The present invention relates to a system for providing neuronal stimulation signals configured to elicit sensory percepts in the cortex of an individual, comprising means for obtaining spatial information relating to the actual or planned position of at least one neuronal stimulation means relative to at least one afferent axon targeting at least one sensory neuron in the cortex of the individual and means for determining at least one neuronal stimulation signal to be applied to at least one afferent axon via the at least one neuronal stimulation means based at least in part on the obtained spatial information. The present invention further relates to a system for communicating conceptual information to an individual, comprising means for selecting at least one neuronal stimulation signal to be applied to at least one afferent axon targeting at least one sensory neuron in the cortex of the individual, wherein the at least one neuronal stimulation signal corresponds to the conceptual information to be communicated and means for transmitting the at least one neuronal stimulation signa to at least one neuronal stimulation means of the individual.

A psychological condition estimation system includes an acquisition unit and an estimation unit. The acquisition unit acquires information about respective activity levels of a plurality of sensory areas of a subject's brain. The estimation unit estimates a sense, which is highly related to the subject's psychological condition, out of a plurality of types of senses corresponding respectively to the plurality of sensory areas, based on the information, acquired by the acquisition unit, about the activity levels of the plurality of sensory areas when the subject is exposed to multiple types of stimuli.

A psychological condition estimation system includes an acquisition unit and an estimation unit. The acquisition unit acquires information about respective activity levels of a plurality of sensory areas of a subject's brain. The estimation unit estimates a sense, which is highly related to the subject's psychological condition, out of a plurality of types of senses corresponding respectively to the plurality of sensory areas, based on the information, acquired by the acquisition unit, about the activity levels of the plurality of sensory areas when the subject is exposed to multiple types of stimuli.

The present invention is directed to a method for inducing an immune response in a subject, including a step of activating neurons in the mesolimbic network of the subject by applying a neurofeedback.

An explainable artificial intelligence system includes a processor that visualizes and provides a diagnosed result, a decision-making structure which is description information for describing a basis for the diagnosis, a description of at least one second brain wave feature, and an importance of the at least one second brain wave feature.

An explainable artificial intelligence system includes a processor that visualizes and provides a diagnosed result, a decision-making structure which is description information for describing a basis for the diagnosis, a description of at least one second brain wave feature, and an importance of the at least one second brain wave feature.

The systems and methods described herein include an external base station with a tethered transceiver, an implanted hub that includes power, telemetry, and processing electronics, and a plurality of implanted satellite that contain reconfigurable front-end electronics for interfacing with electrodes. The system can operate in different modes. In a first mode, called a base boost mode, the external base station is used for closed-loop control of stimulation therapies. In a second, autonomous mode, closed-loop control is performed in the hub without direct influence from the base station. In a third mode, streams of neural data are transmitted to an offline processor for offline analysis.

An example of a system for delivering neurostimulation and sensing one or more signals may include a programming control circuit and a parameter control circuit. The programming control circuit may be configured to control the delivery of the neurostimulation according to stimulation parameters and the sensing of a target neural signal including target neural responses according to sensing parameters. The parameter control circuit may be configured to determine the stimulation parameters and the sensing parameters and may include a recording analyzer. The recording analyzer may be configured to evaluate a sequence of test recording configurations each including a set of recording configuration parameters selected from the stimulation parameters and the sensing parameters and to determine one or more recording configurations suitable for detection of the target neural responses using an outcome of the evaluation.

The clinical diagnosis and monitoring of patients with neurological conditions may be established through behavioral examinations, assessments or evaluations, or neuroimaging scans. The system and methods described herein diagnose the cognitive function of a subject by measuring the neural response of the subject to one or more naturalistic sensory stimuli. The system measures the subject's sensory evoked response to the naturalistic sensory stimuli by computing the statistical comparison between the subject's neural signal and either the raw stimulus signal or the stimulus' signal envelope. A latency value, or other signal feature, is extracted from the subject's sensory evoked response and a diagnosis of the subject's cognitive function is then made based on the identified latency value or other extracted signal feature.

There is described a method of associating a pulsed signal to a corresponding reference pulse shape. The method generally has accessing reference data having a plurality of reference pulse shapes, each reference pulse shape having a sparse array of average coefficients; receiving a pulsed signal having an array of amplitude values, including generating a sparse array of instantaneous coefficients based on said pulsed signal for example using a discrete wavelet transform; calculating a plurality of first distances between said instantaneous coefficients of said sparse array and the average coefficients of each one of said reference pulse shapes, said first distances having a first minimal distance identifying a closer one of the reference pulse shapes; and upon determining that said first minimal distance is below a first distance threshold, associating said sparse array of instantaneous coefficients to the closer one of the reference pulse shapes.