Abstract: A slide carrier includes: a base support; and a slide platform having a surface that is parallel to a first plane defined by a first vector and a second vector, wherein a vector extending in a direction opposite to the direction of gravity is normal with respect to a second plane defined by a third vector and a fourth vector, an angle between the first vector and the third vector is greater than zero degrees and less than 90 degrees, and an angle between the second vector and the fourth vector is greater than zero degrees and less than 90 degrees.

Abstract: Described is a system for automatic adjustment of neurostimulation. The system controls stimulation of specific neural regions through a neural device positioned on a human subject, while simultaneously performing recordings from the neural device using a targeted arrangement of stimulating electrodes and distinct types of recording electrodes of the neural device. Stimulation of the specific neural regions is adjusted in real-time based on the recordings from the neural device.

Abstract: Described is system for mapping user behavior to brain regions of interest. Using a cognitive-behavior model, a behavioral task is selected that is suited for a desired brain state. Using a functional-anatomical model coupled to the cognitive-behavior model, a set of high-definition neurostimulations is selected to be applied to the user during performance of the selected behavioral task. The selected set of high-definition neurostimulations targets specific regions of the user's brain. Changes in the user's brain state are sensed during application of the set of high-definition neurostimulations and performance of the selected behavioral task using at least one brain monitoring technique. The coupled functional-anatomical and cognitive-behavior models are adapted until the desired brain state is reached.

Abstract: Described is a system for automated artifact removal to generate a clean signal. During operation, the system selects initial noise components from a multi-channel, pre-processed signal by performing independent component analysis decomposition on the pre-processed signal to separate and rank the independent components as noise components. A clean signal is then generated through optimized selection of the noise components based on a signal quality index in which the noise components are moved from the original pre-processed signal until a sufficient signal quality is received.

Abstract: The present application generally relates to methods and apparatus for evaluating and assigning a performance metric to a driver response to a driving scenario. More specifically, the application teaches a method and apparatus for breaking a scenario into features, assigning each feature a grade and generating an overall grade in response to a weighted combination of the grades.

Abstract: Described is a system for prediction and active compensation of occupant motor response in a vehicle accident. The system uses a spinal reflex model to generate a stimulus based on an accident scenario of an occupant in a vehicle, the stimulus being a set of proprioceptive signals induced by the accident scenario. A neuromuscular model then determines activation and contraction dynamics based on the stimulus. The activation and contraction dynamics represent muscle contraction forces spanning a skeletal system of the occupant. A musculoskeletal model then generates a predicted motor response of the occupant based on the activation and contraction dynamics. The predicted motor response can be used for a variety of purposes, such as initiating active compensation in a vehicle or modifying airline cabin design parameters to decrease the likelihood of injury to the occupant.

Abstract: Described is a system for neural decoding of neural activity. Using at least one neural feature extraction method, neural data that is correlated with a set of behavioral data is transformed into sparse neural representations. Semantic features are extracted from a set of semantic data. Using a combination of distinct classification modes, the set of semantic data is mapped to the sparse neural representations, and new input neural data can be interpreted.

Abstract: Described is a system for explaining how the human brain represents conceptual knowledge. A semantic model is developed, and a behavioral exam is performed to assess a calibration subject into a cohort and reveal semantic relationships to modify a personalized semantic space developed by the semantic model. Semantic features are extracted from the personalized semantic space. Neural features are extracted from neuroimaging of the human subject. A neuroceptual lattice is created having nodes representing attributes by aligning the semantic features and the neural features. Structures in the neuroceptual lattice are identified to quantify an extent to which the set of neural features represents a target concept. The identified structures are used to interpret conceptual knowledge in the brain of a test subject.

Abstract: Described is a system for automatic adjustment of neurostimulation. The system controls stimulation of specific neural regions through a neural device positioned on a human subject, while simultaneously performing recordings from the neural device using a targeted arrangement of stimulating electrodes and distinct types of recording electrodes and sensors of the neural device. Stimulation of the specific neural regions is adjusted in real-time based on the recordings from the neural device.

Abstract: The present application generally relates to methods and apparatus for evaluating driving performance under a plurality of driving scenarios and conditions. More specifically, the application teaches a method and apparatus for testing a driving scenario repetitively while altering a parametric variation, such as fog level, in order to evaluate driving system performance under changing conditions.

Abstract: The present application generally relates to methods and apparatus for evaluating driving performance under a plurality of driving scenarios and conditions. More specifically, the application teaches a method and apparatus for testing a driving scenario repetitively while altering a parametric variation, such as fog level, in order to evaluate driving system performance under changing conditions.

