CN116603178A - AD nerve regulation and control system and method based on feature extraction and closed loop ultrasonic stimulation - Google Patents
AD nerve regulation and control system and method based on feature extraction and closed loop ultrasonic stimulation Download PDFInfo
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Abstract
The invention discloses an AD nerve regulation and control system and method based on feature extraction and closed-loop ultrasonic stimulation, which belong to the field of transcranial ultrasonic stimulation, and comprise a programmable ultrasonic signal generation module, an ultrasonic stimulation module, an electroencephalogram signal acquisition and processing module, a closed-loop control module, a signal transmission and storage module, an upper computer and an electroencephalogram electrode connected to a test object; the system utilizes the transcranial ultrasonic stimulation technology to stimulate a specific area of a cerebral cortex and implant an electroencephalogram electrode in a target area, detects electroencephalogram signals in the target area in real time, extracts multi-dimensional characteristics such as time domain, nonlinear dynamics, airspace and the like of signals in different frequency bands, takes the obtained characteristics as input of a third-stage processor, and accordingly carries out real-time detection, and continuously adjusts transcranial ultrasonic stimulation parameters according to category diagnosis results so as to inhibit AD aggravation. The invention can provide thought for optimizing the treatment parameters of the Alzheimer disease, and lays foundation for developing the treatment equipment of the Alzheimer disease.
Description
Technical Field
The invention relates to the field of transcranial ultrasonic stimulation, in particular to an AD nerve regulation and control system and method based on feature extraction and closed loop ultrasonic stimulation.
Background
Alzheimer's Disease (AD) is a neurodegenerative disease with progressive memory impairment, cognitive dysfunction and mental dysfunction, and its main pathological features include beta-amyloid (Abeta) deposition, neurofibrillary tangles (neurofibrillary tangles, NFTs), neuronal loss and other behavioral disorders with chronic cognitive dysfunction, memory decline, language disorder, learning ability decline and the like.
By 2019, 1000 ten thousand Alzheimer's Disease (AD) patients exist in China. It is expected that by 2050, our country's alzheimer's disease will reach 3003 tens of thousands, with a proportion of patients over 80 approaching 50%, and there is currently no effective way to treat AD, which will create a heavy burden.
At present, the diseases are mainly clinically treated by medicaments, surgical excision focus areas, transcranial electromagnetic stimulation, deep brain stimulation and the like, but the treatments have the limitations of medicament resistance, invasiveness, limitation to low resolution, superficial brain tissues and the like. Transcranial Ultrasonic Stimulation (TUS) is a non-invasive, noninvasive and focused and high-resolution transcranial nerve treatment technique at brain depth, and has attracted considerable attention. However, the etiology, pathogenesis and action mechanism of ultrasonic stimulation of AD are not clear at present, so that experimental research of a mouse model of Alzheimer's disease plays a vital role in clinical research.
Disclosure of Invention
The technical problem to be solved by the invention is to provide an AD nerve regulation and control system and method based on feature extraction and closed-loop ultrasonic stimulation so as to realize the diagnosis of AD of a specific cerebral cortex of a mouse and the detection of improvement conditions, thereby applying proper ultrasonic stimulation to the specific area of the cerebral cortex in real time.
In order to solve the technical problems, the invention adopts the following technical scheme:
an AD nerve regulation and control system based on feature extraction and closed-loop ultrasonic stimulation comprises a programmable ultrasonic signal generation module, an ultrasonic stimulation module, a signal acquisition and processing module, a closed-loop control module, a signal transmission and storage module, an upper computer and an electroencephalogram electrode; the electroencephalogram electrode is connected to an experimental object; the programmable ultrasonic signal generation module sends the generated stimulation signal to the ultrasonic stimulation module, and the ultrasonic stimulation module sends the stimulation signal to the experimental object in an ultrasonic stimulation mode; the signal acquisition and processing module is connected with the electroencephalogram electrode and is used for acquiring the electroencephalogram signal recorded by the electroencephalogram electrode, preprocessing and frequency-dividing the electroencephalogram signal and sending the processed electroencephalogram signal to the closed-loop control module; the system stimulates a specific area of the cerebral cortex of a subject by utilizing a transcranial ultrasonic stimulation technology, an electroencephalogram electrode is implanted in a target area, an electroencephalogram signal in the target area is detected in real time, then time domain, nonlinear dynamics and airspace multidimensional features of signals in different frequency bands are extracted, the obtained multidimensional features are used as input of a third-stage processor in a closed-loop control module, real-time detection is carried out, and parameters of transcranial ultrasonic stimulation are continuously adjusted according to a category diagnosis result so as to inhibit aggravation of AD of the subject.
