28 results about "Thalamus" patented technology

The invention relates to a brain region positioning magnetic resonance data processing method based on nerve stimulation target optimization, and the method comprises the steps: obtaining the functional magnetic resonance imaging data of a subject, extracting the signal response sequence of each brain region before and after nerve stimulation through time domain analysis, and determining the brain region with a characteristic response time window according to the response delay difference; the method comprises the following steps: detecting delayed oscillation characteristics in a cortex signal based on a neural feedback relationship between a cortex region and a deep structure to determine potential regulatory pathways of thalamus and other deep brain regions so as to position indirect stimulation targets which cannot be directly imaged; decoupling analysis of cerebral blood flow signals and nerve activation signals is carried out on the candidate brain area, and when it is detected that blood flow fluctuation exists in the area but synchronous nerve activation is lacked, it is judged that the area is a pseudo activation area and excluded; according to the method, the time delay correlation degree between the stimulation sequence and the brain region signal is calculated through the improved cross-correlation integral function, and the high-frequency noise interference is suppressed in combination with the nonlinear attenuation item, so that the estimation of the brain region response delay is more stable and repeatable.

Methods and systems for programming stimulation parameters for assisting deep brain stimulation (DBS) in experimental patients are described. A cumulative database includes data from multiple historical adaptation / programming sessions. The data may include various sets of stimulation parameters tried for patients in the database; data relating to the position of electrode leads relative to the anatomical features of the patient's brain, such as alignment with the subthalamic nucleus (STN); scores indicating the therapeutic effectiveness of the stimulation parameters; and data relating to stimulation field models (SFM) of the various sets of stimulation parameters. This database can be used to predict stimulation parameter sets that may be therapeutically effective for experimental patients.

Methods and systems are described for stimulation parameter programming to assist in deep brain stimulation (DBS) of a subject patient. The cumulative database includes data from a plurality of historical adaptation / programming sessions. The data may include various sets of stimulation parameters attempted for the patient in a database; data relating to the position of the electrode lead relative to an anatomical feature of the patient's brain, e.g., alignment with respect to its subthalamic nucleus (STN); a score of the stimulation parameter indicative of therapeutic effectiveness of the stimulation parameter and / or causing a side effect in the patient; and data relating to a stimulation field model (SFM) of the various sets of stimulation parameters. The database may be used to predict sets of stimulation parameters that may be effective or cause side effects to the treatment of the subject patient.

Provided herein are targeting peptides and vectors containing a sequence that encodes the targeting peptides that deliver agents to specific substructures in the brain. Specifically, the targeting peptide is a component of a modified, sequence-specified adeno-associated virus (AAV) capsid protein further wherein the brain substructure may be the globus pallidus, putamen, internal capsule, caudate, claustrum, substantial nigra, motor cortex, insula,.temporal cortex, thalamus, hippocampus, subiculum, and deep cerebellar nuclei.

The present disclosure relates to the treatment of patients with mid- to late-stage Parkinson's Disease using subthalamic nucleus deep brain stimulation (STN-DBS) to a target a defined region of the brain. In particular, by positioning and / or programming the DBS electrode to stimulate cortical input fibers from the primary motor and supplementary motor areas (but not the pre-SMA), improved therapeutic benefits are obtained.

Various embodiments of the present technology generally relate to closed loop deep brain stimulation based on inferred sleep stage from physiological data using machine learning classifiers. Some embodiments, for example, may use subthalamic nucleus (STN) deep brain stimulation (DBS) to treat advanced Parkinson's Disease motor symptoms and improve sleep by identifying sleep stages commensurate with clinician-scored polysomnography (PSG). The DBS may be adapted to include a novel artificial neural network (ANN) that triggers targeted stimulation in response to inferred sleep state from STN local field potentials (LFPs) recorded from implanted DBS electrodes. A feedforward neural network can be trained to prospectively identify sleep stage with PSG-level accuracy. In some embodiments, the machine learning model stored within the DBS may also adapt stimulation during specific sleep stages to treat targeted sleep deficits.

