A method for reconstructing an eye-brain visual pathway model in vitro

Abstract

The present invention discloses a method for reconstructing an eye-brain visual pathway model in vitro, belonging to the technical field of visual neural pathways. Through the multimodal design of structural connection and functional network, the simulation of visual information transmission from the retina to the cortex in an in vitro environment is realized. The multimodal construction method and unique electrical stimulation coding method of the invention provide a flexible and accurate experimental model for the basic research of visual neuroscience, and provide important technical support for visual rehabilitation, brain-computer interface and related neurodrug research and development. Through the innovative signal transmission path optimization, PCA screening and frequency coding method, the present invention not only improves the simulation effect of the in vitro model on the real biological system, but also lays a solid theoretical and technical foundation for the future development of visual repair, artificial visual system and human-computer interaction technology.

Description

Technical Field

[0001] The present invention relates to the technical field of visual neural pathways, and particularly to a method for reconstructing an eye-brain visual pathway model in vitro. Background Art

[0002] The processing and transmission of visual information is a highly complex neural process, involving multi-level processing from the retina to the visual cortex of the brain. Traditionally, the research on visual neural pathways mainly relies on in vivo experiments. Although such research provides rich physiological information, there are problems such as complex operations and ethical restrictions. With the rapid development of technologies such as brain-computer interfaces and visual prostheses, researchers hope to construct an eye-brain visual pathway model in an in vitro environment in order to study the transmission mechanism of visual information under controllable conditions and provide experimental support for visual nerve repair, visual impairment rehabilitation, and human-computer interaction technologies. Summary of the Invention

[0003] The purpose of the present invention is to overcome the technical problems existing in the prior art, and provides a method for reconstructing an eye-brain visual pathway model in vitro.

[0004] The purpose of the present invention is achieved by the following technical solutions:

[0005] Provide a method for reconstructing an eye-brain visual pathway model in vitro, and establish different connection modes by using structural connections and functional networks respectively, specifically including the following three construction modes:

[0006] Structural connection method: Cultivate eye cells and brain cells simultaneously on a single multi-electrode array MEA, and enable physical connections to be formed between the eye cells and the brain cells through natural or guided growth.

[0007] Construction of a functional network based on a virtual retina model: Use a virtual retina model to simulate the response of the retina to light stimulation, and convert the response into an electrical stimulation to the epithelial cells of the MEA through coding, thereby constructing a functional network connection.

[0008] Construction of a functional network based on the separate culture of real eyes and brains: Separate and culture real eye cells and brain cells, encode the response of the real eye cells to light stimulation, and convert the encoding into an electrical stimulation to the brain cells to simulate the eye-brain functional connection in vitro.

[0009] In some embodiments, the structural connection method specifically includes:

[0010] Simultaneously separate and culture retinal primary cells and cerebral cortex primary cells on the MEA. When they grow to a certain stage, remove the separation membrane, and form direct physical connections through natural growth or guided culture to reproduce the structural connection between the eye and the brain.

[0011] In some embodiments, converting the response into electrical stimulation of the MEA epithelial cells through encoding includes:

[0012] The signal of the retinal model response first calculates the Euclidean distance to the cortical neurons according to the retinal position, and selects the cortical neuron with the closest distance as the main object for information transmission.

[0013] In some embodiments, selecting the cortical neuron with the closest distance as the main object for information transmission includes:

[0014] Apply principal component analysis to the response data of all retinal neurons for dimensionality reduction, select the six most important cortical neurons according to the contribution degree, and transmit their signals to the corresponding six MEA electrodes.

[0015] In some embodiments, converting the response into electrical stimulation of the MEA epithelial cells through encoding further includes:

[0016] For the selected cortical neurons, take a time window of 500 ms and calculate the number of spikes within this time window;

[0017] Use clustering to classify the number of spikes in the response of each time window, and obtain multiple frequency categories corresponding to different stimulation frequencies, so as to simulate the transmission of visual information in the cortex.

[0018] Preferably, the clustering method is K-means clustering.

[0019] In some embodiments, by adjusting the stimulation frequency, simulate the neural signal transmission modes with different response intensities.

[0020] Preferably, the different stimulation frequencies include 8 Hz, 6 Hz, 4 Hz, 2 Hz.

[0021] In some embodiments, encoding the response of real eye cells to light stimulation and converting this encoding into electrical stimulation of brain cells includes:

[0022] Perform Euclidean distance calculation and PCA dimensionality reduction processing on the response of real eye cells to light stimulation, select the six cortical neurons with the highest contribution degree, and transmit them to the corresponding MEA electrodes.

