157 results about "Cerebral cortex" patented technology

The invention belongs to the field of electroencephalogram signal processing, and provides a time-frequency space electroencephalogram emotion recognition method based on three-dimensional space position embedding, which comprises the following steps of: firstly, constructing a three-dimensional electrode space position matrix based on an international 10-20 system standard, determining a space adjacency relation between electrodes, and calculating a phase locking value to obtain a functional connection matrix; then, deep feature fusion of an electrode spatial position matrix and a functional connection matrix is realized by adopting a hierarchical cross Transform architecture, the spatial position matrix represents spatial distribution features of a cerebral cortex region, and the functional connection matrix quantifies phase synchronization features of cross-brain region neural oscillation and simulates a brain spatial topological structure; and finally, extracting time, frequency and spatial features of the electroencephalogram signals through combination of a graph attention network and bidirectional long-short-term memory with an attention mechanism for emotion recognition. The method can effectively extract space structure information highly related to the emotional state, and significantly improves the accuracy of emotion recognition.

The invention discloses a closed-loop deep brain regulation and control system for epilepsy treatment, and the system comprises an electroencephalogram signal collection module which collects neural electrophysiological signals in real time by implanting a recording electrode in a cerebral cortex or hippocampal brain area; the electroencephalogram signal real-time analysis module is used for outputting the epileptic seizure period prediction probability xi through a seven-layer full-connection neural network based on the 33-dimensional feature vector so as to realize epileptic seizure early warning; when the zeta is greater than or equal to a threshold value, the electrical stimulation regulation and control module is used for triggering electrical stimulation, filtering out a frequency band required to be regulated and controlled according to filtering, calculating and predicting electrical stimulation intensity and then correcting and outputting pulse stimulation, so that personalized electrical stimulation regulation and control are carried out on a specific frequency band, and detection is continuously carried out until the frequency band becomes normal; and the medicine intervention module is used for triggering a micro-injection pump to carry out medicine infusion through a pulse signal. According to the system, epilepsy treatment is improved from empirical parameter adjustment to accurate regulation and control based on real-time nerve physiological signals, and a safer and more effective treatment choice is provided for a drug-refractory epilepsy patient.

The invention discloses a brain region correlation analysis system and method for autistic children. The system comprises a brain region division module used for dividing the cerebral cortex into a plurality of brain regions; the training data set construction module is used for constructing a training data set, and each training sample comprises a sensor space function connection matrix and a source space function connection matrix corresponding to the sensor space function connection matrix; the signal preprocessing module is used for acquiring a real electroencephalogram signal and calculating a real value of a corresponding sensor space function connection matrix; the deep learning mapping module is used for learning a mapping relation from the sensor space function connection matrix to the source space function connection matrix and outputting a predicted value of the source space function connection matrix; and the brain region correlation analysis module is used for calculating the correlation between the brain regions. The method can be used for accurately analyzing the correlation between the brain areas of the autism children.

The invention provides a hand rehabilitation training glove and system based on electromyographic signal guidance and pressure feedback, and the glove comprises a flexible glove main body which is made of an elastic material, is designed to fit the anatomical structure of a human hand, and is used for collecting bioelectrical signals generated by the remaining hand and forearm muscles of a patient when the patient actively intends to generate power; the embedded signal processing module is used for carrying out amplification, filtering, noise reduction and analog-to-digital conversion processing on the collected original electromyographic signals; and the main control unit is used for calculating time domain and frequency domain characteristic values of the electromyographic signals and identifying the motion intention of the patient based on a preset threshold value or an adaptive algorithm. Weak electromyographic signals are collected and processed in a high-precision mode and immediately converted into local touch pressure feedback corresponding to the functions of the weak electromyographic signals, neural pathway connection between the cerebral cortex and target muscles is enhanced, training interestingness and immersion and compliance of a patient are remarkably improved, and the training effect is improved. And key power is provided for continuous long-term rehabilitation training.

