158 results about "Human brain" patented technology

The invention discloses a human brain specific fluid flow direction identification method comprising the following steps: S1, multi-input network model construction: using a decoder to segment a task, and introducing a boundary detection task; high-density lesions and surrounding edema in the medical image are accurately segmented according to the Vi < T > and an attention mechanism; s2, fluid mechanics model construction and parameter setting, focus classification and risk quantification: optimizing time windows of two times of CT scanning; constructing a three-dimensional geometric model of high-density lesions, peripheral edema and normal brain tissue RO I; constructing initial physical field distribution; setting boundary conditions corresponding to a vascular rupture source and a focus drainage area; and dynamically adjusting the time step length based on the flow velocity and the diffusion coefficient. The invention provides a human brain specific fluid flow direction identification method, which combines image high-dimensional features with a multi-physics field coupling model, and reveals the heterogeneity of human brain specific fluid-blood conversion and contrast agent leakage in absorption and peripheral edema expansion modes.

The invention discloses an artificial intelligence model optimization method based on a brain-like artificial neural network, and the method comprises the steps: inputting a task data set into an artificial intelligence model, carrying out the forward propagation, and discriminating a corresponding dormancy neuron or an activation neuron of the artificial intelligence model in a process of executing an artificial intelligence task; a neuron dormancy matrix or activation matrix is generated as a mask matrix of the artificial intelligence model network weight, and a forward propagation path of the artificial intelligence model is reconstructed, so that dormancy neurons do not participate in the training and testing process of the artificial intelligence model network structure; or only enabling the activated neurons to participate in the training and testing process of the artificial intelligence model network structure; and loading the reconstructed artificial intelligence model at the computing device to execute the artificial intelligence task. According to the method, the working mode that only 0.5%-2.5% of neurons of the human brain are activated and most neurons are in a dormant state is effectively simulated, the calculation cost of the model is greatly reduced while the calculation performance of the model is not reduced, and the calculation efficiency of the model is improved.

A computer-implemented method for decoding speech, language and related semantic neural activity includes: collecting neural signals from an array of electrodes implanted in or on a brain; extracting features from the neural signals to detect distributed signatures of linguistic encoding using non-contiguous coverage of the electrode array; and decoding linguistic units, including phonemes and semantic embeddings from the extracted features. The decoding can utilize a custom neural language model for a limited or impaired brain adapted from a generalized neural language model trained on other human brains with intact speech, linguistic and cognitive regions.

The invention discloses a multi-modal feature fusion prediction method and system for early screening of Alzheimer's disease, and belongs to the technical field of brain disease prediction. The method comprises the following steps: acquiring multi-dimensional data containing cognitive test scores, brain image scanning results and biomarker concentration levels from a patient record database, and performing standardization processing to obtain a multi-dimensional data set in a unified format; key feature vectors are extracted through a dimensionality reduction analysis method to capture the covariant relation between cognitive test scores and brain image changes; when the reduction range of the cognitive test score exceeds a preset threshold value and the brain image displays an atrophy sign, a classification model is constructed through an integrated learning method to preliminarily classify abnormal signals; and fusing the biomarker concentration level to obtain an abnormal signal vector. According to the method, the accuracy and efficiency of early screening of brain diseases such as Alzheimer's disease are remarkably improved through accurate evaluation of key parts of the human brain, such as hippocampus.

Provided are Aβ375 related oligomers / aggregates in human brains and anti-Aβ3175 related oligomers / aggregates antibodies thereof. In addition, the using of anti-Aβ3175 related oligomers / aggregates antibodies for the treatment of Alzheimer's disease (AD) is also provided.

This invention relates to the field of organoid disease models, and discloses a method for constructing a human brain organoid model of early-onset Alzheimer's disease (AD) and its applications. This invention introduces [a specific technology] into human embryonic stem cell lines through single-base editing and lead editing techniques. PSEN1 ΔE9、 PSEN1 M146V and APP Human embryonic stem cell lines carrying four familial pathogenic gene mutations (K670N and M671L) were constructed and induced to differentiate into Alzheimer's disease (AD) brain organoids. The AD brain organoid model established by this invention exhibited tau phosphorylation pathological phenotypes as early as 20 days and Aβ-related phenotypes as early as 40 days, with increased total Aβ, decreased Aβ42 / Aβ40 ratio, and simultaneous aggravation of Aβ-Tau pathology. This represents a complex neurodegenerative pathological model where multiple mutations synergistically regulate Aβ production and tau phosphorylation, which is highly valuable for understanding and studying early-onset familial AD. This invention provides a human brain organoid model for in vitro AD studies and offers a tool for studying the pathological mechanisms of AD and screening drugs.

