143 results about "Synapse" patented technology

The invention discloses a synaptic plastic mechanism bionic circuit based on a threshold symmetric memristor, and relates to the technical field of bionic circuits, the bionic circuit comprises a pre-synaptic neuron circuit, the threshold symmetric memristor and a post-synaptic neuron circuit; the bionic circuit is divided into an excitatory synaptic moldability mechanism circuit and an inhibitory synaptic moldability mechanism circuit according to a synaptic moldability mechanism; the design method of the circuit comprises the following steps: firstly, designing neuron waveforms before and after synapse, then traversing changes of memristive synapse conductance values at different time intervals to obtain a corresponding curve of the conductance changes and the time intervals, verifying the fitting degree of a biological synapse plastic mechanism curve and the curve, and if the fitting degree is low, determining that the biological synapse plastic mechanism curve is not matched with the curve. And if not, redesigning the pulse waveforms before and after synapse. The synaptic plasticity mechanism simulated by the bionic circuit provided by the invention and a biological synaptic STDP mechanism model have a small fitting error, the provided design method is higher in universality, circuit parameters can be adjusted according to different memristors, and different forms of biological synaptic plasticity mechanisms can be simulated.

The subject matter of the present disclosure generally relates to techniques for neuromodulation of a tissue that include applying energy (e.g., ultrasound energy) into the tissue to cause altered activity at a synapse between a neuron and a non-neuronal cell.

The application discloses an ultra-compact non-volatile photonic neural synapse device and belongs to the field of optical computing. The device comprises a substrate, a ridge waveguide, a phase change film and a metal film. The ridge waveguide is arranged above the substrate and covers the whole substrate area. The phase change film is distributed above the ridge type area of the ridge waveguide. The metal film covers the phase change film and has the same geometric parameters as the phase change film. The base mode in the ridge waveguide and the surface plasmon polariton (SPPs) mode of the interface between the phase change film and the metal film form a superimposed light field. The geometric structure of the ridge waveguide will affect the effective mode refractive index of the superimposed mode. The length of the modulation area is further optimized to realize different normalized intensity outputs. By changing the phase state (crystalline state and amorphous state) of the phase change film, the photonic neural synapse has a large output intensity difference under the condition that the phase change film has different phase states.

The invention discloses a synaptic memory cell for neuromorphic calculation, a preparation method and a synaptic array, the synaptic memory cell comprises two gating transistors and two resistance change memristors, and the gating transistors and the resistance change memristors are in one-to-one correspondence connection; the gate transistor comprises a grid electrode, a dielectric layer and a channel layer which are sequentially arranged from bottom to top, and a source electrode and a drain electrode which are arranged on the surface of the channel layer, and a first passivation layer is arranged between the source electrode and the drain electrode; the channel layer is made of hydrogenated amorphous silicon; the resistance change memristor comprises a bottom electrode, a resistance change layer and a top electrode which are sequentially arranged on the drain electrode, and a second passivation layer which is arranged on the surface of the drain electrode and the surface of the first passivation layer; the resistive layer is a hexagonal boron nitride film; and the two resistive memristors are connected with each other through a metal layer arranged on the surface of the top electrode. According to the invention, low-temperature process compatibility is realized, so that three-dimensional stacking integration is facilitated, and the conductivity fluctuation coefficient is remarkably reduced.

The invention discloses a sensing and storage calculation integration method of an electrophysiological sensing device and an artificial synaptic storage calculation device, relates to the technical field of neuromorphic calculation, and aims to solve the problem of separation of wearable health monitoring sensing and storage calculation. The method comprises the following steps: S1, precisely preparing two-dimensional MXene by a liquid phase etching method; s2, constructing an MXene electrophysiological sensing device; s3, constructing an MXene artificial synaptic device; s4, the MXene electrophysiological sensing device in the step S2 and the MXene artificial synapse device in the step S3 are integrated; wherein the step S4 specifically comprises the following steps: S4-1, leading out a source electrode, a grid electrode and a drain electrode of the MXene artificial synapse device through a bonding machine instrument, connecting the grid electrode with the MXene electrophysiological sensor, applying a voltage of 100mV to the source electrode of the MXene artificial synapse device, testing a current change value of a channel material of the MXene artificial synapse device by the drain electrode, and presenting a curve through a mobile terminal, therefore, the human body electrophysiology compression signal can be presented.

