, the method of the present invention can provide new ideas for exploring how the brain processes complex spatial and temporal information, and provide an effective tool for multi-dimensional data analysis in neuroscience research.

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

[0048] Optionally, collecting behavioral data of the tested animal in step S1 includes: recording the spatial position and movement time of the tested animal through a behavioral system to obtain spatial position information and time information, and using the spatial position information and time information as the behavioral data of the tested animal.

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

[0050] Optionally, in step S3, based on the two-dimensional space-time emission spectrum, the interaction between spatial position information and time information is analyzed, the relationship between space and time is quantified by statistical analysis methods, and features in the two-dimensional space-time emission spectrum are extracted, including: finding the space-time emission field in the two-dimensional space-time emission spectrum, specifically: setting a peak emission threshold, and taking a continuous area greater than or equal to the peak emission threshold as the space-time emission field; performing speed sampling on the two-dimensional space-time emission spectrum at a specified gradient for a specified sampling speed to obtain a space-time emission trajectory at the sampling speed; obtaining the space-time centroid on the line segment of the space-time emission trajectory at the sampling speed according to the size of the space-time emission rate corresponding to each point on the line segment of the space-time emission trajectory at the sampling speed; and extracting features in the two-dimensional space-time emission spectrum based on the space-time centroid obtained at 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 spatial-temporal firing map include at least one of a firing rate distribution, an interaction pattern, and a competition-integration mechanism.

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

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

[0055] The present invention aims to achieve a two-dimensional joint measurement of the spatial and temporal firing rates of neurons and quantify the interaction of spatial and temporal information through a new technical method. This solution integrates spatial information and temporal information into a two-dimensional space-time firing map through a series of steps, which can accurately measure the spatial and temporal firing patterns of neurons in complex behavioral tasks. The following is a detailed description of the technical solution, see Figure 1 , 2 .

[0056] S1. Data collection and preprocessing

[0057] In the implementation process of the present invention, data acquisition is a basic step. The present invention 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 the spatial navigation task, thereby improving the comprehensiveness and accuracy of the data.

[0058] (1) Neural activity data collection

[0059] Calcium imaging technology: 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-resolution 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 the brain region is recorded. Compared with calcium imaging, electrophysiological technology provides higher temporal resolution and can more accurately capture the instantaneous activity of neurons.

[0061] (2) Behavioral data synchronization

[0062] While collecting neural activity data, the behavioral system records the spatial position (such as coordinate changes in one-dimensional space) and movement time (such as time stamps from the start of the experiment to each moment) of the animal being tested. By synchronizing the time of behavioral data and neural activity data, we ensure that there is consistent data pairing in both the spatial and temporal dimensions, providing a basis for the subsequent construction of a two-dimensional emission map.

[0063] S2. Construction of two-dimensional space-time emission map

[0064] This step is one of the core technologies of the present invention, and its purpose is to integrate the emission rates of spatial information and temporal information into a two-dimensional emission map.

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

[0066] Specifically for a neuron, first construct a two-dimensional space-time firing frequency matrix, find the spatial position and movement time corresponding to a certain firing of the neuron in a certain experiment, and then the firing frequency 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 satisfies the corresponding spatial position and time node at the same time during the movement;

[0068] Then the two-dimensional space-time emission rate matrix is ​​the quotient matrix (corresponding elements divided) of the two-dimensional space-time emission frequency matrix and the two-dimensional space-time total time length matrix.

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

[0070] See also Figure 3 , a Gaussian filter can be used to smooth the two-dimensional space-time firing rate matrix, and the two-dimensional space-time firing rate matrix after the smoothing operation is used as a two-dimensional space-time firing map.

[0071] S3. Spatial-temporal interaction analysis

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

[0073] It should be noted that it is not a direct measurement of the correlation or mutual information of the space-time field on the two-dimensional space-time emission map, but a measurement of the interactive relationship between the space-time centroids at different speeds.

