California Institute of Technology

Centre National De La Recherche Scientifique

National Institute of Health and Medical Research

Ecole Superieure De Physique Et De Chimie Industrielles De La Ville De Paris

Richard A Andersen

Bijan Pesaran

Partha Pratim Mitra

Krishna V Shenoy

Joel W Burdick

Sohaib A Kureshi

Mikhail G Shapiro

David Maresca

Michael T Wolf

Charlie Demene

Zoran Nenadic

Vasileios Christopoulos

Sumner L Norman

John S Pezaris

Maneesh Sahani

Shiyan Cao

Daniella Meeker

Hansjorg Scherberger

Bradley Greger

Brian D Corneil

Sam Musallam

Edward A Branchaud

Jorge G Cham

Igor Kagan

Melanie Wilke

Methods and systems are provided for decoding movement intentions using functional ultrasound (fUS) imaging of the brain. In one example, decoding movement intentions include determining a memory phase of a cognitive state of the brain, the memory phase between a gaze fixation phase and movement execution phase, and determining one or more movement intentions including one or more of intended effector (e.g., hand, eye) and intended direction (e.g., right, left) according to a machine learning algorithm trained to classify one or more movement intentions simultaneously.

Decoding movement intention using ultrasound neuroimaging

A method and system of compensating for a damaged brain node is disclosed. The damaged node is determined by techniques such as fMRI or neural recording. A healthy node that can compensate for the function of the damaged node is determined. A stimulating electrode is placed on at least one functioning node to bypass the activity from the damaged node to compensate for a missing node. The functioning node is then stimulated to compensate for the damaged node.

Brain repair using electrical stimulation of healthy nodes

Prosthetic devices, methods and systems are disclosed. Eye position and/or neural activity of a primate are recorded and combined. The combination signal is compared with a predetermined signal. The result of the comparison step is used to actuate the prosthetic device.

Prosthetic devices and methods and systems related thereto

The present invention relates to systems and methods for controlling neural prosthetic devices and electrophysiological recording equipment, and for using the same in clinical operation. Various embodiments of the invention are directed to an algorithm for autonomously isolating and maintaining neural action potential recordings. The algorithm may be used in connection with a neural interface microdrive capable of positioning electrodes to record signals from active neurons.

In an embodiment, the invention relates to neural prosthetic devices in which control signals are based on the cognitive activity of the prosthetic user. The control signals may be used to control an array of external devices, such as prosthetics, computer systems, and speech synthesizers. Data obtained from monkeys' movement intentions were recorded, decoded with a computer algorithm, and used to position cursors on a computer screen. Not only the intended goals, but also the value of the reward the animals expected to receive at the end of each trial, were decoded from the recordings. The results indicate that brain activity related to cognitive variables can be a viable source of signals for the control of a cognitive-based neural prosthetic.

Cognitive control signals for neural prosthetics

A prosthetic system may use a decoder to predict an intended action, such as a reach, from processed signals generated from measured neural activity. The decoder may included a cognitive state machine, which transitions between cognitive states based on transition rules.

Cognitive state machine for prosthetic systems

In an embodiment, neural activity of a subject may be measured with an implant in the sensory motor cortex of the subject and used to predict an intended movement. The measured neural activity may be the local field potential (LFP) at an electrode or single unit (SU) activity. The spectral structure of the LFP and the SU activity may be estimated using spectral analysis techniques. The estimated LFP and SU responses may be used to predict and intended movement by the subject.

Neural prosthetic using temporal structure in the local field potential

The present invention provides a processed neural signal that encodes a reach plan, comprising the target location of the planned reach encoded relative to an eye-centered reference frame. The present invention also provides methods for generating and decoding the processed neural signal.

Processed neural signals and methods for generating and using them

The present invention provides a processed neural signal that encodes a reach plan, comprising the target location of the planned encoded relative to an eye-centered reference frame. The present invention also provides methods for generating and decoding the processed neural signal.

A chronic chamber microdrive (&ldquo;CCMD&rdquo;) for neural recording. In one implementation, a CCMD for neural recording from a target site of neural tissue exposed by an opening in a skull of a subject, includes: an outer cylinder, having a longitudinal axis, positioned within the opening and rotatable within the opening; an inner cylinder positioned within the outer cylinder, such that the longitudinal axis of the outer cylinder is within a circumference of the inner cylinder and the inner cylinder rotates within the rotatable outer cylinder; at least one fine leadscrew, positioned longitudinally in the inner cylinder; at least one electrode for neural recording, where at least one of said electrodes is coupled to a corresponding one of said fine leadscrews, where said electrodes are positioned horizontally by rotating the outer cylinder and separately rotating the inner cylinder, and where said electrodes are positioned vertically by rotating said fine leadscrews.

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La Canada, CA, United States of America

Richard A Andersen