The invention discloses a brain level dynamic analysis and virtual intervention method based on thalamus-cortex functional gradient, and belongs to the technical field of neural image analysis and mental disease calculation modeling. The invention aims to solve the problems that the existing research cannot systematically reveal the time sequence damage of thalamic cortex connection in disease development, cannot describe a cortex hierarchy compression mechanism, and lacks a simulation framework for theoretical intervention verification. A set of comprehensive analysis process integrating large-sample multi-center resting state fMRI, functional gradient mapping, sensory movement-highlight network-joint cortical axis construction, cortical separation coefficient calculation and virtual intervention simulation is provided to identify systematic anomalies of the thalamic cortical network in schizophrenia. And the key function of the highlighting network in the hierarchical structure damage process is analyzed. The cross-disease course, multi-scale and multi-network integration method established by the invention can systematically describe the hierarchical recombination process from the sensory region to the joint region in schizophrenia, and provides an innovative technical path for understanding disease neural basis, identifying disease course stage characteristics and exploring potential intervention targets.

The present disclosure relates to systems, devices, and methods for ultrasound neuromodulation of a target brain region to modulate the connectivity within the default mode network. The method involves administering focused ultrasound configured to modulate the connectivity within the default mode network. Modulating the connectivity of the default mode network can promote mental well-being, decrease the frequency and duration of non-present-focused thinking, enhance present-tense experiential engagement, improve attention, reduce mind wandering during tasks, and / or mitigate ruminative thinking. The focused ultrasound can target the anterior thalamus or neighboring structures, utilizing two transducers placed over the temporal window to create a cross beam overlapping the thalamus. Ultrasound may be pulsed within a spectral range of 10-30 Hz, with a duty cycle of less than 15%, and delivered over a period of at least 5 minutes.

The invention discloses a chronic pain relieving method based on virtual reality and time interference nerve regulation, and relates to the technical field of nerve regulation and virtual reality medical treatment, and the method comprises the steps: constructing an individual function vulnerability quantitative model of a multi-dimensional index; generating a dynamic adaptive virtual reality scene synchronized with the pain rhythm and emotion based on the model; configuring double-frequency time interference electric field parameters of targeted thalamus and anterior clasp back; performing millisecond-level synchronization on cognitive emotion events in neural regulation and virtual reality, and performing closed-loop adjustment on intervention parameters based on gamma wave band phase amplitude coupling strength; the pain evolution trend is predicted through the long-short-term memory network, and the subsequent intervention strategy is optimized. According to the invention, multi-dimensional precise targeted intervention on chronic pain is realized, the safety, individual suitability and long-term curative effect of treatment are remarkably improved, and the problems of poor suitability and difficult maintenance of curative effect in chronic pain intervention of old people are solved.

This invention provides the application of deoxycholic acid in the treatment of postherpetic neuralgia. This invention is the first to discover that deoxycholic acid is effective in treating postherpetic neuralgia, and that inhibiting the nucleus tractus solitarius-paraventricular nucleus circuit of the thalamus is also effective in treating postherpetic neuralgia. A synergistic therapeutic effect was achieved when deoxycholic acid was combined with an inhibitor of the nucleus tractus solitarius-paraventricular nucleus circuit. This invention provides a new strategy for the treatment of postherpetic neuralgia.

The invention relates to the technical field of consciousness behavior feature recognition, in particular to a postoperative consciousness monitoring system based on multi-modal data analysis. A consciousness characteristic dominant window is determined by analyzing gamma signal waves of the forehead lobe electroencephalogram signals in the signal acquisition window, the excitation module controls the second acquisition unit to perform illumination excitation on pupils of a target object and acquire pupil state images, and a pupil state change curve is drawn through the information matching module. And constructing a corresponding relation between the consciousness response characterization duration and the consciousness transmission characterization duration, and calculating a follow-up coefficient of the consciousness transmission characterization duration and the consciousness response characterization duration through an early warning module so as to judge whether to send out an early warning prompt or not. Furthermore, multi-modal monitoring of consciousness-related neural activity and peripheral response is realized, and the accuracy of postoperative consciousness monitoring is improved by establishing association between brain neurotransmission and pupil response.