This invention discloses a design and operation method for a multimodal optoelectronic synaptic device based on the synergy of asymmetric structure and defects. The method includes constructing a device with a two-terminal asymmetric structure, consisting of a metal layer / functional layer 1 / functional layer 2 / electrode. The core lies in forming a two-terminal asymmetric functional junction (Schottky junction / heterojunction) on both sides of functional layer 1. This invention utilizes the unified yet differentiated response dynamics (migration and recombination) of defects such as oxygen vacancies in the functional layer to light and electrical signals, achieving a response within an order of magnitude of specific encoded light and electrical signals in a single device. This enables weighted fusion of multimodal signals, non-volatile storage, and selective decoupling. This method is independent of specific material systems (including oxide types, electrode types, doping, etc.) and fabrication processes, providing core operational logic for constructing general-purpose neuromorphic hardware capable of performing in-situ sensing and computation.

The application provides a multi-state neural synapse device based on probability flip and a modulation method thereof, and relates to the technical field of semiconductor devices.The multi-state neural synapse device comprises a plurality of probability devices connected in series; wherein the resistance state of each probability device presents a probabilistic high resistance state or a low resistance state according to different input pulse current densities; the total output voltage of a plurality of probability devices connected in series or the total output voltage of multiple pulse currents of the same probability device is used to simulate the weight of a neuron synapse, so that an artificial synapse device for neuromorphic computing is realized.The multi-state neural synapse device can change the paradigm of neuromorphic computing from deterministic simulation to random bionic simulation, and has unique advantages in adaptive learning and uncertain reasoning scenarios.

The application discloses a parallel polynomial gradient calculation system and method based on a CMOS nerve synapse transistor, and relates to the technical field of calculation systems.The parallel polynomial gradient calculation system based on the CMOS nerve synapse transistor adopts a basic calculation unit containing at least one CMOS transistor, and configures the CMOS transistor to exhibit the dual-mode characteristics of neuron behavior and synapse behavior in a floating substrate operation mode, and meanwhile, combines a parallel array architecture, so that the application realizes a neuromorphic calculation hardware based on a standard CMOS process, utilizes mature CMOS manufacturing technology, avoids special materials and post-integration processes required by emerging devices such as memristors, thereby improving the manufacturability and yield of the system, and reducing production costs.Meanwhile, the inherent device consistency and long-term stability of the CMOS transistor effectively overcome the problems of large differences between devices and state drift in the memristor scheme, and realize high-precision polynomial gradient calculation.

Techniques for measuring single synaptic signals under varying experimental conditions include controlling a video recording microscope to capture, at multiple different times, a first imaged area in a sample holder as a video frame when the sample holder is disposed on a stage and holds a sample of neuronal tissue combined with at least one fluorophore that emits a corresponding electromagnetic wavelength in a synapse during synaptic activity. At least one synaptic region of interest is determined based on a group of pixels in the first imaged area that record electromagnetic emissions from the fluorophore at the different times. An ordered time series of emission intensity is recorded in each of the synaptic region of interest. Peak emission intensity values in the time series are corrected for transmitter label transients. The ordered time series with corrected peak emission intensity values are stored in a data structure with a standard format.

A neural network device according to an embodiment includes a plurality of synapse circuits and a plurality of neuron circuits. A first neuron circuit includes a first terminal to which a synaptic current is supplied. The first neuron circuit includes a secondary battery element, a spike generation circuit, and a reset control circuit. The secondary battery element accumulates a charge according to the synaptic current supplied to the first terminal. The spike generation circuit generates a spike signal when the membrane potential generated from the secondary battery element is larger than a threshold potential being a predetermined potential. The reset control circuit releases the charge accumulated in the secondary battery element during a refractory period being a predetermined time after generation of the spike signal.

