CN106823137B - A kind of method and apparatus optimizing neuromodulation - Google Patents
A kind of method and apparatus optimizing neuromodulation Download PDFInfo
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- CN106823137B CN106823137B CN201611258189.XA CN201611258189A CN106823137B CN 106823137 B CN106823137 B CN 106823137B CN 201611258189 A CN201611258189 A CN 201611258189A CN 106823137 B CN106823137 B CN 106823137B
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Abstract
The invention discloses a kind of methods for optimizing cerebral disease neuromodulation, the following steps are included: analog neuron regulation, screening neuromodulation target spot, parameter calibration and parameter optimization, can get optimum treatment target spot and its corresponding Optimal regulation and control parameter setting by the method.The present invention is not only more objective, efficient in judging neuromodulation, the specific aspects such as the outcome prediction, neuromodulation Sites Screening, regulation parameter optimization of individual level can also be applied to, the neuromodulation method for treatment individuation nerve and mental disorder is greatly optimized.
Description
Technical field
The present invention relates to Neuscience, medical image and electromagnetism crossing domains, more particularly to one kind to be based on magnetic resonance brain
Function couples the conversion of spectrum analysis brain network efficiency, and then the method and apparatus for assisting optimization cerebral disease neuromodulation.
Background technique
Modern neuro control technique (such as deep brain stimulation) be used as a kind of effective surgical treatment, have it is minimally invasive,
The characteristics of reversible, adjustability, greatly reduces the disability rate of operation, can be cerebral disease compared with stereotaxis damages operation
Patient provides a kind of new selection.But application of such technology in clinic at present still suffers from very big challenge, treatment side
The formulation of case, including select suitable action target spot, formulate correct surgical planning, ensure accurately target spot positioning and formulate to close
Regulation parameter of reason etc. all will affect the effect for the treatment of.Clinic can only select target by the surgical experience of doctor at present
Point, setting stimulation parameter, lack strong objective basis and support.Since nerve and the mental disorder cause of disease are complicated, patient in addition
There are individual differences, it is intended to carry out clinical treatment to each sufferer individual using general therapeutic scheme, often influence treatment
Effect leads to unpredictable side effect, or even misses the golden hour of patient.Therefore, it is necessary to it is a kind of it is objective, accurate simultaneously
And quantifiable supplementary means come help doctor screening be appropriate for neuromodulation treatment patient, and be its selection optimize
Neuromodulation therapeutic scheme.
In conjunction with advanced mr imaging technique, can construct by node (different brain areas) and side (between each brain area
Association) composition full brain function network.Based on Graph Theory, full brain function map has been widely used in cerebral disease
The fields such as mechanism study, the mechanism of disease treatment and outcome prediction.A large number of studies show that nerve and mental disorder may be
As caused by the dysfunction of the neural circuitry of connection Different brain region, neuromodulation means can be by the mind in brain network
It is adjusted through loop, radiates and reverses the network property of entire brain network to achieve the effect that adjuvant treatment of diseases.
Conspicuousness between the analysis based on nuclear magnetic resonance image data all only assesses two groups in the past statistically is poor
It is different, still, since the individual difference of Neuropsychic diseases is big, and organizes average effect existing method is unable to satisfy and face
Requirement in bed to individual patient disease treatment, practical poor operability.Therefore, being badly in need of providing one kind for cerebral disease patient can
In the method for the optimization neuromodulation that individual level is assessed, the present invention solves this needs.
Summary of the invention
One aspect of the present invention provides a kind of for optimizing the method for cerebral disease neuromodulation, and the method includes following steps
It is rapid:
A) analog neuron regulates and controls；
B) neuromodulation target spot is screened；
C) parameter calibration and parameter optimization；
By the method can get subject's cerebral disease candidate therapeutic target spot and its corresponding candidate regulatory parameter.
Wherein, the method also includes following steps:
Before step a), MR data, the full brain function net connection map of building disease group macroscopic view are acquired；
Before step b), MR data, the full brain function net connection map of building healthy control group macroscopic view are acquired.
In some embodiments of the invention, the subject is individual level or population level.
In some embodiments of the invention, step a) the neuromodulation simulation, comprising the following steps:
A1 the disease group functional network) based on MR data building, carries out linear scale；
A2) straight-forward network corresponding with functional network is obtained using network deconvolution；
A3) the regulation amplitude based on setting carries out neuromodulation on straight-forward network；
A4) straight-forward network after neuromodulation is obtained to the functional network after neuromodulation using network convolution.
In some embodiments of the invention, the step a2) it is obtained and functional network phase using network deconvolution
Corresponding straight-forward network, comprising the following steps:
A21 functional network) is subjected to singular value decomposition；
A22 fractional linear transformation) is carried out to all singular values；
A23 the fractional linear transformation) based on all singular values obtains straight-forward network.
In some embodiments of the invention, step b) the screening neuromodulation target spot is by quantization index screening mind
The regulation of regulated target spot is assessed, comprising the following steps:
B1) the full brain function network of macroscopic view based on MR data building healthy control group carries out population level assessment；
B2) individual level is assessed.
In some embodiments of the invention, the step b1) population level assessment, comprising the following steps:
B11 the disease group average function network matrix and healthy control group before simulating regulation, after simulation regulation) are calculated separately
The similarity of average function network matrix, and the ratio of the calculating simulation regulation front and back similarity is imitated to quantify to measure treatment
Fruit；
B12) regulation intensity (including Optimal regulation and control intensity) is chosen by maximizing therapeutic effect；
B13 target spot) is screened according to therapeutic effect under the regulation intensity (including Optimal regulation and control intensity).
In some embodiments of the invention, step b2) individual level assessment, comprising the following steps:
B21 it) calculates separately before simulating regulation, individual subject's functional network matrix and healthy control group are flat after simulation regulation
The similarity of equal functional network matrix, and the ratio of the calculating simulation regulation front and back similarity treats effect to quantify to measure
Fruit；
B22) regulation intensity (including Optimal regulation and control intensity) is chosen by maximizing therapeutic effect；
B23 target spot) is screened according to therapeutic effect under the regulation intensity (including Optimal regulation and control intensity).
In some embodiments of the invention, step c) parameter calibration and parameter optimization are to combine neuromodulation device, excellent
Change stimulation parameter, comprising the following steps:
C1 the neuromodulation device of magnetic resonance compatible) is built；
C2) calibration of the stimulation parameter to brain network regulation；
C3) according to step b12) or b22), the middle regulation intensity (including Optimal regulation and control intensity) obtained optimizes stimulation parameter.