The technical scheme of the invention is further improved as follows: the experimental object selects a mouse, the ultrasonic stimulation module is placed in the motor cortex of the mouse, and the electroencephalogram electrode is implanted into the CA1 region of the hippocampus of the mouse.
The technical scheme of the invention is further improved as follows: the closed-loop control module is internally implanted with a three-stage serial processor which is used for carrying out three-stage processing on the electroencephalogram signals after frequency division processing by the signal acquisition and processing module, and the first-stage processor is a strong classifier for carrying out quick screening of suspected AD electroencephalogram signals; the screened electroencephalogram signals enter a second-stage processor, multichannel input of signals is realized by adopting a multi-component transformation modal decomposition algorithm in the second-stage processor, time domain features and nonlinear dynamics features of the signals are extracted from signal components obtained by decomposition, meanwhile, the signal components are combined to construct a new signal matrix, and CSP is adopted to extract spatial features of the signal matrix; combining the three obtained features in a third-stage processor to obtain multi-modal features of the EEG signals, and finally classifying by SVM; stopping calculation if the classification result is not the AD abnormal signal, otherwise diagnosing AD aggravation, and sending the diagnosis result to a programmable ultrasonic signal generating module so as to adjust the stimulation parameters in time to achieve the treatment purpose;
the signal transmission and storage module is used for receiving the working parameters of each module configured by the upper computer and the brain electrical signals transmitted by the closed-loop control module, and storing the brain electrical signals as a data set;
the upper computer is used for training parameters of the three-stage serial processor implanted in the closed-loop control module according to the data set and communicating with the signal transmission and storage module in real time; continuously adjusting working parameters of each module during operation, updating various parameters in a three-stage serial processor implanted in the closed-loop control module, and displaying acquired brain electrical signals in real time;
the programmable ultrasonic signal generation module is used for changing the output of ultrasonic stimulation in real time according to the result obtained by the closed-loop control module or the instruction of the upper computer.
The technical scheme of the invention is further improved as follows: the first-stage processor is a strong classifier trained by adopting an Ada Boost algorithm.
The technical scheme of the invention is further improved as follows: the second-stage processor is used for extracting multi-mode characteristics, wherein the multi-mode data are from the disclosed AD mouse brain electrical data, and the mouse brain electrical data of a model group, a false stimulation group and a normal control group are selected.
The technical scheme of the invention is further improved as follows: the components of the signals in the three-stage serial processor are obtained by an MVMD method.
The technical scheme of the invention is further improved as follows: the step of preprocessing the EEG signal includes filtering and noise reduction.
The technical scheme of the invention is further improved as follows: the SVM classifier can test the test set after training the training set to obtain the classification model.
An AD nerve regulation and control method based on feature extraction and closed loop ultrasonic stimulation comprises the following steps:
step 1, respectively implanting the ultrasonic stimulation module and the electroencephalogram electrode into preset sites of a plurality of mice; the preset site is positioned in the brain region of the mouse; mice were divided into different stimulation groups;
step 2, after all experimental mice implanted with the brain electrode recover for t time, regulating and controlling the output parameters of the ultrasonic stimulation signals of the ultrasonic stimulation module by using the programmable ultrasonic signal generating module;
step 3, after the ultrasonic transducer of the ultrasonic stimulation module receives the stimulation signal, performing ultrasonic stimulation on the intracranial brain preset site of the experimental mouse;
step 4, acquiring the electroencephalogram signals recorded on the electroencephalogram electrodes by using a signal acquisition and processing module, sending the processed electroencephalogram signals to a closed-loop control module, and judging whether the experimental mice need to adjust ultrasonic stimulation parameters according to classification results through processing of a three-stage serial processor; the signal transmission and storage module receives the brain electrical signals transmitted by the closed-loop control module and stores the brain electrical signals as a data set;
step 5, the upper computer trains parameters of the three-stage serial processors implanted in the closed-loop control module according to the existing data set and communicates with the signal transmission and storage module in real time; continuously updating various parameters in the three-stage serial processors implanted in the closed-loop control module, and displaying the acquired brain electrical signals in real time;
step 6, according to the judgment result of the step 4, if the stimulation parameters do not need to be adjusted, the step 7 is carried out, otherwise, the step 3 is returned;
step 7, performing Morris water maze experiments on the experimental mice every T period to obtain evaluation indexes of the Morris water maze experiments; the evaluation indexes of the Morris water maze experiment comprise escape latency and escape path length; judging the difference of evaluation indexes of Morris water maze experiments under the interaction of groups and days, if the difference between the time of the third quadrant and the time of other quadrants among the groups is larger than a preset threshold value, finishing regulation, otherwise, modifying ultrasonic stimulation parameters, and returning to the step 3.
