NEUROANATOMICAL TRACT VISUALIZATION USING SYNAPTIC CONNECTIVITY GRAPHS

    公开(公告)号:US20210298624A1

    公开(公告)日:2021-09-30

    申请号:US16829179

    申请日:2020-03-25

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for neuroanatomical tract visualization using synaptic connectivity graphs. In one aspect, a method comprises: presenting, to a user and through a display, a representation of a synaptic connectivity graph representing synaptic connectivity between neurons in a brain of a biological organism; receiving, from the user, data specifying a seed neuron in the brain; identifying a neuroanatomical tract corresponding to the seed neuron in the brain; and presenting, to the user and through the display, a geometric representation of at least a portion of the brain of the biological organism that visually distinguishes the neuroanatomical tract corresponding to the seed neuron at neuronal resolution.

    VOLUMETRIC SUBSTITUTION OF REAL WORLD OBJECTS

    公开(公告)号:US20200184196A1

    公开(公告)日:2020-06-11

    申请号:US16216558

    申请日:2018-12-11

    Abstract: Implementations of the present disclosure provide techniques for providing a presentation of the objects that are depicted in an image of a scene, where the presentation improves perceiving the object within the scene. Some implementations include obtaining an image of a scene; identifying an object within the image of the scene; obtaining a particular three-dimensional model that corresponds to the object; generating or updating a three-dimensional representation of the scene based at least on the particular three-dimensional model of the object; and providing at least a portion of the three-dimensional representation of the scene that was generated or updated based on the three-dimensional model of the object to a scene analyzer. The three-dimensional representation of the scene can include data indicating an attribute of the object that is not visible or is not directly derived from the image of the scene.

    Neural functional localization using synaptic connectivity graphs

    公开(公告)号:US11636349B2

    公开(公告)日:2023-04-25

    申请号:US16829107

    申请日:2020-03-25

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying one or more regions of a brain of a biological organism that are predicted to be functionally-specialized for performing a task. In one aspect, a method comprises: obtaining data defining a synaptic connectivity graph representing synaptic connectivity between neurons in the brain of the biological organism; identifying a plurality of sub-graphs of the synaptic connectivity graph; determining, for each sub-graph of the plurality of sub-graphs, a performance measure characterizing a performance of a neural network having a neural network architecture that is specified by the sub-graph in accomplishing the task; and determining, based on the performance measures, that one or more sub-graphs of the plurality of sub-graphs correspond to regions of the brain of the biological organism that are predicted to be functionally-specialized for performing the task.

    Scene recognition using volumetric substitution of real world objects

    公开(公告)号:US10755470B1

    公开(公告)日:2020-08-25

    申请号:US16267582

    申请日:2019-02-05

    Abstract: Techniques are provided to estimate of location or position of objects that are depicted in an image of a scene. Some implementations include obtaining an image of a scene; identifying an object within the image of the scene; obtaining a three-dimensional model that corresponds to the object that was identified within the image of the scene, the three-dimensional model being obtained from the database of three-dimensional models; determining, based on data from the three-dimensional model, an estimated depth of the object within the scene; generating or updating a three-dimensional representation of the scene based at least on the estimated depth of the object within the scene; and providing the three-dimensional representation of the scene, including at least a portion of the three-dimensional representation of the scene that was generated or updated based on the three-dimensional model of the object, to the scene analyzer.

    NEURAL FUNCTIONAL LOCALIZATION USING SYNAPTIC CONNECTIVITY GRAPHS

    公开(公告)号:US20210304011A1

    公开(公告)日:2021-09-30

    申请号:US16829107

    申请日:2020-03-25

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying one or more regions of a brain of a biological organism that are predicted to be functionally-specialized for performing a task. In one aspect, a method comprises: obtaining data defining a synaptic connectivity graph representing synaptic connectivity between neurons in the brain of the biological organism; identifying a plurality of sub-graphs of the synaptic connectivity graph; determining, for each sub-graph of the plurality of sub-graphs, a performance measure characterizing a performance of a neural network having a neural network architecture that is specified by the sub-graph in accomplishing the task; and determining, based on the performance measures, that one or more sub-graphs of the plurality of sub-graphs correspond to regions of the brain of the biological organism that are predicted to be functionally-specialized for performing the task.

    SCENE RECOGNITION USING VOLUMETRIC SUBSTITUTION OF REAL WORLD OBJECTS

    公开(公告)号:US20200250879A1

    公开(公告)日:2020-08-06

    申请号:US16267582

    申请日:2019-02-05

    Abstract: Techniques are provided to estimate of location or position of objects that are depicted in an image of a scene. Some implementations include obtaining an image of a scene; identifying an object within the image of the scene; obtaining a three-dimensional model that corresponds to the object that was identified within the image of the scene, the three-dimensional model being obtained from the database of three-dimensional models; determining, based on data from the three-dimensional model, an estimated depth of the object within the scene; generating or updating a three-dimensional representation of the scene based at least on the estimated depth of the object within the scene; and providing the three-dimensional representation of the scene, including at least a portion of the three-dimensional representation of the scene that was generated or updated based on the three-dimensional model of the object, to the scene analyzer.

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