In some embodiments of the invention, the hardware device that the parameter calibration step needs includes: magnetic resonance
The neuromodulation device of imaging device, magnetic resonance compatible.
In some embodiments of the invention, the step c2) calibration of the stimulation parameter to brain network regulation, packet
Include following steps:
C21) by the magnetic resonance compatible part of neuromodulation device by using magnetic resonance compatible between waveguide introducing magnet
Neuromodulation device, by the full brain function magnetic resonance data acquisition synchronous with stimulation, in functional MRI data acquisition
Different phase is arranged different frequency of stimulation, voltage magnitude, pulse width parameter combination, obtains corresponding brain function network square
Battle array；
C22 the corresponding relationship between incentive condition combination and network regulation intensity) is established, realizes parameter calibration.
In some embodiments of the invention, the step c3) according to step b12) or b22) in the regulation that obtains
Intensity (including Optimal regulation and control intensity) optimizes stimulation parameter, comprising the following steps:
C31 the candidate targets screened in neuromodulation target spot) are screened according to the step b), can be obtained for every
The regulation intensity (including Optimal regulation and control intensity) of a target spot；
C32) comparison candidate network regulates and controls intensity, in the corresponding relationship calibrated, finds incentive condition combination (including most
Excellent incentive condition combination), it feeds back to regulation device and carries out parameter optimization.
It is special another aspect provides a kind of device of the relevant cerebral disease therapy target of screening neuromodulation
Sign is, described device use as it is preceding it is any as described in the method for optimization cerebral disease neuromodulation carry out screening neuromodulation phase
The cerebral disease therapy target of pass.
It is special another aspect provides a kind of device of the relevant cerebral disease therapy target of screening neuromodulation
Sign is that described device includes:
Analog neuron regulates and controls module and regulation outcome evaluation module；
Wherein, the neuromodulation module is used for the analog neuron regulation on the basis of network connection of macroscopical brain function；Institute
Regulation outcome evaluation module is stated to be used to go out neuromodulation therapy target by quantifying index screening；
Described device can be used for screening neural and regulate and control relevant cerebral disease therapy target.
Wherein, described device further include:
Magnetic resonance data acquisition and functional network construct module,
Wherein, the magnetic resonance data acquisition and functional network building module are based on MR data constructing function network
Matrix.
In some embodiments of the invention, the function network in the magnetic resonance data acquisition and functional network building module
Network includes disease group functional network and healthy control group functional network.
In some embodiments of the invention, the subject is individual level or population level.
In some embodiments of the invention, analog neuron regulation module includes:
Linear scale unit, network warp product unit, neuromodulation unit and network convolution unit；
Wherein, the linear scale unit is the pre-treatment step for network Deconvolution Algorithm Based on Frequency；The network is anti-
Convolution unit is for obtaining straight-forward network corresponding with functional network；The neuromodulation unit, is based on setting
Regulation strength range carries out bilateral neuromodulation to each target spot on straight-forward network；The network convolution unit, is to be used for
Straight-forward network after neuromodulation is obtained to the functional network after neuromodulation using network convolution；
Wherein, the linear scale is progress after the disease group functional network based on MR data building.
In some embodiments of the invention, the network warp product unit, comprising:
First singular value decomposition unit, first fractional linear transformation's unit and straight-forward network obtaining unit；
Wherein, the first singular value decomposition unit, is that functional network is carried out singular value decomposition；Described first point
Formula linear transform unit is to carry out fractional linear transformation to all singular values；The straight-forward network obtaining unit, is to be based on
The fractional linear transformation of all singular values obtains straight-forward network.
In some embodiments of the invention, the network convolution unit, comprising:
Second singular value decomposition unit, second fractional linear transformation's unit and functional network obtaining unit；
Wherein, the second singular value decomposition unit is that the straight-forward network after neuromodulation is carried out singular value decomposition；
Second fractional linear transformation's unit is to carry out fractional linear transformation to all singular values；The functional network obtains
Unit is obtained, is that the fractional linear transformation based on all singular values obtains the functional network after neuromodulation.
It in some embodiments of the invention, further comprise regulation outcome evaluation module, the regulation outcome evaluation mould
Block includes:
Population level assessment unit and individual level assessment unit；
Wherein, the regulation outcome evaluation is that the full brain Macro-Functions network matrix based on healthy control group carries out.
In some embodiments of the invention, the population level assessment unit, comprising:
Population level quantitative evaluation unit, regulation intensity (including Optimal regulation and control intensity) acquiring unit and target spot effect prediction
Unit；
Wherein, the population level quantitative evaluation unit is to calculate separately simulation to regulate and control forward and backward disease group average function net
The similarity of network matrix and healthy control group average function network matrix, and the ratio of the calculating simulation regulation front and back similarity
Value come quantify measure therapeutic effect；Described regulation intensity (including the Optimal regulation and control intensity) acquiring unit is controlled by maximizing
Therapeutic effect chooses regulation intensity (including Optimal regulation and control intensity)；The target spot effect prediction unit is in the regulation intensity
Therapy target is screened according to therapeutic effect under (including Optimal regulation and control intensity).
In some embodiments of the invention, the individual level assessment unit, comprising:
Individual level quantitative evaluation unit, regulation intensity (including Optimal regulation and control intensity) acquiring unit and target spot effect prediction
Unit；
Wherein, the individual level quantitative evaluation unit is to calculate separately simulation to regulate and control forward and backward individual patient function network
The similarity of network matrix and healthy control group average function network matrix, and the ratio of the calculating simulation regulation front and back similarity
Value come quantify measure therapeutic effect；Described regulation intensity (including the Optimal regulation and control intensity) acquiring unit is controlled by maximizing
Therapeutic effect chooses regulation intensity (including Optimal regulation and control intensity)；The target spot effect prediction unit is in the regulation intensity
Target spot is screened according to therapeutic effect under (including Optimal regulation and control intensity).
The present invention also provides a kind of devices for optimizing neuromodulation therapeutic scheme, which is characterized in that described device includes:
The neuromodulation device of foregoing heretofore described device and magnetic resonance compatible；
Wherein, foregoing heretofore described device is used to screen the target spot of candidate therapeutic cerebral disease；The magnetic
The compatible neuromodulation device of resonance is used for parameter calibration and parameter optimization.
In the present invention, the cerebral disease includes: juvenile's self-closing disease, middle aged disturbance of emotion class disease, old neurological
Property disease.