The invention belongs to the field of biomedical engineering, and particularly relates to an amino acid modified molybdenum disulfide artificial extracellular matrix and application. Preparing an amino acid modified molybdenum disulfide artificial extracellular matrix, inoculating the neuron in-vitro model PC12 cell suspension onto the artificial extracellular matrix, and constructing the nerve cell in-vitro differentiation model. The artificial extracellular matrix with good biocompatibility is obtained by constructing different kinds of amino acid modified molybdenum disulfide nano material artificial extracellular matrixes as the artificial extracellular matrix of nerve cells PC12, and the artificial extracellular matrix improves the activity of the PC12 cells and promotes the differentiation of nerve cell synapses; a neuron in-vitro model with high differentiation and higher activity is constructed, and the artificial extracellular matrix can be used for nerve regeneration and neural engineering.

The invention provides an energy storage system scheduling method, device, equipment and system, and the method comprises the steps: obtaining an operation parameter of an energy storage system, and constructing a multi-dimensional disturbance structure tensor according to the operation parameter; according to the multi-dimensional disturbance structure tensor, establishing a neural synaptic stress structure simulation network model, and according to the neural synaptic stress structure simulation network model, obtaining a synaptic response mapping matrix; performing channel excitation on the current disturbance structure tensor based on the synaptic response mapping matrix to obtain an excitation response sequence; determining a strategy behavior tensor path based on the excitation response sequence and the current disturbance structure tensor; and generating a control instruction according to the strategy behavior tensor path and the strategy evaluation function, and controlling the energy storage system to execute the control instruction. The time sequence sensing capability of the dynamic characteristics of the energy storage system is improved, the problem that a traditional method is insufficient in heterogeneous parameter coupling relation expression capability is solved, differential selection of behavior paths is achieved, and the scheduling effect of the energy storage system is improved.

The invention discloses an active layer based on light regulation free radical bipolar doping, a device, an array and a visual system. The problems that existing neuromorphic vision hardware is low in integration level, single in function and difficult to meet complex requirements are solved. The active layer comprises an organic semiconductor material and a free radical dopant, and wavelength selective reversible bipolar doping can be realized: p-type doping is presented and excitatory response is generated under 808 nm irradiation, and n-type doping is presented and inhibitory response is generated under 450 nm irradiation. Based on the active layer, an optical reconfigurable bipolar neuromorphic device with a simple structure is constructed, and the device has dynamic synaptic characteristics and light-controlled bipolar photoelectric response at the same time. The device is used as a pixel unit, can be integrated on a large scale to form a neuromorphic visual array, and forms a complete system with a signal reading and processing unit. The system can synchronously execute multiple visual functions of motion detection, spatio-temporal information memory and contrast enhancement feature extraction at a sensing front end.

The application discloses a nerve synapse biomimetic photoelectric slowly-varying memristor and a preparation method thereof, and belongs to the field of organic electronics and photoelectric information technology. The device structure of the slowly-varying memristor is a cross structure, and comprises a bottom electrode, a functional layer and a top electrode from bottom to top on a conductive glass. The functional layer is a poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylene vinylene] MEH-PPV layer. The bottom electrode is indium tin oxide ITO, and the top electrode is Ag. The MEH-PPV layer is a continuous and smooth amorphous thin film. The MEH-PPV layer is prepared by a solution spin coating method, and has the advantages of good sustainability, good solubility, simple preparation, excellent photoelectric performance and the like. The prepared nerve synapse biomimetic photoelectric slowly-varying memristor can perform various nerve morphological simulation and has different responses to light with different wavelengths and different intensities. The application has low cost, good repeatability and can be used in an artificial nerve morphological computing system, and provides more possibilities for constructing a visual perception system.

The invention provides a polymorphic synaptic device based on probability flipping and a modulation method thereof, and relates to the technical field of semiconductor devices. The polymorphic neurosynaptic device comprises a plurality of probability devices which are connected in series; wherein the resistance state of each probabilistic device presents a probabilistic high resistance state or low resistance state according to different input pulse current densities; and simulating the weight of the neuronal synapse by using the total voltage of series connection of a plurality of probability devices or the total output voltage of multiple pulse currents of the same probability device, thereby realizing the artificial synapse device for neuromorphic calculation. The polymorphic neuronal synaptic device can enable neuromorphic calculation to be transformed from deterministic simulation to random bionic simulation, and has unique advantages in scenes such as adaptive learning and uncertain reasoning.