The invention provides an automatic driving decision generation method and device, equipment and a storage medium. The automatic driving decision generation method comprises the steps that multiple pieces of current environment information collected by multiple pieces of sensing equipment at the current moment are acquired; judging whether target historical data matched with the multiple pieces of current environment information exists or not; if the target historical data exists, determining a virtual neurotransmitter concentration corresponding to each sensing device according to a historical weight, an original weight and a reliability coefficient corresponding to each sensing device in the target historical data; and generating an automatic driving decision according to the weights of the plurality of sensing devices. According to the method, the adjustment process of the neurotransmitters in the human brain is simulated, the weights of different sensing devices are adjusted through the virtual neurotransmitters with different concentrations, and the automatic driving decision is generated according to the weights of the multiple sensing devices. By simulating the flexibility of information processing of the human brain in a complex environment, the robustness and response speed of the automatic driving system in a variable environment and under the condition that sensing equipment is more and more diverse can be ensured.

The invention relates to the technical field of biological medicines, and provides a method for reducing acetonitrile residues in a recombinant human brain natriuretic peptide stock solution, which comprises the following steps: sequentially carrying out purification chromatography and ultrafiltration treatment on the human brain natriuretic peptide stock solution; during purification chromatography, a mobile phase comprises a phase A and a phase B; the phase A is a mixed solution of citric acid and sodium citrate; and the phase B is a mixed solution of citric acid, sodium citrate and sodium chloride. A chromatographic system is utilized, the recombinant human brain natriuretic peptide is adsorbed on a chromatographic medium under a specific mobile phase condition, then the chromatographic medium is switched to a proper B-phase buffer solution for elution, and in the process, acetonitrile is effectively separated and removed due to the adsorption characteristic difference between the acetonitrile and the recombinant human brain natriuretic peptide on the chromatographic medium. According to the technical scheme, the problem that the residual amount of acetonitrile in the recombinant human brain natriuretic peptide stock solution in related technologies is large is solved.

A system may comprise hardware and software configured to perform computing functions that mimic at least one computing function of a human brain, wherein the hardware and software comprises: analog circuitry configured to perform signal processing of neural signals obtained from living brain tissue using at least one sensor, a computer system comprising a processor, memory accessible by the processor, and computer program instructions stored in the memory and executable by the processor digital circuitry and software configured to process the obtained neural signals to generate a representation of a brain function from the obtained neural signals, and to generate parameters for use by analog and digital circuitry to perform computing functions that mimic at least one computing function of a human brain, and the analog and digital circuitry configured to use the generated parameters to perform computing functions that mimic at least one computing function of a human brain.

The invention relates to a structural network-genetic map biological network model for predicting ischemic stroke and a construction method thereof, and the method comprises the steps: extracting and calculating seven multi-scale morphological features and pairwise Pearson correlation coefficients among the features from T1 weighted imaging data and diffusion tensor imaging data; constructing a 308 * 308 morphological similarity network matrix and a brain network module for identifying ischemic stroke neural dysfunction; 1782 sampling points are extracted from the Airy human brain map, and each sampling point comprises expression data of 10185 genes; the method comprises the following steps: mapping space coordinates of AHBA sampling points to a cortex package of a Desikan-Killiany map, carrying out normalization processing to output 308 * 10185 brain region gene-by-gene expression matrixes, and constructing a structural network-gene map biological network model for predicting ischemic stroke by adopting a partial least square regression method and a bootstrap method. Compared with the prior art, the model determines the specific molecular mechanism related to the phenotypic structure change of ischemic stroke injury, and the stroke occurrence probability is predicted according to the specific molecular mechanism.

The invention belongs to the technical field of human body electroencephalogram signal processing and brain regulation and control, and provides a noradrenaline oscillation time-frequency-phase three-dimensional coupling sleep coordinated regulation and control device which comprises the following steps: calculating a three-dimensional coupling coefficient by combining a time domain correlation coefficient, a frequency domain correlation coefficient and an instantaneous phase difference between multi-modal physiological signals; determining the coupling state of the signal based on the three-dimensional coupling coefficient and a preset threshold value; predicting to obtain an optimal regulation factor and a modal weight based on a coupling coefficient matrix constructed based on a time domain correlation coefficient and a frequency domain correlation coefficient and a constructed three-dimensional coupling double-layer optimization architecture in combination with the multi-modal physiological signal; calculating the optimized stimulation intensity in combination with the modal weight, the optimal regulation factor and the multi-modal signal characteristic parameters; and adaptively selecting a stimulation mode and outputting a stimulation signal according to the coupling state of the current multi-mode signal and the optimized stimulation intensity. Accurate matching of stimulation parameters and nerve-blood vessel-cerebrospinal fluid system collaborative rhythm is realized.