Wherein, the middle aged disturbance of emotion class disease includes depression, obsessive-compulsive disorder, addiction, apositia.
Wherein, the old neurodegenerative disease includes Parkinson, Alzheimer disease.
Advantageous effect of the invention
The present invention is based on magnetic resonance brain functions to couple map, parses brain network efficiency transformation rule, can simulate specific brain regions
The partial result and global effect of area's neuromodulation can quantify total brought by neuromodulation for nerve and mental disorder
The factors such as difference, benefit and risk can also advanced optimize regulation parameter in conjunction with neuromodulation equipment, compared in the past only according to
It is more objective, efficient by the method for experience.This hair is used under the premise of not by any clinical priori by pre-stage test
Bright method accurately has found the optimal target spot (globus pallidus) for the treatment of Parkinson's disease, the result with current clinical treatment Parkinson's disease
It is very consistent.Cerebral disease, such as juvenile's self-closing disease, the middle aged disturbance of emotion class disease (depression, obsessive-compulsive disorder, addiction, anorexia
Disease) and old neurodegenerative disease (Parkinson, Alzheimer disease) etc., it is to recognize since neural circuitry is extremely caused
The obstacles such as know, feel, moving.These diseases are usually along with the dysfunction of cerebral nerve loop.Treatment to such disease
It needs by integrally-regulated to neural circuitry progress, to restore the normal function operating of brain network, and then reaches healing disease
The effect of disease.Therefore, the method through the invention, by constructing function network after magnetic resonance imaging, by analog neuron tune
Control, screening neuromodulation target spot, parameter calibration and parameter optimization, equally applicable the method in above-mentioned disease.Exist at present
The method of the present invention is used in obsessive-compulsive disorder case, the candidate targets filtered out concentrate on Basal ganglia, this and clinic commonly use therapy target
(corpus straitum, nucleus accumbens septi) more coincide, and can prove that this method has general applicability in above-mentioned cerebral disease.Therefore, of the invention
The understanding for neuromodulation mechanism can not only be deepened, outcome prediction, the neuromodulation target of individual level can also be applied to
Point screening, regulation parameter optimization etc., greatly optimize the neuromodulation scheme for treatment Neuropsychic diseases, suitable
The trend for having answered the accurate medical treatment of individuation, thus the society that preferably promotes the well-being of mankind.Based on the above issues, the present invention provides one kind
Optimize the method and apparatus of cerebral disease neuromodulation therapeutic scheme.The present invention can deepen researcher for neuromodulation mechanism
Understand, and has a very wide range of applications prospect for the neuromodulation therapeutic scheme for optimizing cerebral disease.More importantly
Compared with group averaging analysis method in the past, the method can apply to ontoanalysis, to reach the personalized mesh precisely treated
's.
Detailed description of the invention
Fig. 1 shows idea of the invention figure.
Fig. 2 shows the main flows of the method for optimization cerebral disease neuromodulation of the invention.
Fig. 3 shows the refined flow chart of step a) as shown in Figure 2.
Fig. 4 shows the refined flow chart of step b) as shown in Figure 2.
Fig. 5 shows the refined flow chart of step c) as shown in Figure 2.
Fig. 6 shows step b1 as shown in Figure 4) refined flow chart.
Fig. 7 shows step b2 as shown in Figure 4) refined flow chart.
Fig. 8 shows step c2 as shown in Figure 5) refined flow chart.
Fig. 9 shows step c3 as shown in Figure 5) refined flow chart.
Figure 10 shows the specific flow chart of the method for optimization cerebral disease neuromodulation.
Figure 11: the acquisition schematic diagram of curve graph and Optimal regulation and control intensity that difference regulation intensity influences curative effect, wherein
HIP represents hippocampus, PUT represents shell core, PAL represents beans shape globus pallidus, THA represents hypothalamus, and the abscissa of curve graph is regulation
Intensity (%), ordinate are curative effect evaluations.
Figure 12: outcome prediction figure of the present invention to all brain areas as Parkinson's disease neuromodulation therapy target.
Figure 13: curative effect of the present invention in individuation level to all brain areas as Parkinson's disease neuromodulation therapy target
Prognostic chart.Ordinate is patient number, and abscissa is each brain area, and the number in chart represents each brain area and makees in individual patient
For potential target spot sequence (such as: 1 represent according to simulation calculate prediction optimal target spot, and so on.).
Figure 14: magnetic resonance compatible neuromodulation device figure of the present invention.
Specific embodiment
Below by specific embodiment and experimental data, the present invention is further illustrated.Although for clear mesh
, proprietary term is used below, but these terms are not meant to define or limit the scope of the invention.
As used herein, term " MR data " refers to the image number scanned using mr imaging technique
According to.
As used herein, term " functional network ", also referred to as " functional network connection map " refer to and utilize magnetic resonance
It scans the functional image under obtained subject quiescent condition and extracts the time of the magnetic resonance signal of each brain area in conjunction with Partition Mask
Then sequence does mutually the function connects network for each brain area composition of full brain that Pearson's linear correlation obtains.
As used herein, term " network deconvolution " is referred to (including is directly connected to and indirectly from the network observed
Connection) it sets out to obtain the mathematical method of straight-forward network (being only directly connected to).
As used herein, term " network convolution " is referred to (including is directly connected to and in succession from the network observed
Connect) it sets out to obtain the mathematical method of straight-forward network (being only directly connected to)." network deconvolution " and " network convolution " is reciprocal.
As used herein, term " straight-forward network ", which refers to, only is directly connected to not include the network being indirectly connected with.
As used herein, term " singular value decomposition " refers to a kind of important matrix decomposition in linear algebra
(Singular Value Decomposition), is the popularization of normal matrix unitarily diagonalizable in matrix analysis.
As used herein, term " fractional linear transformation " refers to such as and with the linear of fraction.
As used herein, term " neuromodulation " is high-end applications of the ganglioside GM_3 technology in neuroscience field,
It is using implantable or non-implantable technology, using physical means (such as electro photoluminescence, Neural stem cell) or the pharmaceutical means (plant of micro pump
Enter) change nervous centralis, peripheral nerve or autonomic nerves system activity to improve life matter the symptom that improves patient groups
The biomedical engineering technology of amount.For traditional brain is damaged with resection operation, its Special attention will be given to is regulation,
It is exactly that the process is reversible, treatment parameter can be adjusted in vitro.
