19 results about "Cortical surface" patented technology

A method and system for protecting electrode arrays while implanted on a brain including a flexible electrode array including non-penetrating cortical surface microelectrodes, a ceramic layer covering the electrode array and a polymer layer adjacent the ceramic layer, wherein the ceramic layer and the polymer layer hermetically seal the electrode array. The ceramic layer can be configured to exhibit sufficient flexibility to allow the electrode array to be implanted using minimally invasive surgical techniques, while still hermetically sealing the electrode array from a biological environment.

A device and system for real-time visualization of the electrophysiologic activity of a brain, particularly at the cortical surface. The neural device can acquire, process, and display high-spatiotemporal-resolution electrophysiologic data in real-time across entire electrode arrays spanning many thousands of electrodes over identified anatomic regions. The system is compatible with thin-film cortical surface electrodes that record from neural tissues without damaging those tissues. The system can be used to guide diagnostic and therapeutic actions with high precision, and also provides the basis for a brain-computer interface.

Systems and methods for high-bandwidth, minimally invasive brain-computer interfaces (BCIs) are disclosed. The BCIs are configured for deployment and operation in conjunction with a comprehensive interventional electrophysiology procedural suite. Three primary methods of minimally invasive electrode array delivery are disclosed: (1) cortical surface delivery, (2) ventricular delivery, and (3) endovascular delivery. Additionally, systems and methods for interacting with such high-bandwidth electrode arrays are discussed, including real-time imaging, signal processing, and neural decoding. Systems and methods for architectures for accelerating the underlying computational processes (such as graphics processing units or tensor processing units) are also discussed. Multiple applications of BCIs are discussed, with emphasis on restoration, rehabilitation, and augmentation of neurologic function.

Systems and methods for high-bandwidth, minimally invasive brain-computer interfaces (BCIs) are disclosed. The BCIs are configured for deployment and operation in conjunction with a comprehensive interventional electrophysiology procedural suite. Three primary methods of minimally invasive electrode array delivery are disclosed: (1) cortical surface delivery, (2) ventricular delivery, and (3) endovascular delivery. Additionally, systems and methods for interacting with such high-bandwidth electrode arrays are discussed, including real-time imaging, signal processing, and neural decoding. Systems and methods for architectures for accelerating the underlying computational processes (such as graphics processing units or tensor processing units) are also discussed. Multiple applications of BCIs are discussed, with emphasis on restoration, rehabilitation, and augmentation of neurologic function.

Systems and methods for high-bandwidth, minimally invasive brain-computer interfaces (BCIs) are disclosed. The BCIs are configured for deployment and operation in conjunction with a comprehensive interventional electrophysiology procedural suite. Three primary methods of minimally invasive electrode array delivery are disclosed: (1) cortical surface delivery, (2) ventricular delivery, and (3) endovascular delivery. Additionally, systems and methods for interacting with such high-bandwidth electrode arrays are discussed, including real-time imaging, signal processing, and neural decoding. Systems and methods for architectures for accelerating the underlying computational processes (such as graphics processing units or tensor processing units) are also discussed. Multiple applications of BCIs are discussed, with emphasis on restoration, rehabilitation, and augmentation of neurologic function.

Method and systems provide a tool to quantify sensory maps of the brain. Cortical surfaces are conformally mapped to a topological disk where local geometry structures are well preserved. Retinotopy data are smoothed on the disk domain to generate a curve that best fits the retinotopy data and eliminates noisy outliers. A Beltrami coefficient map is obtained, which provides an intrinsic conformality measure that is sensitive to local changes on the surface of interest. The Beltrami coefficient map represents a function where the input domain is locations in the visual field and the output is a complex distortion measure at these locations. This function is also invertible. Given the boundaries and the Beltrami map of a flattened cortical region, a corresponding visual field can be reconstructed. The Beltrami coefficient map allows visualization and comparison of retinotopic map properties across subjects in the common visual field space.

The application relates to the technical field of neural image processing, and particularly discloses a brain atlas division system based on a multi-modal multi-dimensional lateralization index similarity network. The method first performs spatial uniform random sampling on the left hemisphere cortical surface of an individual, and extracts the 5-layer neighborhood of the sampling points by using the grid topological connection relationship; then, according to the cross-hemisphere vertex correspondence, the symmetric neighborhood is positioned in the right hemisphere, and the lateralization index (LI) distribution of the cortical features is calculated; by kernel density estimation modeling and morphological counter divergence algorithm, the LI-MIND correlation matrix representing the whole brain symmetry is constructed; finally, the spectral clustering algorithm is used for feature decomposition and dimension reduction of the matrix, the optimal clustering number is determined according to the contour coefficient, and the smooth individualized brain region division atlas is generated. By introducing the topological neighborhood and the lateralization distribution characteristics, the problem that the traditional brain atlas cannot effectively capture the individual organization left-right hemisphere difference is solved, and the brain region division scheme depending on the lateralization information is provided.

