A mote includes an optical receiver that wirelessly receives a power and data signal in form of NIR light energy within a patient and converts the NIR light energy to an electrical signal having a supply voltage. A control module supplies the supply voltage to power devices of the mote. A clock generation circuit locks onto a target clock frequency based on the power and data signal and generates clock signals. A data recovery circuit sets parameters of one of the devices based on the power and data signal and a first clock signal. An amplifier amplifies a neuron signal detected via an electrode inserted in tissue of the patient. A chip identifier module, based on a second clock signal, generates a recorded data signal based on a mote chip identifier and the neuron signal. A driver transmits the recorded data signal via a LED or a RF transmitter.

A method for resilience training, including: exposing a healthy human subject to one or more stress-evoking perturbations selected to affect activation of deeply located limbic areas; instructing the healthy human subject to perform in a timed relation to the exposing, at least one activity configured to selectively affect activation of said deeply located limbic areas; recording EEG signals from the healthy human subject during the exposing; analyzing the recorded EEG signals to identify at least one EEG signature indicating an activation level of the deeply located limbic areas; determining an activation level of the deeply located limbic areas based on the identified at least one EEG signature; delivering a human-detectable indication to the healthy human subject according to the determined activation level.

A method for resilience training, including: exposing a healthy human subject to one or more stress-evoking perturbations selected to affect activation of deeply located limbic areas; instructing the healthy human subject to perform in a timed relation to the exposing, at least one activity configured to selectively affect activation of said deeply located limbic areas; recording EEG signals from the healthy human subject during the exposing; analyzing the recorded EEG signals to identify at least one EEG signature indicating an activation level of the deeply located limbic areas; determining an activation level of the deeply located limbic areas based on the identified at least one EEG signature; delivering a human-detectable indication to the healthy human subject according to the determined activation level.

Devices, systems, and techniques are disclosed for managing electrical stimulation therapy and/or sensing of physiological signals such as brain signals. For example, a system may assist a clinician in identifying one or more electrode combinations for sensing a brain signal. In another example, a user interface may display brain signal information and values of a stimulation parameter at least partially defining electrical stimulation delivered to a patient when the brain signal information was sensed.

Devices, systems, and techniques are disclosed for managing electrical stimulation therapy and/or sensing of physiological signals such as brain signals. For example, a system may assist a clinician in identifying one or more electrode combinations for sensing a brain signal. In another example, a user interface may display brain signal information and values of a stimulation parameter at least partially defining electrical stimulation delivered to a patient when the brain signal information was sensed.

Devices, systems, and techniques are disclosed for managing electrical stimulation therapy and/or sensing of physiological signals such as brain signals. For example, a system may assist a clinician in identifying one or more electrode combinations for sensing a brain signal. In another example, a user interface may display brain signal information and values of a stimulation parameter at least partially defining electrical stimulation delivered to a patient when the brain signal information was sensed.

Devices, systems, and techniques are disclosed for managing electrical stimulation therapy and/or sensing of physiological signals such as brain signals. For example, a system may assist a clinician in identifying one or more electrode combinations for sensing a brain signal. In another example, a user interface may display brain signal information and values of a stimulation parameter at least partially defining electrical stimulation delivered to a patient when the brain signal information was sensed.

A device and a signal processing method that can monitor human memory performance by recognizing and characterizing high-gamma (65-250 Hz) and beta (14-30 Hz) band oscillations in the left Brodmann Area 40 (BA40) of the brain that correspond with the strength of memory encoding or correct recall. The signal processing method detects high-gamma and beta band oscillations in the electrical signals recorded from left BA40, and quantifies the spectral content, power, duration, onset, and offset of the oscillations. The oscillation's properties are used to classify the subject's memory performance on the basis of a comparison with the subject's prior human memory performance and the properties of the corresponding oscillations. A report of the subject's current memory performance can be utilized in a closed loop brain stimulation device that serves the purpose of enhancing human memory performance.

A device and a signal processing method that can monitor human memory performance by recognizing and characterizing high-gamma (65-250 Hz) and beta (14-30 Hz) band oscillations in the left Brodmann Area 40 (BA40) of the brain that correspond with the strength of memory encoding or correct recall. The signal processing method detects high-gamma and beta band oscillations in the electrical signals recorded from left BA40, and quantifies the spectral content, power, duration, onset, and offset of the oscillations. The oscillation's properties are used to classify the subject's memory performance on the basis of a comparison with the subject's prior human memory performance and the properties of the corresponding oscillations. A report of the subject's current memory performance can be utilized in a closed loop brain stimulation device that serves the purpose of enhancing human memory performance.

A model of neural networks comprised of the fast-spiking class of interneurons regulating neural networks. Fast-spiking neurons regulate activity in neural networks in response to environmental input from thalamic afferents by providing strong, rapid inhibition to a plurality of neurons in advance of excitatory neurons responding to environmental input. Fast-spiking neurons regulate experience dependent plasticity in neural networks by shifting between distinct maturational states in response to experience.