The invention provides a self-adaptive cerebral cortex reconstruction system, method and device based on deep learning and a medium, and the reconstruction system comprises an image preprocessing module which is used for preprocessing input MRI image data to obtain a real curvature image, a real brain tissue segmentation image and a real cerebral cortex; the three-stage grid deformation module is connected with the image preprocessing module; the three-stage grid deformation module comprises three continuous grid deformation modules, and each stage of grid deformation module comprises a deformation model and a physical deformation module; the deformation model is used for predicting a curvature perception static velocity field and a curvature graph; and the physical deformation module calculates differential mapping for each vertex position from the curvature sensing static velocity field so as to generate and obtain a final cerebral cortex surface, so that the accuracy and the efficiency of cerebral cortex reconstruction can be remarkably improved.

The invention relates to the field of ultrasonic sleep aiding, and provides an ultrasonic-infrasound coupled sound wave whole-brain sleep regulation and control method and device. The whole-brain sleep regulation and control method based on the ultrasound-infrasound coupling sound waves comprises the steps that electroencephalogram signals of a user are collected through electroencephalogram collection equipment; physiological parameters of the user are obtained through physiological state monitoring equipment; a control device is adopted to control and adjust the fundamental frequency, pulse width, pulse repetition frequency, difference frequency, intensity and other parameters of two columns of ultrasonic waves generated by a sound wave emission device according to the electroencephalogram signals and the physiological parameters; a sound wave emitting device is adopted to generate and emit two columns of ultrasonic waves which are close in frequency and face to face, the two columns of ultrasonic waves are fed into the brain face to face, and the two columns of ultrasonic signals inhibit the cerebral cortex activity when passing through the cerebral cortex; meanwhile, interference occurs in the deep brain target nuclear region, low-frequency infrasound beat frequency waves are formed, electroencephalogram slow wave rhythm resonance is induced, sleep-related neural activities of the deep brain target nuclear region are synchronized, and coordinated regulation and control of the whole brain region are achieved.

The invention relates to the technical field of medical monitoring, and provides a full cortical nerve-immune monitoring and closed-loop regulation and control system based on nerve electrical stimulation, and the system comprises a regulation and control electrode which is used for detecting the cerebral cortex of a target brain region and the neuroelectric signals of a deep brain region, and is used for the electrical stimulation regulation and control of neurons of the deep brain region; the brain temperature detection assembly is used for detecting temperature information of a target brain region in real time; the cortex imaging device is used for collecting nerve and immune activity images of the whole cortex; the external control device is electrically connected with the regulation and control electrode, the brain temperature detection assembly and the cortex imaging device, and the external control device is used for receiving temperature information detected by the brain temperature detection assembly and image information detected by the cortex imaging device and controlling the regulation and control electrode to work according to the temperature information. According to the invention, high-precision synchronous monitoring and closed-loop regulation and control of deep brain area nerve electrical stimulation and whole cortical nerve-immune activity are realized, an innovative technical means is provided for neuroscience, immunology and clinical medicine research, and the method has important scientific research and clinical application values.

A Bifidobacterium animalis subsp. lactis for reducing Abeta42 deposition and an application, a name of the Bifidobacterium animalis subsp. lactis is Bifidobacterium animalis subsp. lactis IOB-LO7, and classified as Bifidobacterium animalis subsp. lactis, the Bifidobacterium animalis subsp. lactis IOB-LO7 is preserved in the General Microbiology Center of the China General Microbiological Culture Collection Center (CGMCC) on Dec. 23, 2021, with the collection number of CGMCC No. 24185. By reducing the levels of Aβ42 in the cerebral cortex and hippocampus, clearing Aβ amyloid plaques, improving communication between neurons, reducing brain neuroinflammation, and protecting nerve cells, it helps to restore cognitive function and improve Alzheimer's disease. Additionally, it can also improve gut microbiota imbalance caused by Alzheimer's disease.