This invention discloses a method, system, device, and medium for processing data for predicting the risk of neonatal encephalopathy, belonging to the field of medical image processing. The method includes: acquiring conventional thick-slice T1-weighted and T2-weighted images of the neonatal brain; performing super-resolution reconstruction of the magnetic resonance imaging data based on self-supervised learning, reconstructing anisotropic thick-slice images into isotropic thin-slice images; performing quantitative analysis on the reconstructed high-resolution images, extracting multiple quantitative magnetic resonance parameters including brain region volume, cortical surface area, and T1 / T2 ratio; inputting the quantitative magnetic resonance parameters into a pre-trained neonatal encephalopathy prediction model, and outputting the predicted neurodevelopmental outcome. This invention can stably extract quantitative imaging features from conventional clinical thick-slice MRI images without increasing the number of scanning sequences or extending the scanning time, achieving early, objective, and accurate risk assessment of the neurodevelopmental outcome of neonatal encephalopathy, and has high clinical application value.

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

A sensory mapping method for a human brain is disclosed. The method includes the steps of flattening the cortical surface of the human brain, projecting functional imaging data onto the flattened surface, smoothing the functional imaging data, generating a sensory map, registering sensory maps across individuals and analyzing the maps in the common space. The flattening utilizes a conformal parametrization method. The smoothing utilizes a topological smoothing method that utilizes a diffeomorphic smoother. The registering is diffeomorphic. The sensory mapping method may further include a step of processing the functional imaging data to produce topological results.

This invention relates to the technical field of dynamic correction of brain deformation in neurosurgical navigation, specifically to a neurosurgical navigation method and system for adaptive correction of brain deformation. The method involves acquiring preoperative MRI data to extract initial cerebrospinal fluid (CSF) level, three-dimensional domain of the whole brain, and baseline elastic modulus, and recording steady-state intracranial pressure and baseline pulse wave amplitude. Intraoperatively, real-time acquisition of head tilt angle, mean intracranial pressure, pulse wave amplitude, CSF drainage velocity, and observed cortical surface displacement is performed. Based on this, the dynamic absolute height of the CSF level and equivalent elastic modulus are calculated, a total potential energy functional with dynamic physiological boundaries and stiffness constraints is constructed, and the three-dimensional displacement field is solved using observed cortical displacement as a forced boundary. Finally, an inverse addressing strategy is used to correct the images, and navigation is restored via DICOM flow propagation. This invention eliminates the accumulated errors in deep extrapolation caused by neglecting physiological constraints in traditional static models by fusing real-time intraoperative physiological data with a variational model of continuous medium mechanics, thus achieving adaptive correction of brain deformation.

A method for modulating the electrical synchronization of the cerebral cortex within safe limits by computing the orientation of the applied currents with respect to the orientation of the cortical surface and thus cortical columns. Ongoing electroencephalographic monitoring, including the synchronization of induced with stimulating currents, may confirm the precision and safety of the applied currents.

A method and system for protecting electrode arrays while implanted on a brain including a flexible electrode array including non-penetrating cortical surface microelectrodes, a ceramic layer covering the electrode array and a polymer layer adjacent the ceramic layer, wherein the ceramic layer and the polymer layer hermetically seal the electrode array. The ceramic layer can be configured to exhibit sufficient flexibility to allow the electrode array to be implanted using minimally invasive surgical techniques, while still hermetically sealing the electrode array from a biological environment.

The invention relates to the technical field of medical instruments, in particular to a Kirschner wire accurate guide device based on the anterior patella cortex surface, which is characterized by comprising a grip, a positioning frame, an elastic positioning point needle, a guide frame and a sliding guide block, the lower end of the positioning frame is provided with three elastic positioning point needles which are distributed in a spatial non-collinear mode, the guide frame is fixedly connected with the positioning frame and located on one side between the left lower point needle and the right lower point needle, the sliding guide block is transversely connected to the guide frame in a sliding mode, can move left and right and is located below the positioning frame, and a guide hole is formed in the sliding guide block. According to the method, on the premise of not depending on an articular surface and a fracture broken end and not interfering surrounding soft tissues, a stable and objective space reference datum is established on the patella anterior cortex surface, and a kirschner wire is guided to accurately enter an optimal track meeting the biomechanical requirement in the patella.