The application discloses application of anterior piriform cortex GABAergic neurons as an analgesic target point, and relates to the technical field of neuroscience and pain. GABA The application discloses that the neural loop (APC GABA →MD) from the anterior piriform cortex GABAergic neurons to the thalamic dorsal medial nucleus plays a key role in pain regulation. Experiments prove that the loop can not only relieve acute pain, but also has a significant analgesic effect on the clinical treatment of intractable chronic inflammatory pain and neuropathic pain models, and shows a wide treatment application prospect.

Artificial expression constructs for modulating gene expression in targeted central nervous system cell types are described. The artificial expression constructs can be used to express synthetic genes or modify gene expression in GABAergic or glutamatergic neurons within the thalamus. In some cases, the artificial constructs can also be used to express synthetic genes or modify gene expression in neurons within the thalamus as well as a secondary cell type.

This disclosure provides a method for selecting parameters for stimulation of the thalamus using a deep brain stimulator to treat a motor disorder in a subject, such as paralysis of the upper limb and face muscles. Also provided are methods for treating motor disorder in a subject. Also provided is an implantable electrode lead for neuromodulation and recording, configured to provide targeted stimulation and / or recording to multiple anatomically distinct neural structures, specifically the thalamus, the motor cortex, and optionally, the corona radiata, using a single continuous elongate lead body.

A robot arm brain-like control method and control apparatus based on a spiking neural network. The control method comprises: on the basis of a spiking neural network, constructing a cerebellar module, so as to use the cerebellar module to obtain an initial torque instruction for a target robot arm; on the basis of the initial torque instruction, constructing a thalamic module, and using the thalamic module to adjust the initial torque instruction, so as to obtain a final torque instruction; using the final torque instruction to construct a brainstem module, so as to obtain a feedforward torque; and on the basis of spike coding and the feedforward torque, constructing a spinal cord module, and combining the cerebellar module, the thalamic module and the brainstem module to construct a robot arm control model, so as to output a torque control instruction. The control apparatus is used for implementing such a control method. The present invention can solve problems such as reduced control accuracy, impaired universality and inability to adapt to control tasks under complex load conditions, which are caused by significant differences in working requirements when a robot arm executes different tasks due to the impact of the size, mass, etc., of an operated object in complex working scenarios.

The application discloses a dual-system game visual language navigation method and device based on neural cognitive inspiration, which comprises the following steps: acquiring visual feature information and language feature information, extracting visual feature embedding and text feature embedding, and then performing modal alignment and feature fusion to obtain a current state; inputting a state, an action and a global hidden state of a previous moment into a world model based on a gated recurrent unit to generate a current global hidden state; based on the current state and the current global hidden state, based on a multi-brain region collaborative mechanism, generating initial activation tendencies of a goal-oriented system and a habit system by using a prefrontal cortex and a sensory motor cortex, calculating dynamic interest functions of the goal-oriented system and the habit system by using a precingulate gyrus, a thalamus and a premotor cortex, arbitrating and selecting an execution system according to the initial activation tendencies and the dynamic interest functions of the goal-oriented system and the habit system, generating a current execution action by using the execution system, and feeding back and adjusting.

The present disclosure provides myeloid cells, microglial progenitor cells, and microglia-like cells in which a mutant gene has been repaired or replaced, and methods of using such cells to treat disease. Mutations in CSF1R were corrected in human induced pluripotent stem cells. The resulting cells were differentiated into microglial progenitors and then transplanted into the brain of xenotransplantation-compatible CSF1R-AFIRE / AFIRE mice, thereby preventing or reversing phenotypes associated with leukodystrophy, including thalamic microbleeds, calcification, astrogliosis, axonal spheroids, synaptic loss, and accumulation of Tau phosphorylated at threonine residue 217.