A time sequence brain image calibration method based on multi-task adversarial learning belongs to the technical field of medical images, and comprises the following steps: pre-processing a pre-acquired time sequence brain image to remove irrelevant information; a brain image phenotype calibration network is divided into two sub-tasks (local detail reconstruction and global structure transformation), learning is carried out in different modes, and a discriminator in an adversarial learning strategy is adopted to restrain and generate a better calibration brain image. The method is very valuable for improving the brain image and gene association performance, and the state of the human brain can be effectively observed and understood.

The utility model discloses a brain-computer interface connecting structure which comprises a first shell, a second shell and a connecting piece, the first shell and the second shell are used for bearing acquisition electrodes, and the connecting piece is made of flexible materials and is connected and fixed between the first shell and the second shell. And the first shell and the second shell can form a certain angle. Compared with the prior art, the brain-computer interface connecting structure is simple, the hard shells are adopted to fix the acquisition electrodes, the hard shells are connected through the flexible connecting pieces, the hard shells can be matched with the radian of the human brain, and therefore flexibility and stability of the acquisition electrodes are guaranteed at the same time, and quality of signal data monitoring is improved.

The application relates to the technical field of industrial nondestructive testing, and particularly discloses a multi-modal industrial data three-dimensional fusion and visual detection method and system based on brain-like perception. The method is aimed at the problem of multi-modal data heterogeneity and fusion difficulty in synchronous detection of internal and external defects of a weld, and surface optical and internal ultrasonic data are synchronously collected through a binocular camera and an ultrasonic array sensor. After denoising, time sequence alignment and spatial registration, a human brain multi-modal information processing mechanism is simulated, time and space features are respectively extracted based on EEG and fMRI inverse problem solving ideas, and a composite space-time metric is constructed for weighted fusion. Then, three-dimensional reconstruction of internal and external defects of the weld is realized through tensor decomposition and joint inverse solution, and a visual image is generated. Finally, positioning, identification and quantitative analysis of the defects are completed through a lightweight detection network. The application realizes integrated, high-precision and visual synchronous detection of internal and external defect states, and significantly improves the comprehensiveness and reliability of industrial weld nondestructive testing.

1. The name of the design product: brain wave sensor. 2. The use of the design product: the design product is an electronic device, which is controlled by human brain waves. 3. The design points of the design product: shape and pattern. 4. The picture or photo that best indicates the design points: perspective view 1.

The present application relates to the technical field of cognitive impairment rehabilitation, in particular to a brain cognitive recovery training scheme analysis system and method for cognitive impairment, comprising five units of basic information acquisition, cognitive test execution, test report generation, norm updating and training scheme analysis, wherein the norm database is modeled in multiple dimensions according to age, educational background and medical history, a regional correction factor is introduced, data freshness is verified by means of blockchain storage, an adaptive sequence is generated for cognitive test, multi-modal data such as correct answer rate, touch screen trajectory and eye movement data are collected, time domain signal separation and denoising are performed, the training scheme analysis unit locates cognitive defects, matches the training module, monitors the brain electrical theta wave and P300 latency through biological feedback, dynamically adjusts the training intensity and frequency, promotes neural circuit reorganization and improves rehabilitation accuracy.

Embodiments of an implantable system and apparatus for providing electrical and optical deep brain stimulation are disclosed. Through the biological introduction of light-responsive opsins to neurons, the system is operable to transform neurons into optogenetically programmable state and history-dependent logical transformers. Embedded processors of the system are operable to stimulate individual neurons using phase-shifted electrical and / or optical signals through a neural interface comprising a plurality of carbon nanotubes, then electrically and / or optically measure the neurons. Due to the parallelism and chemical superposition of the human brain, the implantable system is operable to establish a quantum-like processing ability using its neural interface.

Systems and methods for neural modeling are disclosed. A perfusable microfluidic platform with human hippocampal organoid integration and functional vasculature is disclosed. Vascularized human brain organoids can be developed on a microphysiological platform. The system can include a membrane configured to enable perfusion throughout the membrane. The membrane can couple with a carrier. The system can include the carrier including channels. The channel can be configured to deliver a first set of cells to the membrane through a lumen of the membrane; and deliver a second set of cells to the membrane through an exterior of the membrane. The system can include monitoring components to continuously and non-invasively measure the onset and development of neural oscillations.

