257 results about "Biological neural network" patented technology

Disclosed are methods and systems for optimized deep or superficial deep-brain stimulation using multiple therapeutic modalities impacting one or multiple points in a neural circuit to produce Long-Term Potentiation (LTP) or Long-Term Depression (LTD). Also disclosed are methods for treatment of clinical conditions and obtaining physiological impacts. Also disclosed are: methods and systems for Guided Feedback control of non-invasive deep brain or superficial neuromodulation; patterned neuromodulation, ancillary stimulation, treatment planning, focused shaped or steered ultrasound; methods and systems using intersecting ultrasound beams; non-invasive ultrasound-neuromodulation techniques to control the permeability of the blood-brain barrier; non-invasive neuromodulation of the spinal cord by ultrasound energy; methods and systems for non-invasive neuromodulation using ultrasound for evaluating the feasibility of neuromodulation treatment using non-ultrasound/ultrasound modalities; neuromodulation of the whole head, treatment of multiple conditions, and method and systems for neuromodulation using ultrasound delivered in sessions.

An information processing system having neuron-like signal processors that are interconnected by synapse-like processing junctions that simulates and extends capabilities of biological neural networks. The information processing systems uses integrate-and-fire neurons and Temporally Asymmetric Hebbian learning (spike timing-dependent learning) to adapt the synaptic strengths. The synaptic strengths of each neuron are guaranteed to become optimal during the course of learning either for estimating the parameters of a dynamic system (system identification) or for computing the first principal component. This neural network is well-suited for hardware implementations, since the learning rule for the synaptic strengths only requires computing either spike-time differences or correlations. Such hardware implementation may be used for predicting and recognizing audiovisual information or for improving cortical processing by a prosthetic device.

A robotic architecture for capturing the autonomous performance advantages the animal models enjoy in the natural environment is disclosed. A biomimesis process is employed to allow selective utilization of basic physical components and adaptation of a common control paradigm for each of different vehicle types. The biomimetic architecture involves five functional elements: a basic biomorphic plant for capturing the biomechanical advantages of the model organism; a neural circuit-based controller consisting of a finite state machine; myomorphic actuators producing linear graded force in response to trains of current pulses for mediating movements; labeled line code output by neuromorphic sensors; and a reactive behavioral sequencer executing command sequences defined within a behavioral library.

Provided is a neural network optimization method based on a floating number operation inline function library, wherein the model of neural unit is Y=1/(1+exp(-Sigma wi*xi)). The value range of i is 1 to n, and n is the number of neural units. The floating-point operations inline function is structured in a dikaryon chip, namely, function library IQ math Library. In the neural network optimization method based on a floating number operation inline function library, except that the step _IQ(x[i]) is carried out in circulation, the rest steps are all carried out outside the circulation body, and the efficiency of the execution of all the steps as a whole is greatly improved compared with a floating point arithmetic. The neural network optimization method based on a floating number operation inline function library optimizes the transplant of back propagation (BP) neural network on transcranial magnetic stimulation (TMS) 3206464T, and the accuracy of a result is decided through a beginning decimal calibration. On the premise of guaranteeing the accuracy of the result does not influence the recognition rate, BP network awareness efficiency is greatly improved.

It is the purpose of this invention to provide methods and systems for non-invasive deep brain neuromodulation using ultrasound for the treatment of anorgasmia, hypo-orgasmia, and for the production of orgasms (Orgasmatron). This can include impacting one or multiple points in a neural circuit to produce Long-Term Potentiation (LTP) or Long-Term Depression (LTD). The ultrasound transducers are attached at fixed positions on a holder. Use of ancillary monitoring or imaging to provide feedback is optional. Control of the ultrasonic transducers includes control of direction of the energy emission, intensity, frequency, and phase/intensity relationships to targeting and accomplishing up-regulation and/or down-regulation.