The technical scheme of the invention is further improved as follows: the Morris water maze test of the experimental mice comprises the following steps:
701, equally dividing the water maze into 4 areas; the water maze is provided with a visible platform positioned above the water surface;
702, enabling the experimental mice to enter water, wherein the water inlet point is a pool wall at the middle point of each area;
703, acquiring a swimming track of the organism by using a CCD camera and storing the swimming track in a video acquisition card;
704, uploading the swimming track of the experimental mouse to a computer by the video acquisition card; the computer performs image recognition on the swimming track of the experimental mouse to obtain an evaluation index of the Morris water maze experiment; the escape latency is the time from entry of water to boarding of the visible platform for the experimental mice.
By adopting the technical scheme, the invention has the following technical progress:
the AD nerve regulation and control system and method based on the feature extraction and the closed loop ultrasonic stimulation can detect whether the brain electrical signal of the specific cerebral cortex is an abnormal AD signal or not, and can adjust proper ultrasonic stimulation parameters according to the detection result, so that accurate monitoring and nerve regulation and control of the specific cerebral cortex can be realized.
According to the invention, the motor cortex of the mouse is selected as a stimulation target point, a transcranial ultrasonic stimulation paradigm is designed, a chronic stimulation experiment is carried out, an experimental control group is designed, and the transcranial ultrasonic stimulation effect is evaluated from the perspective of animal behaviours and brain electrical signals, so that the optimal stimulation parameters are found. In order to detect the nerve regulation effect, the difference of the ultrasonic stimulation of different parameters on AD nerve activity regulation is evaluated by recording the physiological signals acquired and analyzed by implanting brain electrodes into the hippocampus CA1 (AP: 2.06, ML: + -1.5, DV: 1.25) of the mice, and a thought is provided for the treatment parameter optimization of Alzheimer disease.
Drawings
For a clearer description of embodiments of the invention or of the solutions of the prior art, the drawings that are used in the description of the embodiments or of the prior art will be briefly described, it being obvious that the drawings in the description below are some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive faculty for a person skilled in the art;
FIG. 1 is a block diagram of a system in an embodiment of the invention;
FIG. 2 is a schematic diagram of a closed loop control module in a system according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a multi-modal feature extraction process in an embodiment of the invention;
the device comprises a programmable ultrasonic signal generation module, a programmable ultrasonic signal generation module and a control module, wherein 1 is a programmable ultrasonic signal generation module; 2. an ultrasonic stimulation module; 3. an electroencephalogram electrode; 4. a signal acquisition and processing module; 5. a closed loop control module; 51. a data receiving sub-module; 52. a category diagnosis sub-module; 53. a parameter configuration sub-module; 54. a stimulus control submodule; 6. a signal transmission and storage module; 7. and an upper computer.
Detailed Description
It is noted that the terms "comprises" and "comprising," and any variations thereof, in the description and claims of the present invention and in the foregoing figures, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.
The invention is described in further detail below with reference to the attached drawings and examples:
as shown in fig. 1, the embodiment provides an AD nerve regulation and control system based on feature extraction and closed-loop ultrasonic stimulation, which comprises a programmable ultrasonic signal generation module 1, an ultrasonic stimulation module 2, an electroencephalogram electrode 3, a signal acquisition and processing module 4, a closed-loop control module 5, a signal transmission and storage module 6 and an upper computer 7;
the programmable ultrasonic signal generation module 1 can send the generated stimulation signal to the ultrasonic stimulation module 2 according to the processing result obtained by the closed-loop control module 5 or the instruction of the upper computer 7, and the output of ultrasonic stimulation is changed in real time; the electroencephalogram electrode 3 is electrically connected to an experimental object (mouse) and is used for collecting electroencephalogram signals of the mouse;
the signal acquisition and processing module 4 is electrically connected with the electroencephalogram electrode 3 and is used for acquiring an electroencephalogram signal recorded by the electroencephalogram electrode 3, performing serial processing such as analog-to-digital conversion, filtering and noise reduction on the acquired electroencephalogram signal and sending the processed electroencephalogram signal to the closed-loop control module 5.
