Neural signals of a subject intending certain postures can be decoded and a controllable device can be commanded to perform certain actions based on the decoded intended postures with a system, and method of use thereof, including a brain machine interface (BMI) device. The system also includes electrodes in communication with the subject's nervous system to record the neural signals and the controllable device, both in communication with the BMI device. The BMI device can store instructions and previously calibrated neural activity patterns for the certain postures and a processor for receiving the neural signals, pre-processing the neural signals, decoding the neural signals into neural activity patterns, and matching the neural activity patterns to the previously calibrated neural activity patterns. If a match is determined, then the BMI device can send a command, previously linked to the intended posture, to the controllable device to perform the action.

A method of identifying brain structures is disclosed. The method comprises imaging the cortex of the brain via inversion recovery magnetic resonance imaging, such that at least two areas are zeroed in terms of their longitudinal relaxation times, and associating the two areas with different brain structures, thereby identifying brain structures.

A system for determining parameters of porous media or material, which in an embodiment is biological tissue, includes an actuator and a displacement monitor. The actuator is adapted to apply a displacement to tissue at a particular frequency selected from a range of frequencies, and the force monitor adapted to monitor a mechanical response of tissue. The system also has a processor coupled to drive the actuator and to read the mechanical response, the processor coupled to execute from memory a poroelastic model of mechanical properties of the material, and a convergence procedure for determining parameters for the poroelastic model such that the model predicts mechanical response of the tissue to within limits.

A system and method for using a virtual reality or an augmented reality environment for the measurement and/or improvement of human vestibulo-ocular performance can be implemented by combining a video camera based eye orientation sensor, a head orientation sensor, a display, and an electronic circuit that connects the eye sensor, head sensor, and display. The system and method can be operated in the range of frequencies between 0.01 Hertz and 15 Hertz. The system and method can use a Fourier transform to compute a gain and a phase. The system and method can be used for measuring vestibulo-ocular reflex, dynamic visual acuity, dynamic visual stability, kinetic visual acuity, retinal image stability, or foveal fixation stability in a non-clinical setting. The system and method can be completely portable, head-worn, and self-contained.

A two-photon imaging system capable of imaging of an image region in real time is presented. The imaging system comprises a source of excitation light that provides the excitation light as a plurality of laser beamlets. The plurality of laser beamlets is collectively scanned by a single-axis scanner along a first direction in the focal plane of the image region and oriented such that neither the rows nor columns are aligned with the first direction. As a result, each laser beamlet scans a different sub-region of the image region and the plurality of sub-regions are simultaneously scanned. As a result, the entirety of the image region is scanned in the same amount of time required to scan one image sub-region.

Provided herein are methods for classifying or characterizing a biological sample in vivo or ex vivo in real-time using time-resolved spectroscopy and/or electrical stimulation. A biological sample may produce a responsive fluorescence signal when irradiated by a light excitation signal or pulse at a predetermined wavelength. The responsive fluorescence signal may be recorded. The intensity of the excitation wavelength may be recorded and used to normalize the recorded responsive fluorescence signal. The biological sample may produce a responsive electrical signal in response to electrical stimulation. Raw fluorescence decay data may be generated from the responsive fluorescence signal and pre-processed. The pre-processed raw fluorescence decay data may be de-convolved to remove an instrument response function therefrom and generate true fluorescence decay data. The biological sample may be characterized in response to the responsive fluorescence signal, the responsive electrical signal, the normalized responsive fluorescence signal, and/or the true fluorescence decay data.

Balance measurement systems and methods thereof include at least one measurement device or indicator and an unstable or dynamic device or surface or other balance device. In example forms, the at least one measurement device is generally removably mounted to a portion of the body of a user (and/or to a portion of the balance device) such that the movements and body behavior of a user (and/or the balance device) can be measured as the user attempts to balance on the balance device. According to one example form, the unstable device includes a suspended rope or slackline. According to other example forms, the balance device includes a generally unstable platform.

A neural-interface probe is provided. The probe may comprise a chip, a wire bundle substrate, and an encapsulant material. The chip may comprise a plurality of bond pads. The wire bundle substrate may comprise a plurality of wires extending through the substrate. The plurality of wires may comprise: (1) a proximal portion connected to the plurality of bond pads to thereby couple the chip to the substrate, and (2) a flexible distal portion configured to interface with neural matter. The encapsulant material may be disposed at least between the chip and the wire bundle substrate.

The present method and system provides a neuromodulation therapy including receiving a plurality of input data relating to a patient, the input data including brain value measurements and body value measurements. The method and system includes analyzing the input data in reference to reference data generated based on machine learning operations associated with existing patient data and reference database data. Based thereon, the method and system includes electronically determining, a brain malady and a severity value for the patient and electronically generating a treatment protocol for the patient, the treatment protocol includes transcranial stimulation parameters. Therein, the method and system includes applying a transcranial stimulation using the transcranial stimulation parameters based on the treatment protocol.

When operating a brain stimulation device, it is critical to understand and control the network effects associated with the area being targeted for stimulation. The combined system and methods provided herein provides the operator with a real-time view of the brain network potentially affected by the stimulation. The system and method are capable of increasing the accuracy of diagnostic information. Additionally, disclosed herein are a system and method for combining navigated brain stimulation data and anatomical data with brain connectivity data for an individual.