Neural activity real-time monitoring system based on cerebral cortex endogenous signal

Abstract

The invention discloses a neural activity real-time monitoring system based on cerebral cortex endogenous signals, and belongs to the technical field of cerebral cortex neural activity monitoring and analysis, the neural activity real-time monitoring system comprises a hardware part and a software part, and the hardware part comprises an animal head flexible fixing device and a camera fixing and adjusting support; and the software part comprises visual stimulation control software, an analog signal receiver, data acquisition control software and online data analysis software which are connected in sequence. According to the neural activity real-time monitoring system based on the cerebral cortex endogenous signals, cerebral cortex imaging of large animals is achieved, the functions of long time history, large scale (2-5 cm), long working focal length (5-50 cm), multiple working angles, online multi-task comparative analysis and the like are achieved, and compared with the prior art, the neural activity real-time monitoring system based on the cerebral cortex endogenous signals has the advantages that the neural activity real-time monitoring system based on the cerebral cortex endogenous signals is more accurate. The system has remarkable advantages in the aspects of imaging quality and operation convenience, and can be widely applied to the field of neuroscience research.

Description

Technical Field

[0001] The present invention relates to the technical field of cerebral cortex neural activity monitoring and analysis, and in particular to a real-time neural activity monitoring system based on cerebral cortex endogenous signals. Background Art

[0002] With the proposal and implementation of the "China Brain Project", research related to cognitive neuroscience has received great attention, and the establishment of a brain research technology platform is crucial. In order to observe the brain's activities in real time when processing different tasks, and then accurately locate the functional areas of the brain, cortical imaging technology has been widely used in the field of brain function research.

[0003] However, current cortical imaging technology is more targeted at small experimental animals, with a small imaging field of view and no need to consider the angle of the animal's head. The brain size of some large animals, including primates (macaques), is much larger than that of rodents (mice, rats). Traditional imaging equipment for rodents is difficult to meet the brain imaging needs of large animals such as macaques.

[0004] In addition, existing imaging systems do not have the ability to perform real-time online analysis of the collected image data, and can only perform systematic offline analysis, and are unable to quickly adjust experimental parameters according to actual conditions. Summary of the invention

[0005] The purpose of the present invention is to provide a real-time monitoring system for neural activity based on endogenous signals of the cerebral cortex, which realizes the imaging of the cerebral cortex of large animals and has the functions of long time course, large scale (2-5cm), long working focal length (5-50cm), multiple working angles and online multi-task comparative analysis. Compared with the existing technology, this system has significant advantages in imaging quality and ease of operation, and can be widely used in the field of neuroscience research.

[0006] To achieve the above-mentioned purpose, the present invention provides a real-time monitoring system for neural activity based on endogenous signals of the cerebral cortex, including a hardware part and a software part, wherein the hardware part includes a flexible fixing device for the animal head, a camera fixing and adjustment bracket; the software part includes a visual stimulation control software, an analog signal receiver, an online data analysis software, and a data acquisition control software connected in sequence.

[0007] Preferably, the flexible fixing device for the animal skull consists of a base, a connecting arm, a head clamp, and a skull pin. The base is fixed on the laboratory table, the connecting arm connects the base and the head clamp, three skull pins are installed on the head clamp, a pressure knob is provided on the outer side of the skull pin, and a spring lock is provided on the head clamp.

[0008] Preferably, the camera fixing and adjusting bracket is composed of a base rod, a first sliding locking block, a connecting piece, a crossbeam rod, a second sliding locking block, a universal ball head, a handle, and an X / Y / Z-axis manual translation stage.

[0009] Preferably, the base rod is fixed on the laboratory table, a first sliding locking block is provided on the base rod, the right side of the first sliding locking block is connected to the crossbeam through a connecting piece, and a second sliding locking block is provided on the crossbeam.

[0010] Preferably, a universal ball head is provided on the second sliding locking block, a handle is provided at the bottom of the universal ball head, one side of the handle is connected to an X / Y / Z-axis manual translation stage, and a camera is fixed on the clamping piece of the X / Y / Z-axis manual translation stage.

[0011] Preferably, the visual stimulation control software is installed on the main control computer a, the data acquisition control software and the online data analysis software are installed on the main control computer b, the analog signal receiver is a NI-USB device, and the USB port and AI port of the NI-USB device are electrically connected to the main control computer a and the main control computer b respectively.

[0012] Preferably, the data acquisition control software sets basic acquisition parameters of the camera, records the cerebral cortical activity signal, and simultaneously receives external input signals to control the start of recording of the camera.

[0013] Preferably, the online data analysis software reads the stored image data, and finally obtains the activity difference of the cerebral cortex under different stimulation conditions through analysis, and displays it online in the form of a graph.