This invention discloses a method and system for pilot safety risk analysis based on neural computation. The method includes: identifying safety risk factors; establishing a mapping relationship between safety risk factors and unsafe pilot behaviors; establishing a structural model of the cortico-basal ganglia-thalamus neural circuit; establishing AMPA and GABA neural synapse computational models based on the theories of double exponential synapses and α-β synapses, respectively; establishing a computational model of the cortico-basal ganglia-thalamus neural circuit; calculating the thalamic discharge rate under the influence of different safety risk factors, and simulating the regulatory mechanisms of dopamine and acetylcholine during the formation of safety risks. This invention conducts safety analysis from the perspective of pilot neurodynamics, providing key physiological basis and theoretical support for improving risk analysis models and optimizing system design by analyzing the neural regulatory mechanisms of acetylcholine and dopamine during the formation of safety risks.

The application provides a PEDOT:PSS / IGZO optoelectronic neurosynaptic memristor with nociceptor function and a preparation method and application thereof. The memristor comprises a bottom electrode, a resistance change function layer and a top electrode arranged in sequence, wherein the resistance change function layer is a double-layer heterojunction structure composed of PEDOT:PSS and an IGZO thin film, the IGZO is indium gallium zinc oxide, and the IGZO thin film is arranged on the bottom electrode. The memristor has the characteristics of simulating a biological neurosynapse and nociceptor function, and can balance the electrical control precision and the light response capability.

The subject matter of the present disclosure generally relates to techniques for neuromodulation of a tissue (e.g., an organ) that include applying energy (e.g., ultrasound energy) into the tissue to cause altered activity at a synapse between a neuron and a non-neuronal cell. In one embodiment, the energy is applied to cause competing or opposing effects for bi-directional control of physiological processes.

The application discloses application of TESC as an Alzheimer's disease prevention and treatment target and relates to the field of biological medicines. A TESC overexpression (TESC-OE) hippocampal neuron cell line is constructed through lentivirus transfection, and the result shows that TESC-OE has the ability to resist A beta-induced neuron apoptosis and synapse damage. A TESC overexpression model in the hippocampus of a mouse is constructed through stereotactic injection of an adeno-associated virus, and the result shows that the hippocampal gray matter volume in the brain of the TESC-OE mouse is significantly larger than that of a wild type mouse. A beta stereotactic modeling is performed on the basis of TESC overexpression in the hippocampus, and the result shows that the TESC-OE mouse can significantly resist A beta-induced hippocampal atrophy, learning and memory dysfunction and impaired synaptic plasticity. Immunoblotting analysis reveals the molecular mechanism that TESC can increase the expression of anti-apoptotic genes in the hippocampus and reduce the expression of pro-apoptotic genes to exert a neuroprotective effect.

An object of the present invention is to provide a neuromorphic system including a synaptic unit capable of causing a gradual change in resistance for analog information processing, and an operating method therefor. In order to achieve the above object, an aspect of the present invention may provide a neuromorphic system including an input signal unit for generating an input signal, a synapse unit including a plurality of synaptic units that receive a signal of the input signal unit and cause a current to flow according to a set weight, an output signal unit for generating an output signal by receiving a current generated from the synapse unit, and a controller unit for controlling the input signal unit, the synapse unit, and the output signal unit, in which the input signal unit includes a digital-to-analog converter (DAC), the synaptic units include a plurality of memory cells that are connected to each other and are each capable of selectively storing a logic state, the plurality of memory cells are arranged in a cross-point structure including an input electrode line and an output electrode line that cross each other to form one or more memory arrays, the output signal unit includes an analog-to-digital converter (ADC), and the controller unit generates an analog input signal through the DAC in the input signal unit, allows the generated analog input signal to be applied to each of the plurality of memory cells included in the synaptic unit so that a current flows, and generates a sum of currents flowing from the plurality of memory cells as the output signal through the ADC in the output signal unit.