The invention discloses a cerebral cortex stimulation central nervous regulation system and method based on a pulse magnetic coil, and the system comprises a pulse magnetic stimulation module, a neural signal collection module, a central control module and a man-machine interaction module, and is additionally provided with a three-dimensional positioning module and a multi-level safety monitoring module. The pulse magnetic stimulation module generates a focused pulse magnetic field, the neural signal acquisition module acquires multi-brain-region electric signals, and the central control module dynamically regulates stimulation parameters after analyzing the signals to form closed-loop regulation; the three-dimensional positioning module ensures accurate positioning of the coil, the safety monitoring module monitors parameters in real time and triggers emergency protection, and the man-machine interaction module realizes convenient operation and data management. According to the method, adjustment is completed through initialization, signal acquisition and analysis, precise stimulation, positioning adjustment and safety monitoring. The scheme is non-invasive, accurate, safe and suitable for nerve research and disease treatment, the regulation effect and use safety are improved, and development of the nerve regulation technology is promoted.

The invention discloses a magnetoencephalogram-based epilepsy lesion positioning method and system and a medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: carrying out the preprocessing of a structure image of a patient, carrying out the registration with the magnetoencephalogram of the patient, carrying out the grid division of a cerebral cortex region based on the preprocessed structure image and a registration result, and obtaining a forward model of the patient; performing preprocessing and spine wave detection on the magnetoencephalogram to obtain a spine wave time point sequence; based on the forward model and the ratchet wave time point sequence, using a magnetic dipole algorithm to calculate a source coordinate and a source direction of a ratchet wave time point, and classifying the ratchet wave time point sequence according to the source coordinate and the source direction to obtain a clustering result; calculating the source coordinate and the source direction of the class center of each class in the clustering result by using a magnetic dipole algorithm; generating a clinical report of the patient; according to the positioning method, the problems of large epilepsy diagnosis difference and error proneness caused by level difference of different doctors are solved, and the epilepsy focus position can be quickly determined.

The invention relates to an integrated flexible corticobrain electrode and a preparation method thereof.The flexible corticobrain electrode is composed of a flexible substrate layer, a wire layer and an insulating layer which are sequentially arranged in a stacked mode, the wire layer comprises an electrode contact array, a bonding pad contact array and a wire set, and the wire set spirally surrounds the electrode contact array; the bonding pad contact array is located on the outer side of the wire group; the electrode contact array and the flexible substrate layer and the insulating layer which correspond to each other up and down jointly form a signal acquisition electrode, the wire group and the flexible substrate layer and the insulating layer which correspond to each other up and down jointly form a connecting wire, and the bonding pad contact array and the flexible substrate layer and the insulating layer which correspond to each other up and down jointly form a bonding pad. The integrated flexible cortical brain electrode has the advantages of being small in size, high in flexibility and large in flux, in the using process, the signal collecting electrode can be better attached to a cerebral cortex collecting site, the problems of brain tissue damage and connection failure cannot occur, and the integrated flexible cortical brain electrode is friendly to experimental surgery operation.

The invention provides a whole cerebral cortex nerve photoelectric information processing method and device under a memory mechanism. The method comprises the following steps: collecting whole cerebral cortex calcium imaging signals and hippocampus sharp ripple signals generated by an experimental animal aiming at each group of visual stimulation sequences; under the same time step, phase-locked correlation analysis is carried out on the whole cerebral cortex calcium imaging signal and the hippocampal sharp ripple signal to obtain a neural activity association relationship, and the neural activity association relationship comprises a corresponding relationship between different visual stimuli and different signal combinations. The neural photoelectric information incidence relation between the whole cerebral cortex and the deep brain nuclei under the memory mechanism can be analyzed in the visual cognition prediction process, namely visual prediction is carried out by analyzing the whole cerebral cortex activity and the hippocampus sharp ripple discharge, and a basis is provided for constructing a visual prediction model based on the neural activity incidence relation; the attention mechanism about the neural activity association relationship is added for constructing the visual prediction model, so that the visual prediction accuracy of the visual prediction model can be improved.

