CN106823137A

CN106823137A - A kind of method and apparatus for optimizing neuromodulation

Info

Publication number: CN106823137A
Application number: CN201611258189.XA
Authority: CN
Inventors: 王征; 陈潇宇
Original assignee: Individual
Current assignee: Chen Xiaoyu; Wang Zheng
Priority date: 2016-12-30
Filing date: 2016-12-30
Publication date: 2017-06-13
Anticipated expiration: 2036-12-30
Also published as: CN106823137B

Abstract

The invention discloses a kind of method for optimizing cerebral disease neuromodulation, comprise the following steps：Analog neuron regulation and control, screening neuromodulation target spot, parameter calibration and parameter optimization, optimum treatment target spot and its corresponding Optimal regulation and control parameter setting can be obtained by methods described.The present invention is not only more objective in neuromodulation is judged, efficient, the specific aspects such as outcome prediction, neuromodulation Sites Screening, the regulation and control parameter optimization of individual level can also be applied to, the neuromodulation method for treatment individuation nerve and mental disorder is greatly optimized.

Description

A kind of method and apparatus for optimizing neuromodulation

Technical field

Magnetic resonance brain is based on the present invention relates to Neuscience, medical image and electromagnetism crossing domain, more particularly to one kind Function connection spectrum analysis brain network efficiency conversion, and then the method and apparatus for aiding in optimization cerebral disease neuromodulation.

Background technology

Modern neuro control technique (such as DBS) as a kind of effective surgical treatment, with it is minimally invasive, The characteristics of reversible, adjustability, compared with stereotaxis damages operation, the disability rate of operation is greatly reduced, can be cerebral disease Patient provides a kind of new selection.But, current application of such technology in clinic 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 and control parameter of reason etc., will all influence the effect for the treatment of.Current clinic can only select target by the surgical experience of doctor Point, setting stimulation parameter, lack strong objective basis and support.Because nerve and the mental disorder cause of disease are complicated, patient in addition There is individual difference, it is intended to clinical treatment is carried out to each sufferer is individual using general therapeutic scheme, often influence treatment Effect, causes unpredictable side effect, or even the golden hour for missing patient.Accordingly, it would be desirable to it is a kind of it is objective, accurate simultaneously And quantifiable supplementary means come help doctor screen be appropriate for neuromodulation treatment patient, and be its selection optimize Neuromodulation therapeutic scheme.

With reference to advanced mr imaging technique, can build by node (different brain areas) and side (between each brain area Association) composition full brain function network.Based on Graph Theory, full brain function collection of illustrative plates has been widely used in cerebral disease The fields such as study mechanism, the mechanism of disease treatment and outcome prediction.Numerous studies show that nerve and mental disorder are probably Caused by due to the dysfunction of the neural circuitry for connecting Different brain region, neuromodulation means can be by the god in brain network It is adjusted through loop, radiates and reverse the network property of whole brain network so as to reach the effect of adjuvant treatment of diseases.

The conspicuousness that the analysis based on nuclear magnetic resonance image data was all simply assessed between two groups on statistical significance in the past is poor It is different, but, because the individual difference of Neuropsychic diseases is big, and average effect is organized so that existing method cannot meet faces Requirement in bed to individual patient disease treatment, actual poor operability.Therefore, be badly in need of for cerebral disease patient provides one kind can The method of the optimization neuromodulation being estimated in individual level, the present invention solves this needs.

The content of the invention

One aspect of the present invention provides a kind of method for optimizing cerebral disease neuromodulation, and methods described includes following step Suddenly：

A) analog neuron regulation and control；

B) neuromodulation target spot is screened；

C) parameter calibration and parameter optimization；

The candidate therapeutic target spot and its corresponding candidate regulatory parameter of subject's cerebral disease can be obtained by methods described.

Wherein, methods described is further comprising the steps of：

Before step a), acquisition of magnetic resonance data builds the full brain function net connection collection of illustrative plates of disease group macroscopic view；

Before step b), acquisition of magnetic resonance data builds the full brain function net connection collection of illustrative plates of healthy control group macroscopic view.

In some embodiments of the invention, the subject is individual level or population level.

In some embodiments of the invention, step a) the neuromodulations simulation, comprises the following steps：

A1) the disease group functional network built based on MR data, carries out linear scale；

A2) straight-forward network corresponding with functional network is obtained using network deconvolution；

A3) the regulation and control amplitude based on setting carries out neuromodulation on straight-forward network；

A4 the straight-forward network after neuromodulation) is obtained into functional network after neuromodulation using network convolution.

In some specific embodiments of the invention, the step a2) obtained and functional network phase using network deconvolution Corresponding straight-forward network, comprises the following steps：

A21 functional network) is carried out into singular value decomposition；

A22 fractional linear transformation) is carried out to all of singular value；

A23) fractional linear transformation based on all singular values obtains straight-forward network.

In some embodiments of the invention, step b) the screenings neuromodulation target spot is by quantifying index screening god The regulation and control assessment of regulated target spot, comprises the following steps：

B1) the full brain Macro-Functions network for building healthy control group based on MR data carries out population level assessment；

B2) individual level assessment.