It is used herein, term " cerebral disease ", also referred to as " nerve and mental disorder " refers to due to neural circuitry
Abnormal caused cognition, feeling, dyskinesia etc., such as (depression is forced for juvenile's self-closing disease, middle age disturbance of emotion class disease
Disease, addiction, apositia) and old neurodegenerative disease (Parkinson, Alzheimer disease) etc..Body is normally neural
Loop is the inherent balance system (i.e. normal brain network) being made of electro photoluminescence and chemical signal, but disease (including
Factor congenital and posteriority) break this balance, so as to cause feeling, movement or cognition, impaired (i.e. brain network is different
Often).Although the cause of disease of these diseases is complicated, there is a general character, i.e., usually along with the dysfunction of cerebral nerve loop.
The treatment of such disease is needed by integrally-regulated to neural circuitry progress, to restore the normal function fortune of brain network
Turn, and then achievees the effect that cure disease.Therefore, based on " neuromodulation means can be by the neural circuitry in brain network
It is adjusted, radiates and reverses the network property of entire brain network to achieve the effect that adjuvant treatment of diseases." this science vacation
If can be effective that is, by physics (electricity, magnetic etc.) means intervention to appropriate target spot in conjunction with domestic and international a large amount of clinical evidence
Treat above-mentioned cerebral disease.The method of the invention can be directed to above-mentioned cerebral disease, be carried out by constructing function net connection map
The screening of candidate therapeutic target spot and the parameter optimization of neuromodulation.Method i.e. of the invention not instead of disease treatment method is waited
The method for selecting the screening of therapy target and the parameter optimization of neuromodulation.
It is used, term " target spot ", also referred to as " brain area target spot ", is referred to according to different function and anatomical structure pair herein
The subregion that brain carries out, including cortex, deep nuclei, these brain areas are related to neuromodulation, including but not limited to described in table 1
Brain partition information.
Experimental method in following embodiments is unless otherwise specified conventional method.Device used in it, material,
Reagent etc. can be bought from commercial channels unless otherwise specified.
Specific embodiment
The group method of the optimization cerebral disease neuromodulation of embodiment 1
After the detailed description for reading embodiment of the disclosure in conjunction with the following drawings, it better understood when of the invention
Features described above and advantage.In the accompanying drawings, each component is not necessarily drawn to scale, and has similar correlation properties or feature
Component may have same or similar appended drawing reference.
Fig. 1 shows the general conception of this patent.Neuromodulation mould based on proposition simulation from local diffusion to overall network
Type, each patient is carried out analog neuron regulation (subgraph A) first by us.The full brain of patient after the regulation being then based on
The functional network of functional network and healthy control group, the quantitative evaluation regulating effect on population level and individual level, thus
It chooses target for modulation (subgraph B).
Fig. 2 shows the broad flow diagram of presently preferred embodiments of the present invention, detailed step is as follows:
One, on the basis of macroscopical brain function couples map, analog neuron regulation
1, it is constructed based on MR data wait regulate and control a group functional network
Briefly, full brain Macro-Functions network is constructed using pretreated functional MRI data.
Wherein, specific pretreatment process includes preceding ten time points for removing data；To each image different scanning layer
Time difference be corrected；Function image is registrated to structural images and is normalized in normed space；Use linear regression
Remove spatial movement artifact；Remove the breathing of low frequency and high frequency and the noise of heart.Later, using standard brain map template extraction
The average time sequence of full brain subregion (not including cerebellum).By the Pearson correlation building for calculating each brain area time series
Full brain function connects map.
2, linear scale
Wherein, all network matrixes including patient and normal healthy controls are ensured into subsequent network multiplied by zoom factor α
Deconvolution Method can convergence.
The determination method of α is as follows:
For each network matrix, α need to meet inequality:Here λ+And λ-Point
Not thus after Singular Value Decomposition Using maximum absolute value positive feature and negative feature value.β is to think determining parameter, this parameter
Setting range be greater than 0 be less than or equal to 1 (0 β≤1 <), preferably 0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,
1.0.Then, the α value for meeting inequality above is found.
3, straight-forward network corresponding with functional network is obtained using network deconvolution
1) functional network is subjected to singular value decomposition first.
Functional network is represented with F, D represents straight-forward network, F=U ∑ VT, wherein UUT=I, VTV=I, and ∑=diag
(λ1, λ2..., λn)。
Then, fractional linear transformation is carried out to all singular values.
Following fractional linear transformation is to all singular values:
Finally, the fractional linear transformation based on all singular values obtains straight-forward network.
Straight-forward network can be expressed as D=USVT。
4, it is directed to each target for modulation, the regulation amplitude based on setting carries out neuromodulation on straight-forward network
The step be straight-forward network D is done regional area neuromodulation simulate and simulate be all left and right bilateral simultaneously
Neuromodulation.I.e. for some brain area i to be regulated and controled, the left brain area in left side is 2 × i-1, and right side is 2 × i.That
When carrying out neuromodulation, to 2 × i-1 row of D matrix, 2 × i-1 column, 2 × i row and 2 × i row are respectively multiplied by certain
A number x, x × 100% are to regulate and control intensity.It here will be under all regulation intensity of each brain area in a certain range
Carry out regulation simulation.
5, the straight-forward network after neuromodulation is obtained to the functional network after neuromodulation using network convolution
Wherein, the straight-forward network after neuromodulation is subjected to singular value decomposition first.
D=USVT, wherein UUT=I, VTV=I, and S=diag (η1, η2..., ηn)。
Then, fractional linear transformation is carried out to all singular values:
Finally, the fractional linear transformation based on all singular values obtains the functional network after neuromodulation: F=U ∑ VT。
Two, the neuromodulation therapy target filtered out respectively by quantizating index in group and individual level is (including optimal
Neuromodulation therapy target)
1, the functional network of the full brain macroscopic view of normal healthy controls is constructed
The specific process flow of MR data is identical as disease group, and the object only analyzed is normal healthy controls.
Wherein, full brain Macro-Functions network is constructed using pretreated functional MRI data.
Specific pretreatment process includes preceding ten time points for removing data；To the time of each image different scanning layer
Difference is corrected；Function image is registrated to structural images and is normalized in normed space；It is removed using linear regression empty
Between motion artifacts；Remove the breathing of low frequency and high frequency and the noise of heart.Later, using the full brain of standard brain map template extraction point
The average time sequence in area's (not including cerebellum).Pearson correlation by calculating each brain area time series constructs full brain function
Map can be connected.
