Paradromics, Inc.

Caeleste Cvba

Robert Edgington

Matthew R Angle

Bart Dierickx

Bert Luyssaert

Yifan Kong

Edmund Huber

Peng Gao

Mina-Elraheb Saad Hanna

Kunal Sahasrabuddhe

Aleksandar Tadic

Matthew Stephen Hopper

Harbaljit Sohal

Aamir Ahmed Khan

Ahmed Abdelmoneem

Jean Pierre Vermeiren

Amir Babaiefishani

Devin Fell

Kevin Boergens

The present disclosure provides systems, devices, and methods for penetrating a biological membrane. The system may comprise a laser unit configured to generate one or more laser beams. The system may comprise a set of targeting optics configured to direct the one or more laser beams to a target region of the biological membrane. The system may comprise a raster scanner operatively coupled to the laser unit and the set of targeting optics. The system may comprise a non-transitory computer readable storage medium comprising a set of instructions. The set of instructions may be configured to control at least one of the laser unit, the set of targeting optics, or the raster scanner to photodisrupt the target region of the biological membrane to a target depth while minimizing damage to one or more blood vessels in proximity to the target region.

Systems, devices, and methods for tissue layer removal

A sensor circuit that is capable of sensing of neural action potentials is disclosed. The circuit can be designed to minimize power dissipation and total silicon area so that it can be incorporated into a massively parallel sensor array and ultimately implanted in the body (e.g. into the brain) in a safe manner. The circuit can also be designed to be tunable such that it can be optimized in silico prior to fabrication, and can be optimized through the use of controllable current sources after fabrication.

Low-area, low-power neural recording circuit, and method of training the same

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

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Austin, TX, United States of America

Robert Edgington