42 results about "Frontal lobe" patented technology

The invention provides a head-mounted diagnosis and treatment device, a brain-computer interface system and a brain activity monitoring intervention method. The head-mounted diagnosis and treatment device comprises a head-mounted structure, at least one active electrode, at least one pair of stimulation electrodes and a control module, the head-mounted structure comprises a head beam supporting part and a frontal lobe wearing part, the two ends of the frontal lobe wearing part are connected with the two opposite sides of the head beam supporting part respectively, and the active electrode is arranged on the inner side of the frontal lobe wearing part. The active electrode is arranged on the head beam supporting part and used for collecting electroencephalogram signals of a frontal lobe area contact part, the stimulation electrode is arranged on the inner side of the head beam supporting part and used for forming electrical stimulation on the frontal lobe area contact part, and the control module is electrically connected with the active electrode and the stimulation electrode and used for determining the brain function state according to the electroencephalogram signals collected by the active electrode and controlling the stimulation electrode according to the determined brain function state. Thus, electrical stimulation therapy is formed. According to the head-mounted diagnosis and treatment device, the brain-computer interface system and the brain activity monitoring intervention method, diagnosis and treatment can be integrated, and the head-mounted diagnosis and treatment device is easy to wear and portable.

Compositions comprising microalgal extracellular vesicles (MEVs) formulated for intranasal delivery are provided, whereby upon intranasal administration, the MEVs are transported by a specific route, to specific regions in the brain via the olfactory nerve after intranasal administration, and to interconnected brain regions through the lateral olfactory tract (LOT). The MEVs are transported via neuronal axonal transport. The MEVs have the ability to cross synapses including: (i) synapses between olfactory sensory neurons (OSNs) and mitral / tufted neurons; (ii) synapses between mitral / tufted neurons and local neurons in multiple brain regions colonized by the lateral olfactory tract (LOT); and (iii) synapses between neurons in brain regions colonized by the LOT and neurons from the frontal cortex, hippocampus, thalamus, and hypothalamus. The compositions contain extracellular vesicles (MEVs) from microalgae loaded with bioactive cargo for the treatment, detection, diagnosis, or monitoring of diseases, disorders, or conditions of or involving the brain, particularly neuronal delivery of the cargo. The compositions and methods have multiple applications as therapeutic and diagnostic agents for the treatment, diagnosis, and monitoring of diseases, disorders, or conditions of or involving the brain. The compositions can be used in methods and uses for the treatment of cancers involving the brain, and can be used, for example, to deliver therapeutic agents for psychiatric diseases, disorders, conditions, and to deliver therapeutic agents for neurodegenerative diseases, disorders, and conditions.

The invention discloses a method for determining an OAB target based on brain network characteristics. The method comprises the following steps: a) detecting the functional connection strength of the right forehead cortex of a patient in a resting state through functional magnetic resonance imaging; b) identifying significantly weakened brain region connections, including paracentral lobules, cerebellar lower feet and marginal systems, as compared to a healthy control group; c) determining the number of white matter fiber bundles with abnormal structural connection in the brain interval by combining a diffusion tensor imaging fiber tracking technology; and d) selecting a brain region with abnormal function and structure connection as a nerve regulation treatment target.

A system for estimating a subject's functional brain age using non-invasive electroencephalography (EEG), the system includes: an EEG acquisition module (101) configured to record multichannel EEG signals from the subject; a stimulation control module (102) configured to present a predefined sequence of cognitive and sensory tasks that specifically target the frontal, temporal, parietal and occipital brain regions, and to generate synchronized event markers; a data processing module (103) configured to prepare the recorded EEG signals by filtering, artifact removal, normalization and segmentation into task-oriented time windows; a machine learning module (104) comprising one or more self-monitoring contrastive learning encoders configured to transform the preprocessed EEG signals into latent feature representations; and a brain age estimation module (105) configured to process the latent feature representations to generate a BrainAge Score indicating a difference between a predicted biological brain age and the subject's chronological age.