The application discloses a new use of Leonurine or a pharmaceutically acceptable salt thereof in the preparation of a medicament for treating radiation-induced brain injury, specifically, providing a safe and effective therapeutic drug for iron death, neuroinflammation, neuron damage and lipid metabolism disorder accompanying the radiation-induced brain injury, solving the technical problem of lack of specific treatment means in the prior art, and having a wide clinical application prospect. Experiments adopt a C57BL / c mouse 30 Gy whole brain X-ray radiation model, and results show that Leonurine can significantly improve the body weight decrease and survival rate of the model mice, reduce the serum IL-6 and IFN-alpha levels, inhibit the activation of microglial cells in the cerebral cortex and hippocampus, protect and repair damaged neurons, and improve the ultrastructure of mitochondria and synapses; meanwhile, the expression of GPX4 and SLC7A11 proteins in the brain tissue is up-regulated, the GSH content is increased to inhibit iron death, and the levels of GPE, GPS and GPC related to lipid metabolism are restored.

The invention discloses a brain tumor real-time identification system and method based on cortical electroencephalogram signals, and relates to the technical field of medical artificial intelligence, and the method comprises the following steps: obtaining multi-channel ECoG signals in real time; the multi-channel ECoG signals are updated in real time, the multi-channel ECoG signals updated in real time are preprocessed, and the preprocessed multi-channel ECoG signals are obtained; performing channel feature extraction on the ECoG signal of each channel to obtain various ECoG signal features under each channel as channel features; calculating segmentation thresholds of different channel characteristics under each channel based on an automatic threshold segmentation algorithm; carrying out confidence evaluation on the segmentation threshold values of different channel characteristics under each channel; and marking the channel of which the confidence coefficient is smaller than a set tumor marking threshold value as a tumor area. Accurate positioning of a tumor area can be achieved, functional state changes of the cerebral cortex can be reflected in real time, and doctors can conveniently master real-time changes of cortex functions in time.

The invention relates to a brain-computer interface system which comprises a flexible electrode array, a receiving device, a flexible connecting wire and external equipment, wherein the flexible electrode array is implanted into a meninx middle artery in a minimally invasive manner through a superficial temporal artery puncture and a vascular intervention procedure; the receiving device is embedded under the skin of a head and is provided with a signal transmitter; the external equipment is provided with a signal receiver. A flexible electrode array is implanted in an anterior branch or posterior branch of a main branch of a middle meninx artery through a superficial temporal artery intravascular minimally invasive technology, the number of electrodes and the array are arranged according to needs, and a receiving device buried in the subcutaneous part of the head is electrically connected with the flexible electrode array implanted in the middle meninx artery. Craniotomy is not needed, operative complications are avoided, minimally invasive implantation reaches the surface of the cerebral cortex, operation of a doctor is easier, the operation time is shortened, and the comfort level of a patient is improved.

A cerebral cortex model-based simplicial network for diagnosing mental disorder is disclosed. A cerebral cortex model-based method for diagnosing mental disorder performed by a mental disorder diagnosis system, according to one embodiment, may comprise the steps of: modeling a cerebral cortex mesh as a cerebral cortex simplicial complex; and performing message passing for diagnosing a mental disorder using relationship information of the modeled cerebral cortex simplicial complex through a message passing neural network.

