A system and method is provided for modeling brain dynamics in normal and diseased states.

According to one aspect of the invention, there is provided a method for monitoring hemodynamics, comprising the steps of: acquiring information on a posture of a first subject wearing a monitoring device; estimating a motion artifact predicted to be included in a spectroscopic measurement signal from the first subject which is measured by the monitoring device, with reference to the acquired information on the posture of the first subject, and a motion artifact estimation model for defining a correlation between a posture of at least one subject and a motion artifact occurring in a signal measured from the at least one subject; and removing the estimated motion artifact from the measurement signal from the first subject.

A diagnostic gage (12) that can be implemented into a tissue-simulating headform (17) or other anthropomorphic surrogate test device (11) as a means of determining the internal strain within the test surrogate. One embodiment of the gage consists of a matrix or substrate embedded with x-ray contrast agents (14) and a series of holes within the substrate (15) that provide contrasting markers in an x-ray image and a means of closely coupling the gage to the test specimen. The relative motion of these contrasting markers can be monitored using x-ray fluoroscopy equipment (e.g., source (10) and detector (13)). This gage provides a means of determining the internal strain within a headform surrogate model for the purpose of evaluating the performance of helmets in terms of reducing the occurrence of concussion among other biomechanical injuries from trauma.

Systems and methods for mapping neuronal circuitry in accordance with embodiments of the invention are illustrated. One embodiment includes a method for generating a neuronal shape graph, including obtaining functional brain imaging data from an imaging device, where the functional brain imaging data includes a time-series of voxels describing neuronal activation over time in a patient's brain, lowering the dimensionality of the functional brain imaging data to a set of points, where each point represents the brain state at a particular time in the timeseries, binning the points into a plurality of bins, clustering the binned points, and generating a shape graph from the clustered points, where nodes in the shape graph represent a brain state and edges between the nodes represent transitions between brain states.

Systems, methods and devices are implemented for microscope imaging solutions. One embodiment of the present disclosure is directed toward an epifluorescence microscope. The microscope includes an image capture circuit including an array of optical sensor. An optical arrangement is configured to direct excitation light of less than about 1 mW to a target object in a field of view of that is at least 0.5 mm.sup.2 and to direct epi-fluorescence emission caused by the excitation light to the array of optical sensors. The optical arrangement and array of optical sensors are each sufficiently close to the target object to provide at least 2.5 μm resolution for an image of the field of view.

Methods and devices for computationally constructing brain potentials across whole brain using electrocorticography signals recorded from a small region on the brain surface are disclosed. In some embodiments of the disclosed technology, a method includes obtaining a plurality of locally recorded surface potentials from a plurality of first cortical areas of a brain surface; and performing a virtual reconstruction of an average brain activity for individual cortical areas and a pixel-level cortex-wide brain activity for a plurality of cortical areas of the brain surface including the plurality of first cortical areas based on the plurality of locally recorded surface potentials.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a mental health prediction for a patient. One of the methods includes obtaining brain data captured by one or more sensors characterizing a brain of a patient; determining a network graph from the brain data, wherein: a node of the network graph corresponds to a parcellation in the brain of the patient, and a subset of nodes of the network graph corresponds to a particular functional area of the brain; generating, for each of a plurality of nodes in the network graph, a measure of centrality of the node; generating, for the particular functional area of the brain and using the generated measures of centrality, a health score representing a measure of health of the functional area of the brain; generating a mental health prediction for the patient using the health score.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a mental health prediction for a patient using a centrality ranking of the brain of the patient. One of the methods includes obtaining brain data of a patient, wherein the brain data comprises, for each of a plurality of pairs of parcellations formed from a set of parcellations where each pair comprises a first parcellation and a second parcellation, data characterizing a number of tracts connecting the first parcellation and the second parcellation; determining a network graph from the brain data; generating, for each of a plurality of nodes in the network graph, a measure of centrality of the node; determining a centrality ranking of the plurality of nodes of the network graph according to the respective measures of centrality; generating a mental health prediction for the patient using the determined centrality ranking.

A technique for reliably measuring brain atrophy based on image data, such as data collected as part of an MRI scan of a subject's brain. Rather than measure anatomical features of the brain in one of the scan planes as output by an MRI system, the image data is reformatted to generate a slice that may be transverse to those scan planes. The transverse slice is generated by determining a location of anatomical landmarks and reformatting the image data to represent a slice through these anatomical landmarks. The Anterior and Posterior Commissures are useful landmarks and ventricle area is a useful characteristic to measure from the slice. The rate of change of this measured characteristic can be tracked to determine disease progression and may be useful for diagnosis or evaluation of treatments, and the technique may be applied during clinical trials.

One aspect of the invention provides a method including: obtaining neural activity data for a first subject and a second subject during verbal interaction between the first subject and the second subject; and calculating coherence between the neural activity data for the first subject and the neural activity data for the second subject. Another aspect of the invention provides a non-transitory, tangible computer-readable medium comprising computer-readable program instructions for implementing the one or more of the methods described herein.