The application provides a Chinese spoken language intention recognition brain-computer interface system based on a sound-meaning integration double model, belongs to the technical field of biomedical engineering, and relates to language brain-computer interface technology. Taking sound-meaning integration as the core, the stereotactic intracranial electroencephalogram (sEEG) technology is adopted to collect neural signals of the brain articulatory motor coding area and the semantic concept organization coding area. The system comprises a voice initiation decoder, a speech decoder, a semantic decoder and a Chinese word speech-semantic fusion synthesizer, the target decoder is constructed by extracting high gamma band features of key brain areas of the frontal lobe (left inferior frontal gyrus, premotor cortex, etc.), the temporal lobe (anterior temporal lobe, dorsolateral temporal lobe, etc.). At the same time, a visual and auditory induction training paradigm is matched, three tasks of listening to sound to group words, looking at words to group words and word association are set, and the subjects are supported to generate words independently. The system effectively solves the homonym and near homonym word ambiguity problem in Chinese spoken language recognition, and provides a precise interactive tool for ALS and other speech disorder patients.

The invention provides a Chinese spoken language intention recognition brain-computer interface system based on pronunciation-meaning integration double models, belongs to the technical field of biomedical engineering, and relates to a language brain-computer interface technology. Sound-sense integration is taken as a core, and a stereotactic intracranial electroencephalogram (sEEG) technology is adopted to acquire neural signals of a brain phonetic motion coding region and a semantic concept organization coding region. The system comprises a sound production starting decoder, a voice decoder, a semantic decoder and a Chinese word voice-semantic fusion synthesizer, and a target decoder is constructed by extracting high gamma wave band characteristics of key brain regions of frontal lobe (left subfrontal gyrus, anterior cortex of motion and the like) and temporal lobe (anterior temporal lobe, dorsal lateral temporal lobe and the like). Meanwhile, an audio-visual induction training normal form is matched, three tasks of listening word combination, character reading word combination and vocabulary association are set, and subjects are supported to autonomously generate vocabularies. The system effectively solves the problem of ambiguity of homophonous and near-phonetic words in spoken Chinese recognition, and provides an accurate interaction tool for speech disorder patients such as ALS and the like.

The present application discloses a system and interactive method for evaluating the cognitive function of a subject based on fNIRS. The head cap and near-infrared light emitting / receiving probe in the system enable the imaging range to cover the frontal lobe, temporal lobe, and occipital lobe; the cognitive assessment paradigm interactive device sequentially executes the inhibitory control assessment paradigm, the alert attention assessment paradigm, the selective attention assessment paradigm, the core attention network assessment paradigm, the working memory assessment paradigm, and the cognitive control assessment paradigm in a single-block mode in an order of execution from simple to difficult; the signal acquisition device collaboratively collects near-infrared brain function imaging time series data during the sequential execution of each assessment paradigm; the processing device evaluates the cognitive function of the subject based on the near-infrared brain function imaging time series data and the behavioral data generated based on the assessment paradigm. The present application can obtain brain function data of more dimensions associated with cognitive function in a relatively short period of time, which is convenient for clinical evaluation and analysis of the cognitive function of the subject from multiple angles based on fNIRS.

The application provides a frontal lobe EEG sleep quality prediction method and system. The method comprises the following steps: constructing a sleep quality prediction model based on the electroencephalogram signal data of the frontal lobe region; and performing sleep quality prediction by using the sleep quality prediction model to obtain a sleep prediction result. In the technical solution, the sleep quality problem that has not occurred can be predicted in advance, thereby providing a basis for improving the sleep quality.

A digital method of therapeutic brain stimulation is provided. The method comprises presenting to a user in a UI a group of trials by sequentially displaying symbols against a background. The symbols are randomly displayed one at a time against one several contexts in the background to stimulate the user's parietal or frontal lobes or motor cortex. A user response is received for each display of a symbol indicating whether the symbol is the same or different from an immediately prior symbol for the same context, wherein each trial has a maximum allowed response time for the user input after which any response is counted as a false alarm. A user score is generated for the group of trials, wherein the score compares correct identification and incorrect false alarm responses for the group of trials against a user score of a previous group of trials.