This invention discloses a time-interference-based system for optimizing stimulation parameters of the subthalamic nucleus in Parkinson's disease, belonging to the field of stimulation parameter optimization technology. The system includes: a multimodal data acquisition and preprocessing module for acquiring motor neural data and performing data preprocessing; a gait electromyographic stability assessment module for analyzing motor stability characteristics to construct stability indices and determine stability improvement before and after stimulation; a stimulation dose-response modeling module for identifying the half-effect equivalent stimulation intensity and target stability level, inferring the potential improvement trend of the current stimulation, generating candidate stimulation parameter combinations and improvement predictions; and a comprehensive benefit parameter optimization module for fitting the improvement response time constant, obtaining an evaluation window, assessing the comprehensive benefit, and selecting recommended stimulation parameters. This invention solves the technical problem of existing technologies where large fluctuations and high noise in single-modal data make it difficult to stably reflect the patient's true neuromotor state, leading to unreliable stimulation parameter optimization.

Disclosed herein are systems and devices for providing stimulation based on electroencephalogram (EEG) data. An example Non-Invasive EEG / Ultrasound Stimulation Electronic Patch (NEUSleeP) device can provide, via a wearable ultrasound transducer, non-invasive ultrasound stimulation to the subject's subthalamic nucleus (STN) or other target areas of the subject's brain.

The invention relates to the technical field of nerve regulation and control, in particular to a Parkinson's disease REM sleep intervention system based on medial subthalamic nuclear power stimulation, which comprises an image data acquisition module for acquiring preoperative structural magnetic resonance, diffusion tensor imaging and resting state functional magnetic resonance data of a patient; the individualized target region positioning module is used for constructing an individualized brain structure-function connection group of a patient, identifying by using a probabilistic fiber tracking algorithm, and positioning a target region of a subthalamic nucleus abdominal inner side joint region; the electrode planning and parameter generation module is combined with a deep brain electrical stimulation volume activation prediction model to generate a deep brain directional electrode implantation planning path and a stimulation parameter initial scheme; the stimulation parameter regulation and early warning module is used for collecting patient monitoring data, analyzing the relevance between the rapid eye movement sleep behavior disorder symptom improvement degree and stimulation parameters, dynamically adjusting, and periodically monitoring the change of the Monte-eye cognitive assessment scale score of the patient at the same time. Therefore, the problems of extremely high curative effect heterogeneity, fixed postoperative stimulation parameters and the like in the prior art are solved.

The present disclosure relates to the treatment of patients with early-stage Parkinson's Disease using subthalamic nucleus deep brain stimulation (STN-DBS) to a target a defined region of the brain. In particular, by positioning and / or programming the DBS electrode to stimulate cortical input fibers from the supplementary motor area (but not the pre-SMA), improved therapeutic benefits are obtained.

The invention relates to the technical field of biomedicine, in particular to a thalamus / interbrain organ and neuron culture method. The invention provides a method for efficiently differentiating thalamic / interbrain organs and neurons by using human embryonic stem cells or induced pluripotent stem cells. It is found that in the early stage of cell differentiation, the c-JUN gene plays an important role in promoting nerve maturation and maintaining tight junction, the growth rate and the size of thalamus / interbrain organs can be remarkably increased by overexpressing c-JUN or adding c-JUN protein in thalamus / interbrain differentiation, the obtained organs have high-abundance neurons and tight junction protein, and the cell differentiation effect is good. And high expression of thalamus / interbrain characteristic signal protein TCF7L2 is realized. The neurons have abundant nerve fibers and adherent growth ability under the 2D culture condition, and the lifetime is long. The invention provides an efficient 2D neuron and 3D organoid differentiation technology for researching related development and pathology of thalamus / interbrain.