Abstract: The present application generally relates to methods and apparatus for evaluating and assigning a complexity metric to a driving scenario. More specifically, the application teaches a method and apparatus for breaking a scenario into subtasks, assigning each subtask a complexity value and generating an overall complexity metric in response to a weighted combination of the subtask complexities as well as human-perceived task complexity.

Abstract: The present application generally relates to methods and apparatus for evaluating and assigning a performance metric to a driver response to a driving scenario. More specifically, the application teaches a method and apparatus for breaking a scenario into features, assigning each feature a grade and generating an overall grade in response to a weighted combination of the grades.

Abstract: Described is a system for patient-specific rehabilitation that can be performed outside a clinic. The system monitors a patient in real-time to generate a quantitative assessment of a physical state and a motivational state of the patient using sensor data obtained from sensors. Predictions related to the patient are generated utilizing patient-specific biomechanical and neurocognitive models implemented with predictive simulations. Video feed of the patient is registered with sensor data and a set of simulation data. Rehabilitation guidance instructions are conveyed to the patient through dialog-based interactions.

Abstract: Described is a system for enhancing memories during sleep. The system detects, via at least one sensor, brain activity of a user as the user learns a new episode pattern or recalls an episode pattern. The episode pattern is temporally compressed. A specific sleep stage is detected in the user. Upon detection of the specific sleep stage, the system automatically recreates the temporally compressed episode pattern by applying neural stimulation to the user to ensure the consolidation of the episode pattern in the user.

Abstract: Described is system for mapping user behavior to brain regions of interest. Using a cognitive-behavior model, a behavioral task is selected that is suited for a desired brain state. Using a functional-anatomical model coupled to the cognitive-behavior model, a set of high-definition neurostimulations is selected to be applied to the user during performance of the selected behavioral task. The selected set of high-definition neurostimulations targets specific regions of the user's brain. Changes in the user's brain state are sensed during application of the set of high-definition neurostimulations and performance of the selected behavioral task using at least one brain monitoring technique. The coupled functional-anatomical and cognitive-behavior models are adapted until the desired brain state is reached.

Abstract: Described is a system for system for gait intervention and fall prevention. The system is incorporated into a body suit having a plurality of distributed sensors and a vestibulo-muscular biostim array. The sensors are operable for providing biosensor data to the analytics module, while the vestibulo-muscular biostim array includes a plurality of distributed effectors. The analytics module is connected with the body suit and sensors and is operable for receiving biosensor data and analyzing a particular user's gait and predicting falls. Finally, a closed-loop biostim control module is included for activating the vestibulo-muscular biostim array to compensate for a risk of a predicted fall.

Abstract: Described is a system for augmenting team performance via individual neurostimulation. An assessment is generated for each team member of a team while the team member is performing a behavioral task using neuroimaging data. A target brain state is selected in team members for team performance enhancement. The target brain state is associated with specific brain regions, and the system determines a HD-tCS neurostimulation needed to reach the specific brain regions to induce the target brain state in the team members. The determined HD-tCS neurostimulation is applied to the team members while simultaneously sensing, via real-time neuroimaging, neural activity in each team member while the team member performs a behavioral task. Team performance is enhanced by adjusting the HD-tCS neurostimulation of each team member, based on the sensed neural activity, to direct each team member toward the target brain state.

Abstract: Described is a system for training and assessment. In operation, the system classifies a subject's baseline brain state and behavioral performance. Training goals are assessed to specify tasks the subject is to perform and a desired level of performance. The subject is subjected to neurological stimulation while the subject performs specified tasks. Behavioral data is assessed to determine if the subject has achieved the training goals. If the subject has achieved the training goals, the system stops. Alternatively, if the individual has not achieved the training goals, then neurological data is reviewed to identify activation states and values of the neurological stimulation that resulted in increased performance values from the baseline behavioral performance. The activation states and values of the neurological stimulation are adjusted to match those that resulted in increased performance values. The process is repeated until the subject has achieved the training goals.

Abstract: Described is a system for automatic adjustment of neurostimulation. The system controls stimulation of specific neural regions through a neural device positioned on a human subject, while simultaneously performing recordings from the neural device using a targeted arrangement of stimulating electrodes and distinct types of recording electrodes of the neural device. Stimulation of the specific neural regions is adjusted in real-time based on the recordings from the neural device.