Provided are compositions containing microalgae extracellular vesicles (MEVs) formulated for intranasal delivery, whereby, upon intranasal administration the MEVs traffic through specific routes following intranasal administration to specific regions in the brain via the olfactory nerve and throughout the lateral olfactory tract (LOT) to interconnected brain regions. The MEVs traffic via neuronal axonal transport. The MEVs have the ability to cross-over synapses including: (i) the synapses between the olfactory sensory neurons (OSN) and the mitral / tufted neurons; (ii) the synapses between the mitral / tufted neurons and the local neurons in the various brain regions colonized by the lateral olfactory tract (LOT); and (iii) the synapses between the neurons in the brain regions colonized by the LOT and neurons from the frontal cortex, the hippocampus, the thalamus, and the hypothalamus. The compositions contain extracellular vesicles from microalgae (MEVs) that are loaded with bioactive cargo for treating, detecting, diagnosing, or monitoring a disease, disorder, or condition of the brain or involving the brain, particularly providing neuronal delivery of the cargo. The compositions and methods have a variety of applications as therapeutics and diagnostics for treating, diagnosing, and monitoring a disease, disorder, or condition of the brain or involving the brain. The compositions can be used in methods and uses for treating cancers involving the brain, and can be used, for example, to deliver therapeutics for psychiatric diseases, disorders, conditions, and to deliver therapeutics for neurodegenerative diseases, disorders, and conditions.

The utility model discloses a transcranial magnetic stimulation helmet with a focus on a frontal lobe, which relates to the technical field of transcranial magnetic stimulation and comprises a helmet, a first coil and a second coil, the first coil and the second coil are connected in series, the first coil surrounds the bottom of the helmet at intervals, and the second coil surrounds the top of the helmet at intervals. The first coil and the second coil are gathered on the right front side and / or the left front side of the helmet to form a gathering part I and a gathering part II, and the gathering part II is located on the front side of the gathering part I. According to the transcranial magnetic stimulation helmet with the focus located on the frontal lobe, the first coil and the second coil are gathered and overlapped at the frontal lobe, the intensity and the concentration ratio of an induction electric field are enhanced, and magnetic stimulation can act on the left side and the right side more accurately or act on frontal lobe areas on the two sides at the same time through the layout; meanwhile, through an air bag adjusting mechanism, the helmet can adapt to different head types, the shaking problem of the helmet is solved, and the stimulation stability and the repeated positioning accuracy are improved.

The present application provides a transcranial physical stimulation device, which includes at least a phototherapy unit and an AC transcranial electrical stimulation unit. The phototherapy unit is configured to irradiate transcranial near-infrared light to at least the frontal lobe, temporal lobe, and parietal lobe of the subject's head. The AC transcranial electrical stimulation unit includes a first scalp electrode pair and a second scalp electrode pair. The first scalp electrode pair forms a first electric field and acts on a target deep part. The second scalp electrode pair forms a second electric field and acts on the target deep part. The first electric field and the second electric field are AC oscillating electric fields applied simultaneously, with a frequency of more than 1000 Hz and a frequency difference of 10 Hz-80 Hz. The device is easy to operate and can provide comprehensive, gentle, and comfortable transcranial physical therapy for multiple brain areas involved in AD. It can also coordinate transcranial alternating current (tACS) to provide targeted and precise treatment of deep parts of the brain such as the hippocampus.

The invention discloses a relapse risk monitoring and early warning method based on heart and brain behavior intelligent fusion, and belongs to the technical field of drug banning and health monitoring. Three-mode data of HRV sample entropy (electrocardio), prefrontal lobe theta wave coherence (electroencephalogram) and motion fractal dimension (behavior) of a patient abstained from drugs are collected in a non-stimulation mode through a wearable device; motion interference is suppressed by adopting a motion-driven cascade filtering technology (kurtosis detection and self-adaptive band elimination filtering); inputting the data into a space-time diagram convolution-federated learning hybrid model (ST-FedGCN), and outputting a relapse risk level (1-5 levels) and expected relapse time; when the risk probability value is Rgt; and when the risk level is 0.82 or the risk level is greater than or equal to 4, the portable tDCS equipment is automatically triggered, and 1.5 mA regulation and control current is applied to the front frontal lobe on the back and outer side of the right side. Laboratory dependence is broken through, community dynamic monitoring is achieved, the prediction accuracy is larger than 90%, the relapse rate is reduced, and powerful support is provided for drug banning work.

Methods, systems and devices for reducing anxiety, including increasing relaxation and / or calm. In some variations these methods may include reducing anxiety, increasing relaxation and / or calm by non-invasive temperature regulation of the frontal cortex prior to and / or during sleep. The subject may have an anxiety disorder, or may not have a diagnosed anxiety disorder.