[0074] Specifically, first find the space-time emission field in the two-dimensional space-time emission map. For example, take 30% of the peak emission as the peak emission threshold, and the continuous area with more than or equal to 30% peak emission can be used as the space-time emission field, see Figure 4 The left picture in is the (two-dimensional) space-time emission field.

[0075] Secondly, based on the actual movement in a certain experiment, the possible range of movement speed is estimated, and then the speed is sampled according to a certain gradient, such as from 5cm / s to 30cm / s, and the speed is sampled every 2.5cm / s on the two-dimensional space-time emission spectrum. For a certain sampling speed, the space-time relationship at this speed will be a ray starting from the origin (the origin of the two-dimensional space-time spectrum). This ray will intersect with the space-time emission field (the continuous area with more than or equal to 30% peak emission) to obtain a line segment, which represents the space-time emission trajectory at this speed, see Figure 4 The right picture in the figure shows sampling at 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 velocity line segment can be obtained. Figure 5 Schematic diagram of the spatial-temporal centroid distribution of a neuron, where white points represent negative correlations.

[0077] Finally, based on the space-time centroids obtained at different speeds, the competition and integration mechanisms are quantified, see Figure 5Specifically, the relationship between the space-time centroids can be measured by methods such as Pearson correlation analysis, 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 center of mass in space and the velocity, or the relationship between the center of mass in time and the velocity can also be measured, see Figure 6 These analyses contribute to our understanding of how neurons integrate and process multiple pieces of information during complex spatial and temporal tasks.

[0079] S4. Visualization and interpretation of data results

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

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

[0082] Through maps and analysis results, we reveal how neurons process spatial and temporal information simultaneously, and further explore their roles in neural circuits.

[0083] See also Figure 8 The present invention also provides a space-time two-dimensional emission spectrum analysis system, which is used to implement the corresponding methods in the above-mentioned multiple method embodiments and has the beneficial effects of the corresponding method embodiments. The system includes:

[0084] A neural data acquisition module, used to collect neural activity data of the tested animal, the neural data acquisition module includes a calcium imaging device and an electrophysiological recording device;

[0085] The behavioral recording module is used to synchronously collect the behavioral data of the tested animals, and the behavioral data includes spatial position information and time information;

[0086] Data processing and analysis module, used to achieve synchronization of neural activity data and behavioral data, construction of two-dimensional space-time emission maps, space-time interaction analysis and statistical analysis of results;

[0087] A visualization and interpretation module is used to provide a visualization display and interpretation tool for data. The visualization display and interpretation tool for data is used to convert a two-dimensional space-time emission map into a heat map to realize visualization processing of the two-dimensional space-time emission map;

[0088] Computing platform, including high performance computing workstations, which are used for real-time or offline data analysis;

[0089] Among them, the neural data acquisition module, behavioral recording module, data processing and analysis module, visualization and interpretation module and computing platform are communicated and connected.

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

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

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

[0093] Disadvantages of existing technologies: Current studies usually measure spatial information and temporal information separately, evaluating spatial dimensions (such as the firing rate of place cells) or temporal dimensions (such as the firing rate of time cells) separately. This separate processing method cannot fully reflect the interaction between spatial and temporal information, and ignores their synchronization and synergy in actual neural activities.

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

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

[0096] Disadvantages of existing technologies: Although some existing studies have shown that there is a certain interaction between space and time information, these studies mostly focus on the impact of a single dimension and lack in-depth quantitative analysis of space-time interaction. Traditional research methods do not integrate space and time information into a whole for analysis, nor do they quantify the mutual influence between them.

[0097] Advantages of the present invention: Based on the two-dimensional space-time emission map, the present invention uses statistical analysis methods (such as correlation analysis, interaction strength calculation, etc.) to quantify the interaction between space and time information, and directly reveals their competition-integration mechanism in the neural circuit. Through this method, the interaction pattern of space and time information can be clarified, thereby providing a deeper understanding of the neural coding mechanism.