The signal transmission and storage module 6 can transmit the received brain electrical signals to the upper computer 7 in a wired or wireless manner for real-time display and analysis of the brain electrical signals, and in a low-power consumption operation mode, the signal transmission and storage module 6 is not in physical connection with the upper computer 7, and directly stores the received brain electrical signals in an on-board SD memory for subsequent offline analysis and processing.
The closed-loop control module 5 performs multidimensional (time domain, nonlinear dynamics, airspace, etc.) feature extraction and classification on the electroencephalogram signal after receiving the preprocessed electroencephalogram signal, determines whether the AD aggravation occurs in the specific cerebral cortex in real time, and after the classification result is transmitted to the stimulus control sub-module 54, the stimulus control sub-module 54 configures different ultrasonic stimulus modes and parameters according to the configured stimulus parameters and the classification result and feeds back the different ultrasonic stimulus modes and parameters to the programmable ultrasonic signal generating module 1. The programmable ultrasonic signal generation module 1 applies corresponding ultrasonic stimulation pulses according to the received stimulation parameters to intervene on intracranial neuron conditions in corresponding areas, and the closed-loop intervention process of the system on AD diagnosis is completed.
Further, as shown in fig. 2, the closed loop control module 5 includes a data receiving sub-module 51, a category diagnosing sub-module 52, a parameter configuring sub-module 53, and a stimulus controlling sub-module 54; the data receiving sub-module 51, as an interface between the signal collecting and processing module 4, the signal transmitting and storing module 6 and the closed-loop control module 5, can be responsible for receiving and buffering the electroencephalogram signal of the signal collecting and processing module 4, and configuring parameters of an upper computer transmitted by the signal transmitting and storing module 6, and the like through an SPI communication mode. After the data buffer in the data receiving sub-module 51 obtains a neural signal time sequence with a predetermined length, the neural signal sequence enters the category diagnosis sub-module 52, which is essentially a three-stage serial processor, to determine whether the current electroencephalogram signal is an AD signal emphasis segment. The classification result is transmitted to the stimulus control sub-module 54, and the stimulus control sub-module 54 transmits different stimulus mode parameters to the programmable ultrasonic signal generating module 1 according to the corresponding configuration parameters such as stimulus time, stimulus intensity, duty cycle and the like transmitted by the upper computer in the parameter configuration sub-module 53, and if the diagnosis result of the specific cerebral cortex nerve signal is an abnormal AD signal, the corresponding region is stimulated by corresponding ultrasonic.
Further, the classifier used by the closed loop control module 5 to construct the three-stage serial processor is obtained by Real AdaBoost algorithm based on the criteria that minimizes the loss function in the positive and negative sample sets in the training set. Wherein classifier c i The method comprises the steps of outputting one value when the corresponding characteristic value f of the signal is larger than a threshold value theta, and outputting the other value otherwise. The piecewise function and the threshold value output by the classifier are obtained by training the acquired electroencephalogram signals.
The first stage processor is a strong classifier, and H (x) is obtained through training of a Real AdaBoost algorithm. Classifier c used in the first stage i And the corresponding small calculated quantity features such as amplitude values, frequency spectrums and the like of different rhythms after frequency division are beneficial to the rapid screening of suspected abnormal AD signals.
H(x)＝∑a＝1，…na (2)
The second-stage processor further decomposes the signals subjected to rapid screening by adopting an MVMD method, extracts time domain features and nonlinear dynamic features of the signals from signal components obtained by decomposition, combines the signal components to construct a new signal matrix, and extracts spatial features of the signal matrix by adopting CSP.