The application provides a neural snake venom poisoning discrimination data processing method and system based on neural electrical signals, and relates to the technical field of signal processing. The method comprises the following steps: converting the neural electrical signals of a subject into a digitized multi-channel time sequence matrix; obtaining a multi-channel time sequence signal through band-pass filtering, power interference suppression, hierarchical artifact removal, baseline correction and resampling; extracting time domain, frequency domain, time-frequency domain and synapse and neuromuscular transmission characteristics, wherein the characteristics include four train-of-four ratios, repetitive nerve stimulation response decrement rates, acetylcholine release frequencies and amplitude variation coefficients corresponding to acetylcholine release; standardizing the characteristics and performing dimensionality reduction by principal component analysis to obtain an optimized characteristic set; inputting a pre-trained poisoning discrimination model to output poisoning probability, confidence and key abnormal characteristics. The application solves the problem that the prior art lacks a specific processing flow and a full-process engineering scheme for neural snake venom poisoning, resulting in low discrimination accuracy and difficulty in meeting emergency clinical needs.

The application discloses a simulation system supporting fast large-scale brain simulation, and belongs to the technical field of brain simulation.The simulation system comprises a hardware device layer, which provides a plurality of hardware device resources; a data communication layer, which provides a plurality of types of communication modes between the computing nodes; an operation abstraction layer, which provides a plurality of types of neuron models, synapse models, connection rules and learning rules; an API layer, which provides an API interface and receives user requirements through the API interface; a hardware abstraction layer, which calls corresponding hardware kernels; and a network abstraction layer, which firstly records the topological structure of a brain simulation network, performs resource allocation and neuron cluster mapping, then creates the brain simulation network on the hardware device, and finally performs training or execution of the brain simulation network.The application fully utilizes cluster hardware resources to realize faster and larger-scale brain simulation, and solves the problems of lack of resource scheduling and resource allocation, insufficient utilization of device parallelism, too long communication time consumption, and limited support of hardware and interfaces.

The application discloses application of SCAMP5 in treatment of autism spectrum disorder. The application research proves that, compared with a CON group, VPA-induced ASD rats have significant neurotransmitter release disorder and synapse signal path abnormality in hippocampus, overexpression of SCAMP5 protein can improve abnormal release of Glu, abnormal expression of scaffold protein Homer1b / c and downstream protein IP3R, and meanwhile, can relieve autism-like behaviors, space working memory and synapse development abnormality of ASD rats. The application provides a new target and a new potential drug for treatment of autism spectrum disorder, and provides a new idea for target treatment of ASD by in-depth exploration of potential path in pathogenesis of autism.

The application discloses a two-end vertical structure organic electrochemical biomimetic synapse device and a preparation method and a biomimetic neural morphological chip thereof. The device comprises a bottom electrode, a first organic mixed ion-electron conductor layer, a first ion gel layer and a top electrode which are sequentially stacked. The first ion gel layer is configured to provide anions. The first organic mixed ion-electron conductor layer is configured to transport anions and electrons. The top electrode is configured to apply a bias voltage to drive the migration of anions. In terms of structure, the four-layer stacked structure realizes ion path innovation, and the vertical channel sharply reduces the delay time to the microsecond level. In terms of device mechanism, the low reduction potential of the organic ion-electron mixed conductor and the depletion of the de-doped carriers are utilized, the current spontaneously reverses under the action of a certain voltage, and the simulation of artificial synapse sensitization and habituation is realized at the single device level.

The application relates to an artificial visual nervous system based on a bimodal neural device, comprising a bimodal visual information calculation array composed of a physical convolution kernel array and a synapse calculation array, the physical convolution kernel array is used for receiving an ambient light signal and converting into an electrical signal output, the synapse calculation array is used for receiving the electrical signal and converting into a visual signal, and the physical convolution kernel array and the synapse calculation array are both composed of a plurality of bimodal transistors. The application has excellent bimodal collaborative calculation capability, the receptive field mechanism (excitatory / inhibitory response) of a retinal bipolar cell is simulated through the physical convolution kernel array, image feature extraction and preprocessing are realized, the synaptic plasticity (LTP / LTD mechanism) of a central nervous system is simulated in combination with the synapse calculation array, high-level calculation of the visual signal is completed, and a complete visual nerve bionic system is formed by virtue of an array composed of single devices.