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

[0099] Disadvantages of existing technologies: In traditional research, the firing patterns of neurons are usually presented in a single time dimension or space dimension, which cannot intuitively show how neurons fire under the interaction of space and time. Due to the single-dimensional analysis method, it is difficult for researchers to fully understand the complexity of neural circuits.

[0100] Advantages of the present invention: The present invention provides a visualization method for space-time firing maps, which can intuitively display the firing characteristics of neurons in the spatial and temporal dimensions, making it easier for researchers to quickly analyze and understand how neurons process these two 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 application scenarios

[0102] Disadvantages of existing technologies: Although existing technologies have made progress in the analysis of neuronal firing patterns, most studies are limited to a specific type of neurons or specific experimental tasks and are difficult to be widely applied to the study of other types of neural circuits or neurodegenerative diseases.

[0103] Advantages of the present invention: The two-dimensional space-time emission map of the present invention is not only suitable for basic research in the field of neuroscience, but also has a wide range of application prospects. It can be extended to the study of neurodegenerative diseases (such as Parkinson's disease, Alzheimer's disease, etc.), and helps to explore the functional disorders of neural circuits in diseases and their recovery mechanisms. In addition, the universality and extensibility of the method of the present invention provide theoretical support for future neurorehabilitation technology.

[0104] (5) Improve experimental efficiency and accuracy

[0105] Disadvantages of existing technologies: 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 may lead to inconsistent data or missing important interactive information during the experiment.

[0106] Advantages of the present invention: The present invention simplifies the experimental process through unified measurement and analysis of two-dimensional space-time maps, reduces errors and inconsistencies that may occur in multi-step analysis, and improves the efficiency and accuracy of the experiment. Through automated data processing and analysis, the present invention can obtain more accurate results in a shorter time, improving experimental output and research progress.

[0107] Experimental verification

[0108] The present invention has been verified by experiments of multiple 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 invention has been applied in multiple experimental tasks, especially in experiments such as spontaneous running tasks in virtual reality environments, driven running tasks, and spontaneous movement on circular realistic tracks, in which neuronal firing was recorded. In the experiment, the firing patterns of neurons were recorded synchronously when the animals were active at different spatial positions and time points. By constructing a two-dimensional space-time firing map, we found that most hippocampal neurons showed obvious space-time firing fields, which could simultaneously encode the spatial position and movement time of the animal. During the experiment, we analyzed the space-time centroid at different speeds, and measured the intensity of the effect of the time variable on the space variable by the slope of the linear fit of the space-time centroid. It was found that most slopes were negative, see Fig. 9 , the horizontal axis represents the slope of the space-time centroid fitting, that is, the space centroid = slope × time centroid + intercept; the vertical axis represents the significance level of the fitting (logarithmic p value, the point above the black dotted line represents p < 0.05, that is, the neuron with significant space-time fitting); Fig. 9 The middle left picture shows: Virtual reality spontaneous running task; Fig. 9 The middle picture shows: VR-driven running task; Fig. 9 The middle right picture shows spontaneous motion on a circular real track. Blue represents neurons with significant speed-time fit; green represents neurons with significant speed-space fit; red represents neurons with significant speed-time and speed-space fit.

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

[0112] In further experiments, the spatial-temporal firing maps of the present invention were applied to conditions without visual input to examine how spatial-temporal interactions change in the absence of visual information, see Fig.10 , where each row is a neuron and each column from left to right is a different task moment in chronological order. The experimental results show that in this case, the space-time discharge field shows obvious drift, especially the spatial information and time information show a more independent or loose interaction mode in the environment without visual feedback. However, despite this, the negative correlation between the space-time centroids is still maintained, which further verifies that the present invention can still effectively quantify the law of space-time interaction in the absence of external visual input. This shows that as the animal's movement speed changes, the interaction of spatial and temporal information shows a synergistic and competitive mechanism in the space-time discharge map.

