207 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 discloses a cognitive impairment screening method and device based on a VR eye tracker and near-infrared brain imaging. The device comprises a virtual reality scene generation module, an eye tracker data acquisition module, a near-infrared brain imaging module, a data evaluation processing module and a cognitive impairment screening module. The eye tracker data acquisition module is used for acquiring an eye movement data information set of a user in a virtual reality scene in real time; the eye movement data information set comprises a fixation point information sequence, a pupil area information sequence and an eye hopping frequency information sequence; the near-infrared brain imaging module is used for acquiring a blood oxygen information set of cerebral cortex when a user completes a cognitive task; the blood oxygen information set of the cerebral cortex comprises a brain blood oxygen information sequence; the data evaluation processing module is used for carrying out evaluation processing on the collected eye movement data information set and the blood oxygen information set of cerebral cortex to obtain cognitive disorder information of the user; the cognitive impairment information comprises information about whether cognitive impairment exists or not and the degree of the cognitive impairment.

The invention belongs to the technical field of brain analysis and detection, and particularly discloses a cerebral cortex secreted substance detection method which comprises the following steps: creating a first folder, and storing brain detection data of a detector into the first folder; configuring detection software; creating a second folder, and constructing a first association relationship between the second folder and the first folder; processing the brain detection data through detection software to generate analysis data, and storing the analysis data in a second folder; creating a third folder, and copying the analysis data into the third folder; constructing a second association relationship among the analysis data in the third folder, and marking the analysis data in the third folder through the second association relationship and the first association relationship; outputting the third folder as a detection result; the method has the following advantages that through hierarchical folder management, data backup and parallel processing, data management transparency and processing efficiency are improved, automatic analysis is achieved, data integrity is ensured, and result output is simplified.

The invention relates to the technical field of sleep state monitoring, and particularly discloses an intelligent sleep state monitoring method and device based on brain waves, brain wave signals of a user are collected through EEG equipment, and a signal processing and analysis algorithm based on artificial intelligence and deep learning is introduced at the rear end to analyze the brain wave signals, so that the sleep state monitoring accuracy is improved. And the sleep state of the user is monitored based on full-frequency aggregation of the brain wave signals. In this way, the sleep state of the user can be automatically identified and displayed in real time based on the brain waves of the user, and improvement suggestions are provided when the sleep state is identified to be poor. For example, a brain balance regulator is used for sleep regulation, and a non-invasive and non-invasive weak stimulation technology is adopted for regulation. According to the method, the prior data table between the sleep state and the current mode is constructed by using an experiment, so that after the sleep state is obtained, the current mode can be adaptively adjusted based on prior knowledge to adjust cerebral cortex neural activity, and the sleep improvement of a user can be better assisted.

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 present disclosure provides a method and a system for fully automatically segmenting a cerebral cortex surface based on a graph network, belongs to the field of medical image technology and devices, and solves the problem that space mapping noise is easily introduced in the mapping process in the related art, and a lot of time is cost for mapping to a sphere surface space to finish segmentation and then mapping back to an original space. The method includes: registering a cerebral magnetic resonance image to a standard template space; performing cerebral cortex surface reconstruction on the registered cerebral magnetic resonance image based on a deep neural network; calculating adjacency matrices among the vertexes of the reconstructed cerebral cortex; acquiring corresponding distinguishing features of each grid vertex of the cerebral cortex surface as corresponding feature vectors of the point so as to obtain a cerebral cortex surface segmentation result; and mapping the cerebral cortex surface segmentation result back to the original coordinate space from the standard template space. According to the present disclosure, graph structure modeling is performed on the reconstructed cerebral cortex surface, and the global topological structure features are learned based on the graph network, thus realizing the accurate segmentation of the cerebral cortex surface.

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 discloses an implantable neural electrode device separated from the cerebral cortex through magnetic control telescopic contact, and belongs to the technical field of brain signal research. Comprising a flexible substrate, a magnetostrictive deformation substrate, a magnetostrictive deformation film, an elastic component and an electrode, a plurality of rectangular grooves which are arranged in order are formed in one side of the flexible substrate; the two magnetostrictive deformation films are attached to the two sides of the magnetostrictive deformation substrate respectively, and the magnetostrictive deformation film on one side is used for fixing the magnetostrictive deformation substrate in the rectangular groove of the flexible substrate; the electrode is fixed on the magnetic deformation substrate and is used for acquiring an electroencephalogram signal; and the elastic assembly is used for pulling the deformed magnetic deformation substrate to recover to a plane state. The device is fixed under the dura mater and can be bent under the drive of a magnetic field, effective contact between the neural electrode and the cerebral cortex is achieved, and compared with a traditional semi-intrusive neural electrode, the detection quality and stability of electroencephalogram signals are improved.

