13 results about "Cognitive diseases" patented technology

The invention relates to a composition comprising at least 50 mg / g of one or more omega-3 fatty acids, at least 10 mg / g of one or more xanthophylls, at least 1 mg / g of one or more sterols and at least 2 μg / g of one or more phycoprostanes, and to the use of said composition in particular as a food supplement for the prevention of the onset of cognitive disorders.

Methods and systems for improving medical conditions by delivering a focused ultrasound signal to target sites of the brain. The focused ultrasound signal can have a mechanical index of between about 1.0 to about 8.0 and / or an acoustic pressure of between about 1.0 MPa to about 3.0 MPa. The medical condition can comprise addiction (including binge eating), anxiety disorders and anxiety associated disorders, tinnitus, neurodegenerative disorders, neuropsychiatric disorders, cognitive disorders, neurodevelopmental disorders, post-traumatic stress disorder, stroke recovery, and combinations thereof.

Cannabinoid analogs may exhibit anti-inflammatory properties such as by inhibition of cannabinoid type 2 (CB2) receptors. Pharmaceutical compositions comprising the cannabinoid analogs may be used to treat various diseases and conditions in mammals, including pain, anxiety, a sleep disorder, addiction, epilepsy, depression, post-traumatic stress disorder or Alzheimer's disease. In some examples, the pharmaceutical compositions may be administered for treating a cognitive disorder or for improving cognition.

The present disclosure relates generally to medical imaging and, more particularly, it relates to methods and systems for performing processing of magnetic resonance (MR) imaging of the brain which may be useful in the diagnosis of cognitive disorders. More specifically, the invention includes methods for processing cortical diffusion data from a region of a subject's brain, comprising determining values for the Axial Columnar Refraction (ACR) using values for AngleR and Axial Diffusivity.

The application discloses a cognitive disorder screening device and method based on a VR eye tracker and a brain-computer interface, and the device comprises a virtual reality scene generation module, an eye tracker data acquisition module, a brain-computer interface data acquisition module, a data analysis processing module and a cognitive disorder screening module. The virtual reality scene generation module is used for generating a virtual reality scene containing a cognitive task. The data analysis processing module is used for analyzing and processing the acquired eye movement data information set and electroencephalogram signal information set, and extracting a characteristic parameter sequence. The cognitive disorder screening module is used for performing cognitive disorder screening processing on the characteristic parameter sequence, and obtaining cognitive disorder information of a user. The cognitive disorder information comprises information about whether there is a cognitive disorder and a cognitive disorder degree.

The present application relates to the fields of medicine, health care products and food technology, and in particular to a traditional Chinese medicine composition for mood and cognitive impairment caused by degenerative diseases, which is made of the following raw materials by weight: 1-35 parts of radix puerariae, 1-35 parts of semen ziziphi spinosae, 1-35 parts of radix bupleuri, 1-35 parts of clematis, 1-35 parts of radix astragali, and 1-35 parts of herba eriodes. The present application has the effects of preventing and treating mood and cognitive impairment caused by various degenerative diseases, reducing anxiety-like response and depression level caused by degenerative diseases, preventing overexcitability of the nervous system, significantly improving learning and cognitive ability, and having stable effects without inhibiting normal nerve activity and hormone level.

This invention discloses a submillimeter-level diffusion magnetic resonance imaging (DTI) method for extracting the radial index of cortical layered cognitive structures, relating to the field of medical image processing technology. This invention aims to address the problems of existing technologies failing to accurately quantify the directionality of cortical microstructures and neglecting the heterogeneity of cortical layering. The method includes: acquiring DTI data and performing high-fidelity preprocessing such as MP-PCA denoising, Gibbs artifact removal, and Gaussian process distortion correction; estimating the diffusion tensor and extracting the principal feature vector based on the preprocessed data; reconstructing the cortical white matter and pia mater surface using T1 images and extracting the normal vector; calculating the absolute value of the dot product of the diffusion principal feature vector and the surface normal vector to construct a radial index map; and segmenting the cortex into multiple intermediate layers based on the principle of equal volume and extracting layering parameters. Through refined high-resolution data processing and geometric modeling, this invention can accurately quantify the radial alignment integrity of cortical nerve fibers, providing highly sensitive imaging markers for cognitive disorders such as schizophrenia.

New use of 1-amino-3,5-dimethyladamantane hydrochloride in treating or preventing cognitive impairment, reducing microglia in the cortex and hippocampus, reducing neuron loss in the cortex and hippocampus, and ameliorating the mitochondrial dysfunction state. The cognitive impairment includes cognitive impairment in systemic lupus erythematosus, Parkinson's disease, lateral sclerosis, stroke, multiple sclerosis, rheumatoid arthritis, inflammatory bowel disease, attention deficit hyperactivity disorder, sepsis-related encephalopathy, or mild cognitive disorder. The present application also provides a corresponding drug and a treatment or prevention method.

Methods of assessing or obtaining an indication of the presence of a cognitive disorder by analysing microstructural changes in regions of the brain are provided. The invention particularly relates to methods of assessing or obtaining an indication of the presence of types of dementia, for example Alzheimer's disease, by analysing changes in minicolumns in regions or layers of the cortex of the brain or of the whole brain.

The present application relates to the field of disease prediction in bioinformatics, and particularly relates to a cognitive disease classification method based on gene communication mode and multi-view learning. The present application uses a gene network reasoning algorithm to operate on the screened sample-gene expression matrix to obtain a gene regulatory network; combines the importance score of the gene regulatory network and the gene module information to obtain a gene module communication tensor; respectively extracts features from the gene module communication tensor and the sample-gene expression matrix, and puts the extracted features into a Transformer encoder and an interleaved decoder for feature fusion to obtain odd layer and even layer features, splices the features of the two layers and puts them into a multi-layer perceptron to finally classify Alzheimer's disease into different stages. The present application provides a neural network framework for double-view learning of gene communication analysis of Alzheimer's disease, fuses two-view information of gene module communication tensor and transcriptome, and improves the accuracy of brain disease stage classification.

A cognitive impairment auxiliary analysis method based on multi-view brain network feature fusion, belonging to the field of medical information processing technology, solves the technical problem that existing technologies struggle to fully exploit the correlations and complementarities between multi-level structural features of patients' brain functional connectivity data, leading to low accuracy in assessing patients' brain functional status. This method uses rs-fMRI as input data, extracts multi-level brain connectivity information by constructing functional connectivity networks and higher-order functional connectivity networks, and builds a multi-view local-global graph neural network model (MVLG-GNN) to achieve collaborative modeling, adaptive fusion, and auxiliary analysis combining group relationships of subjects from multiple views of brain connectivity features. This invention is also applicable to the field of Alzheimer's disease brain data processing.