[0113] In summary, under multiple experimental conditions, the present invention not only reveals how spatial information and temporal information interact in neuronal firing, but also further verifies the existence of competition and integration mechanisms. The understanding of these mechanisms provides a new perspective in neuroscience on how space and time jointly regulate behavior in neural networks, and also provides a new theoretical basis for the treatment of neurodegenerative diseases (such as Parkinson's disease, Alzheimer's disease, etc.).

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

[0115] (1) The core of the present invention is to construct a two-dimensional space-time emission map, but in some specific experiments, the following modified designs can be used as alternatives:

[0116] Multidimensional space-time maps. If the experiment involves higher-dimensional spatial tasks (such as 3D space exploration tasks), the two-dimensional map can be expanded into a three-dimensional or higher-dimensional space-time map. In this case, the map construction method can adapt to the spatial requirements of different dimensions by adding additional dimensional information (such as height or depth, etc.).

[0117] Multi-channel data fusion map. If the experiment involves multiple neural areas (for example, different areas of the hippocampus and cortex are involved in spatial tasks at the same time), multi-channel data fusion technology can be used to generate more complex spatial-temporal emission maps to better reveal the collaborative working mode between multiple brain regions.

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

[0119] Early diagnosis and intervention of cognitive impairment. The two-dimensional spatial-temporal firing pattern analysis of the present invention can be used for early detection and diagnosis of cognitive impairment (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 between space and time in motor tasks, providing new technologies for the rehabilitation of movement disorders. For example, in the rehabilitation process of Parkinson's patients, by analyzing the spatial-temporal emission pattern of motor-visual feedback, a personalized neurorehabilitation training program can be designed.

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

[0122] Education and virtual reality training. Using the analysis technology of the present invention, more effective virtual reality (VR) or augmented reality (AR) training systems can be designed, especially in spatial navigation and cognitive training applications. Personalized training optimization can be performed by real-time tracking of learners' spatial-temporal performance in VR environments.

[0123] It should be noted that the present invention may be a method, a system, an apparatus and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present invention.

[0124] Computer readable storage medium can be a tangible device that can hold and store instructions used by an instruction execution device. Computer readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. More specific examples (non-exhaustive list) of computer readable storage medium include: a portable computer disk, 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 disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, for example, a punch card or a convex structure in a groove on which instructions are stored, and any suitable combination thereof. The computer readable storage medium used here is not interpreted as a transient signal itself, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagated by a waveguide or other transmission medium (for example, a light pulse by an optical fiber cable), or an electrical signal transmitted by a wire.

[0125] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0126] The computer program instructions for performing the operation of the present invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, Python, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed entirely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be personalized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present invention.

[0127] Various aspects of the present invention are described herein with reference to the flow charts and / or block diagrams of the methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each box of the flow chart and / or block diagram and the combination of each box in the flow chart and / or block diagram can be implemented by computer-readable program instructions.

[0128] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0129] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0130] The flow charts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the systems, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a part of a module, a program segment or an instruction, and a part of the module, a program segment or an instruction contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions. It is well known to those skilled in the art that it is equivalent to implement it by hardware, implement it by software, and implement it by combining software and hardware.

[0131] Embodiments of the present invention have been described above, and the above description is exemplary, 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 used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the marketplace, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein. The scope of the present invention is defined by the appended claims.

Claims

1. A space-time two-dimensional emission spectrum analysis method, characterized in that: include: S1. Data collection and preprocessing: The neural activity data of the neurons of the tested animals in the spatial navigation task are collected in real time through neuroimaging technology. At the same time, the behavioral data of the tested animals are collected, and the neural activity data and behavioral data are preprocessed. The behavioral data includes spatial position information and time information. S2. Construction of a two-dimensional space-time firing map: Based on the collected spatial position information and time information, the firing rate of each neuron at the corresponding spatial position and time point is calculated to obtain the spatial dimension firing rate data and the time dimension firing rate data, and a two-dimensional space-time firing map is constructed based on 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 emission map, analyze the interaction between spatial position information and time information, quantify the relationship between space and time through statistical analysis methods, and extract features from the two-dimensional space-time emission map; S4. Visualization and interpretation of data results: Visualize the two-dimensional space-time firing map to intuitively display the activity characteristics of neurons in the spatial and temporal dimensions.