2, predicted treatment target spot and its curative effect on population level
1) quantitative evaluation is carried out to the curative effect of simulation regulation on population level
The functional network matrix of the functional network matrix of the disease group before regulation and healthy control group is put down respectively first
, that is, be directed to each group, will organize in all individuals functional network matrix be added after divided by organize in number, obtain group averagely a square
Battle array.The similarity of the averaging network matrix of the averaging network matrix and healthy control group of disease group before calculating regulation.Similarity
Circular it is as follows: by the upper triangular portions of two matrixes according to column vector, then calculate the Pearson of two vectors
Correlation, this value are the similarity of the quantization of the two matrixes.
Then Quantified therapy effect: the disease group after the simulation regulation obtained for some target spot under a certain regulation intensity
Network matrix be averaged.The similarity of the mean matrix of mean matrix and healthy control group after calculating simulation regulation.By this
The similarity of similarity and the first step, which is divided by, is calculated the opposite variation with the similarity of proper network matrix of regulation front and back.Phase
Regulate and control the therapeutic effect of the quantization of this target spot under intensity thus like the opposite variation of degree.
Under different target spots use different regulation intensity recurring quantization therapeutic effects the step for, finally obtain for
In modification scope it is all regulation intensity under all target spots therapeutic effect.
2) regulation intensity (including Optimal regulation and control intensity) is selected according to quantitative evaluation
For each target spot, the regulation intensity for selecting to obtain optimum therapeuticing effect is as Optimal regulation and control intensity.
3) target spot is ranked up and is screened according to the curative effect of target spot each under Optimal regulation and control amplitude
Therapeutic effect of all target spots under Optimal regulation and control intensity is ranked up, first place is filtered out and is controlled as what is recommended
Target spot is treated, first 5 are used as potential therapy target.
3, individuation predicted treatment target spot and its curative effect
1) quantitative evaluation is carried out to the curative effect of simulation regulation in individual level
The functional network matrix of healthy control group is averaged first, the functional network matrix of the individual patient before calculating regulation
With the similarity of the averaging network matrix of healthy control group.The circular of similarity is as follows: by upper the three of two matrixes
Then angle part calculates the pearson correlation value of two vectors according to column vector, this value is the similar of the quantization of the two matrixes
Degree.
Then, for some target spot under a certain regulation intensity, the function network of the individual patient after calculating simulation regulation
The similarity of network matrix and the mean matrix of healthy control group.The similarity of this similarity and the first step is divided by, tune is calculated
The opposite variation with the similarity of proper network matrix of control front and back.The opposite variation of similarity regulates and controls this target spot under intensity thus
Quantization therapeutic effect.
Under different target spots use different regulation intensity recurring quantization therapeutic effects the step for, finally obtain for
In modification scope it is all regulation intensity under all target spots therapeutic effect.
2) regulation intensity (including Optimal regulation and control intensity) is selected according to quantitative evaluation
For each target spot, the optimal regulation intensity of the effect that obtains medical treatment is selected as Optimal regulation and control intensity.
3) target spot is ranked up and screens (step b) 33) according to the curative effect of target spot each under Optimal regulation and control amplitude
Therapeutic effect of all target spots under Optimal regulation and control intensity is ranked up, first place is filtered out and is controlled as what is recommended
Target spot is treated, first 5 are used as potential therapy target.
Three, in conjunction with neuromodulation device, optimize stimulation parameter
1, the neuromodulation device of magnetic resonance compatible is built
The hardware device for needing to be related to includes: the neuromodulation device of MR imaging apparatus, magnetic field compatibility.Concrete operations
When, between needing the magnetic resonance compatible part of neuromodulation equipment introducing magnet by waveguide, and in functional MRI number
While according to acquisition, implement stimulation.
2, calibration of the stimulation parameter to brain network regulation
1) it is obtained using the stimulating apparatus of magnetic resonance compatible by the full brain function magnetic resonance data acquisition synchronous with stimulation
Obtain brain function network matrix under the conditions of different stimulated (including frequency of stimulation, voltage magnitude, pulse width)
To equipment adjustable parameter, including frequency, amplitude, pulsewidth etc., certain combination is set, which should follow safety
Effectively, it is evenly distributed, has the characteristics that regional representativeness.
2) corresponding relationship between incentive condition combination and network regulation intensity is established, realizes calibration
It is deduced to obtain calculated value according to measured value when calibration, to realize the brain network tune for covering entire adjustable parameter range
Controlling intensity corresponding relationship, it is strong can to inquire its effect in brain network that is, under the guide of any adjustable parameter combination
Degree.
3, stimulation parameter is optimized according to regulation intensity (Optimal regulation and control intensity)
1) in above-mentioned predicted treatment target spot step, the Optimal regulation and control intensity for each target spot can be obtained
2) comparison optimal network regulates and controls intensity, in the corresponding relationship calibrated, finds optimal incentive condition combination, feedback
Parameter optimization is carried out to stimulating apparatus
According to the optimal target spot that regulation assessment component screens, its corresponding Optimal regulation and control amplitude compares optimal network tune
Intensity is controlled, in the corresponding relationship calibrated, optimal incentive condition combination is found, feeds back to stimulating apparatus and carry out parameter optimization.
Above-mentioned steps through the invention finally can get optimum treatment target spot and its corresponding Optimal regulation and control parameter setting.
The present invention can not only deepen the understanding for neuromodulation mechanism, can also apply to outcome prediction, the nerve of individual level
Target for modulation screening, regulation parameter optimization etc., greatly optimize the neuromodulation for treatment nerve and mental disorder
Scheme has complied with the trend of the accurate medical treatment of individuation, thus the society that preferably promotes the well-being of mankind.
The detailed process of the optimization cerebral disease neuromodulation of embodiment 2
The link of the present embodiment includes: magnetic resonance data acquisition link 1, functional network building link 2, neuromodulation simulation
Link 3, regulation assessment component 4, parameter calibration link 5, parameter optimization link 6；The device of the present embodiment is related to: magnetic resonance is set
Standby, neuromodulation device.Figure 10 shows the flow chart of entire embodiment.Particular content includes:
Magnetic resonance data acquisition link 1:
For obtaining the magnetic resonance raw data of building brain function network.It briefly, is obtained using magnetic resonance imaging
Full brain structural images and tranquillization state functional MRI data.Specifically, subject will lie low in magnetic in data acquisition
Some sponge fillers will be placed on resonance image-forming is scanning bed, between head and coil to reduce the puppet of image caused by head movement
Shadow, and the influence for configuring earplug to reduce noise of equipment to subject.The image of acquisition includes: conventional positioning picture, high-resolution
Anatomical structure picture closes for analyzing the tranquillization state functional MRI of brain network function connection in this demands subject
Eye keeps awake resting state, without specific regular thinking activities.