Radiosurgical techniques and systems treat behavioral disorders (such as depression, Obsessive-Compulsive Disorder (“OCD”), addiction, hyperphagia, and the like) by directing radiation from outside the patient toward a target tissue within the patient's brain, typically without imposing surgical trauma. The target will often be included in a neural circuit associated with the behavioral disorder. A cellularly sub-lethal dose of the radiation may be applied and the radiation can mitigate the behavioral disorder, obesity, or the like, by modulating the level of neural activity within the target and in associated tissues. Hypersensitive and/or hyperactive neuronal tissue may be targeted, with the radiation downwardly modulating hyperactive neuronal activity. By down-regulating the activity of a target that normally exerts negative feedback or a limiting effect on a relevant neural circuit, the activity of the circuit may be increased.

Disclosed are methods and systems and methods for patient-feedback control of non-invasive deep brain or superficial neuromodulation using sound impacting one or multiple points in a neural circuit to produce acute effects and, with application in multiple sessions, Long-Term Potentiation (LTP) or Long-Term Depression (LTD) to treat indications such as neurologic and psychiatric conditions. One or more of sonic transducer positioning, intensity, frequency, dynamic sweeps, phase/intensity relationships, and firing patterns are changed through feedback from the patient to optimize patient experience through up-regulation or down regulation. Examples are decreases in acute pain or tremor due to more effective impact on the neural targets.

Disclosed are methods and systems for optimized deep or superficial deep-brain stimulation using multiple therapeutic modalities impacting one or multiple points in a neural circuit to produce Long-Term Potentiation (LTP) or Long-Term Depression (LTD). Also disclosed are methods for treatment of clinical conditions and obtaining physiological impacts. Also disclosed are: methods and systems for Guided Feedback control of non-invasive deep brain or superficial neuromodulation; patterned neuromodulation, ancillary stimulation, treatment planning, focused shaped or steered ultrasound; methods and systems using intersecting ultrasound beams; non-invasive ultrasound-neuromodulation techniques to control the permeability of the blood-brain barrier; non-invasive neuromodulation of the spinal cord by ultrasound energy; methods and systems for non-invasive neuromodulation using ultrasound for evaluating the feasibility of neuromodulation treatment using non-ultrasound/ultrasound modalities; neuromodulation of the whole head, treatment of multiple conditions, and method and systems for neuromodulation using ultrasound delivered in sessions.

The invention provides an Izhikevich neural network synchronous discharging simulation platform based on an FPGA. The simulation platform comprises an FPGA neural network computing processor and an upper computer which are connected with each other. The FPGA neural network computing processor comprises an FPGA chip, an off-chip memorizer array and an Ethernet communication module, wherein the FPGA chip receives an upper computer control signal output by the off-chip memorizer array, and receives a presynaptic membrane potential signal output by the off-chip memorizer array. The upper computer is in communication with the FPGA chip and the off-chip memorizer array through a VB programming realization man-machine operating interface and the Ethernet communication module, and a neural network model is established on the FPGA chip through Verilog HDL language programming. The Izhikevich neural network synchronous discharging simulation platform has the advantages that the hardware modeling of the phenotype and physiological type neural network model is achieved through an animal-free experiment serving as a biological neural network on the basis of an FPGA neural network experiment platform conducting computation at a high speed, and the consistency with true biological nerve cells on the time scale can be achieved.

A method of training a biological neural network using a controller, comprising:

• • applying a cycle comprising:
    • stimulating a neural network by said controller applying at least an input signal to the network;
    • detecting an output response of the network by said controller; and
    • modifying said stimulation by said controller for at least a period of time if said response matches a desired at least approximate response; and
  • repeating said cycle of stimulation, detection and modification at least one more time until said neural network is trained to generate a desired output response for said input signal.

Disclosed are methods and devices for ultrasound-mediated non-invasive deep brain neuromodulation impacting one or a plurality of points in a neural circuit using patterned inputs. These are applicable whether the ultrasound beams intersect at the targets or not. Depending on the application, this can produce short-term effects (as in the treatment of post-surgical pain) or long-term effects in terms of Long-Term Potentiation (LTP) or Long-Term Depression (LTD) to treat indications such as neurologic and psychiatric conditions. The ultrasound transducers are used with control of frequency, firing pattern, and intensity to produce up-regulation or down-regulation.