[0023] In some embodiments, it further includes:

[0024] Verify the feasibility of different construction modes.

[0025] It should be further noted that the technical features corresponding to the above embodiments can be combined or replaced with each other without conflict to form a new technical solution.

[0026] Compared with the prior art, the beneficial effects of the present invention are:

[0027] (1) The present invention proposes three different construction methods, which respectively utilize structural connections and functional networks to provide various means for reconstructing the in vitro visual pathway. Each method has a unique implementation manner, adapting to different experimental requirements and research scenarios. By constructing an eye-brain visual pathway model in vitro, the present invention provides a highly controllable experimental platform for the research of the visual nervous system, helping scientists deeply understand the visual information transmission process from the retina to the cortex. This model not only contributes to basic research, but also provides an experimental basis for visual rehabilitation, the development of brain-computer interface technology, and neurodrug screening. The specific application values include:

[0028] Visual rehabilitation and treatment: Simulating the normal visual pathway provides potential technical support for the nerve repair and rehabilitation of visually impaired patients.

[0029] Brain-computer interface (BCI): Providing an experimental platform for visual information decoding and transmission in the brain-computer interface can promote the development of human-computer interaction technology.

[0030] Neurodrug screening: As a test platform for new neurodrugs, it helps to evaluate the effects of drugs on the visual nervous system.

[0031] Visual neuroscience research: The invention provides a flexible and highly controllable experimental model to study the visual signal transmission process between the eye and the brain in vitro, providing a new tool for understanding the working mechanism of the visual nervous system.

[0032] (2) In the method of constructing the functional network, the present invention designs a unique electrical stimulation coding method to efficiently transmit retinal signals and stimulate cortical cells. Among them, through Euclidean distance calculation and PCA screening, the effectiveness and accuracy of signal transmission are ensured, making the model closer to the neural information transmission method in the biological system. The flexibility of frequency coding is improved: through cluster analysis, frequency coding is performed on different response intensities, establishing a more refined functional network connection, and enhancing the bionic authenticity of the in vitro visual pathway model. Description of the Drawings

[0033] Figure 1 It is a schematic diagram showing the construction of an in vitro eye-brain visual pathway model according to an embodiment of the present invention;

[0034] Figure 2 It is a flowchart showing the construction of an in vitro eye-brain visual pathway model according to an embodiment of the present invention. Detailed Embodiment

[0035] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. The components of the embodiments of the present application described and illustrated in the drawings here can be arranged and designed in various different configurations. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0036] It should be noted that all the defects existing in the above prior art solutions are the results obtained by the inventor after practice and careful research. Therefore, the discovery process of the above problems and the solutions proposed by the embodiments of the present application below for the above problems should be the contributions made by the inventor to the present application during the invention and creation process, and should not be understood as the technical content known to those skilled in the art.

[0037] In view of the technical problems pointed out in the background art, based on the National Key Research and Development Program (2022YFF1202900), the embodiments provided by the present invention are as follows:

[0038] Provide a method for reconstructing an eye-brain visual pathway model in vitro. Refer to Figure 1 , including the following three construction modes:

[0039] Structural connection method: Cultivate eye cells and brain cells simultaneously on a single multi-electrode array MEA, so that physical connections are formed between the eye cells and the brain cells through natural or guided growth; specifically, cultivate primary retinal cells and primary cerebral cortex cells separately on a single MEA. When they grow to a certain stage, remove the separation membrane, and form direct physical connections through natural growth or guided culture, reproducing the structural connection between the eye and the brain. The electrical response of the eye cells to light stimulation is collected by the MEA and transmitted to the brain cells, constructing an in vitro visual pathway model of structural connection.

[0040] Construction of a functional network based on a virtual retina model: Use a virtual retina model to simulate the response of the retina to light stimulation, and convert the response into an electrical stimulation of the epithelial cells on the MEA through coding. This method establishes a functional connection through the response of the virtual retina to light stimulation, simulates the information transmission process between the retina and the cortex, and provides a flexible visual pathway simulation method.

[0041] Construction of a functional network based on the separated culture of real eyes and brains: Separate and culture real eye cells and brain cells, encode the response of the real eye cells to light stimulation, and convert the encoding into an electrical stimulation of the brain cells to simulate the functional connection between the eye and the brain in vitro. This method is based on the response data of real biological cells, enhancing the biological rationality of the model.