Functional network constructs link 2:
For constructing the functional network of disease group, healthy control group.Briefly, using pretreated functional MRI
Data construct full brain Macro-Functions network.Specific pretreatment process includes preceding ten time points for removing data；To each figure
As the time difference of different scanning layer is corrected；Function image is registrated to structural images and is normalized in normed space；
Spatial movement artifact is removed using linear regression；Remove the breathing of low frequency and high frequency and the noise of heart.Then, using standard brain
The average time sequence of the full brain subregion of map template extraction (not including cerebellum).By the Pierre for calculating each brain area time series
Gloomy correlation constructs full brain function and connects map.
31 step of linear scale:
All network matrixes including patient and normal healthy controls ensure subsequent network deconvolution side multiplied by zoom factor α
Method can convergence.The determination method of α is as follows:
For each network matrix, α need to meet inequality:Here λ+And λ-Point
Not thus after Singular Value Decomposition Using maximum absolute value positive feature and negative feature value.β is to think determining parameter, this parameter
Setting range be greater than 0 be less than or equal to 1 (0 β≤1 <), preferably 0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,
1.0.Then, the α value for meeting inequality above is found.
Important step one of of the linear scale as screening candidate targets method of the present invention, can make after lacking the step
Screening inaccuracy and the reduction of candidate targets conspicuousness etc. at candidate targets influences.
32 step of network deconvolution:
It is to obtain straight-forward network corresponding with functional network using network deconvolution, further comprises the first singular value point
Solution, the first fractional linear transformation, straight-forward network obtain.
First singular value decomposition is that functional network is carried out singular value decomposition.Functional network is represented with F, D represents direct net
Network, F=U ∑ VT, wherein UUT=I, VTV=I, and ∑=diag (λ1, λ2..., λn)。
First fractional linear transformation is to carry out fractional linear transformation to all singular values:
Straight-forward network obtains the fractional linear transformation based on all singular values and obtains straight-forward network, and straight-forward network indicates are as follows: D
=USVT。
33 step of neuromodulation:
It is that the regulation amplitude based on setting carries out neuromodulation on straight-forward network.It more specifically, is to straight-forward network D
The neuromodulation for doing regional area is simulated and what is simulated is all the neuromodulation of left and right bilateral simultaneously.Note will adjust some
The brain area i of control, the left brain area in left side are 2 × i-1, and right side is 2 × i.When so carrying out neuromodulation, to D matrix
Respectively multiplied by the number x of some, x × 100% is to regulate and control by force for 2 × i-1 row, 2 × i-1 column, 2 × i row and 2 × i row
Degree.It here will be to carrying out regulation simulation under all regulation intensity of each brain area in a certain range.
34 step of network convolution:
It is that the straight-forward network after neuromodulation is obtained to the functional network after neuromodulation using network convolution.Further packet
Include the second singular value decomposition, the second fractional linear transformation, functional network acquisition.
Second singular value decomposition is that the straight-forward network after neuromodulation is carried out singular value decomposition:
D=USVTT, wherein UUT=I, VTV=I, and S=diag (η1, η2..., ηn)。
Then fractional linear transformation is carried out to all singular values by the second fractional linear transformation:
Finally, obtaining the function after the fractional linear transformation based on all singular values obtains neuromodulation by functional network
Network: F=U ∑ VT。
Regulate and control outcome evaluation link 4:
Go out optimal neuromodulation target spot by quantifying index screening.The link is divided into population level assessment 41 and individual level
Assessment 42.
Population level assesses 41 steps:
It is predicted treatment target spot and its curative effect on population level.It further comprise population level quantitative evaluation, optimal tune
The acquisition of control amplitude, target spot effect prediction, Sites Screening.
Population level quantitative evaluation is to carry out quantitative evaluation to the curative effect of simulation regulation on population level.Distinguish first
The functional network matrix of the functional network matrix of disease group before regulation and healthy control group is averaged, that is, is directed to each
Group, will organize in all individuals functional network matrix be added after divided by the interior number of group, obtain a group mean matrix.Before calculating regulation
The similarity of the averaging network matrix of the averaging network matrix and healthy control group of disease group.The circular of similarity is such as
Under: by the upper triangular portions of two matrixes according to column vector, then calculate the pearson correlation value of two vectors, this value be this two
The similarity of the quantization of a matrix.
Then, the network matrix of the disease group after the simulation regulation obtained for some target spot under a certain regulation intensity takes
It is average.The similarity of the mean matrix of mean matrix and healthy control group after calculating simulation regulation.By this similarity and first
The similarity of step, which is divided by, is calculated the opposite variation with the similarity of proper network matrix of regulation front and back.The opposite change of similarity
Change the therapeutic effect for regulating and controlling the quantization of this target spot under intensity thus.
Previous step is repeated, the treatment effect for all target spots under regulation intensity all in modification scope is calculated
Fruit.
Optimal regulation and control amplitude obtains, and is to select Optimal regulation and control intensity according to quantitative evaluation.For each target spot, select
The optimal regulation intensity of the effect that obtains medical treatment is as Optimal regulation and control intensity.
Target spot effect prediction is that target spot is ranked up and is screened according to the curative effect of target spot each under Optimal regulation and control amplitude.
Therapeutic effect of all target spots under Optimal regulation and control intensity is ranked up.
Sites Screening will filter out first place as the therapy target recommended, and first 5 are used as potential therapy target.
Individual level assesses 42 steps:
It is predicted treatment target spot and its curative effect on population level.It further comprises individual level quantitative evaluation, optimal
The acquisition of regulation amplitude, target spot effect prediction, Sites Screening.
Individual level quantitative evaluation is to carry out quantitative evaluation to the curative effect of simulation regulation in individual level.
The functional network matrix of healthy control group is averaged first, the functional network matrix of the individual patient before calculating regulation
With the similarity of the averaging network matrix of healthy control group.The circular of similarity is as follows: by upper the three of two matrixes
Then angle part calculates the pearson correlation value of two vectors according to column vector, this value is the similar of the quantization of the two matrixes
Degree.
