Massachusetts Institute of Technology

Precision Neuroscience Corporation

Precision Neurotechnologies LLC

Other

William E. Butler and Angiowave Imaging, LLC

Benjamin I Rapoport

Demetrios Papageorgiou

Jason Chen

Rahul Sarpeshkar

Woradorn Wattanapanitch

William E Butler

Todd A Thorsen

Soumyajit Mandal

Jakub Tadeusz Kedzierski

Jeremy Bert Muldavin

Scott K Arfin

Michale Sean Fee

The present disclosure relates to a method of generating visual percepts using conformal electrode arrays. The electrode arrays can be placed into the ventricular system or cerebral venous sinuses, which function as minimally invasive techniques for precise spatial and temporal localization of electrical activity within the brain, and precise electrical stimulation of brain tissue, to diagnose and restore function in conditions caused by abnormal electrical activity in the brain. The disclosure further comprises a system for using these arrays to generate time-varying electric fields to stimulate the visual pathways of the brain, including the optic radiations and the occipital cortex, in ways that lead to visual perception.

Visual prosthesis employing ventricular or endovascular neural electrode arrays

The brain appears to have organized cardiac frequency angiographic phenomena with such coherence as to qualify as vascular pulse waves. Separate arterial and venous vascular pulse waves may be resolved. This disclosure states the method of extracting a spatiotemporal reconstruction of the cardiac frequency phenomena present in an angiogram obtained at faster than cardiac frequency. A wavelet transform is applied to each of the pixel-wise time signals of the angiogram. If there is motion alias then instead a high frequency resolution wavelet transform of the overall angiographic time intensity curve is cross-correlated to high temporal resolution wavelet transforms of the pixel-wise time signals. The result is filtered for cardiac wavelet scale then pixel-wise inverse wavelet transformed. This gives a complex-valued spatiotemporal grid of cardiac frequency angiographic phenomena. It may be rendered with a brightness-hue color model or subjected to further analysis.

Device and method for spatiotemporal reconstruction of a moving vascular pulse wave in the brain and other organs

The present disclosure relates to an array of electrodes on a flexible scaffolding, with the ability to collapse into an axial configuration suitable for deploying through a narrow cylindrical channel. The electrode arrays can be placed into the ventricular system of the brain, constituting a minimally invasive platform for precise spatial and temporal localization of electrical activity within the brain, and precise electrical stimulation of brain tissue, to diagnose and restore function in conditions caused by abnormal electrical activity in the brain.

Conformal electrode arrays for electrophysiologic recording and neural stimulation within the cerebral ventricles

Visual prosthesis employing virtual neural electrode arrays

A glucose fuel cell for reception into a given constrained volume of implantation in a vertebrate in which the glucose fuel cell has access to fluid containing glucose. The fuel cell includes an anode adapted to oxidize the glucose, a cathode adapted to reduce an oxidant, and a membrane disposed between the anode and the cathode and separating the anode from the cathode. At least one of the anode or cathode define a flexible sheet that is geometrically deformed to be receivable into the given constrained volume of implantation and increase volumetric power density. Related methods of making a glucose fuel cell of this type and implantable assemblies including the glucose fuel cell are also disclosed.

Flexible and implantable glucose fuel cell

A microchip for performing a neural decoding algorithm is provided. The microchip is implemented using ultra-low power electronics. Also, the microchip includes a tunable neural decodable filter implemented using a plurality of amplifiers, a plurality of parameter learning filters, a multiplier, a gain and time-constant biasing circuits; and analog memory. The microchip, in a training mode, learns to perform an optimized translation of a raw neural signal received from a population of cortical neurons into motor control parameters. The optimization being based on a modified gradient descent least square algorithm wherein update for a given parameter in a filter is proportional to an averaged product of an error in the final output that the filter affects and a filtered version of its input. The microchip, in an operational mode, issues commands to controlling a device using learned mappings.

Low-power analog-circuit architecture for decoding neural signals

An ultra-low-power circuit for wireless neural recording and stimulation is provided. The circuit includes a neural amplifier with adaptive power biasing for use in multi-electrode arrays and a decoding and/or learning architecture. An impedance-modulation telemetry system provides low-power data telemetry. Also, the circuit includes a wireless link for efficient power transfer, and at least one circuit for wireless stimulation of neurons.

Low-power analog architecture for brain-machine interfaces

A micropower neural amplifier with adaptive power biasing for use in multi-electrode arrays is provided. The micropower neural amplifier includes a low noise gain stage. The low noise gain stage is implemented using an amplifier and pseudoresistor elements.

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New York, NY, United States of America

Benjamin I Rapoport