Abstract: An intercom system including an intercom network, a user panel, and a wireless access point. The user panel includes a user panel wireless transceiver, a user panel short range communication transceiver, and a user panel electronic controller. The wireless access point communicatively coupled with the intercom network via a first intercom interface, the wireless access point includes an access point wireless transceiver, an access point short range communication transceiver, and an access point electronic controller.

Abstract: A cranial implant that facilitates functional ultrasound imaging is disclosed. The example cranial implant replaces a section of a skull. The cranial implant in includes a support section shaped to replace a removed section of the skull. The implant includes a window of sonolucent material allowing functional ultrasound imaging through an ultrasound probe on the window. The window is shaped to allow access to a region of interest in the brain from the ultrasound probe.

Abstract: An apparatus and method for a pre-trained brain machine interface based on brain state data is disclosed. An initial session of determining brain state data during performance of a task by a subject at a first time is conducted. The brain state data correlated with task performance are recorded. A pre-training set of the brain state data is assembled. A decoder module of the brain machine interface system is pre-trained via the pre-training set of the recorded brain state data to decode intentions of the subject correlated with brain state. A current session is conducted at a second time subsequent to the first time. The current session includes the decoder module accepting a brain state data input of the brain of the subject, decoding a brain state output from the brain state data input, and generating a control signal to perform the task based on the determined brain state output.

Abstract: An apparatus and method for a feature extraction network based brain machine interface is disclosed. A set of neural sensors sense neural signals from the brain. A feature extraction module is coupled to the set of neural sensors to extract a set of features from the sensed neural signals. Each feature is extracted via a feature engineering module having a convolutional filter and an activation function. The feature engineering modules are each trained to extract the corresponding feature. A decoder is coupled to the feature extraction module. The decoder is trained to determine a kinematics output from a pattern of the plurality of features. An output interface provides control signals based on the kinematics output from the decoder.

Abstract: 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.

Abstract: 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 a 4×4 mm patch of the posterial parietal cortex illustrated that a single neural recording array could decoded movements of a large extent of the body. Cognitive activity is functionally segregated between body parts.

Abstract: 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 a 4×4 mm patch of the posterial parietal cortex illustrated that a single neural recording array could decoded movements of a large extent of the body. Cognitive activity is functionally segregated between body parts.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.