The invention discloses a cerebral cortex penetrator small blood vessel magnetic resonance imaging method based on an inflow enhancement effect. The method comprises the following steps: modeling a penetrator small blood vessel to generate a blood vessel TOF (Time of Flight) image; calculating the blood vessel-grey matter contrast ratio of the blood vessel TOF image under different FAs and different TRs, and optimizing the FAs and the TRs according to the blood vessel-tissue contrast ratio; obtaining a structural image of the in-vivo brain tissue, performing cortex reconstruction, and calculating an angle of a surface normal of each cortex vertex relative to the B0 field to obtain a cortex angle graph; adjusting a single-layer blood vessel scanning plane angle according to the cortex angle diagram; and according to the optimized FA and TR and the single-layer blood vessel scanning plane angle determined in the step S4, carrying out magnetic resonance imaging on the cerebral cortex perforation small blood vessel. The invention further discloses a cerebral cortex puncturing small blood vessel magnetic resonance imaging device based on the inflow enhancement effect. According to the method and the device, magnetic resonance imaging of the cerebral cortex perforation small blood vessel can be realized under the non-invasive and contrast-agent-free conditions.

The invention provides an animal multi-dimensional state recognition system and method based on full-cortical neural activity, and the system comprises a stimulation generation module which is used for forming target stimulation under the condition that a stimulation generation instruction is received; the full cortical neuron imaging module is used for collecting full cortical nerve response change data generated by the experimental animal under the condition that the experimental animal receives target stimulation; the electroencephalogram signal acquisition module is used for acquiring an electrophysiological signal generated by an experimental animal under the condition that the experimental animal receives target stimulation; the response behavior detection module is used for collecting a physiological response motion state formed by the experimental animal under the condition that the experimental animal receives the target stimulation; and the synchronous recording and analyzing module is used for synchronously analyzing the whole cerebral cortex nerve response change data, the electrophysiological signal and the physiological response motion state to obtain causal association between the nerve activity and the response behavior of the experimental animal under target stimulation. Multi-dimensional state data corresponding to animal response behaviors are synchronously collected, and a foundation is laid for brain function research and analysis.

The present invention belongs to the technical field of medical image segmentation methods and relates to an automatic segmentation method for the cerebral cortex surface based on a geometric neural network. The method comprises acquiring a brain sMRI image, reconstructing the cerebral cortex surface, and extracting multidimensional morphological features of the cerebral cortex surface; decomposing the multidimensional morphological features of the cerebral cortex surface using a graph Laplacian to obtain a spectral representation of the cerebral cortex surface manifold; extracting contextual information of the cerebral cortex surface of a target image using a segmentation module with a U-shaped hierarchical structure, extracting anatomical prior information of the cerebral cortex surface of an atlas image using an auxiliary module with the same structure, and fusing information from the segmentation module and the auxiliary module using a non-local attention feature fusion module to output a predicted probability map of the segmentation label of the cerebral cortex surface of the target image. The present invention has better real-time performance and makes full use of the intrinsic structural information of the cortical surface and the global information of brain regions.

The invention relates to a cerebral cortex metabolism visualization method and system. The method comprises the steps of obtaining a first functional image and a structure image of the brain of a target patient; based on the target neural network model, performing denoising processing on the first functional image to obtain a second functional image; wherein the target neural network model is obtained by training an initial neural network model based on a sample set, the sample set comprises multiple groups of samples, and each group of samples comprises a first functional image sample and a structure image sample of the brain of a sample patient; generating a three-dimensional grid model of the cerebral cortex according to the structure image; and mapping the metabolic information in the second functional image into the three-dimensional grid model, and visualizing the metabolic information in the three-dimensional grid model. By adopting the method, accurate correspondence and visual fusion expression of the brain anatomical structure information and metabolism information of the target patient can be realized, and the observation efficiency of a doctor is improved.

A method for achieving super-resolution in localizing electrical fields measured at the head surface with electroencephalography through a generative model of the cerebral cortex that has a very high resolution of cortical surface dipoles constructed from the known properties of human cerebral cortex and adapted to optimize the Bayesian explanation the individual's cortical surface electrical fields. The iterative optimization of the prior (generative) with the posterior (observed) fields with extensive data from extended recordings provides a probabilistic estimation of the individual's functional brain activity that can be used to train artificial neural network approximations of the individual's mental activity.