The invention relates to the technical field of cranial nerve regulation and control, and discloses a dynamic closed-loop nerve regulation and control method integrating an ultrasonic array element and an fNIRS probe, which adopts a mode of combining a near-infrared light detector and the ultrasonic array element, can utilize the characteristics of transcranial focused ultrasound to stimulate deep nuclei of the brain, and utilizes near-infrared to observe the change of cerebral cortex in real time. Real-time observation of brain blood oxygen level change caused by cortical excitability of each brain region of a brain function network is realized, closed-loop feedback is formed, then dynamic parameter adjustment is performed on the phased array ultrasonic array, dynamic closed-loop nerve regulation and control of the integrated ultrasonic array element and the near-infrared brain function imaging probe are realized, and the brain blood oxygen level change is observed in real time. And the maximum change of the cortex excitability of the expected brain region or the brain network node is obtained through the focusing process, so that the precision of the stimulation target region is realized.

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 embodiment of the invention provides a phototherapy intelligent regulation and control device, a control method thereof, electronic equipment and a storage medium, and belongs to the technical field of medical instruments. The phototherapy intelligent regulation and control device comprises a photon cap, a phototherapy module, a monitoring module and a processing module, the phototherapy module and the monitoring module are fixed on a clamping seat of the photon cap, and the processing module is connected with the phototherapy module and the monitoring module; wherein the phototherapy module is used for emitting first near-infrared light, and non-invasive therapy can be achieved in a non-invasive mode; the monitoring module is used for detecting the blood oxygen level of the cerebral cortex and sending the detected oxyhemoglobin concentration to the processing module for analysis, and can monitor and feed back data in real time, so that the treatment process is transparent; the processing module is used for regulating and controlling the treatment parameters of the first near-infrared light emitted by the phototherapy module according to the change speed of the oxyhemoglobin concentration, the treatment parameters can be automatically regulated and controlled according to the detected data, and the intelligent degree of treatment is improved.

The invention provides a control system for optimizing sleep quality in a driving cabin and a control method thereof, and relates to the technical field of driving cabin environment adjusting systems.The control system comprises a sleep-aiding switch key used for starting a switch signal in a one-key mode; the controller assembly is used for sending a control instruction; the brain wave detection assembly is used for collecting weak electric signals of the cerebral cortex and analyzing different brain wave characteristic signals; the seat posture adjusting assembly is used for storing and adjusting the seat state; the artificial natural breathing assembly is used for detecting and controlling the oxygen concentration; the water molecule atomization assembly is used for controlling the atomization amount of water molecules according to the humidity data; the noise interference elimination assembly is used for blocking noise transmission; and the three-in-one control assembly is used for adjusting music, an air conditioner and light. The technical problems that only indexes in a single cab are changed, the sleep state of a driver cannot be detected, and the environment suitable for sleep cannot be automatically adjusted are solved. The technical effect of intelligently improving the sleep quality of the personnel in the driving cabin is 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 utility model discloses an electrode assembly of an implantable brain-computer interface. The electrode assembly comprises a flexible electrode and a switching device, the detection part of the flexible electrode is in contact with the biological cerebral cortex, an electric signal of the biological brain is obtained through the detection part, and then the electric signal is transmitted to the switching device through the transmission part of the electrode and the first interface; and then the data is transmitted to the external equipment through the second interface of the switching device. In other words, the flexible electrode and the detection part, the transmission path and the first interface included in the flexible electrode are more suitable for being in contact with the biological cerebral cortex and obtaining the electric signals under the condition that brain tissue is not damaged, and the switching device and the second interface included in the switching device are more suitable for transmitting the electric signals and ensuring the signal quality. Through mutual cooperation of the first interface of the flexible electrode and the second interface of the switching device, it is guaranteed that the biological brain tissue is not damaged, electric signals are obtained under the condition that rejection reaction is avoided, and transmission can be carried out under the conditions of high efficiency and signal quality guaranteeing.

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 utility model provides a folding transcranial magnetic stimulation coil, which comprises a left coil and a right coil, the left coil and the right coil are symmetrically arranged, the left coil and the right coil are respectively folded along a transverse axis and a longitudinal axis, and the folding angle is variable. The folding angles of the two coils along the transverse axis and the longitudinal axis are adjusted, the fitting degree of the coils and the human brain is improved, the stimulation intensity and the stimulation depth of the transcranial magnetic stimulation coil on the cerebral cortex layer are improved on the basis that focusing performance is kept, and the transcranial magnetic stimulation coil is simple in structure, convenient to machine and capable of being widely applied to the technical field of medical equipment.

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 present invention relates to the field of medical data analysis technology, and in particular to an automatic electroencephalogram analysis method and system. An automatic electroencephalogram analysis method comprises: taking original electroencephalogram signal data; sending the electroencephalogram signal data into an electroencephalogram signal noise reduction model for processing to output noise-reduced electroencephalogram signal data. The present invention performs noise reduction processing on the original electroencephalogram signal data through the electroencephalogram signal noise reduction model, which can reduce the influence of various noise sources in the original electroencephalogram signal data, thereby improving the quality of the expression of the electrical activity of the patient's cerebral cortex, and facilitating the subsequent use of the electroencephalogram signal data; and in the electroencephalogram signal noise reduction model, the features similar to the influence of noise patterns in the original electroencephalogram signal data are aggregated by dynamic routing, providing a reference for subsequent noise reduction operations, and can effectively adapt to dynamically changing noise to obtain a better noise reduction effect.