Paradromics, Inc.

Edmund Huber

Matthew R Angle

Konrad P Kording

Richard C Gerkin

Yifan Kong

Robert Edgington

A system for monitoring neural activity of a living subject is provided. The system may comprise a correspondence module configured to be in communication with (1) a neural module and (2) one or more additional modules comprising a sensing module, another neural module, and/or a data storage module. The neural module(s) are configured to collect neural data indicative of perceptions experienced by the living subject. The sensing module may be configured to collect (1) sensor data indicative of real-world information about an environment around the living subject, and/or (2) sensor data indicative of a physical state or physiological state of the living subject. The data storage module may be configured to store prior neural data and/or prior sensor data. The correspondence module may be configured to measure a correspondence (a) between the neural data collected by the neural module(s) and the sensor data collected by the sensing module, (b) between the neural data collected by two or more neural modules, and/or (c) between the neural data collected by the neural module(s) and the prior data stored in data storage module. The measured correspondence can be used to determine a presence, absence, or extent of a potential cognitive or physiological disturbance of the living subject.

Systems and methods for detecting corrupt or inaccurate sensory representations

Systems and methods for processing neural signals are provided. A neural data analysis system may comprise a feature extraction module configured to extract a plurality of features from neural signal waveforms obtained by an implanted neural interface probe with a plurality of channels or electrodes, and transmit the extracted features as a plurality of discrete outputs. The neural data analysis system may also comprise a feature-event coalescence module configured to receive the plurality of discrete outputs from the feature extraction module, and construct a model-based inference of bioelectric activity based on feature event statistics, prior knowledge of bioelectric signals, and/or a behavioral model of the feature extraction module. The neural data analysis system may further comprise an approximator module configured to receive a plurality of coalesced events from the feature-event coalescence module, and apply a series of transformations to the coalesced event data to generate a higher entropy neural code.

System and methods for processing neural signals

A system and method for testing the quality of a conductor is disclosed. Specifically, a system of testing a conductor using voltage source generator that is capacitively-coupled through the conductor to voltage detector is disclosed. The voltage source generates a varying voltage signal which induces a voltage signal in the capacitively coupled microwire conductor. The voltage detector that is also capacitively-coupled to the conductor measures the induced voltage. Using the detected voltage signal, the voltage detector determines whether there are any conductive breaks in the conductor.

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San Francisco, CA, United States of America

Edmund Huber