Artificial neural networks (ANNs) are computing systems that imitate a human brain by learning to perform tasks by considering examples. These ANNs are typically created by connecting several layers of neural units using connections, where each neural unit is connected to every other neural unit either directly or indirectly to create fully connected layers within the ANN. However, by representing an artificial neural network utilizing paths from an input of the ANN to an output of the ANN, a complexity of the ANN may be reduced, and the ANN may be trained and implemented in a much faster manner when compared to fully connected layers within the ANN. More specifically, the ANN may be trained sparse from scratch in order to avoid a more expensive procedure of training the ANN and compressing it afterwards.

This invention belongs to the field of biomedicine and relates to a method for preparing a Kabuki syndrome brain organoid model and its application. This invention provides the application of GSK-3 inhibitors in the preparation of drugs for treating Kabuki syndrome. Currently existing Kabuki models include heterozygous mice, zebrafish, and 2D human cell models. However, the complexity of human brain development cannot be compared to animal models or single 2D cell models. In this invention, the inventors used CRISPR-CAS9 gene editing technology to knock out KMT2D and established a Kabuki syndrome brain organoid model using brain organoid technology. Studies have found that, compared to the wild type, the Kabuki syndrome brain organoid exhibits premature differentiation of excessive GABAergic neurons. Furthermore, by testing the dosage and time window of the small molecule chir99021, we found that this small molecule can restore the phenotype of abnormal neuronal differentiation in the Kabuki syndrome brain organoid. This discovery will provide new insights for the treatment of Kabuki syndrome.

The application relates to a variational correlation evaluation method and device, which comprises the following steps: acquiring magnetic resonance image data to obtain to-be-processed data; determining an iteration position sequence of the to-be-processed data and extracting iteration features to obtain a training set and a test set; inputting the training set into a variational correlation evaluation classification model for iteration training and testing, judging whether the trained variational correlation evaluation classification model converges or not, and obtaining the variational correlation evaluation classification model when the model converges, and performing effective feature extraction based on the variational correlation evaluation classification model; determining each effective feature position sequence, converting the effective feature position sequence into a three-dimensional brain structure matrix, covering the three-dimensional brain structure matrix to a preset standard human brain template, and identifying effective features related to each stimulation condition. The application quantifies the contribution of a single voxel in the process of executing a specific cognitive function, and finally identifies and extracts the least amount of features that can best represent the target stimulation condition.

1. Name of the product in this design: Portable EEG-Near Infrared Synchronous Acquisition Device. 2. Purpose of this design: For use in medical research, neuroscience experiments and brain-computer interface applications, to simultaneously acquire electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) signals from the human brain. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The present application belongs to the technical field of biological medicine, and particularly relates to Hermetia illucens extract, an extraction method thereof and application thereof in preventing and treating tumors. The present application extracts polar components from Hermetia illucens powder, and the obtained Hermetia illucens extract has a significantly better inhibitory activity on the proliferation of Cal27 human tongue squamous cell carcinoma cells, Colo205 human colorectal cancer cells and U87 MG human brain astrocytoma cells than the Hermetia illucens powder without separation under the same mass concentration. In animal experiments, the Hermetia illucens extract can significantly prolong the survival cycle of MOC-1 tongue squamous cell carcinoma mice, and has a significantly better treatment effect than the Hermetia illucens powder and is close to the positive drug cisplatin.

The present disclosure provides a visual imaging and recognition device, which can be applied to the field of image processing technology. The device comprises: an imaging sensor for acquiring two-dimensional image information and three-dimensional depth information of a target object; a signal shaping and coding module for signal shaping and coding the two-dimensional image information and the three-dimensional depth information to obtain target two-dimensional image information and target three-dimensional depth information; a processing module for processing and recognizing the target two-dimensional image information and the target three-dimensional depth information to generate a recognition result; an output module for signal synchronous buffering and outputting the recognition result; and a programmable microcontroller for providing synchronous control signals to the imaging sensor, the signal shaping and coding module, the processing module and the output module to control the synchronous and coordinated operation of the device. The device can naturally imitate the working mechanism of the human brain visual system and has the advantages of high performance and low power consumption.