[0014] Therefore, the present invention adopts the above-mentioned real-time monitoring system of neural activity based on endogenous signals of cerebral cortex, which uses a skull fixing bracket to firmly fix the animal skull at any angle, and adjusts the angle between the camera and the animal head through multiple mechanical components, so as to achieve fast focusing and stable long-term imaging of the cortex with a large field of view. While collecting endogenous signals of the animal cerebral cortex, multi-threaded software is used to complete online data analysis, help quickly determine the functional areas of the cerebral cortex, and achieve real-time monitoring and analysis of neural activity.

[0015] It also has the following advantages: (1) The imaging field of view is large, the working focal length is long, and the imaging camera is easy to set up, which can quickly and conveniently collect a wide range of cerebral cortical activities; (2) The device has a wide range of angle adjustment, and can achieve precise focus on different brain areas at any angle, making it suitable for imaging large animals with cerebral cortex at different angles; (3) The data acquisition system can monitor the state of the cortex in real time and promptly detect unexpected situations during the experiment; (4) The data acquisition system can analyze the response characteristics of the cortex online, making it easy to quickly explore experimental parameters and change experimental conditions in a timely manner; (5) The equipment adopts modular design, which is easy to replace.

[0016] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a structural schematic diagram of an embodiment of a real-time monitoring system for neural activity based on endogenous signals of cerebral cortex of the present invention; Figure 2 It is a schematic diagram of the process of realizing online data analysis by the software part of the present invention; Figure 3 is a distribution diagram of the brightness values ​​of all pixels in the C2-C1 original image of the present invention; Figure 4 The present invention calculates Figure 3 Distribution of standard deviation (sd) of median brightness values; Figure 5 is a distribution diagram of brightness values ​​greater than or less than 2sd in the present invention; Figure 6 is a distribution diagram of brightness values ​​after transformation in the present invention; Figure 7 It is the enhanced image finally obtained in the present invention.

[0018] Reference numerals 1. Laboratory table; 2. Base; 3. Connecting arm; 4. Spring lock; 5. Head clamp; 6. Skull pin; 7. Pressure knob; 8. Base rod; 9. First sliding locking block; 10. Connecting piece; 11. Crossbeam rod; 12. Second sliding locking block; 13. Universal ball head; 14. Handle; 15. X / Y / Z axis manual translation stage. DETAILED DESCRIPTION

[0019] The technical solution of the present invention is further described below through the accompanying drawings and embodiments.

[0020] Unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0021] Embodiment 1 The present invention provides a real-time monitoring system for neural activity based on endogenous signals of cerebral cortex, including hardware and software parts, such as Figure 1 As shown, the hardware part includes a flexible fixing device for the animal head, a camera fixing and an adjusting bracket.

[0022] The animal head flexible fixing device consists of a base 2, a connecting arm 3, a head clamp 5, and a skull nail 6. The base 2 is fixed on the experimental table 1, and the connecting arm 3 connects the base 2 and the head clamp 5. The angle and length of the connecting arm 3 can be adjusted to ensure the flexibility of the skull position.

[0023] Three skull pins 6 are mounted on the head clamp 5, and a pressure knob 7 is provided on the outside of the skull pins 6. The head clamp 5 is provided with a spring lock 4. Pull up the spring lock 4, expand and contract the head clamp 5 to a width close to the size of the skull, and after determining the fixing position of the skull pins 6, tighten the pressure knob 7 to fix the skull stably and firmly. The position selection of the three skull pins 6 is flexible, ensuring that the cortex of any brain area can be fully exposed.

[0024] The camera fixing and adjusting bracket is composed of a base rod 8, a first sliding locking block 9, a connecting piece 10, a crossbeam rod 11, a second sliding locking block 12, a universal ball head 13, a handle 14, and an X / Y / Z axis manual displacement stage 15.

[0025] The base rod 8 is fixed on the experimental table 1 . A first sliding locking block 9 is provided on the base rod 8 . The right side of the first sliding locking block 9 is connected to a crossbeam 11 through a connecting piece 10 . A second sliding locking block 12 is provided on the crossbeam 11 .

[0026] A universal ball head 13 is provided on the second sliding locking block 12 , a handle 14 is provided at the bottom of the universal ball head 13 , one side of the handle 14 is connected to an X / Y / Z-axis manual translation stage 15 , and a camera is fixed on the clamping piece of the X / Y / Z-axis manual translation stage 15 .

[0027] By adjusting the position and rotation angle of each component of the camera holder and the bracket, three-axis horizontal movement can be performed. The position and angle of the camera lens can be adjusted arbitrarily to ensure that its focal plane is parallel to the cortex of each brain area, thereby achieving clear imaging of neuronal activities in different cortical regions.