In some specific embodiments of the invention, the step b1) population level assessment, comprise the following steps：

B11) disease group average function network matrix and healthy control group respectively before calculating simulation regulation and control, after simulation regulation and control The similarity of average function network matrix, and calculate its ratio come quantify weigh therapeutic effect；

B12 regulation and control intensity (including Optimal regulation and control intensity)) are chosen by maximizing therapeutic effect；

B13 target spot) is screened according to therapeutic effect under regulation and control intensity (including Optimal regulation and control intensity).

In some specific embodiments of the invention, step b2) individual level assessment, comprise the following steps：

B21) individual subject's functional network matrix and healthy control group are flat respectively before calculating simulation regulation and control, after simulation regulation and control The similarity of equal functional network matrix, and calculate its ratio and quantify to weigh therapeutic effect；

B22 regulation and control intensity (including Optimal regulation and control intensity)) are chosen by maximizing therapeutic effect；

B23 target spot) is screened according to therapeutic effect under regulation and control intensity (including Optimal regulation and control intensity).

In some embodiments of the invention, step c) parameter calibrations and parameter optimization are to combine neuromodulation device, excellent Change stimulation parameter, comprise 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) in obtain regulation and control intensity (including Optimal regulation and control intensity) optimization stimulation parameter.

In some specific embodiments of the invention, the hardware device that the parameter calibration step needs includes：Magnetic resonance The compatible neuromodulation device in imaging device, magnetic field.

In some specific embodiments of the invention, described step c2) calibration of the stimulation parameter to brain network regulation, bag Include following steps：

C21) by the magnetic resonance compatible part of neuromodulation equipment by between waveguide introducing magnet, using magnetic resonance compatible Stimulating apparatus, by the full brain function magnetic resonance data acquisition synchronous with stimulation, in the difference of functional MRI data collection In the stage, different frequency of stimulation, voltage magnitude, pulse width parameter combination are set, corresponding brain function network matrix is obtained；

C22 the corresponding relation between incentive condition combination and network regulation intensity) is set up, parameter calibration is realized.

In some specific embodiments of the invention, the step c3) according to step b12) or b22) the middle regulation and control for obtaining Intensity (including Optimal regulation and control intensity) optimizes stimulation parameter, comprises the following steps：

C31 the candidate targets that obtain are screened in) screening neuromodulation target spot according to the step b), can be obtained for every The regulation and control intensity (including Optimal regulation and control intensity) of individual target spot；

C32) contrast candidate network regulation and control intensity, in the corresponding relation calibrated, finds incentive condition combination (including most Excellent incentive condition combination), feeding back to stimulating apparatus carries out parameter optimization.

Another aspect provides a kind of device for screening the related cerebral disease therapy target of neuromodulation, it is special Levy and be, described device employ it is preceding it is any as described in optimization cerebral disease neuromodulation method carry out screen neuromodulation phase The cerebral disease therapy target of pass.

Another aspect provides a kind of device for screening the related cerebral disease therapy target of neuromodulation, it is special Levy and be, described device includes：

Analog neuron regulates and controls module and regulation and control outcome evaluation module；

Wherein, the neuromodulation module is used for the analog neuron regulation and control on the basis of macroscopical brain function network connection；Institute Stating regulation and control outcome evaluation module is used to go out neuromodulation therapy target by quantifying index screening；

Described device can be used to screen the related cerebral disease therapy target of neural's regulation and control.

Wherein, described device also includes：

Magnetic resonance data acquisition and functional network build module,

Wherein, it is based on MR data constructing function network that the magnetic resonance data acquisition and functional network build module Matrix.

In some embodiments of the invention, the magnetic resonance data acquisition and functional network build the function network in module Network includes disease group functional network and healthy control group functional network.

In some embodiments of the invention, described analog neuron regulation and control module includes：

Linear scale unit, network warp product unit, neuromodulation unit and network convolution unit；

Wherein, described linear scale unit, is the pre-treatment step for network Deconvolution Algorithm Based on Frequency；Described network is anti- Convolution unit, is for obtaining the straight-forward network corresponding with functional network；Described neuromodulation unit, is based on setting Regulation and control strength range carries out bilateral neuromodulation to each target spot on straight-forward network；Described network convolution unit, be for Straight-forward network after neuromodulation is obtained into the functional network after neuromodulation using network convolution；

Wherein, the linear scale is to be based on being carried out after the disease group functional network that MR data builds.

In some specific embodiments of the invention, described network warp product unit, including：

First singular value decomposition unit, first fractional linear transformation's unit and straight-forward network obtaining unit；

Wherein, the first described singular value decomposition unit, is that functional network is carried out into singular value decomposition；Described first point Formula linear transform unit, is to carry out fractional linear transformation to all of singular value；Described straight-forward network obtaining unit, is to be based on The fractional linear transformation of all singular values obtains straight-forward network.

In some specific embodiments of the invention, described network convolution unit, including：

Second singular value decomposition unit, second fractional linear transformation's unit and functional network obtaining unit；

Wherein, the second described singular value decomposition unit, is that the straight-forward network after neuromodulation is carried out into singular value decomposition； Second described fractional linear transformation's unit, is to carry out fractional linear transformation to all of singular value；Described functional network is obtained Unit is obtained, is that the fractional linear transformation based on all singular values obtains the functional network after neuromodulation.

In some embodiments of the invention, described regulation and control outcome evaluation module, including：

Population level assessment unit and individual level assessment unit；

Wherein, described regulation and control outcome evaluation is that the full brain Macro-Functions network matrix based on healthy control group is carried out.