The invention provides a traditional Chinese medicine composition with functions of softening hardness and dredging collaterals as well as a preparation method and application of the traditional Chinese medicine composition. The traditional Chinese medicine composition with the functions of softening hardness and dredging collaterals is prepared from the following raw material medicines in parts by weight: 20-40 parts of turtle shells, 20-40 parts of radix paeoniae alba, 14-22 parts of sedum sarmentosum, 9-21 parts of teasel roots, 9-21 parts of rhizoma acori graminei, 9-21 parts of astragalus membranaceus, 14-22 parts of ligusticum wallichii and 3-15g of honey-fried licorice roots. The traditional Chinese medicine composition has the advantages that the traditional Chinese medicine composition adopts a treatment method of softening hardness to dissipate stagnation, dredging collaterals and relieving spasm, and can improve clinical symptoms such as cognitive impairment related to small cerebral vasculopathy of a patient, and / or anxiety and depression, and / or sleep disorder and the like. In-vitro experiments prove that the traditional Chinese medicine composition has a protection effect on human brain microvascular endothelial cell injury caused by hypoxia and reoxygenation, and can promote cell proliferation and inhibit cell apoptosis. Therefore, the traditional Chinese medicine composition can be applied to prevention and / or treatment of clinical symptoms related to small cerebral vasculopathy under the pathological mechanism of pulse stagnation and collateral arthralgia.

A personal system to collect and remove electromagnetic radiation (EMR) and excess magnetic and voltage fields from a human body includes portable and non-portable embodiments that, when applied to skin, can causes EMR fields to be drawn out of the body toward a magnet before which the wave is split into separate electrical and the magnetic fields at the surface of the containers. Extraneous magnetic fields coming from the body are absorbed into the magnetic field of the internal magnet while simultaneously donating electrons and creating electrical current within the body to reduce oxidative stress inflammation. A portable handheld system includes a fanny / back pack, a revised standard insulated conductive grounding cord and a specialized cap for mobile use of standard grounding equipment. The system includes more high-powered non-portable similarly functioning EMR-removing vacuum-like booster instruments and protective wearable outer gear.

The invention provides an audio-visual synchronization nerve regulation method and a related device. The method comprises the following steps: acquiring an electroencephalogram signal of a user; according to the electroencephalogram signals, gamma wave power values of a preset frequency band are extracted from a plurality of continuous time windows through a spectrum analysis method; according to the gamma wave power values and the electroencephalogram signals in the adjacent time windows, the gamma wave change rate is determined through a time difference method; determining a current stimulation state according to the gamma wave change rate; according to the current stimulation state and the gamma wave change rate, a proportional function algorithm is adopted to determine stimulation intensity or frequency adjustment amplitude; determining new stimulation regulation and control parameters according to the stimulation intensity or the frequency regulation amplitude; according to the new stimulation regulation and control parameters, visual and auditory pulse same-frequency stimulation signals are determined, and by establishing a second-level adaptation mechanism of the stimulation parameters and neural activity fluctuation, under the premise of guaranteeing audio-visual stimulation synchronization, the stimulation intensity and frequency can be dynamically adjusted along with the instant response characteristics of the human brain gamma rhythm all the time, and the nerve synchronization efficiency is improved.

The invention provides a brain organoid / encephalitis B virus infected brain organoid model and a construction method and application thereof, and belongs to the technical field of organoid. The invention provides the kit for constructing the brain organoid, the brain organoid is constructed on the basis of the kit, the construction method of the brain organoid is provided, and the constructed brain organoid model shows clear staged development characteristics, completely reproduces cell diversity in the human brain development process and forms ventricular-like structural characteristics. The encephalitis B virus infected brain organ model constructed on the basis of the obtained brain organs can be used for deeply analyzing the pathogenic process and related immune response characteristics of JEV infected human brain, researching and developing vaccines related to encephalitis B virus and screening antiviral drugs.

An object of the present invention is to provide a method of evaluating intercellular interactions in neuroinflammation using a co-culture containing human-derived neural cells capable of mimicking human brain functions. According to the present invention, there is provided a method of evaluating intercellular interactions in neuroinflammation, the method including a step of producing a co-culture containing at least two cells selected from the group consisting of human-derived astrocytes, human-derived neurons, human-derived microglia, and human-derived oligodendrocytes, a step of applying an inflammatory stimulation to a first cell contained in the co-culture, a step of detecting at least one selected from the group consisting of an inflammatory response marker in the cells contained in the co-culture, neural activity of the cells, and cell morphology, and a step of evaluating, over time, a change in at least one selected from the group consisting of the inflammatory response marker, the neural activity, and the cell morphology in the first cell and a second cell different from the first cell contained in the co-culture.