[0028] The software part includes visual stimulation control software, analog signal receiver, data acquisition control software, and online data analysis software, which are connected in sequence. The visual stimulation control software is installed on the main control computer a, the data acquisition control software and the online data analysis software are installed on the main control computer b, and the analog signal receiver is a NI-USB device, which is electrically connected to the main control computer a and the main control computer b respectively.

[0029] The open source stimulus playback software Monkeylogics installed on the main control computer a controls the type of visual stimulation, the start time, playback duration, and number of cycles of each stimulus playback; and sends analog signals to the main control computer b through the NI-USB device connected to it. The self-developed data acquisition control software in the main control computer b confirms that the received analog signal reaches the preset voltage threshold, and then starts the camera connected to it for image acquisition. The camera is equipped with an additional lens focusing component, which can adjust the final object distance (the distance between the lens and the cortex after focusing) by adjusting the distance between the camera port and the lens port. The camera's shooting frequency (the number of image frames recorded per second) and the single recording duration are controlled by the data acquisition control software.

[0030] In addition to receiving external analog signal input to start camera recording, the data acquisition control software can view the real-time image in the imaging window for focusing the camera lens, and can manually save the image in a single camera lens.

[0031] The acquired images will be stored in the specified folder in the npy format according to the corresponding stimulation conditions and the order of acquisition.

[0032] While the camera is collecting data, the online data analysis software will use a multi-threaded approach to analyze the collected image data according to the preset analysis requirements. If two sets of data are selected for comparison, each set of data corresponds to the images collected under the specified stimulation conditions. Through matrix operations such as accumulation, averaging, subtraction, dot division, and numerical normalization of the image two-dimensional matrix, the activity differences of the cortex under different stimulation conditions are obtained, and finally displayed online in the form of a graph. The software will automatically perform signal enhancement processing on the image to make the brain signal more prominent.

[0033] The analysis process does not affect the camera's data collection. In addition, after each round of data collection (all stimulus conditions are played in full), the analysis software can automatically update the results and display the new results on the interface. The software also has the function of loading and viewing previously saved image data, and can batch save npy format data as mat files.

[0034] The software part has the following functions: 1. Camera basic acquisition parameter settings: 1) The camera takes photos at its maximum shooting frequency (e.g. 52 frames / second) and saves all photos: 2) Set the duration of each acquisition (e.g. 4 seconds); 3) Set the acquisition frequency of the output image (such as 4 frames / second).

[0035] 2. Receive external input signals and control the camera to start recording: The software monitors the trigger signal sent by the NI-USB device in real time. When the signal voltage reaches the threshold, the camera starts recording. When the camera imaging time reaches the acquisition time (such as 4 seconds), the camera stops acquiring and enters the waiting state until the next trigger signal arrives.

[0036] 3. Data storage: 1) Several conditions (number of cases) are set in advance in the software program; 2) According to the number of situations, the stored image data is numbered. For example, if the number of situations is 5, when the camera receives the first trigger signal, the first image is stored and named T1_C1_F1, the second is T1_C1_F2, and so on until T1_C1_F208; When the camera receives the second trigger signal, the first picture is stored and named T1_C2_F1, the second is T1_C2_F2, and so on until T1_C2_F208; When the camera receives the sixth trigger signal, the first picture is stored as T1_C6_F1, the second as T1_C6_F2, and so on until T1_C6_F208.

[0037] 4. Realize online data analysis and result display: The flowchart for realizing online data analysis is as follows: Figure 2 shown.

[0038] 1) Average the images collected each time: If the acquisition frequency set in the interface is 4 frames / second and the acquisition time is 4 seconds: a total of 4×52=208 images are collected, and 208 / (4 frames / second*4 seconds)=13 images are averaged (all image values ​​are added and then divided by 13), resulting in 16 images. The newly obtained images are stored in a new folder and renamed such as T1_C1_F1avg, T1_C1_F2avg, and finally T1_C1_F16avg. And so on, complete the image average under different situations and different experimental repetitions, such as T1_C2_F1avg, T2_C1_F1avg.

[0039] 2) Calculate the averaged graph: First calculate the result (two-dimensional matrix) in each case, the calculation method is: a. Calculate the average results of the images from T1_C1_Fn1avg to T1_C1_Fn2avg (the values ​​of n1 and n2 can be set in the control interface, such as n1=8, n2=16) to get P2; b. Calculate the average results of images T1_C1_F1avg to T1_C1_F3avg to get P1; c. Calculate (P2-P1). / P1, and get C1; d. Calculate in this way and get the results C2, C3, C4... e. According to the image acquisition settings, you can calculate results such as C2-C1, C3-C1, C4-C1, C4-C2, etc. The results are output to a new folder and displayed on the screen in the form of pictures. The results are named according to the calculation content, such as C2-C1.

