Systems and methods for deep brain stimulation using kinematic feedback in accordance with embodiments of the invention are illustrated. One embodiment includes a deep brain stimulation system, including an implantable neurostimulator, a first inertial measurement unit (IMU), a second IMU, and a controller, where the controller is communicatively coupled to the implantable neurostimulator, the first IMU, and the second IMU, and where the controller is configured to obtain kinematic data from the first IMU and the second IMU, identify an abnormal movement event based on the kinematic data, and modify deep brain stimulation provided by the implantable neurostimulator based on the identified abnormal movement event.

Methods and systems are disclosed for analyzing interactions between low-frequency oscillations and high-frequency activity in electromagnetic brain signals such as EEG, MEG, SEEG, and ECoG signals in subjects in real-time that does not depend on the signals being contained within narrow frequency bands, sinusoidal, sustained and monolithic. The disclosed methods and systems can be applied to electromagnetic brain signals to detect brain activity alterations associated with neurological and psychiatric diseases.

An illustrative optical measurement system may include a primary controller; a plurality of secondary controllers communicatively coupled to the primary controller; and a plurality of modules, each module included in the plurality of modules comprising: a light source configured to emit light directed at a target, and a plurality of detectors configured to detect photon arrival times for the light after the light is scattered by the target; wherein: the plurality of modules is divided into a plurality of module subsets, and each module subset included in the plurality of module subsets is communicatively coupled to a respective secondary controller included in the plurality of secondary controllers.

Methods, devices, and systems induce neuromodulation by focusing a source of stimulation through a skull/brain interface in the form of an aperture formed in the skull, a naturally occurring fenestration in the skull, or a transcranial channel. Methods, devices, and systems identify where to locate skull/brain interfaces, accessories that can be used with the interfaces, and features for controlling stimulation delivered through the interfaces. Multiple indications for the skull/brain interfaces include diagnosis and treatment of neurological disorders and conditions such as epilepsy, movement disorders, depression, Alzheimer's disease, autism, coma, and pain.

A hot/cold sensation estimating device according to one embodiment includes a sensing unit and an estimating unit. The sensing unit is configured to sense a behavioral thermoregulatory reaction and an autonomic thermoregulatory reaction of living matter against an ambient environment based on sensor data acquired through a sensor for sensing vital activities of the living matter. The estimating unit is configured to estimate a hot/cold sensation sensed by the living matter based on a sensing result of the behavioral thermoregulatory reaction and a sensing result of the autonomic thermoregulatory reaction.

Quantitative susceptibility mapping methods, systems and computer-accessible medium include generating images of tissue magnetism property from complex magnetic resonance imaging data using the Bayesian inference approach. The tissue magnetism images is then used to monitor remyelination, such as remyelination in multiple sclerosis patients in response to therapy. Multiple sclerosis lesions defined on magnetic resonance imaging are further characterized on tissue magnetism images into hyperintense, isointense and hypointense parts for measuring remyelination. Thus, magnetic susceptibility information and other tissue properties associated with at least one structure are determined.

Mechanisms including: receiving a first set of observed spike counts (FSoOSCs) for the spiking cells; determining a set of probabilities (SoPs) by: retrieving the SoPs from stored information (SI); or calculating the SopS based on the SI, wherein the SI regards possible biological states (BSs) of a subject, wherein each of the possible BSs belongs to at least one of a plurality of time sequences (PoTSs) of BSs, wherein each of the PoTSs of BSs corresponds to a possible action of the subject, and wherein each probability in the set of probabilities indicates a likelihood of observing a possible spike count for one of the plurality of spiking cells; identifying using a hardware processor a first identified BS of the subject from the possible BSs based on the FSoOSCs and the set of probabilities; and determining an action to be performed based on the first identified BS.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating visualization data for a selected neuro-network. In one aspect, a method comprises: receiving selection data selecting a network in a brain of a subject; processing magnetic resonance image data of the brain to identify a set of tracts that are predicted to be included in the selected network; processing the set of tracts to identify a proper subset of the set of tracts as being spurious tracts; generating a set of valid tracts by filtering the spurious tracts from the set of tracts that are predicted to be included in the selected network; providing visualization data for the selected network showing a three-dimensional spatial representation of both: (i) the valid tracts, and (ii) the spurious tracts, wherein the spurious tracts are visually distinguished from the valid tracts.

A system and methods for labeling tractography, having a tract segmentation and a tract labeling atlas, in a presence of a lesion in a brain, involving: a graphical user interface (GUI) comprising a tool configured to facilitate adjusting a displacement for intraoperatively reperforming the tract segmentation in approximately real time, modeling deformation of the tract labeling atlas by facilitating modeling a force exerted by the lesion on the brain, and defining parameters of a size, a shape, and a level of the displacement condition; and a processor in communication with the GUI and configured to: determine whether an infiltration condition and a displacement condition appears in the tractography; if the infiltration condition and the displacement condition is determined to appear in the tractography, estimate the infiltration condition and the displacement condition; if the displacement condition is determined to appear in the tractography, instruct the GUI to render the tool and model the force exerted by the lesion on the brain by using the parameters, whereby a new tract segmentation and a new tract labeling atlas are provided; and if the displacement condition is determined to be absent from the tractography, refrain from modeling the force, a presence of only the infiltration condition being assumed.

Concussion sensing helmet and methods of use including at least one accelerometer, at least one force sensor, at least one indicator, and a processor configured to receive and process accelerometer input from the at least one accelerometer and force sensor input from the at least one force sensor, and to instruct the at least one indicator to signal a concussion condition when the accelerometer input and the force sensor input are consistent with an impact sufficient to cause a concussion.