In some specific embodiments of the invention, the population level assessment unit, including：

Population level quantitative evaluation unit, regulation and control intensity (including Optimal regulation and control intensity) acquiring unit and target spot effect are pre- Survey unit；

Wherein, the population level quantitative evaluation unit, is that calculating simulation regulates and controls forward and backward disease group average function net respectively The similarity of network matrix and healthy control group average function network matrix, and calculate its ratio come quantify weigh therapeutic effect； Described regulation and control intensity (including Optimal regulation and control intensity) acquiring unit, is to choose regulation and control intensity (bag by maximizing therapeutic effect Include Optimal regulation and control intensity)；Described target spot effect prediction unit, is the root under regulation and control intensity (including Optimal regulation and control intensity) Therapy target is screened according to therapeutic effect.

In some specific embodiments of the invention, the individual level assessment unit, including：

Individual level quantitative evaluation unit, regulation and control intensity (including Optimal regulation and control intensity) acquiring unit and target spot effect are pre- Survey unit；

Wherein, described individual level quantitative evaluation unit, is that calculating simulation regulates and controls forward and backward individual patient function network respectively The similarity of network matrix and healthy control group average function network matrix, and calculate its ratio come quantify weigh therapeutic effect； Described regulation and control intensity (including Optimal regulation and control intensity) acquiring unit, is to choose regulation and control intensity (bag by maximizing therapeutic effect Include Optimal regulation and control intensity)；Described target spot effect prediction unit, is the root under regulation and control intensity (including Optimal regulation and control intensity) Target spot is screened according to therapeutic effect.

Present invention also offers a kind of device for optimizing neuromodulation therapeutic scheme, it is characterised in that described device includes：

Foregoing heretofore described device, the neuromodulation device of magnetic resonance compatible；

Wherein, foregoing heretofore described device is used to screen the target spot of candidate therapeutic cerebral disease；The magnetic Resonant device and neuromodulation device are 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, described middle aged disturbance of emotion class disease includes depression, obsession, addiction, apositia.

Wherein, described old nerve degenerative diseases include Parkinson, Alzheimer disease.

The beneficial effect of the invention

The present invention couples collection of illustrative plates based on magnetic resonance brain function, parses brain network efficiency transformation rule, can simulate specific brain regions The partial result and global effect of area's neuromodulation, can be for nerve and mental disorder, and it is total that quantization neuromodulation is brought The factors such as difference, benefit and risk, with reference to neuromodulation equipment, can also further Optimum Regulation parameter, compared in the past only according to It is more objective, efficient by the method for experience.By pre-stage test, on the premise of not by any clinical priori, using this hair Bright method have found the optimal target spot (globus pallidus) for the treatment of Parkinson's, the result with current clinical treatment Parkinson's exactly It is very consistent.Cerebral disease, such as juvenile's self-closing disease, the middle aged disturbance of emotion class disease (depression, obsession, addiction, apocleisis Disease) and old nerve degenerative diseases (Parkinson, Alzheimer disease) etc., it is to recognize because neural circuitry is extremely caused The obstacle such as know, feel, moving.These diseases are generally along with the dysfunction of cerebral nerve loop.Treatment to such disease Need integrally-regulated by carrying out to neural circuitry, so as to recover the normal function operating of brain network, and then reach healing disease The effect of disease.Therefore, by the method for the invention, by constructing function network after magnetic resonance imaging, adjusted by analog neuron Control, screening neuromodulation target spot, parameter calibration and parameter optimization, the equally applicable methods described in above-mentioned disease.Exist at present The inventive method is used in obsession case, the candidate targets for filtering out concentrate on Basal ganglia, this and clinic commonly use therapy target (corpus straitum, nucleus accumbens septi) more coincide, and may certify that this method has general applicability in above-mentioned cerebral disease.Therefore, the present invention The understanding for neuromodulation mechanism can not only be deepened, outcome prediction, the neuromodulation target of individual level can also be applied to The aspects such as point screening, regulation and control parameter optimization, greatly optimize the neuromodulation scheme for treatment Neuropsychic diseases, suitable The trend for having answered individuation precisely medical, so that the society that preferably promotes the well-being of mankind.Based on above mentioned problem, the invention provides one kind The method and apparatus for optimizing cerebral disease neuromodulation therapeutic scheme.The present invention can deepen researcher for neuromodulation mechanism Understand, and had a very wide range of applications prospect for optimizing the neuromodulation therapeutic scheme of cerebral disease.What is more important, Compared with group averaging analysis method in the past, the method can apply to ontoanalysis, so as to reach the mesh of personalized precisely treatment 's.

Brief description of the drawings

Fig. 1 shows idea of the invention figure.

Fig. 2 shows the main flow 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 particular flow sheet of the method for optimizing cerebral disease neuromodulation.

Figure 11：Curve map and the acquisition schematic diagram of Optimal regulation and control intensity that difference regulation and control intensity influences on curative effect, wherein HIP represents hippocampus, PUT and represents shell core, PAL and represent beans shape globus pallidus, THA and represents hypothalamus, and the abscissa of curve map is regulation and control Intensity (%), ordinate is curative effect evaluation.

Figure 12：The present invention to all brain areas as Parkinson's neuromodulation therapy target outcome prediction figure.