The application discloses a kind of covalent functionalization MXene artificial synapse and preparation method thereof, it is related to the technical field of artificial intelligence, the present application aims at solving how to enrich the overall characteristics of brain-like neural chip, promote artificial intelligence technology problem, the present application includes including following steps: selecting substrate;Utilize photoetching process on the substrate on gate, source and drain are patterned and are handled, in utilizing electron beam evaporation deposition metal layer and stripping obtains metal electrode pattern;Utilize photoetching process on the substrate on channel region is patterned and is handled;MAX phase material is obtained by in-situ acid etching combined with mechanical stripping few-layer T X MXene;Form uniform T i3C2T X MXene film on the substrate by coating process, and obtain channel region pattern by stripping;Preparation of iodonium salt solution, prepared device is immersed in iodonium salt solution so that it is completed covalent functionalization;Preparation of electrolyte solution, on T i3C2T X MXene channel layer, gate and exposed substrate drop casting electrolyte.

The application is a kind of bionic nerve circuit model based on artificial synapse device. The circuit model is composed of n multi-stage connections of synapse-LIF artificial neuron devices. The composition of the synapse-LIF artificial neuron device includes synapse-like device and cytoplasm-like device. The synapse-like device includes artificial synapse device, voltage dividing resistor and voltage control switch. The cytoplasm-like device includes one comparator. Through different combinations of the four devices, namely excitatory synapse-like device, inhibitory synapse-like device, excitatory cytoplasm-like device and inhibitory cytoplasm-like device, the devices of six circuits, including feedforward excitation circuit, feedforward inhibition circuit, feedback inhibition circuit, lateral inhibition circuit, disinhibition circuit and mutual inhibition circuit, are formed. The application realizes the functions of perception afferent, information integration and motor control in the motor nervous system through the circuit model group, which is helpful for the repair or reconstruction of damaged motor conduction circuit.

The application discloses a multifunctional silicon-based optoelectronic neural synapse device, which comprises a silicon-on-oxide layer, a photoelectric response layer and a top electrode, wherein the silicon-on-oxide layer is composed of an oxide layer and a silicon substrate, the oxide layer is located on the silicon substrate, the photoelectric response layer is located on the oxide layer and is a semiconductor perovskite film, and the top electrode is located on the photoelectric response layer and is an inert metal material. The device can perform electrical signal writing under lower energy consumption and low crosstalk, and has completed multiple light regulation functions. The application further provides a preparation method of the multifunctional silicon-based optoelectronic neural synapse device. The preparation method has the advantages of low cost, high fault tolerance and simple operation.

The application discloses a memristor, a method for preparing the same and an artificial synapse device, and the memristor comprises a glass cone and a polyelectrolyte structure on the inner wall of the glass cone; the glass cone has a first end opening and a second end opening arranged oppositely, the diameter of the first end opening is smaller than that of the second end opening, and the polyelectrolyte structure is located on the inner wall of the first end opening. Thus, the memristor has low power consumption of a picojoule level, a low working potential and high efficiency. When a pulse potential stimulus is applied, the memristor can generate a double-pulse facilitation and a double-pulse inhibition effect similar to a neuron synapse, and due to the existence of an ion effect, the effective regulation of the plasticity of the system can be realized. Further, the signal transduction function based on ions can be realized by being combined with a micro-injection system. In addition, the memristor has excellent stability and designability and the like.

The application discloses a kind of all ferroelectric neural-paradigm units and preparation methods thereof.A kind of all ferroelectric neural-paradigm unit, the all ferroelectric neural-paradigm unit structure includes the upper electrode array, ferroelectric layer and lower electrode array sequentially arranged from top to bottom;The single electrode shape of the upper electrode array and the lower electrode array is rectangle, the width of single electrode is 1nm~10 μm respectively, the spacing between adjacent electrodes is 10nm~50 μm;The width ratio of the single electrode of the upper electrode array and the single electrode of the lower electrode array is 0.001~1000;The upper electrode array and the lower electrode array electrode staggered arrangement, the angle range of staggered angle is 0~180°.The application can efficiently simulate neuron firing, synaptic plasticity and other behaviors by fine changing electric field loading conditions to regulate polarization, shielding, space charge dynamics in ferroelectric functional layer, can also realize the simulation of neuron and synapse simultaneously, to build all ferroelectric brain network.