To provide a driver cognitive function improvement system which activates frontal and parietal lobes of the brain while preventing a driver from feeling discomfort.SOLUTION: A driver cognitive function improvement system includes: a sound input device 2 which is installed in a vehicle cabin and collects sound; a sound output device 3 which is installed in the vehicle cabin and outputs sound; an operation part 4 for allowing a driver to select one of a plurality of types of induction sound which has effect of inducing gamma waves in a driver's brain; a control part 6 for generating induction sound in the selected type and allowing the sound output device 3 to output induction sound so that it is overlapped with sound collected by the sound input device 2 when a sound pressure level of sound collected by the sound input device 2 is a prescribed threshold XdB or more. The control part 6 generates induction sound by amplitude-modulating sound collected by the sound input device 2 or specified sound which is previously stored by a gamma wave frequency in accordance with the type of induction sound selected by the operation part 4.SELECTED DRAWING: Figure 3

The application discloses an individualized cognitive function adjusting device based on cross-frequency coupling, which comprises a peak frequency automatic extraction module, a spectrum analysis and automatic frequency extraction are used to obtain the peak frequency of the frontal lobe theta oscillation and the parietal lobe gamma oscillation of an individual baseline as the stimulation frequency of transcranial alternating current stimulation; a target site determination module is used to automatically output the stimulation site of tACS by determining the positive and negative power values corresponding to the peak frequency between the left and right brain regions, and the stimulation equipment outputs current to the corresponding brain region according to the output stimulation site; a signal-to-noise ratio calculation module is used to adaptively output the stimulation current intensity of tACS according to the signal-to-noise ratio value at the peak frequency; and a multi-mode regulation model is used to set the peak nesting and valley nesting modes according to the cross-frequency tACS, so that the targeted regulation of cognitive function disorders such as memory, attention and emotion processing is realized.

The invention provides an anesthesia depth monitoring system and method based on machine learning, and the system comprises an obtaining module which is used for obtaining a brain frontal lobe electroencephalogram signal and a brain parietal lobe electroencephalogram signal of a target object injected with anesthetics in a preset time length in a current period; the conversion module is used for converting the brain frontal lobe electroencephalogram signals and the brain parietal lobe electroencephalogram signals of the preset duration into characteristic values of multiple dimensions; the determining module is used for inputting the characteristic values of the multiple dimensions into an anesthesia depth monitoring model pre-trained based on a machine learning model to obtain the current anesthesia depth in the target object, the anesthesia depth monitoring model pre-trained based on the machine learning model is obtained by training electroencephalogram data of various anesthetics under various injection concentrations. According to the scheme, anesthesia depth monitoring is carried out by combining machine learning with electroencephalogram characteristics, and the technical effects of effectively improving the accuracy of anesthesia depth monitoring and widening the application range are achieved.

A compact and concealed electroencephalography (EEG) headband includes a main continuous band spanning across central, frontal, parietal and temporal lobes of a brain. The headband has comb pieces located at evenly spaced distances along a top of the main continuous band. Each comb piece has a triangular shape to facilitate electrode-scalp contact and houses a dry EEG electrode. A grounding electrode is located on a bottom of the main continuous band, contacting a mastoid bone. Stability comb pieces are located along the main continuous band to hold it flush against a scalp. Electronics and wiring are embedded in the main continuous band.

A blue light therapy device includes a domed shaped main body having a fixed array of optical emitters along the inside surface. Each of the optical emitters of the fixed array includes a blue light LED that applies optical emissions to the hippocampus and entorhinal cortex area of the recipient's brain in form of blue light between 400 nm and 470 nm to each side of the recipient's head at a location just above their ears. A second array of optical emitters are located on adjustable arms that are positionable within the nostrils of the recipient to apply optical emissions to the frontal and temporal lobes of the brain of the recipient. The device also includes a controller that is connected to the arrays, a user interface, an eye shield, and a chin strap.

1. The name of the design product: wearable EEG head ring. 2. The use of the design product: used for wearing on the head to collect multi-channel EEG signals of frontal and temporal lobes, realize emotion monitoring and brain health assessment, etc. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

A device for relieving dementia symptoms is disclosed. The device for relieving dementia symptoms includes a light stimulation part disposed at a location within a preset radius from an eyeball and frontal lobe of a patient and configured to relieve dementia symptoms of the patient by radiating light having a preset wavelength band to an optic nerve and frontal lobe of the patient, and a central processing unit configured to control an operation of the light stimulation part.