The invention discloses an automatic partitioning method and system for a multi-modal brain atlas in combination with a human connection group plan. The method comprises the following steps: firstly, acquiring T1 weighted sMRI data and fMRI data collected for a target tested brain, and converting the T1 weighted sMRI data and the fMRI data into an NIFTI format conforming to a BIDS standard; preprocessing and whole-brain segmentation reconstruction are carried out on the sMRI data, the preprocessed fMRI data are registered to a cortex surface model obtained through reconstruction, and the two types of registered data are converted to an MNI standard space; and finally, fMRI data in an MNI standard space is registered to a Conte69 template and then down-sampled to a spatial resolution required by a CIFTI space, and the two types of data are mapped to a CIFTI gray scale space and packaged. According to the method framework, mapping from a non-HCP standard protocol data set to an HCPMMP standard partition is realized for the first time, and possibility is provided for brain function research on a wider multi-mode data set.

The application provides a local sensor array design method for brain magnetic source positioning. The method comprises the following steps: obtaining a scalp surface and a cortex surface of a subject based on a head nuclear magnetic resonance image, obtaining a grid of the scalp surface by using a three-dimensional reconstruction technology, and further generating a candidate sensor array; selecting a dipole source of a brain functional area of interest based on a Brodmann partition system, and calculating array sensitivity corresponding to the selected dipole source by using a Frobenius norm; determining an initial position of the local sensor array based on the array sensitivity, and determining the volume of the sensor and the distance between adjacent sensors based on a size radius and a spacing radius. The local sensor array design method realized by the application is simple and efficient, has strong practicability and universality, and can obtain more accurate source estimation under the condition that the number of sensors is limited.

The invention relates to an MRI negative focal cortex anomaly automatic detection method. The method comprises the following steps: performing cortex surface reconstruction according to an MRI image of a patient; sketching a lesion mask, mapping the sketched lesion mask to the reconstructed cortex surface, and mapping lesion vertexes in the lesion mask to symmetrical vertexes in the healthy half brain; extracting a cortex feature of each mapped vertex; smoothing the extracted cortical features of each vertex by using a plurality of smoothing kernels, and carrying out standardization processing on three granularities, namely in-individual granularity, between-hemisphere granularity and between-individual granularity; grouping the training set, establishing and training a plurality of randomly initialized neural networks, integrating the neural networks into an integrated model, and performing final prediction on each vertex after standardization processing; and taking the vertexes of which the finally predicted lesion values are higher than a specified threshold as lesion vertexes, and screening and clustering the lesion vertexes. The method can help the MRI negative patient to automatically locate the epilepsy focus, and improves the detection rate of the MRI negative epilepsy patient.

According to the cerebral cortex multi-signal layer surface reconstruction method and system and the terminal provided by the invention, signal extraction is performed on the low-signal layer region presented in the image according to the brain region ultrahigh-field magnetic resonance image of the target object, and the initial low-signal layer inner surface and the initial low-signal layer outer surface obtained through extraction are subjected to surface reconstruction on the surface of the target object. Performing iterative optimization based on a preset multi-surface optimization energy function to obtain a target low-signal layer inner surface and a target low-signal layer outer surface; therefore, the multi-signal-layer surface of the cerebral cortex of the target object is reconstructed, and a basis is provided for quantitatively analyzing each signal layer and predicting the development degree and development trend of the cerebral cortex of the target object, whether a lesion occurs or not, the lesion type and the lesion degree and the like.

The application discloses a kind of biological fusion type three-dimensional nerve electrode, including depth sensing unit and two parts of plane sensing unit.Local field potential and deep brain electrical complex signal can be acquired simultaneously in cortical surface, and it has good biocompatibility and compliance.The maximum length of plane sensing unit is 5-20mm, and the thickness is less than 100μm.To ensure the accuracy of the nerve electrode, the minimum diameter of the sensing circuit is less than or equal to 50μm, the diameter of the depth sensing unit is less than or equal to 75μm, and the implantation depth range is 2-5mm.The number of sensing channels in the plane sensing unit part is 16-50, and the number of sensing channels in the depth sensing unit part is 25-60.During the manufacturing process, microchannels and other coupling structures are reserved on the plane sensing unit, and the integrated manufacturing of the nerve electrode is realized by printing and assembling from bottom to top layer by layer.