Signal decomposition: the MVMD method achieves a change from a single channel input signal to a multi-channel input signal, and can keep the frequency of each IMF component the same when decomposing data. The components obtained by decomposition are taken as the input of an iterator, the center frequency and the bandwidth are taken as the updating targets of the iterator, and the output of the iterator is the k components. Assuming that the signal of the C sampling channels is X (t), it can be expressed in mathematical form as [ X ] 1 (t),x 2 (t),…x C (t)]。
(1) Let k components be included in the signal first, and satisfy:
(2) In vector u k In (t), the data analysis is represented as Hilbert-Huang transform (HHT)And taking this as a reference to find the single-sided spectrum, then multiplying by the exponential term +.>The center frequency is adjusted. Recalculating->The objective function is optimized to keep each obtained component as far as possible to form the original signal while minimizing the bandwidth of the component, and the following is the solved optimization problem:
wherein, the liquid crystal display device comprises a liquid crystal display device,is an analytical expression form of the data.
(3) To solve this variation problem, a Lagrangian of the form:
(4) UpdatingAnd->From the updated values obtained, u can be calculated k (t) and the magnitude of the center frequency, whereby decomposed individual signal components can be obtained. The further update mode is:
the update frequency is:
extracting time domain features: after adopting HHT method, the change characteristic of EEG signal in time direction can be obtained by analyzing component characteristic, and the instantaneous energy Hu can be obtained according to the instantaneous amplitude of IMF k (t)]Information on the frequency domain and amplitude variations can be obtained:
U k (t)＝u k (t)+jH[u k (t)] (8)
calculating an energy amplitude value for the sampled signal:
wherein n is the number of sampling points,is the magnitude of the discrete signal i. The average instantaneous energy value reflects the change of the signal in the time domain and is denoted as F 1 。
Nonlinear dynamics characteristics: introducing information difference and analysis signal complexity of the multi-scale entropy observation signal in multiple modes, sampling the decomposed IMF function to obtain discrete signals of different modes, performing series analysis, averaging and dimension transformation, and finally obtaining a sample entropy value when the time sequence length is M:
SampEn(m,r,M)＝-ln[C m+1 (r)/C m (r)] (10)
repeating the above calculation to obtain entropy features under multiple scales, combining the features to obtain multi-scale entropy features of EEG signals, and marking as F 2 。
CSP airspace characteristics: combining the obtained IMF components with the sampled signals of the components to obtain a signal matrix composed of the total number k of the components and the signals of the sampling points n, namely k multiplied by n as the object of CSP processing, taking the components of C3 and C4 channels as an example, and marking the spatial characteristics as F 3 The matrix thereof can be expressed as:
the third-stage processor combines the extracted multiple feature information, and the obtained multi-modal feature is denoted as f= { F 1 ,F 2 ,F 3 The whole process is shown in fig. 3.To avoid the difference in values of the different features, the extracted features are normalized:
F e ＝(F e -μ e )/σ e ,e＝1,2,3 (12)
wherein mu e 、σ e The mean and standard deviation at the time of characteristic e are shown respectively. And classifying the F which completes the normalized feature. Based on the common representation, an SVM classifier is introduced to obtain a final diagnosis result.
An AD nerve regulation and control method based on feature extraction and closed loop ultrasonic stimulation comprises the following steps:
to evaluate the therapeutic effect of transcranial ultrasound stimulation by control experiments, AD mouse models were used and grouped by the following method: AD mice were randomly divided into 2 groups, including the stimulated group (ADT group), the sham-stimulated group (ADs group), while healthy mice served as the normal control group (WT group). The sham group was prepared by reserving a stimulation area in the motor cortex of AD mice and implanting the electroencephalogram electrode 3 in the hippocampus, but without applying any ultrasonic stimulation.
Step 1, respectively implanting the ultrasonic stimulation module 2 and the electroencephalogram electrode 3 into preset sites of mice in a stimulation group (ADT group), a pseudo stimulation group (ADS group) and a control group (WT group); the preset site is positioned in the brain region of the mouse;
specifically, the mice in the experiment are placed in a gas anesthesia induction box, anesthesia is adjusted to 2.5L/min, and the mice are left for about 2 minutes until the toes of the mice are pinched without leg shrinking reaction. The chloral hydrate with the proportion of 1% is used for realizing surgical anesthesia by intraperitoneal injection according to the weight proportion.