The application provides a tannic acid astringency perception evaluation method based on an EEG technology, and belongs to the technical field of cross of sensory evaluation and neural engineering. The method acquires the EEG signals of subjects under the stimulation of tannic acid with different concentrations through a standardized EEG data acquisition scheme, analyzes the power spectral density (PSD) of the delta band (1-4 Hz), time-frequency analysis and the neural activation characteristics of the frontal lobe region after pretreatment, and realizes the objective evaluation of the astringency intensity of tannic acid. The application solves the problems of large subjective error and non-uniform standard in the traditional tannic acid astringency evaluation, utilizes the high time resolution advantage of the EEG technology, clearly defines the positive correlation between the PSD value of the delta band and the concentration of tannic acid and the role of the frontal lobe as the core perception brain region, and provides an objective and accurate new method for the tannic acid quality evaluation in the food field.

A composition containing microalgae extracellular vesicles (MEVs) formulated for intranasal delivery is provided, whereby upon intranasal administration, the MEVs travel through a specific pathway, via the olfactory nerve, through the lateral olfactory tract (LOT) to interconnected brain regions, and to specific regions within the brain. The MEVs are transported via neuronal axonal transport. The MEVs have the ability to cross synapses, including (i) synapses between olfactory nerve neurons (OSNs) and mitral / tufted neurons, (ii) synapses between mitral / tufted neurons and local neurons in various brain regions anchored by the lateral olfactory tract (LOT), and (iii) synapses between neurons in brain regions anchored by the LOT and neurons from the frontal cortex, hippocampus, thalamus, and hypothalamus. The composition contains microalgae (MEV)-derived extracellular vesicles loaded with a bioactive cargo for treating, detecting, diagnosing, or monitoring diseases, disorders, or conditions of or involving the brain, and specifically provides neuronal delivery of the cargo. The compositions and methods have a variety of applications as therapeutic and diagnostic agents for treating, diagnosing, and monitoring diseases, disorders, or conditions of or involving the brain. The compositions can be used in methods and uses for treating cancers involving the brain, for example, to deliver therapeutic agents for psychiatric diseases, disorders, and conditions, and to deliver therapeutic agents for neurodegenerative diseases, disorders, and conditions.

This invention discloses a real-time cognitive load assessment system based on multimodal psychophysiological signals, relating to the field of cognitive load assessment technology. The system includes: an EEG signal acquisition module for acquiring bilateral EEG signals of the subject within a continuous sliding time window, wherein the bilateral EEG signals include at least a first EEG signal from a first brain region and a second EEG signal from a second brain region; a feature extraction module for analyzing a situational feature sequence characterizing bilateral brain activity based on the first and second EEG signals; and a system that constructs situational and synergistic features of bilateral brain activity. The situational features quantify the growth relationship between the left and right hemispheres in the allocation of cognitive resources by analyzing the fluctuation of the ratio of instantaneous power in the bilateral frontal lobes within a specific frequency band. The synergistic features avoid the problem of incomplete representation of the load state by single-dimensional features by analyzing the synchronization degree of instantaneous phase in the bilateral frontal lobes within a specific frequency band.

The present application relates to a light treatment device for treating mental diseases including depression, comprising a cover configured to accommodate the head of a patient, and an array of near-infrared irradiation units arranged in the cover, the array of near-infrared irradiation units being configured to emit near-infrared light with a first central wavelength of 800nm-820nm and an average power density greater than 40mW / cm 2 2 to the head of the patient, and at least in the case of treating depression, the average power density of the near-infrared light emitted to the frontal lobe and temporal lobe of the head is 80mW / cm 2 2-200mW / cm 2 2. The light treatment device further comprises a cooling mechanism comprising a refrigerating machine and a passage for delivering the cold air generated by the refrigerating machine to the head of the patient to dissipate heat from the head of the patient. The light treatment device of the present application can improve the comfort of the patient, improve the treatment compliance of the patient, prolong the single treatment time, and ensure good treatment effect on mental diseases such as depression.

The present application relates to a light treatment device for treating psychological disorders including depression, comprising a housing configured to receive a patient's head, and an array of near-infrared irradiation units disposed in the housing, the array of near-infrared irradiation units is configured to emit near-infrared light with a first central wavelength of 800 nm to 820 nm and an average power density greater than 40 mW / cm < 2 > to the head of a patient, and the average power density of the near-infrared light emitted to the frontal lobe and the temporal lobe of the head is 80 mW / cm < 2 > to 200 mW / cm < 2 > at least under the condition of treating depression. The cooling mechanism comprises a refrigerating machine and a passage for conveying cold air generated by the refrigerating machine to the head of the patient so as to cool the head of the patient. According to the light treatment equipment, the comfort of a patient can be improved, the treatment compliance of the patient is improved, the single treatment time is prolonged, and a good treatment effect on psychological diseases such as depression is ensured.