Disclosed are methods and systems for treatment planning for deep brain or superficial neuromodulation using ultrasound and other treatment modalities impacting one or multiple points in a neural circuit to produce acute effects or Long-Term Potentiation (LTP) or Long-Term Depression (LTD) to treat indications such as neurologic and psychiatric conditions. Ultrasound transducers or other energy sources are positioned and the anticipated effects on up-regulation and/or down-regulation of their direction of energy emission, intensity, frequency, firing/timing pattern, and phase/intensity relationships mapped onto the recommended treatment-planning targets. The maps of treatment-planning targets onto which the mapping occurs can be atlas (e.g., Tailarach Atlas) based or image (e.g., fMRI or PET) based. Atlas and imaged-based maps may be representative and applied directly or scaled for the patient or may be specific to the patient.

Disclosed are devices for producing shaped or steered ultrasound for non-invasive deep brain or superficial neuromodulation impacting one or a plurality of points in a neural circuit. Depending on the application this can produce short-term effects (as in the treatment of post-surgical pain) or long-term effects in terms of Long-Term Potentiation (LTP) or Long-Term Depression (LTD) to treat indications such as neurologic and psychiatric conditions. The ultrasound transducers are used with control of direction of the energy emission, control of intensity, control of frequency for up-regulation or down-regulation, and control of phase/intensity relationships for focusing on neural targets.

The invention provides a deep brain stimulation FPGA experimental platform of a basal ganglia and thalamencephalon network for the parkinson's disease. The experimental platform comprises an FPGA development board and an upper computer, which are connected with each other; the FPGA development board is used for realizing a basal ganglia and thalamencephalonneuron network model and a deep brain stimulation controller; the upper computer is used for designing an upper computer software interface and being communicated with the FPGA development board. The experimental platform has the benefits that as an animal-free experiment means of a biological neural network, and on the basis of the high-speed computation FPGA neuron network, the experimental platform realizes the modeling of the neuron network of a complex parkinson's disease focus area, and the neuron network model can be consistent with real biological neuron on a time scale. The platform provides a visual research platform, closer to the real neuron network, for researching the discharging mechanism of the parkinson's disease and the abnormal discharging mode of the basal ganglia and thalamencephalonneuron network controlled by deep brain stimulation, and has a significant practical value in researching the treatment of the parkinson's disease.

The quantum computer comprises a quasi-one-dimensional layout superconducting quantum bit array, a control circuit and a reading circuit, The superconducting quantum bit array comprises two or more than two net-shaped units which are arranged in a net chain shape. The control circuit is coupled with the superconducting quantum bits through a microwave transmission line and used for controlling thesuperconducting quantum bits in a preset mode; And the reading circuit is coupled to one path of microwave signal line by a coplanar superconducting microwave resonant cavity for reading, is connected with an external circuit, and is used for reading the quantum state of the superconducting quantum bit by adopting a frequency division multiplexing mode. According to the embodiment of the invention, the hardware resource consumption of the quantum computer is reduced.

The present invention relates to methods for searching and constructing a 3D motif image database, wherein said 3D motif image database can be used to understand the connection relationship of a 3D network, e.g. a neural network comprising biological neural networks or artificial neural networks. The searching and constructing methods are applied on the 3D motif image database, a proper computer-aided graphic platform. The database not only facilitates the management of the huge amount of categorized data but also rationally excavates the hidden information cloaked within.

A diagnostic tool has a packet based network medium attachment unit, a measurement interface, a network interface, and a microprocessor for reading DLPDUs from a network segment and for taking simultaneous measurements of DLPDUs on the segment. The measurement data is associated with a stored DLPDU if the DLPDU is still active on the network segment when the measurement data is read by the microprocessor. The diagnostic tool utilizes a currently active attribute to determine the status of a DLPDU.