2. The method according to claim 1, characterized in that In step S1, the neural activity data of the neurons of the tested animal in the spatial navigation task are collected in real time by using the neuroimaging technology, including: The neural activity data of the neurons of the tested animals in the spatial navigation task were collected in real time by using calcium imaging technology and whole-brain electrophysiological recording technology. The specific steps are as follows: Calcium imaging technology records the activity of neurons by using calcium ion indicators, where changes in calcium ion concentration in the calcium ion indicator are used to reflect the firing activity of neurons; Whole-brain electrophysiological recording technology records the overall electrical activity of an animal's brain area by implanting a microelectrode array.

3. The method according to claim 1, characterized in that: The behavioral data collected from the tested animal in step S1 includes: The spatial position and movement time of the tested animal are recorded by the behavioral system to obtain spatial position information and time information, which are used as behavioral data of the tested animal.

4. The method according to claim 1, characterized in that: In step S2, a two-dimensional space-time emission map is constructed according to the spatial dimension emission rate data and the temporal dimension emission rate data, including: According to the spatial dimension firing rate data and the temporal 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 is ​​smoothed by a Gaussian filter, and the two-dimensional space-time firing rate matrix after the smoothing operation is used as a two-dimensional space-time firing map.

5. The method according to claim 4, characterized in that In step S3, based on the two-dimensional space-time emission map, the interaction between the spatial position information and the time information is analyzed, the relationship between space and time is quantified by a statistical analysis method, and the features in the two-dimensional space-time emission map are extracted, including: Find the space-time emission field in the two-dimensional space-time emission map, specifically: set the peak emission threshold, and take the continuous area greater than or equal to the peak emission threshold as the space-time emission field; Performing speed sampling on a two-dimensional space-time emission map at a specified sampling speed according to a specified gradient to obtain a space-time emission trajectory at 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 at the sampling speed, the space-time centroid on the line segment of the space-time firing trajectory at the sampling speed is obtained; Based on the space-time centroids obtained at different speeds, features in the two-dimensional space-time emission map are extracted.

6. The method according to claim 5, characterized in that The statistical analysis method includes at least one of correlation analysis and interaction strength calculation.

7. The method according to claim 5, characterized in that The features in the two-dimensional spatial-temporal firing map include at least one of a firing rate distribution, an interaction pattern, and a competition-integration mechanism.

8. The method according to claim 1, characterized in that In step S4, the two-dimensional space-time emission map is visualized, including: The two-dimensional space-time emission map is converted into a heat map through data visualization and interpretation tools to achieve visualization of the two-dimensional space-time emission map.

9. A space-time two-dimensional emission spectrum analysis system, characterized in that: include: A neural data acquisition module, used to collect neural activity data of the tested animal, the neural data acquisition module includes a calcium imaging device and an electrophysiological recording device; The behavioral recording module is used to synchronously collect the behavioral data of the tested animals, and the behavioral data includes spatial position information and time information; Data processing and analysis module, used to achieve synchronization of neural activity data and behavioral data, construction of two-dimensional space-time emission maps, space-time interaction analysis and statistical analysis of results; A visualization and interpretation module is used to provide a visualization display and interpretation tool for data. The visualization display and interpretation tool for data is used to convert a two-dimensional space-time emission map into a heat map to realize visualization processing of the two-dimensional space-time emission map; Computing platform, including high performance computing workstations, which are used for real-time or offline data analysis; Among them, the neural data acquisition module, behavioral recording module, data processing and analysis module, visualization and interpretation module and computing platform are communicated and connected.

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