Figure 13：The present invention in individuation level to all brain areas as Parkinson's neuromodulation therapy target curative effect Prognostic chart.Ordinate is patient number, and abscissa is each brain area, and each brain area of digitized representation in chart is made in individual patient For potential target spot sequence (such as：1 represents the optimal target spot that prediction is calculated according to simulation, by that analogy.).

Figure 14：Magnetic resonance compatible neuromodulation installation drawing of the present invention.

Specific embodiment

Below by specific embodiment and experimental data, the present invention is further illustrated.Although for clearly mesh , proprietary term has been used below, but these terms are not meant to define or limit the scope of the present invention.

As used herein, term " MR data " refers to the image number obtained using mr imaging technique scanning According to.

As used herein, term " functional network ", also referred to as " functional network connection collection of illustrative plates ", reference utilize magnetic resonance Functional image and combination Partition Mask under the tested quiescent condition that scanning is obtained extract the time of the magnetic resonance signal of each brain area Then sequence does mutually the function connects network of each brain area composition of full brain that Pearson's linear correlation is obtained.

As used herein, term " network deconvolution " is referred to and (including is directly connected to and indirectly from the network observed Connection) setting out obtains the mathematical method of straight-forward network (being only directly connected to).

As used herein, term " network convolution " is referred to and (including is directly connected to and in succession from the network observed Connect) setting out obtains the mathematical method of straight-forward network (being only directly connected to)." network deconvolution " is reciprocal with " network convolution ".

As used herein, term " straight-forward network " refers to and is only 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 " is referred 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 so as to improve the symptom of patient groups, improve life matter The biomedical engineering technology of amount.Damaged with for resection operation relative to traditional brain, its Special attention will be given to is regulation and control, It is exactly that the process is reversible, treatment parameter can be adjusted in vitro.

Used herein, term " cerebral disease ", also referred to as " nerve and mental disorder " refers to due to neural circuitry Abnormal caused cognition, sensation, dyskinesia etc., such as juvenile's self-closing disease, middle age disturbance of emotion class disease (depression, are forced Disease, addiction, apositia) and old nerve degenerative diseases (Parkinson, Alzheimer disease) etc..Body is normally neural Loop is the inherent balance system (i.e. normal brain network) being made up of electro photoluminescence and chemical signal, but disease (including Factor congenital and posteriority) break this balance, so as to cause to feel, move or cognitive impaired (i.e. brain network is different Often).Although the cause of disease of these diseases is complicated, with a general character, i.e., generally along with the dysfunction of cerebral nerve loop. The treatment of such disease is needed it is integrally-regulated by carrying out to neural circuitry, so as to recover the normal function fortune of brain network Turn, and then reach the effect of cure diseases.Therefore, based on " neuromodulation means can be by the neural circuitry in brain network It is adjusted, radiates and reverse the network property of whole brain network so as to reach the effect of adjuvant treatment of diseases." vacation of this science If, with reference to domestic and international substantial amounts of clinical evidence, i.e., by physics (electricity, magnetic etc.) the means intervention to appropriate target spot, can be effective 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 collection of illustrative plates The screening of candidate therapeutic target spot and the parameter optimization of neuromodulation.I.e. the method for the present invention is not methods for the treatment of diseases, but is waited The method for selecting the screening of therapy target and the parameter optimization of neuromodulation.

Used herein, term " target spot ", also referred to as " brain area target spot ", referred to according to difference in functionality and anatomical structure pair The subregion that brain is carried 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 technique in following embodiments, unless otherwise specified, is conventional method.Device wherein used, material, Reagent etc., unless otherwise specified, can buy from commercial channels.

Specific embodiment

Embodiment 1 optimizes the group method of cerebral disease neuromodulation

After the detailed description for reading embodiment of the disclosure in conjunction with the following drawings, better understood when of the invention Features described above and advantage.In the accompanying drawings, each component is not necessarily drawn to scale, and with similar correlation properties or feature Component may have same or like reference.

Fig. 1 shows the general conception of this patent.Based on neuromodulation mould of the proposition simulation from local diffusion to overall network Type, each patient is simulated neuromodulation (subgraph A) by us first.The full brain of the patient being then based on after the regulation and control for obtaining The functional network of functional network and healthy control group, the quantitative evaluation regulating effect on population level and individual level, so that Choose target for modulation (subgraph B).

Fig. 2 shows the broad flow diagram of presently preferred embodiments of the present invention, and detailed step is as follows：

First, on the basis of macroscopical brain function connection collection of illustrative plates, analog neuron regulation and control

1st, built based on MR data and treat regulation and control group functional network

Briefly, full brain Macro-Functions network is built using pretreated functional MRI data.

Wherein, specific pretreatment process includes preceding ten time points of removal data；To each image different scanning layer Time difference be corrected；In being registrated to function image structural images and normalize to normed space；Use linear regression Removal spatial movement artifact；Breathing and the noise of heart of removal low frequency and high frequency.Afterwards, standard brain map template extraction is used The average time sequence of full brain subregion (not including cerebellum).Built by the Pearson correlation for calculating each brain area time series Full brain function connection collection of illustrative plates.

2nd, linear scale

Wherein, all network matrixs including patient and normal healthy controls are multiplied by zoom factor α to ensure follow-up network 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 Wei after this Singular Value Decomposition Using maximum absolute value positive feature and negative feature value.β is the parameter for thinking to determine, this parameter Setting range be more than 0 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 values for meeting inequality above are found.