[0042] Among them, the structural connection method enables a direct physical connection between the eye and brain cells, simulating the direct structural connection of visual information in the biological system, which can better reproduce the structural connection between the eye and brain, and provide an experimental platform for studying the physical conduction mechanism of visual signals.

[0043] The construction mode of the functional network based on the virtual retina model specifically includes:

[0044] Method description: Utilize the response of the virtual retina model to light stimulation, and convert it into electrical stimulation of cortical cells on the MEA through an encoding algorithm to establish a functional network connection.

[0045] Electrical stimulation encoding method: The signals responded by the retina model first calculate the Euclidean distance to cortical neurons according to the retinal position, and select the cortical neuron with the closest distance as the main information transmission object. Considering the limitation of the number of MEA electrodes, principal component analysis (PCA) is applied to the response data of all retinal neurons for dimensionality reduction, and the six most important neurons are selected according to the contribution degree, and their signals are transmitted to the corresponding six MEA electrodes.

[0046] Time window and frequency encoding: For the selected retinal neurons, a 500 - ms time window is taken, and the number of spikes within this time window is calculated. K - means clustering is used to classify the responses (number of spikes) of each time window, obtaining four frequency categories (4, 3, 2, 1), which correspond to the stimulation frequencies of 8 Hz, 6 Hz, 4 Hz, and 2 Hz respectively, so as to simulate the transmission of visual information in the cortex.

[0047] This mode uses the virtual retina model to construct an in vitro visual pathway, optimizes the transmission path of the stimulation signal by combining PCA and clustering analysis, effectively simulates the functional information transmission from the retina to the cortex, and does not require the use of real eye cells, providing a flexible and controllable implementation method for functional network connection. A highly controllable and easily adjustable functional visual information transmission model is constructed.

[0048] Furthermore, the construction mode of the functional network based on the separate culture of real eyes and brains specifically includes:

[0049] Method description: Separate the culture of real eye cells and brain cells, respectively collect the responses of eye cells to light stimulation, and encode according to the retinal response, and convert it into electrical stimulation of brain cells to simulate the eye - brain functional connection in vitro.

[0050] Electrical Stimulation Coding Method: The response of real eye cells to light stimulation also uses Euclidean distance calculation and PCA dimensionality reduction. The six neurons with the highest contribution are selected and transmitted to the corresponding MEA electrodes. For the spike data of the retinal response, K-means clustering is performed within a 500-ms time window to obtain four types of frequencies (4, 3, 2, 1), corresponding to stimulation frequencies of 8 Hz, 6 Hz, 4 Hz, and 2 Hz respectively.

[0051] This mode is based on the response data of real cells and combines electrical stimulation coding methods to achieve functional connection through frequency regulation. This method uses real eye and brain cells and is based on real biological responses, enhancing the biological rationality of the model. To a certain extent, it reproduces the biological signal transmission mechanism between the eye and the brain, making the model closer to the real biological system and further verifying the effect of the virtual model for constructing a functional network based on the virtual retina model.

[0052] Furthermore, combined with Figure 2 , in the functional network (the second and third methods), the present invention designs a unique electrical stimulation coding method to achieve efficient signal transmission from the retina to the cortex, specifically including:

[0053] Optimization of the Retina-Cortex Neuron Distance: By calculating the Euclidean distance from each retinal neuron to the cortical neuron, cortical neurons with relatively close distances are preferentially selected as stimulation targets to ensure the effectiveness of information transmission, simulating the characteristic of "more information is transmitted when the distance is closer" in the biological system.

[0054] PCA Dimensionality Reduction Processing: Considering the limitation of the number of MEA electrodes, principal component analysis (PCA) is performed on the response signals of all retinal neurons, the contribution of each neuron is calculated, and the six neurons with the highest contribution are selected and mapped to the six electrodes of the MEA for electrical stimulation. This method not only ensures the effectiveness of signal transmission but also solves the problem of limited electrode quantity.

[0055] Response Frequency Coding: In the selected retinal neurons, a 500-ms time window is set, the number of spikes in the retinal neuron response is counted, and K-means clustering is applied to divide the responses into four categories, representing different stimulation frequencies (8 Hz, 6 Hz, 4 Hz, 2 Hz). This frequency coding method makes the electrical signal transmission in the model closer to the response of the real biological system by adjusting different stimulation frequencies.