Craniectomy was performed in the motor cortex (AP: -1.54, ML: + -1.5), forming a viewing window for the ultrasound stimulation and implanting a glass plate. The brain electric signal collecting electrode is implanted into the CA1 (AP: 2.06, ML: + -1.5, DV: 1.25) of the Hippocampus, the brain electric electrode for collecting/recording is implanted into the CA1 region of the mouse Hippocampus, and two skull nails are additionally arranged at the nasal bone position for grounding and reference.
Step 2, after all experimental mice implanted with the brain electrode 3 recover for t time, regulating and controlling the output parameters of the ultrasonic stimulation signals of the ultrasonic stimulation module 2 by using the programmable ultrasonic signal generation module 1;
specifically, mice diagnosed with AD were treated after 1 week of recovery, at which time all mice were 5 months of age. The stimulus group mice receive the signals delivered by the stimulus control submodule 54 to the programmable ultrasound signal generating module 1, the programmable ultrasound signal generating module 1 sends the generated stimulus signals to the ultrasound stimulus module 2, and the ultrasound stimulus module 2 emits the stimulus signals in the form of ultrasound stimulus to the viewing window area of the implanted glass sheet.
Step 3, after the ultrasonic transducer of the ultrasonic stimulation module 2 receives the stimulation signal, performing ultrasonic stimulation on the intracranial brain preset site of the experimental mouse;
step 4, acquiring the brain electrical signals recorded on the brain electrical electrodes 3 by using the signal acquisition and processing module 4, sending the processed brain electrical signals to the closed-loop control module 5, and judging whether the experimental mice need to adjust ultrasonic stimulation parameters according to classification results through processing of three-stage serial processors; the signal transmission and storage module 6 receives the brain electrical signals transmitted by the closed-loop control module 5 and stores the brain electrical signals as a data set;
step 5, the upper computer 7 trains parameters of the three-stage serial processor implanted in the closed-loop control module 5 according to the existing data set and communicates with the signal transmission and storage module 6 in real time; various parameters in the three-stage serial processor implanted in the closed-loop control module 5 are continuously updated, and the acquired electroencephalogram signals are displayed in real time;
step 6, according to the judgment result of the step 4, if the stimulation parameters do not need to be adjusted, the step 7 is carried out, otherwise, the step 3 is returned;
step 7, performing Morris water maze experiments on the experimental mice every T period to obtain evaluation indexes of the Morris water maze experiments; the evaluation indexes of the Morris water maze experiment comprise escape latency and escape path length; judging the difference of evaluation indexes of Morris water maze experiments under the interaction of groups and days, if the difference between the time of the third quadrant and the time of other quadrants among the groups is larger than a preset threshold value, finishing regulation, otherwise, modifying ultrasonic stimulation parameters, and returning to the step 3.
Specifically, in order to evaluate the safety of ultrasonic stimulation, ensuring that anxiety-related side effects are not caused, a Morris water maze experiment was designed. And (3) carrying out Morris water maze experiments on the experimental mice every T period to obtain evaluation indexes of the Morris water maze experiments: escape latency and escape path length, analyzing whether the group and day have significant primary effects on the two indicators, and there is a significant difference in group x day interactions; if there is a significant difference between the time in the third quadrant and the time in the other quadrants between the groups, these results indicate that the ADT group can effectively distinguish the quadrant in which the platform is located from the other quadrants, while the remaining groups are inferior in their distinguishing ability. Otherwise, the problem of the stimulation scheme is indicated, and the stimulation parameters can be adjusted.
The Morris water maze (Morris water maze, MWM) comprises a water maze, a computer, a video acquisition card, a CCD camera and other devices. Two virtual vertical lines are arranged in the pool to divide the pool into I, II, III, IV four quadrants, the water inlet point of the mouse is arranged on the pool wall at the midpoint of each quadrant, and a cylindrical visible platform with the diameter of 10cm is arranged at the center of the third quadrant. Proper amount of compound coloring agent is added into water to be prepared into white, so that a behavior analysis system can track the swimming track of a mouse in the experimental process.