Then, for some target spot under a certain regulation intensity, the function network of the individual patient after calculating simulation regulation
The similarity of network matrix and the mean matrix of healthy control group.The similarity of this similarity and the first step is divided by, tune is calculated
The opposite variation with the similarity of proper network matrix of control front and back.The opposite variation of similarity regulates and controls this target spot under intensity thus
Quantization therapeutic effect.
Previous step is repeated, all target spots under all regulation intensity are calculated for single patient in modification scope
Therapeutic effect.
Optimal regulation and control amplitude obtains, and is to select Optimal regulation and control intensity according to quantitative evaluation.For each target spot, select
The optimal regulation intensity of the effect that obtains medical treatment is as Optimal regulation and control intensity
Target spot effect prediction is that target spot is ranked up and is screened according to the curative effect of target spot each under Optimal regulation and control amplitude.
Therapeutic effect of all target spots under Optimal regulation and control intensity is ranked up.
Sites Screening will filter out first place as the therapy target recommended, and first 5 are used as potential therapy target.
Parameter calibration link 5:
Corresponding relationship for establishing between neuromodulation device parameter and brain network regulation intensity.What the link needed to be related to
Hardware device includes: the neuromodulation device of MR imaging apparatus, magnetic field compatibility.Concrete implementation example is as follows: will be neural
The magnetic resonance compatible part of adjusting device by waveguide introduce magnet between, functional MRI data acquisition different phase,
Different frequencies, amplitude, width parameter combination are set, to obtain under different parameters facilities, brain network is modulated
Power establishes a parameter combination with this and regulates and controls the corresponding relationship between intensity, realizes parameter calibration.
Parameter optimization link 6:
For determining the most optimized parameter selection treated for individual.Specifically, according to regulation assessment component sieve
Obtained optimal target spot is selected, its corresponding Optimal regulation and control amplitude, comparison optimal network regulates and controls intensity, in the corresponding relationship calibrated
In, optimal incentive condition combination is found, stimulating apparatus is fed back to and carries out parameter optimization.
It finally can get optimum treatment target spot and its corresponding Optimal regulation and control parameter setting through this embodiment.
The outcome prediction and Sites Screening of quantitative evaluation in 3 patient Parkinson of embodiment
Method according to the embodiment 1 completes magnetic resonance data acquisition link 1, function network in patient Parkinson
Network constructs link 2, neuromodulation simulation link 3, regulation assessment component 4, parameter calibration link 5 and parameter optimization link 6.
Figure 11 shows the outcome prediction of quantitative evaluation with the artificial example of Parkinson's disease.There is shown 5 brain areas to adjust
Control the curative effect variation of (- 60%~+60%) in range.The dashed lines labeled position of Optimal regulation and control intensity (is when curative effect-regulation is strong
It writes music regulation intensity value corresponding to curative effect maximum in line).It can be seen that there are maximum for curve, it means that regulation amplitude is deposited
In optimized scope.This meets medicine common sense, and too small regulation does not have too big effect, and excessive regulation is then inevitable
Very more side effects can be caused.
Figure 12 shows the therapeutic effect of each brain area of prediction as the target spot of the neuromodulation of Parkinson's disease, that is,
Therapeutic effect under the Optimal regulation and control intensity of each brain area.Globus pallidus (GP) is optimal target for modulation.The target for modulation of first five
Including hypothalamus (THA), hippocampus (HIP), shell core (PUT) and gyri occipitales superiores (SOG).Wherein brain partition information involved in Figure 12 is detailed
It is shown in Table 1.
Standard brain partition information involved in 1 present invention of table
Figure 13 shows the Sites Screening of the neuromodulation of Parkinson's disease individual human.In figure, each column are a patients,
Every a line is a brain area.Each patient has been marked as the brain area of the target for modulation of first five and has come out, and what number represented is name
It is secondary.It can be seen that globus pallidus (GP) is still optimal target for modulation for most patients, but for a part of disease
Other brain areas and hippocampus in basal ganglia region are also best at least first five target for modulation for people.
4 magnetic resonance compatible neuromodulation device of embodiment
Figure 14 shows magnetic resonance compatible neuromodulation device figure of the present invention.It is illustrated in figure with cartoon graphics formula
Device architecture and the Kane equations of zoopery.Whole device includes four parts altogether: magnetic resonance imaging unit, magnetic resonance number
According to analytical unit, electromagnetic stimulation control unit and magnetic resonance compatible electromagnetic stimulation unit.According to described in the technology of the present invention method
Content, general flow is as follows: firstly, electromagnetic stimulation parameter is arranged by computer control system, via electromagnetic stimulation module,
Electromagnetic stimulation isolator generates specified stimulated current (voltage), introduces magnetic resonance imaging environment by cable after filtering, leads to
Cross magnetic resonance compatible electromagnetic stimulation unit.Then, implement deep brain stimulation, transcranial magnetic stimulation or warp in the specific brain area of animal
Cranium galvanic current stimulation, magnetic resonance imaging unit electromagnetic stimulation simultaneously, acquire corresponding brain function data, and be transmitted to magnetic resonance
Data analysis unit carries out brain network analysis, after a series of electromagnetic stimulation Experiment Parameters, obtains parameter calibration.Finally, root
According to the calibration content, the therapeutic scheme of subsequent individual level disease is instructed to optimize, i.e., technical solution according to the present invention, knot
Optimal target spot and regulation amplitude are closed, it is corresponding to obtain optimal stimulus parameter, and then optimize neuromodulation scheme.
From the above result that it is not difficult to find out that, the present invention constructs brain net on the basis of being based on magnetic resonance configurations, performance data
Network model, is calculated by mathematical model, filter out treatment Parkinson's disease optimal target spot (globus pallidus), this result with face at present
The result of bed treatment Parkinson's disease is very consistent.Cerebral disease, for example, juvenile's self-closing disease, middle aged disturbance of emotion class disease (depression,
Obsessive-compulsive disorder, addiction, apositia) and old neurodegenerative disease (Parkinson, Alzheimer disease) etc., it is due to nerve
The obstacles such as the extremely caused cognition of loop, feeling, movement.These diseases are usually along with the dysfunction of cerebral nerve loop.
The treatment of such disease is needed by integrally-regulated to neural circuitry progress, to restore the normal function fortune of brain network
Turn, and then achievees the effect that cure disease.Therefore, the method through the invention, passes through constructing function net after magnetic resonance imaging
Network, it is equally applicable in above-mentioned disease by analog neuron regulation, screening neuromodulation target spot, parameter calibration and parameter optimization
The method.Use the method for the present invention in obsessive-compulsive disorder case at present, the candidate targets filtered out concentrate on Basal ganglia, this with
Clinic common therapy target (corpus straitum, nucleus accumbens septi) is more coincide, and can be proved that this method has in above-mentioned cerebral disease and generally be fitted
The property used.