[0056] This electrical stimulation coding method has the following technical advantages: It optimizes the signal transmission path: Through Euclidean distance calculation and PCA screening, it ensures the effectiveness and accuracy of signal transmission, making the model closer to the neural information transmission method in the biological system. It improves the flexibility of frequency coding: Through cluster analysis for frequency coding of different response intensities, a more refined functional network connection is established, enhancing the bionic authenticity of the in vitro visual pathway model.

[0057] Through the above three methods, the present invention can construct an in vitro eye-brain visual pathway model under different conditions, providing diverse choices from structural connection to functional network, and providing flexible experimental means for studying various mechanisms of the visual nervous system.

[0058] Furthermore, the present invention also analyzes the eye-brain signal transmission mechanism through information theory, verifies the feasibility of the eye-brain visual pathway models constructed by different methods, and explores the impact of light response on the eye-brain transmission mechanism through graph theory analysis of the functional network and conducts in vitro clinical trials, etc.

[0059] The above specific embodiments are detailed descriptions of the present invention. It cannot be determined that the specific embodiments of the present invention are only limited to these descriptions. For those of ordinary skill in the technical field to which the present invention belongs, without departing from the concept of the present invention, several simple deductions and substitutions can still be made, which should all be regarded as belonging to the protection scope of the present invention.

Claims

1. A method for reconstructing an eye-brain visual pathway model in vitro, characterized in that, Including: Structural connection method: Culturing primary eye cells and primary brain cells simultaneously on a single multi-electrode array (MEA), enabling a physical connection to form between the primary eye cells and primary brain cells through natural or guided growth. Functional network construction based on a virtual retina model: Using a virtual retina model to simulate the response of the retina to light stimuli, and converting the response into an electrical stimulus to the epithelial cells of the MEA through encoding to construct a functional network connection; the converting the response into an electrical stimulus to the epithelial cells of the MEA through encoding includes: The signals of the response of the retina model are first used to calculate the Euclidean distance to cortical neurons according to the retinal position, and the cortical neurons with the closest distance are selected as the main information transfer objects. The selecting the cortical neurons with the closest distance as the main information transfer objects includes: Applying principal component analysis to the response data of all retinal neurons for dimensionality reduction, selecting the six most important cortical neurons according to the contribution degree, and transmitting their signals to the corresponding six MEA electrodes. Functional network construction based on the separate culture of real eyes and brains: Separately culturing real eye cells and brain cells, encoding the response of real eye cells to light stimuli, and converting the encoding into an electrical stimulus to brain cells to simulate the eye-brain functional connection in vitro.

2. The method for reconstructing an eye-brain visual pathway model in vitro according to claim 1, wherein The structural connection method specifically includes: Simultaneously separating and culturing primary retinal cells and primary cortical cells on the MEA, removing the separation membrane at a certain growth stage, and forming a direct physical connection through natural growth or guided culture to reproduce the structural connection between the eye and the brain.

3. The method for reconstructing an eye-brain visual pathway model in vitro according to claim 1, characterized in that The converting the response into an electrical stimulus to the epithelial cells of the MEA through encoding further includes: For the selected cortical neurons, taking a time window of 500 ms and calculating the number of spikes within this time window. Using clustering to classify the number of spikes in the responses of each time window, obtaining multiple frequency categories corresponding to different stimulation frequencies, thereby simulating the transmission of visual information in the cortex.

4. The method for reconstructing an in vitro eye-brain visual pathway model according to claim 3, wherein The clustering method is K-means clustering.

5. The method for reconstructing an eye-brain visual pathway model in vitro according to claim 3, wherein, By adjusting the stimulation frequency, simulating the transmission modes of nerve signals with different response intensities.

6. The method for reconstructing an eye-brain visual pathway model in vitro according to claim 3, wherein The different stimulation frequencies include 8 Hz, 6 Hz, 4 Hz, and 2 Hz.

7. The method for reconstructing an eye-brain visual pathway model in vitro according to claim 1, wherein The encoding the response of real eye cells to light stimuli and converting the encoding into an electrical stimulus to brain cells includes: Performing Euclidean distance calculation and PCA dimensionality reduction processing on the response of real eye cells to light stimuli, selecting the six cortical neurons with the highest contribution degree, and transmitting them to the corresponding MEA electrodes.

8. The method for reconstructing an eye-brain visual pathway model in vitro according to claim 1, wherein Also including: Verifying the feasibility of different construction modes.

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