The application provides an electroencephalogram emotion recognition method based on double-flow time-space asymmetry physiological region division. The recognition method comprises the following steps: step one, after frequency division extraction of the electroencephalogram signal, the signal is sent to a dynamic time layer; step two, the electroencephalogram signal with extracted time-frequency features is divided into four regions of frontal lobe, temporal lobe, parietal lobe and occipital lobe according to physiology, and is sent to an asymmetry space layer as a first flow; step three, the original electroencephalogram signal is first divided into four regions of frontal lobe, temporal lobe, parietal lobe and occipital lobe, and is sent to an asymmetry space layer; step four, the signal with extracted space features is sent to a dynamic time layer as a second flow; step five, five regions of the four regions in the first flow plus global electroencephalogram region and five regions of the second flow are sent to a high-level fusion layer for fusion. Compared with the prior art, the application realizes weight distribution of different physiological regions on specific emotions, so that each region of the electroencephalogram is more sensitive to emotion recognition.

The present application relates to a neuromodulation device for treating hippocampus-related brain diseases. The neuromodulation device comprises a phototherapy part and a transcranial alternating current stimulation (tACS) part. The phototherapy part irradiates near-infrared light toward at least a frontal lobe or a temporal lobe, such that the near-infrared light acts on at least a part of the hippocampus. The tACS part applies tACS of a second frequency, and an electric field action range covers at least a part of the hippocampus. When the near-infrared light is continuous light, the second frequency is in one of five representative frequency bands of brain waves. When the near-infrared light is pulsed light having a first frequency, the first frequency and the second frequency also satisfy a preset frequency relationship. The preset frequency relationship comprises: a deviation being less than a threshold, or having a preset frequency band coupling relationship. Transcranial electrical stimulation can produce analgesic and relaxing effects, which can reduce the discomfort of a subject during treatment. Therefore, the treatment time can be prolonged and / or the power density of near-infrared light can be increased as needed, so as to improve the therapeutic effect. The photoelectric bimodal stimulation can improve modulation effects on endogenous oscillations of the brain.

The invention discloses a neck near-infrared light stimulation and head magnetic stimulation wearable cognitive function improvement system, and belongs to the technical field of nerve regulation and control. The system comprises a high-intensity narrow-pulse near-infrared light stimulation module for the neck and the lower jaw, a low-intensity composite rhythm magnetic stimulation module for the forehead lobe and the temporal lobe, a portable controller and a head and neck sleeve. The near-infrared light enhances drainage of cerebrospinal fluid through a thermo-acoustic effect; magnetic stimulation induces multi-brain-region nerve rhythm resonance and cross rhythm coupling to improve the cognitive function; the controller controls the output parameters of the two stimuli and coordinates the frequency multiple relation and the phase difference of the two stimuli. The problems of single intervention mechanism and lack of space-time coordination in the prior art are solved, and bimodal multi-target combined regulation and control of metabolic clearance and nerve rhythm are realized. The system is suitable for auxiliary intervention of neurological diseases such as Alzheimer's disease and the like.

The invention relates to an occlusion target detection method, a neural network model and a calculation program product. The method comprises the following steps: acquiring a feature matrix corresponding to a to-be-recognized image; on the basis of the feature matrix and the frontal lobe output matrix, updating the activation state of temporal lobe neurons to obtain a temporal lobe output matrix; on the basis of the temporal lobe output matrix, updating an activation state of a frontal lobe neuron to obtain a new frontal lobe output matrix; first iteration operation is executed until a first ending condition is met, the first iteration operation is stopped, a first steady-state temporal lobe neural network model is obtained, and the first iteration operation comprises updating the activation state of the temporal lobe neurons and updating the activation state of the frontal lobe neurons; and processing the to-be-recognized image based on the first steady-state temporal lobe neural network model to obtain a recognition result. According to the method provided by the embodiment of the invention, the recognition precision can be adaptively maintained when different types of shielding are faced, and the recognition accuracy and stability are enhanced.