The Morris water maze test method for the experimental mice comprises the following steps:
1) Dividing the water maze into 4 areas equally; the water maze is provided with a visible platform positioned above the water surface;
2) Enabling the experimental mice to enter water, wherein the water inlet point is a pool wall at the middle point of each area;
3) The swimming track of the experimental mouse is collected by using a CCD camera and is stored in a video acquisition card;
4) The video acquisition card uploads the swimming track of the experimental mouse to the computer; the computer performs image recognition on the swimming track of the experimental mouse to obtain an evaluation index of the Morris water maze experiment; the escape latency is the time from entry of water to landing of the experimental mice.
In particular, the visible platform extends 1 cm above the water surface. Mice were placed in pools at different quadrant walls. The time it takes the mouse to find and board the visible platform within 60s is recorded as Escape latency (Escape latency). If the mouse does not find the visible platform within 60s, the mouse is guided to the visible platform and placed on the visible platform for 15-20 s, and the escape latency period is recorded to be 60s. At the same time, the path length before the mouse escaped to the visible platform was recorded. If the escape latency and path length of each group were not significantly different, each group of mice was considered to have similar motor and visual abilities.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.
Claims (10)
1. The AD nerve regulation and control system based on feature extraction and closed-loop ultrasonic stimulation is characterized by comprising a programmable ultrasonic signal generation module (1), an ultrasonic stimulation module (2), a signal acquisition and processing module (4), a closed-loop control module (5), a signal transmission and storage module (6), an upper computer (7) and an electroencephalogram electrode (3); the electroencephalogram electrode (3) is connected to an experimental object; the programmable ultrasonic signal generation module (1) sends the generated stimulation signal to the ultrasonic stimulation module (2), and the ultrasonic stimulation module (2) transmits the stimulation signal to the experimental object in an ultrasonic stimulation mode; the signal acquisition and processing module (4) is connected with the electroencephalogram electrode (3) and is used for acquiring the electroencephalogram signals recorded by the electroencephalogram electrode (3), preprocessing and frequency division processing the electroencephalogram signals and sending the processed electroencephalogram signals to the closed-loop control module (5); the system utilizes a transcranial ultrasonic stimulation technology to stimulate a specific area of the cerebral cortex of an experimental object, an electroencephalogram electrode (3) is implanted in a target area, an electroencephalogram signal of the target area is detected in real time, then time domain, nonlinear dynamics and airspace multidimensional features of signals in different frequency bands are extracted, the obtained multidimensional features are used as input of a third-level processor in a closed-loop control module (5), real-time detection is carried out, and parameters of transcranial ultrasonic stimulation are continuously adjusted according to a category diagnosis result so as to inhibit the aggravation of AD of the experimental object.
2. The AD neuromodulation system based on feature extraction and closed loop ultrasound stimulation as claimed in claim 1, wherein the subject selects a mouse, the ultrasound stimulation module (2) is placed in the motor cortex of the mouse, and the electroencephalogram electrode (3) is implanted in the hippocampal CA1 region of the mouse.
3. The AD nerve regulation and control system based on feature extraction and closed-loop ultrasonic stimulation according to claim 1, wherein a three-stage serial processor is implanted in the closed-loop control module (5) and is used for carrying out three-stage processing on the brain electrical signals after frequency division processing by the signal acquisition and processing module (4), and the first-stage processor is a strong classifier and is used for carrying out quick screening on suspected AD brain electrical signals; the screened electroencephalogram signals enter a second-stage processor, multichannel input of signals is realized by adopting a multi-component transformation modal decomposition algorithm in the second-stage processor, time domain features and nonlinear dynamics features of the signals are extracted from signal components obtained by decomposition, meanwhile, the signal components are combined to construct a new signal matrix, and CSP is adopted to extract spatial features of the signal matrix; combining the three obtained features in a third-stage processor to obtain multi-modal features of the EEG signals, and finally classifying by SVM; stopping calculation if the classification result is not the AD abnormal signal, otherwise diagnosing AD aggravation, and sending the diagnosis result to the programmable ultrasonic signal generating module (1) so as to adjust the stimulation parameters in time to achieve the treatment purpose;
the signal transmission and storage module (6) is used for receiving working parameters of each module configured by the upper computer (7) and the brain electrical signals transmitted by the closed-loop control module (5), and storing the brain electrical signals as a data set;
the upper computer (7) is used for training parameters of the three-stage serial processor implanted in the closed-loop control module (5) according to the data set and communicating with the signal transmission and storage module (6) in real time; continuously adjusting working parameters of each module during operation, updating various parameters in a three-stage serial processor implanted in the closed-loop control module (5), and displaying acquired brain electrical signals in real time;
the programmable ultrasonic signal generation module (1) is used for changing the output of ultrasonic stimulation in real time according to the result obtained by the closed-loop control module (5) or the instruction of the upper computer (7).