The invention discloses a preparation method of a recombinant pseudorabies virus for expressing reverse neural circuit tracing of green fluorescin with high sensitivity, and application, including (1) the preparation of the recombinant pseudorabies virus for expressing green fluorescin with high sensitivity; (2) the application to marking of a neural circuit. The recombinant pseudorabies virus for expressing the green fluorescin with high sensitivity is successfully prepared by using a platform. The recombinant pseudorabies virus for expressing reverse neural circuit tracing of green fluorescin with high sensitivity is successfully obtained. Wide application value is realized in aspects of neural circuit marking, medicine screening platform building, medicine inhibition virus action mechanism, viral vaccine and diagnostic reagent invention and development, animal model building, virus replication, pathogenic mechanism analysis and the like.

The invention discloses an artificial cochlea device, which comprises an external circuit and an internal circuit which are mutually coupled in an electromagnetic wireless mode. A sound acquisition unit of the external circuit acquires voice signals; an analog-digital convertor converts the acquired simulative voice signals into digital voice signals; a coder codes the digital voice signals; a power amplifier emits high-power carrier waves; and a modulator loads the coded digital voice signals onto power carrier waves and emits the digital voice signals through an external antenna. An internal antenna of the internal circuit receives the power carrier waves and the modulated voice signals; a rectifying circuit converts AC energy of the received power carrier waves into DC energy to be used for the internal circuit; an electric stimulation generator carries out demodulation, sound signal mapping and stimulating pulse generation on the received voice signals; and a channel select switch conducts and selects electrodes in different electrode arrays by time-sharing. The electrodes directly stimulate auditory nerves so as to achieve the aim of repairing auditory sensation. The device has the advantages of convenient use and low cost.

A semiconductor device includes: an interface chip including a read timing control circuit that outputs, in response to a command signal and a clock signal supplied from the outside, a plurality of read control signals that are each in synchronization with the clock signal and have different timings; and core chips including a plurality of internal circuits that are stacked on the interface chip and each perform an operation indicated by the command signal in synchronization with the read control signals. According to the present invention, it is unnecessary to control latency in the core chips and therefore to supply the clock signal to the core chips.

An application specific integrated circuit (ASIC) is disclosed. The ASIC comprises an internal circuit coupled between a power line and ground and an output buffer coupled to the internal circuit; wherein the output buffer provides an output signal. The ASIC includes a fault detection circuit coupled between the power line and ground; and a first protection block configured to receive a first control signal from the fault detection circuit. The first switch is coupled to the power line, the output buffer and the internal circuit. The first protection block prevents current from flowing between the power line and ground when a fault condition is detected. The ASIC further includes a second protection block configured to receive a second control signal from the fault detection circuit, wherein the second protection block is coupled to the output signal, the power line and ground. The second protection block prevents current from flowing between the power line and ground or the power line and the output line when a fault condition is detected.

The invention relates to a bidirectional digital modulation multi-channel manual cochlear system, pertaining to the arts of electronic information technology and medical appliance. The system comprises external and internal circuits and electrodes. The external circuit is for collecting sound signal and sending to the internal circuit after enlarging, digitalizing and modulating in wireless way, at the same time, providing interface for programming and measuring the internal circuit.< The internal circuit demodulates the received signal, and deals the demodulated data by the built-in digital signal-processing unit, to control the outlet of electrode assemblies, program on line or provide reversal results. The system integrates the low-power consumption digital signal-processing unit to the internal circuit, so the external circuit only sends narrow range sound signal, to cancel the width limitation of wireless transmission band, and improve the accuracy of dealing. Moreover, the system provides with remote updating.

Embodiments relate to a neural processor circuit with scalable architecture for instantiating one or more neural networks. The neural processor circuit includes a data buffer coupled to a memory external to the neural processor circuit, and a plurality of neural engine circuits. To execute tasks that instantiate the neural networks, each neural engine circuit generates output data using input data and kernel coefficients. A neural processor circuit may include multiple neural engine circuits that are selectively activated or deactivated according to configuration data of the tasks. Furthermore, an electronic device may include multiple neural processor circuits that are selectively activated or deactivated to execute the tasks.