3rd, the straight-forward network corresponding with functional network is obtained using network deconvolution

1) functional network is carried out into singular value decomposition first.

Functional network is represented with F, D represents straight-forward network,Wherein, And ∑=diag (λ₁, λ₂..., λ_n)。

Then, fractional linear transformation is carried out to all of singular value.

Following fractional linear transformation is done to all of singular value：

Finally, the fractional linear transformation based on all singular values obtains straight-forward network.

Straight-forward network can just be expressed as

4th, for each target for modulation, the regulation and control amplitude based on setting carries out neuromodulation on straight-forward network

The step be the neuromodulation that straight-forward network D does regional area is simulated and simulated be all left and right bilateral simultaneously Neuromodulation.I.e. for some brain area i to be regulated and controled, its 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 rows of D matrix, 2 × i-1 row, 2 × i rows and 2 × i rows are multiplied by certain respectively Individual several x, x × 100% is intensity.Here will be under each brain area all regulation and control intensity within the specific limits Carry out regulation and control simulation.

5th, the straight-forward network after neuromodulation is obtained into the functional network after neuromodulation using network convolution

Wherein, the straight-forward network after neuromodulation is carried out into singular value decomposition first.

WhereinAnd S=diag (η₁, η₂..., η_n)。

Then, fractional linear transformation is carried out to all of singular value：

Finally, the fractional linear transformation based on all singular values obtains the functional network after neuromodulation：

2nd, the neuromodulation therapy target filtered out respectively by quantizating index in colony and individual level is (including optimal Neuromodulation therapy target)

1st, the functional network of the full brain macroscopic view of normal healthy controls is built

The specific handling process of MR data is identical with disease group, and the object simply analyzed is normal healthy controls.

Wherein, full brain Macro-Functions network is built using pretreated functional MRI data.

Specific pretreatment process includes preceding ten time points of removal data；To the time of each image different scanning layer Difference is corrected；In being registrated to function image structural images and normalize to normed space；Removed using linear regression empty Between motion artifacts；Breathing and the noise of heart of removal low frequency and high frequency.Afterwards, the full brain of standard brain map template extraction point is used The average time sequence in area's (not including cerebellum).Full brain work(is built by the Pearson correlation for calculating each brain area time series Collection of illustrative plates can be connected.

2nd, predicted treatment target spot and its curative effect on population level

1) curative effect to simulation regulation and control on population level carries out quantitative evaluation

The functional network matrix of the functional network matrix of the disease group before regulation and control and healthy control group is put down respectively first , i.e., for each group, will organize after interior all individual functional network matrixes are added divided by number in group, obtain a group average square Battle array.Calculate the similarity of the averaging network matrix of the averaging network matrix and healthy control group of the disease group before regulation and control.Similarity Circular it is as follows：By two upper triangular portions of matrix according to column vector, two Pearsons of vector are then calculated Correlation, this value is the similarity of the quantization of the two matrixes.

Then Quantified therapy effect：Disease group after the simulation regulation and control obtained for some target spot under a certain regulation and control intensity Network matrix be averaged.The similarity of the mean matrix of mean matrix and healthy control group after calculating simulation regulation and control.By this Similarity is divided by with the similarity of the first step and is calculated the relative change of the front and rear similarity with proper network matrix of regulation and control.Phase Like degree relative change be this regulate and control intensity under this target spot quantization therapeutic effect.

Under different target spots use different regulation and control intensity recurring quantization therapeutic effects the step for, finally give for The therapeutic effect of all target spots under all regulation and control intensity in modification scope.

2) according to quantitative evaluation selection regulation and control intensity (including Optimal regulation and control intensity)

For each target spot, the regulation and control intensity for obtaining optimum therapeuticing effect is selected as Optimal regulation and control intensity.

3) curative effect according to each target spot under Optimal regulation and control amplitude is ranked up and screening to target spot

Therapeutic effect of all target spots under Optimal regulation and control intensity is ranked up, first place is filtered out as controlling for recommending Target spot is treated, first 5 used as potential therapy target.

3rd, individuation predicted treatment target spot and its curative effect

1) curative effect to simulation regulation and control in individual level carries out quantitative evaluation

It is first that the functional network matrix of healthy control group is average, calculate the functional network matrix of the individual patient before regulation and control With the similarity of the averaging network matrix of healthy control group.The circular of similarity is as follows：By two upper the three of matrix Then angle part calculates two Pearson's correlations of vector according to column vector, and this value is the similar of the quantization of the two matrixes Degree.

Then, for some target spot, the function network of the individual patient after calculating simulation regulation and control under a certain regulation and control intensity The similarity of the mean matrix of network matrix and healthy control group.The similarity of this similarity and the first step is divided by and is calculated tune Relative change before and after control with the similarity of proper network matrix.The relative change of similarity is this target spot under this regulation and control intensity Quantization therapeutic effect.

For each target spot, the regulation and control intensity of the best results that obtain medical treatment is selected as Optimal regulation and control intensity.

3) curative effect according to each target spot under Optimal regulation and control amplitude is ranked up and screening (step b) 33) to target spot

3rd, with reference to neuromodulation device, stimulation parameter is optimized

1st, the neuromodulation device of magnetic resonance compatible is built

The hardware device that needs are related to includes：The compatible neuromodulation device in MR imaging apparatus, magnetic field.Concrete operations When, it is necessary to the magnetic resonance compatible part of neuromodulation equipment is introduced into magnet by waveguide between, and in functional MRI number While according to collection, implement to stimulate.