1. Name of the product in this design: Flash Stimulator. 2. Purpose of this design: To serve as an auxiliary diagnostic device in the field of neurology that induces abnormal electrical discharges in the cerebral cortex through light-sensing input from the visual system. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D rendering 1.

The invention provides a cerebral cortex thickness measurement method and system based on a level set image segmentation algorithm, and belongs to the technical field of neural image analysis, and the method comprises the steps: obtaining a brain magnetic resonance imaging image, and carrying out the skull stripping processing; performing three-dimensional visualization on the stripped image through volume rendering, and acquiring three-dimensional coordinates of points of interest and a region of interest on the surface of the cortex by using a preset interaction means; using a level set method to carry out brain grey matter and brain white matter segmentation on the region of interest to obtain a brain grey matter segmentation layer and a brain white matter segmentation layer, and storing three-dimensional coordinate data of points in the segmentation layers; calculating the minimum Euclidean distance according to the three-dimensional coordinate data of the points in the segmentation layer and the three-dimensional coordinates of the points of interest to obtain the cortex thickness of the points of interest; the method solves the problems that the existing cerebral cortex thickness measurement lacks a visual means, is not supported by a mathematical model, cannot be accurate to the thickness of an interest point, and cannot display and retain comprehensive information.

The invention discloses a portable frequency-adjustable transcranial magnetic stimulation system and a stimulation method thereof. The system comprises an application program, a central control system and an intervention module, wherein the application program, the central control system and the intervention module are arranged in portable insomnia therapeutic equipment; the application program and the intervention module are both connected with the central control system. According to the invention, accurate matching with human body natural slow wave rhythm (Delta wave 1-4Hz and Theta wave 4-8Hz) is realized by releasing 1-8Hz Gamma low-frequency magnetic pulse waves capable of inhibiting excessive activity through control, slow wave synchronism is enhanced through frequency-phase resonance of magnetic field-neural oscillation, sleep is improved, and an instantaneous alternating magnetic field is generated to penetrate through skull to act on cerebral cortex, so that sleep quality is improved. Compared with a traditional medicine therapy, an invasive therapy and a non-invasive therapy, the side effect is smaller, the risk is lower, sleep can be further improved by playing soothing music, and the sleep neural circuit can be conveniently regulated and controlled at home to conveniently improve insomnia.

The present application relates to a method, device, electronic device and storage medium for generating a cerebral cortical morphological network, wherein the method comprises: obtaining a cerebral cortical reconstructed image of a target object; segmenting the cerebral cortical reconstructed image to obtain multiple target areas of the cerebral cortex and a vertex set of each target area; connecting the vertices in the vertex set of each target area to obtain a sub-network corresponding to each target area; determining the state of the target leaf node based on whether the target leaf node is adjacent to other leaf nodes; if the state of the target leaf node is a to-be-connected state, determining a connecting leaf node corresponding to the target leaf node; connecting the leaf nodes in the to-be-connected state in each sub-network to the corresponding connecting leaf nodes to generate a cerebral cortical morphological network of the target object. Through the present application, the problem of low efficiency in generating a cerebral cortical morphological network is solved, and the efficiency of generating a cerebral cortical morphological network is improved.

The utility model discloses a fixing device for conscious imaging of rodents, which belongs to the technical field of microscopic imaging and comprises a head fixing frame, and the head fixing frame comprises an auxiliary supporting component, a displacement mechanism and a head fixing device. The auxiliary supporting assembly is composed of a plurality of fixing rods and fixing pieces, and a head fixing device is arranged on the auxiliary supporting assembly and located over the rotating disc. One end of the auxiliary supporting assembly is provided with a displacement mechanism, and the upper end of the displacement mechanism is provided with an optical panel. The position of the head fixing device can be precisely adjusted, so that the head fixing device is located at a position suitable for microscope observation; the head of a rodent in a natural activity state can be fixed, and four limbs of the rodent are allowed to freely move under stress, so that huge body movement caused by conditions of stress, movement and the like can be eliminated when the rodent is fixed under the device after being trained; the physiological activities of the head, the face, the cerebral cortex and the like of the animal can be subjected to high-time and spatial-resolution image recording in a waking state and a sleeping state.