This method is without any clinical experience, objective, accurate and quantifiable supplementary means.Therefore,
The present invention can not only deepen the understanding for neuromodulation mechanism, can also apply to outcome prediction, the nerve of individual level
Target for modulation screening, regulation parameter optimization etc., greatly optimize the neuromodulation for treatment nerve and mental disorder
Scheme has complied with the trend of the accurate medical treatment of individuation, thus the society that preferably promotes the well-being of mankind.
More than, it is illustrated based on embodiments of the present invention, but the present invention is not limited thereto, those skilled in the art
Member it should be understood that can be implemented in a manner of carrying out modifications and changes in the range of the purport of the present invention, such deformation and
The mode of change ought to belong to the scope of protection of the present invention.
Claims (13)
1. the device that a kind of screening neural regulates and controls relevant cerebral disease therapy target, which is characterized in that described device packet
It includes:
Analog neuron regulates and controls module and regulation outcome evaluation module；
Wherein, the analog neuron regulation module is used for the analog neuron regulation on the basis of network connection of macroscopical brain function；Institute
Regulation outcome evaluation module is stated to be used to go out neuromodulation therapy target by quantifying index screening；
The analog neuron regulates and controls module
Linear scale unit, network warp product unit, neuromodulation unit and network convolution unit；
Wherein, the linear scale unit is used for the pre-treatment step of network Deconvolution Algorithm Based on Frequency；The network warp product unit is
For obtaining straight-forward network corresponding with functional network；The neuromodulation unit is the regulation strength range based on setting
Bilateral neuromodulation is carried out on straight-forward network to each target spot；The network convolution unit is for will be after neuromodulation
Straight-forward network obtains the functional network after neuromodulation using network convolution；
Wherein, linear scale is carried out after constructing disease group functional network based on tranquillization state functional MRI data.
2. device as described in claim 1, which is characterized in that the network warp product unit, comprising:
First singular value decomposition unit, first fractional linear transformation's unit and straight-forward network obtaining unit；
Wherein, the first singular value decomposition unit, is that functional network is carried out singular value decomposition；The first fraction line
Property converter unit, be that fractional linear transformation is carried out to all singular value；The straight-forward network obtaining unit is based on all
The fractional linear transformation of singular value obtains straight-forward network.
3. device as described in claim 1, which is characterized in that the network convolution unit, comprising:
Second singular value decomposition unit, second fractional linear transformation's unit and functional network obtaining unit；
Wherein, the second singular value decomposition unit is that the straight-forward network after neuromodulation is carried out singular value decomposition；It is described
Second fractional linear transformation's unit, be that fractional linear transformation is carried out to all singular value；The functional network obtains single
Member is that the fractional linear transformation based on all singular values obtains the functional network after neuromodulation.
4. device as described in any one of claims 1-3, which is characterized in that described device further include:
The acquisition of tranquillization state functional MRI data and functional network construct module,
Wherein, the tranquillization state functional MRI data acquisition and functional network building module are based on tranquillization state functional MRI
Data constructing function network matrix.
5. device as claimed in claim 4, which is characterized in that the tranquillization state functional MRI data acquisition and functional network
The functional network constructed in module includes disease group functional network and healthy control group functional network.
6. device as described in any one of claims 1-3, which is characterized in that the subject is individual level or group's water
It is flat.
7. device according to claim 1-3, which is characterized in that the regulation outcome evaluation module includes:
Population level assessment unit and individual level assessment unit；
Wherein, regulation outcome evaluation is that the full brain Macro-Functions network matrix based on healthy control group carries out.
8. device as claimed in claim 7, which is characterized in that the population level assessment unit, comprising:
Population level quantitative evaluation unit, regulation intensity acquiring unit and target spot effect prediction unit；
Wherein, the population level quantitative evaluation unit is before calculating separately simulation regulation, disease group is average after simulation regulation
The similarity of functional network matrix and healthy control group average function network matrix, and calculating simulation regulation front and back is described similar
The ratio of degree come quantify measure therapeutic effect；The regulation intensity acquiring unit is to choose tune by maximizing therapeutic effect
Control intensity；The target spot effect prediction unit is to screen therapy target according to therapeutic effect under the regulation intensity.
9. device as claimed in claim 7, which is characterized in that the individual level assessment unit, comprising:
Individual level quantitative evaluation unit, regulation intensity acquiring unit and target spot effect prediction unit；
Wherein, the individual level quantitative evaluation unit is before calculating separately simulation regulation, simulates individual subject after regulation
The similarity of functional network matrix and healthy control group average function network matrix, and calculating simulation regulation front and back is described similar
The ratio of degree come quantify measure therapeutic effect；The regulation intensity acquiring unit is to choose tune by maximizing therapeutic effect
Control intensity；The target spot effect prediction unit is to screen therapy target according to therapeutic effect under the regulation intensity.
10. device as described in any one of claims 1-3, which is characterized in that the cerebral disease includes: that such as juvenile is self-closing
Disease, middle aged disturbance of emotion class disease, old neurodegenerative disease.
11. device as claimed in claim 10, which is characterized in that the middle aged disturbance of emotion class disease include depression,
Obsessive-compulsive disorder, addiction, apositia.
12. device as claimed in claim 10, which is characterized in that the old neurodegenerative disease include Parkinson,
Alzheimer disease.
13. a kind of device of the relevant cerebral disease therapeutic scheme of optimization neuromodulation, which is characterized in that described device includes:
Such as the neuromodulation device of the described in any item devices of claim 1-9 and magnetic resonance compatible；
Wherein, the described in any item devices of claim 1-9 are for screening the candidate that neural regulates and controls relevant cerebral disease
Therapy target；The neuromodulation device of the magnetic resonance compatible is used for parameter calibration and parameter optimization.
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| CN110432888B (en) * | 2019-08-15 | 2021-11-23 | 任鹏宇 | Screening method of vestibular nerve weight information coding neurons |
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| CN111067522A (en) * | 2019-12-16 | 2020-04-28 | 中国科学院深圳先进技术研究院 | Brain addiction structural map assessment method and device |
| CN111870808A (en) * | 2020-07-27 | 2020-11-03 | 杭州般意科技有限公司 | Intervention method of transcranial direct current stimulation |
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