2nd, calibration of the stimulation parameter to brain network regulation

1) using the stimulating apparatus of magnetic resonance compatible, by the full brain function magnetic resonance data acquisition synchronous with stimulation, obtain Obtain the brain function network matrix of 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, the combination should follow safety Effectively, be evenly distributed, with regional representativeness the features such as.

2) corresponding relation between incentive condition combination and network regulation intensity is set up, calibration is realized

Deduced according to measured value during calibration and obtain calculated value, so as to realize that the brain network for covering whole adjustable parameter scope is adjusted Control intensity corresponding relation, i.e., under the guide of any adjustable parameter combination, can inquire its effect in brain network strong Degree.

3rd, according to regulation and control intensity (Optimal regulation and control intensity) optimization stimulation parameter

1) in above-mentioned predicted treatment target spot step, the Optimal regulation and control intensity for each target spot can be obtained

2) contrast optimal network regulation and control intensity, in the corresponding relation calibrated, finds optimal incentive condition combination, feedback Parameter optimization is carried out to stimulating apparatus

According to the optimal target spot that regulation and control assessment component screening is obtained, its Optimal regulation and control amplitude is corresponded to, contrast optimal network is adjusted Control intensity, in the corresponding relation calibrated, finds optimal incentive condition combination, and feeding back to stimulating apparatus carries out parameter optimization.

By above-mentioned steps of the present invention, optimum treatment target spot and its corresponding Optimal regulation and control parameter setting can be finally obtained. The present invention can not only deepen the understanding for neuromodulation mechanism, can also apply to outcome prediction, the nerve of individual level The aspects such as target for modulation screening, regulation and control parameter optimization, greatly optimize the neuromodulation for treatment nerve and mental disorder Scheme, has complied with the precisely medical trend of individuation, so that the society that preferably promotes the well-being of mankind.

Embodiment 2 optimizes the idiographic flow of cerebral disease neuromodulation

The link of the present embodiment includes：Magnetic resonance data acquisition link 1, functional network builds the simulation of link 2, neuromodulation Link 3, regulation and control assessment component 4, parameter calibration link 5, parameter optimization link 6；The device of the present embodiment is related to：Magnetic resonance sets Standby, neuromodulation device.Figure 10 shows the flow chart of whole embodiment.Particular content includes：

Magnetic resonance data acquisition link 1：

The magnetic resonance raw data of brain function network is built for obtaining.Briefly, it is to be obtained using magnetic resonance imaging Full brain structural images and tranquillization state functional MRI data.Specifically, in data acquisition, subject will lie low in magnetic Some sponge fillers will be placed on resonance image-forming is scanning bed, between head and coil pseudo- to reduce the image that head movement is caused Shadow, and earplug is configured to reduce influence of the noise of equipment to subject.The image of collection includes：Conventional positioning picture, high-resolution Anatomical structure picture, for analyzing the tranquillization state functional MRI of brain network function connection, closes in this demands subject Eye keeps clear-headed resting state, and specific regularity thinking activities are not carried out.

Functional network builds link 2：

Functional network for building disease group, healthy control group.Briefly, pretreated functional MRI is used Data build full brain Macro-Functions network.Specific pretreatment process includes preceding ten time points of removal data；To each figure As the time difference of different scanning layer is corrected；In being registrated to function image structural images and normalize to normed space； Spatial movement artifact is removed using linear regression；Breathing and the noise of heart of removal low frequency and high frequency.Then, standard brain is used The average time sequence of the full brain subregion of collection of illustrative plates template extraction (not including cerebellum).By the Pierre for calculating each brain area time series Gloomy correlation builds full brain function connection collection of illustrative plates.

The step of linear scale 31：

All network matrixs including patient and normal healthy controls are multiplied by zoom factor α to ensure follow-up network deconvolution side Method can convergence.The determination method of α is as follows：

For each network matrix, α need to meet inequality：Here λ+and λ- The positive feature and negative feature value of maximum absolute value respectively after this Singular Value Decomposition Using.β is the parameter for thinking to determine, this parameter Setting range be more than 0 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 values for meeting inequality above are found.

Linear scale can be made as one of important step for screening candidate targets method of the present invention after lacking the step The influences such as inaccurate and candidate targets conspicuousness reduction are screened into candidate targets.

The step of network deconvolution 32：

It is to obtain the straight-forward network corresponding with functional network using network deconvolution, further includes the first singular value point Solution, the first fractional linear transformation, straight-forward network are obtained.

First singular value decomposition is that functional network is carried out into singular value decomposition.Functional network is represented with F, D represents direct net Network,Wherein,And ∑=diag (λ₁, λ₂..., λ_n)。

First fractional linear transformation is to carry out fractional linear transformation to all of singular value：

Straight-forward network obtains the fractional linear transformation based on all singular values and obtains straight-forward network, and straight-forward network is expressed as：

The step of neuromodulation 33：

It is that the regulation and control amplitude based on setting carries out neuromodulation on straight-forward network.More specifically, it is to straight-forward network D Do that the neuromodulation of regional area simulates and simulate is all left and right bilateral neuromodulation simultaneously.Note will be adjusted for some The brain area i of control, its left brain area in left side is 2 × i-1, and right side is 2 × i.When so carrying out neuromodulation, to D matrix 2 × i-1 rows, 2 × i-1 row, 2 × i rows and 2 × i rows are multiplied by the several x of certain respectively, and x × 100% is strong Degree.Here will be to carrying out regulation and control simulation under each brain area all regulation and control intensity within the specific limits.