The application discloses a dual-system game visual language navigation method and device based on neural cognitive inspiration, which comprises the following steps: acquiring visual feature information and language feature information, extracting visual feature embedding and text feature embedding, and then performing modal alignment and feature fusion to obtain a current state; inputting a state, an action and a global hidden state of a previous moment into a world model based on a gated recurrent unit to generate a current global hidden state; based on the current state and the current global hidden state, based on a multi-brain region collaborative mechanism, generating initial activation tendencies of a goal-oriented system and a habit system by using a prefrontal cortex and a sensory motor cortex, calculating dynamic interest functions of the goal-oriented system and the habit system by using a precingulate gyrus, a thalamus and a premotor cortex, arbitrating and selecting an execution system according to the initial activation tendencies and the dynamic interest functions of the goal-oriented system and the habit system, generating a current execution action by using the execution system, and feeding back and adjusting.

This application relates to the field of robotic arm control technology, and particularly to a brain-like control method and device for robotic arms based on spiking neural networks. The method includes: constructing a cerebellum module based on a spiking neural network to obtain initial torque commands for the target robotic arm; constructing a thalamus module based on the initial torque commands and adjusting the initial torque commands using the thalamus module to obtain final torque commands; constructing a brainstem module using the final torque commands to obtain feedforward torque; constructing a spinal cord module based on pulse coding and feedforward torque, and combining the cerebellum module, thalamus module, and brainstem module to construct a robotic arm control model to output torque control commands. This solves the problems in related technologies where, in complex working scenarios, the size and mass of the manipulated object significantly affect the working requirements of the robotic arm when performing different tasks, leading to reduced control accuracy and impaired versatility, making it unable to adapt to control tasks under complex load conditions.

This invention relates to a brain region localization magnetic resonance imaging (fMRI) data processing method based on neural stimulation target optimization. It acquires functional magnetic resonance imaging (fMRI) data from subjects, extracts signal response sequences of each brain region before and after neural stimulation through time-domain analysis, and identifies brain regions with characteristic response time windows based on differences in response delay. Based on the neural feedback relationship between the cortex and deep structures, it detects delayed oscillation features in cortical signals to identify potential regulatory pathways in the thalamus and other deep brain regions, thereby locating indirect stimulation targets that cannot be directly imaged. It performs decoupling analysis of cerebral blood flow signals and neural activation signals on candidate brain regions; when blood flow fluctuations are detected in a region but synchronous neural activation is lacking, it is identified as a spurious activation area and excluded. This invention calculates the time-delay correlation between the stimulation sequence and brain region signals using an improved cross-correlation integral function, and combines a nonlinear attenuation term to suppress high-frequency noise interference, making the estimation of brain region response delay more stable and repeatable.

This disclosure provides a method for optimizing surgical placement of stimulation leads within the thalamus to treat a motor disorder in a subject, such as paralysis of the upper-limb and face muscles, which cause speech motor deficits. Also provided are methods for treating motor disorders in a subject.

The invention provides a Parkinson disease course quantitative evaluation method and system based on multi-scale feature fusion, and the method comprises the steps: simulating the continuous disease course progress of a Parkinson state from health to severe based on a constructed cortex-basal node-thalamus neural circuit model, so as to obtain neuron pulse sequence signals of each brain region at different progress stages; the method comprises the following steps: performing multi-scale feature extraction on a neuron pulse sequence signal to obtain a microscopic discharge feature, a macroscopic oscillation feature and a network synchronization feature; performing contribution degree sorting on the microcosmic discharge features, the macroscopic oscillation features and the network synchronization features through a recursive feature elimination algorithm to screen out a core feature subset most sensitive to the progress of the disease course; and inputting the screened core feature subset into the constructed machine learning model to output an evaluation result of the Parkinson disease course. According to the method, the saturation effect of a single index in the later period of the disease course is overcome, the linear evaluation of the whole disease course is realized, and the severity of the disease can be more comprehensively and accurately quantified.