The invention discloses a digital word pulse coding method (DWSFE) and a digital word pulse coding system fusing space and frequency characteristics, which are used for text information processing of a pulse neural network (SNN). The method comprises the following steps: constructing two vocabulary vector space modeling methods, namely interval semantic division vector coding (SSPE) and continuous semantic division vector coding (CSPE), based on a cerebral cortex semantic partitioning principle in neuroscience; converting the semantic vector into a pulse sequence with frequency characteristics through variable intensity Poisson coding (VIPE); and designing an unsupervised clustering SNN architecture containing a lateral suppression mechanism. According to the method, efficient pulse coding of text information is achieved, 100% classification accuracy is achieved under 400-dimensional word vectors, and compared with a traditional word embedding method, the application performance of SNN is greatly improved. The invention provides a low-power-consumption text processing system suitable for a neuromorphic computing device.

The invention discloses a gradient tuning type excitation coil structure and system for biological electromagnetic stimulation, and relates to the technical field of biological electromagnetic stimulation. The coil structure comprises a plurality of layers of 8-shaped stimulation coils which are horizontally placed above a biological electromagnetic stimulation target area, the inner diameter of each layer of 8-shaped stimulation coil is gradually increased layer by layer from bottom to top, and two coil units in each layer of 8-shaped stimulation coil are bilaterally symmetrical. The multi-layer 8-shaped stimulation coil is used for accessing excitation current through the discharge circuit so as to play a biological electromagnetic stimulation role on a target area, so that the focusing performance of the target area can be remarkably improved on the premise of not losing much induced electric field intensity through gradually increasing the inner diameters of the coils from bottom to top layer by layer, and the focusing performance of the target area is improved. Parts of hidden dangers caused by too large focusing area are eliminated, high electric field intensity is generated at the cerebral cortex, effectiveness of brain stimulation is guaranteed, and practical application and popularization are facilitated.

The invention relates to a method for constructing a growth model of a brain in a life cycle, and the method comprises the steps: obtaining brain MRI images of individuals of different age groups, and dividing the cerebral cortex into n regions; constructing a morphological feature network for sMRI of the brain MRI image of the individual, and performing morphological feature similarity degree analysis to obtain a first phenotype; constructing a functional network for the fMRI of the brain MRI image of the individual; constructing a structure-function coupling matrix for the morphological feature network and the function network, and calculating to obtain a second phenotype; selecting the first phenotype and the second phenotype of each individual as dependent variables and the age of each individual as a smooth item to carry out GAMLSS modeling, and selecting JSU distribution to respectively fit the change of the first phenotype and the second phenotype along with the age to generate a reference growth curve. The method can be used for studying the growth mode of the brain network in the whole life cycle, studying life cycle association between morphological characteristics and functional characteristics of different areas and the like.

The application discloses a kind of implanted nerve electrode devices of magnetic control telescopic contact and separation cerebral cortex, belong to brain signal research technical field.It includes: flexible substrate, magnetostrictive deformation substrate, magnetostrictive film, elastic component and electrode;The flexible substrate side is provided with several rectangular grooves arranged in order;Two pieces of the magnetostrictive film are pasted to the two sides of the magnetostrictive deformation substrate, and the magnetostrictive film on one side is used to fix the magnetostrictive deformation substrate in the rectangular groove of the flexible substrate;The electrode is fixed on the magnetostrictive deformation substrate, for collecting electroencephalogram;The elastic component is used to pull the deformed magnetostrictive deformation substrate to restore flat state.The device is fixed under dura mater, and can be bent under the drive of magnetic field, realizes the effective contact of nerve electrode and cerebral cortex, compared with traditional semi-invasive nerve electrode, improves the detection quality and stability of electroencephalogram.