The step of network convolution 34：

It is that the straight-forward network after neuromodulation is obtained into the functional network after neuromodulation using network convolution.Further wrap 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 into singular value decomposition：

WhereinAnd S=diag (η₁, η₂..., η_n)。

Then fractional linear transformation is carried out to all of singular value by the second fractional linear transformation：

Finally, the function after the fractional linear transformation based on all singular values obtains neuromodulation is obtained by functional network Network：

Regulation and control outcome evaluation link 4：

Go out optimal neuromodulation target spot by quantifying index screening.The link is divided into population level and assesses 41 and individual level Assessment 42.

Population level assesses 41 steps：

It is predicted treatment target spot and its curative effect on population level.Further include population level quantitative evaluation, optimal tune The acquisition of control amplitude, target spot effect prediction, Sites Screening.

Population level quantitative evaluation, is that the curative effect to simulation regulation and control on population level carries out quantitative evaluation.Distinguish first The functional network matrix of the functional network matrix of the disease group before regulation and control and healthy control group is average, i.e., for each Group, will organize after interior all individual functional network matrixes are added divided by number in group, obtain a group mean matrix.Before calculating regulation and control The similarity of the averaging network matrix of disease group and the averaging network matrix of healthy control group.The circular of similarity is such as Under：By two upper triangular portions of matrix according to column vector, then calculate two Pearson's correlations of vector, this value for this two The similarity of the quantization of individual matrix.

Then, the network matrix of the disease group after the simulation regulation and control for being obtained for some target spot under a certain regulation and control intensity takes Averagely.The similarity of the mean matrix of mean matrix and healthy control group after calculating simulation regulation and control.By this similarity and first The similarity of step is divided by and is calculated the front and rear relative change with the similarity of proper network matrix of regulation and control.The relative change of similarity The therapeutic effect of the quantization of this target spot under change as this regulation and control intensity.

Previous step is repeated, is calculated and is controlled curative effect for all target spots under all regulation and control intensity in modification scope Really.

Optimal regulation and control amplitude is obtained, and is to select Optimal regulation and control intensity according to quantitative evaluation.For each target spot, select The regulation and control intensity of the best results that obtain medical treatment is used as Optimal regulation and control intensity.

Target spot effect prediction, is target spot to be ranked up and screening according to the curative effect of each target spot 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 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 includes individual level quantitative evaluation, optimal The acquisition of regulation and control amplitude, target spot effect prediction, Sites Screening.

Individual level quantitative evaluation, is that the curative effect to simulation regulation and control in individual level carries out quantitative evaluation.

Previous step is repeated, all target spots under all regulation and control intensity in the modification scope are calculated for single patient Therapeutic effect.

Optimal regulation and control amplitude is obtained, and is to select Optimal regulation and control intensity according to quantitative evaluation.For each target spot, select The regulation and control intensity of the best results that obtain medical treatment is used as Optimal regulation and control intensity

Parameter calibration link 5：

For setting up the corresponding relation between neuromodulation device parameter and brain network regulation intensity.The link needs what is be related to Hardware device includes：The compatible neuromodulation device in MR imaging apparatus, magnetic field.Concrete implementation example is as follows：By nerve Between the magnetic resonance compatible part of adjusting device introduces magnet by waveguide, in the different phase of functional MRI data collection, Different frequencies, amplitude, width parameter combination are set, so as to obtain under different parameters facilities, brain network is modulated Power, the corresponding relation between a parameter combination and regulation and control intensity is set up with this, realizes parameter calibration.

Parameter optimization link 6：

For determining for the individual the most optimized parameter selection treated.Specifically, according to regulation and control assessment component sieve The optimal target spot that choosing is obtained, corresponds to its Optimal regulation and control amplitude, contrast optimal network regulation and control intensity, in the corresponding relation calibrated In, optimal incentive condition combination is found, feeding back to stimulating apparatus carries out parameter optimization.

Optimum treatment target spot and its corresponding Optimal regulation and control parameter setting can be finally obtained by the present embodiment.

The outcome prediction and Sites Screening of quantitative evaluation in patient Parkinson of embodiment 3

Method according to embodiment 1, completes magnetic resonance data acquisition link 1, function network in patient Parkinson Network builds link 2, neuromodulation simulation link 3, regulation and control 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.Adjusted there is shown 5 brain areas The curative effect change of (- 60%~+60%) in the range of control.The dashed lines labeled position of Optimal regulation and control intensity (be when curative effect-regulation and control by force The regulation and control intensity level write music in line corresponding to curative effect maximum).It can be seen that there is maximum in curve, it means that regulation and control amplitude is deposited In optimized scope.This meets medical science general knowledge, and too small regulation and control do not have too big effect, and excessive regulation and control are then inevitable Very many side effects can be triggered.

Figure 12 shows each brain area of prediction as the therapeutic effect of the target spot of the neuromodulation of Parkinson's, 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).The brain partition information being related in wherein Figure 12 is detailed It is shown in Table 1.

Standard brain partition information involved in the present invention of table 1

Figure 13 shows the Sites Screening of the neuromodulation of Parkinson's individual human.In figure, each row are a patients, It is a brain area per a line.Each patient has been marked out as the brain area of the target for modulation of first five, and digitized representation 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 the optimal at least target for modulation of first five for people.