[0040] Read the original C2-C1 image, subtract the average brightness of the image from the original brightness value (negative value means strong in C2, positive value means strong in C1), and the distribution of brightness values ​​of all pixels is shown in the figure below: Figure 3 shown.

[0041] f. After each repeated experiment, the calculation results are refreshed. For example, after T1_C5_F208 (5 cases, 4 seconds for each case) is completed, the first data analysis is performed; after T2_C5_F208 is completed, another analysis is performed. The analysis here requires averaging the results of different repeated experiments; and so on.

[0042] calculate Figure 3 The standard deviation (sd) of the brightness values ​​of all pixels in the image is shown in the following figure. Figure 4 As shown, in this embodiment, sd is 4.678, Figure 5The brightness of pixels with brightness values ​​exceeding 2sd is changed to the brightness value corresponding to 2sd. For example, the values ​​of pixels with brightness values ​​less than -9.35 (2sd) are changed to -9.35; the values ​​of pixels with brightness values ​​greater than 9.35 are changed to 9.35.

[0043] The distribution of brightness values ​​after transformation is as follows Figure 6 As shown, the enhanced image of C2-C1 is finally obtained as Figure 7 As shown. Therefore, through the combination of software and hardware, the rapid and stable acquisition and real-time monitoring of cortical functional signals of large animals can be completed.

[0044] Therefore, the present invention adopts the above-mentioned real-time monitoring system of neural activity based on endogenous signals of the cerebral cortex to realize the imaging of the cerebral cortex of large animals, and has the functions of long time course, large scale (2-5cm), long working focal length (5-50cm), multiple working angles and online multi-task comparative analysis. Compared with the existing technology, this system has significant advantages in imaging quality and ease of operation, and can be widely used in the field of neuroscience research.

[0045] It is worth noting that the contents not elaborated in detail in the present invention are all prior art and are well known to those skilled in the art.

[0046] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. A real-time monitoring system for neural activity based on endogenous signals of the cerebral cortex, characterized in that: It includes hardware and software parts. The hardware part includes a flexible fixing device for the animal head, a camera fixing and adjustment bracket; the software part includes visual stimulation control software, an analog signal receiver, data acquisition control software, and online data analysis software connected in sequence.

2. A real-time monitoring system for neural activity based on endogenous signals of cerebral cortex according to claim 1, characterized in that: The animal skull flexible fixation device consists of a base, a connecting arm, a head clamp, and a skull pin. The base is fixed on a laboratory table, the connecting arm connects the base and the head clamp, three skull pins are installed on the head clamp, a pressure knob is provided on the outer side of the skull pin, and a spring lock is provided on the head clamp.

3. The real-time monitoring system for neural activity based on endogenous signals of cerebral cortex according to claim 1, characterized in that: The camera fixing and adjusting bracket is composed of a base rod, a first sliding locking block, a connecting piece, a crossbeam rod, a second sliding locking block, a universal ball head, a handle, and an X / Y / Z axis manual displacement stage.

4. A real-time monitoring system for neural activity based on endogenous signals of cerebral cortex according to claim 3, characterized in that: The base rod is fixed on the experimental table, a first sliding locking block is arranged on the base rod, the right side of the first sliding locking block is connected to the crossbeam rod through a connecting piece, and a second sliding locking block is arranged on the crossbeam rod.

5. A real-time monitoring system for neural activity based on endogenous signals of cerebral cortex according to claim 4, characterized in that: The second sliding locking block is provided with a universal ball head, a handle is provided at the bottom of the universal ball head, one side of the handle is connected to the X / Y / Z-axis manual translation stage, and a camera is fixed on the clamping piece of the X / Y / Z-axis manual translation stage.

6. The real-time monitoring system for neural activity based on endogenous signals of cerebral cortex according to claim 1, characterized in that: The visual stimulation control software is installed on the main control computer a, the data acquisition control software and the online data analysis software are installed on the main control computer b, the analog signal receiver is a NI-USB device, and the USB port and AI port of the NI-USB device are electrically connected to the main control computer a and the main control computer b respectively.

7. The real-time monitoring system for neural activity based on endogenous signals of cerebral cortex according to claim 1, characterized in that: The data acquisition control software sets the basic acquisition parameters of the camera, records the cerebral cortex activity signal, and receives the external input signal to control the start recording of the camera.

8. The real-time monitoring system for neural activity based on endogenous signals of cerebral cortex according to claim 1, characterized in that: The online data analysis software reads the stored image data, and finally obtains the activity difference of the cerebral cortex under different stimulation conditions through analysis, and displays it online in the form of a graph.

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