4. The AD neuromodulation system based on feature extraction and closed loop ultrasound stimulation as in claim 3, wherein the first-stage processor is a strong classifier trained using the Ada Boost algorithm.
5. The AD neuromodulation system based on feature extraction and closed loop ultrasound stimulation of claim 3, wherein the second processor is configured to perform multi-modal feature extraction, wherein the multi-modal data is derived from published AD mouse brain electrical data on the one hand, and from selected set model, pseudo-stimulation and normal control mouse brain electrical data on the other hand.
6. The AD neuromodulation system based on feature extraction and closed loop ultrasound stimulation of claim 3, wherein the components of the plurality of signals in the three-stage serial processor are derived using MVMD methods.
7. An AD neuromodulation system based on feature extraction and closed loop ultrasound stimulation as in claim 3, wherein the step of preprocessing the EEG signal comprises filtering and noise reduction.
8. The AD neuromodulation system based on feature extraction and closed-loop ultrasound stimulation of claim 3, wherein the SVM classifier is capable of testing the test set after training the training set to obtain the classification model.
9. A method of modulating an AD neuromodulation system based on feature extraction and closed loop ultrasound stimulation according to any of claims 1-8, comprising the steps of:
step 1, respectively implanting the ultrasonic stimulation module (2) and the electroencephalogram electrode (3) into preset sites of a plurality of mice; the preset site is positioned in the brain region of the mouse; mice were divided into different stimulation groups;
step 2, after all experimental mice implanted with the brain electrode (3) recover for t time, regulating and controlling the output parameters of the ultrasonic stimulation signals of the ultrasonic stimulation module (2) by using the programmable ultrasonic signal generating module (1);
step 3, after the ultrasonic transducer of the ultrasonic stimulation module (2) receives a stimulation signal, performing ultrasonic stimulation on a preset intracranial brain site of the experimental mouse;
step 4, acquiring the electroencephalogram signals recorded on the electroencephalogram electrodes (3) by utilizing the signal acquisition and processing module (4), sending the processed electroencephalogram signals to the closed-loop control module (5), and judging whether the experimental mice need to adjust ultrasonic stimulation parameters according to classification results through processing of the three-stage serial processors; the signal transmission and storage module (6) receives the brain electrical signals transmitted by the closed-loop control module (5) and stores the brain electrical signals as a data set;
step 5, the upper computer (7) trains parameters of the three-stage serial processor implanted in the closed-loop control module (5) according to the existing data set, and communicates with the signal transmission and storage module (6) in real time; continuously updating various parameters in the three-stage serial processor implanted in the closed-loop control module (5), and displaying the acquired brain electrical signals in real time;
step 6, according to the judgment result of the step 4, if the stimulation parameters do not need to be adjusted, the step 7 is carried out, otherwise, the step 3 is returned;
step 7, performing Morris water maze experiments on the experimental mice every T period to obtain evaluation indexes of the Morris water maze experiments; the evaluation indexes of the Morris water maze experiment comprise escape latency and escape path length; judging the difference of evaluation indexes of Morris water maze experiments under the interaction of groups and days, if the difference between the time of the third quadrant and the time of other quadrants among the groups is larger than a preset threshold value, finishing regulation, otherwise, modifying ultrasonic stimulation parameters, and returning to the step 3.
10. The method for AD neuromodulation based on feature extraction and closed loop ultrasound stimulation of claim 9, wherein the step of performing a Morris water maze test on the experimental mice comprises:
701, equally dividing the water maze into 4 areas; the water maze is provided with a visible platform positioned above the water surface;
702, enabling the experimental mice to enter water, wherein the water inlet point is a pool wall at the middle point of each area;
703, acquiring a swimming track of the organism by using a CCD camera and storing the swimming track in a video acquisition card;
704, uploading the swimming track of the experimental mouse to a computer by the video acquisition card; the computer performs image recognition on the swimming track of the experimental mouse to obtain an evaluation index of the Morris water maze experiment; the escape latency is the time from entry of water to boarding of the visible platform for the experimental mice.
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