The magnetic resonance compatible neuromodulation device of embodiment 4

Figure 14 shows magnetic resonance compatible neuromodulation installation drawing of the present invention.Illustrated with cartoon diagram form in figure Device architecture and the Kane equations of zoopery.Whole device includes four parts altogether：Magnetic resonance imaging unit, magnetic resonance number According to analytic 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：First, by computer control system set electromagnetic stimulation parameter, via electromagnetic stimulation module, Electromagnetic stimulation isolator, the stimulating current (voltage) specified of generation, after filtering after magnetic resonance imaging environment is introduced by cable, lead to Cross magnetic resonance compatible electromagnetic stimulation unit.Then, the specific brain area in animal implements DBS, transcranial magnetic stimulation or warp Cranium galvanic current stimulation, magnetic resonance imaging unit simultaneously, gathers corresponding brain function data, and transmit to magnetic resonance in electromagnetic stimulation Data analysis unit carries out brain network analysis, by after a series of electromagnetic stimulation Experiment Parameters, obtaining parameter calibration.Finally, root According to the calibration content, the therapeutic scheme optimization of follow-up individual level disease, i.e., according to technical solutions according to the invention, knot are instructed Optimal target spot and regulation and control amplitude are closed, correspondence obtains optimal stimulus parameter, and then optimizes neuromodulation scheme.

From the above result that being not difficult to find out, the present invention builds brain net on the basis of based on magnetic resonance configurations, performance data Network model, is calculated by Mathematical Modeling, filters out the optimal target spot (globus pallidus) for the treatment of Parkinson's, and this result is faced with present The result of bed treatment Parkinson's is very consistent.Cerebral disease, such as juvenile's self-closing disease, middle aged disturbance of emotion class disease (depression, Obsession, addiction, apositia) and old nerve degenerative diseases (Parkinson, Alzheimer disease) etc., it is due to nerve The obstacles such as the extremely caused cognitive, sensation of loop, motion.These diseases are generally along with the dysfunction of cerebral nerve loop. The treatment of such disease is needed it is integrally-regulated by carrying out to neural circuitry, so as to recover the normal function fortune of brain network Turn, and then reach the effect of cure diseases.Therefore, by the method for the invention, by constructing function net after magnetic resonance imaging Network, it is equally applicable in above-mentioned disease by analog neuron regulation and control, screening neuromodulation target spot, parameter calibration and parameter optimization Methods described.Use the inventive method in obsession case at present, the candidate targets for filtering out concentrate on Basal ganglia, this with The conventional therapy target (corpus straitum, nucleus accumbens septi) of clinic more coincide, and may certify that this method has in above-mentioned cerebral disease and generally fits 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 The aspects such as target for modulation screening, regulation and control parameter optimization, greatly optimize the neuromodulation for treatment nerve and mental disorder Scheme, has complied with the precisely medical trend of individuation, so that 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 to this, those skilled in the art Member it should be understood that can be implemented in the way of being deformed and being changed in the range of purport of the invention, such deformation and The mode of change, ought to belong to protection scope of the present invention.

Claims

1. a kind of method for optimizing cerebral disease neuromodulation, it is characterised in that the described method comprises the following steps：

A) analog neuron regulation and control；

B) neuromodulation target spot is screened；

C) parameter calibration and parameter optimization；

2. the method for claim 1, it is characterised in that methods described is further comprising the steps of：

3. the method for claim 1, it is characterised in that the subject is individual level or population level.

4. the method as described in claim any one of 1-3, it is characterised in that step a) the analog neurons regulation and control, including：

A1) the full brain function net connection collection of illustrative plates of disease group macroscopic view built based on MR data, carries out linear scale；

5. method as claimed in claim 4, it is characterised in that the step a2) obtained using network deconvolution and function network The corresponding straight-forward network of network, it is comprised the following steps：

A21 functional network) is carried out into singular value decomposition；

6. the method as described in claim any one of 1-3, it is characterised in that step b) the screenings neuromodulation target spot is logical The regulation and control assessment for quantifying index screening neuromodulation target spot is crossed, is comprised the following steps：

B1 the full brain Macro-Functions net connection collection of illustrative plates of healthy control group) is built based on MR data, population level is carried out and is commented Estimate；

B2) individual level assessment.

7. method as claimed in claim 6, it is characterised in that the step b1) population level assessment, comprise the following steps：

B11 the disease group average function network matrix and healthy control group) respectively before calculating simulation regulation and control, after simulation regulation and control are average The similarity of functional network matrix, and calculate its ratio come quantify weigh therapeutic effect；

B12) regulation and control intensity is chosen by maximizing therapeutic effect；

B13 therapy target) is screened according to therapeutic effect under the regulation and control intensity.

8. method as claimed in claim 6, it is characterised in that step b2) individual level assessment, comprise the following steps：

B21 the individual subject's functional network matrix and healthy control group) respectively before calculating simulation regulation and control, after simulation regulation and control are average The similarity of functional network matrix, and calculate its ratio come quantify weigh therapeutic effect；

B22) regulation and control intensity is chosen by maximizing therapeutic effect；

B23 therapy target) is screened according to therapeutic effect under the regulation and control intensity.

9. the method as described in claim any one of 1-3, it is characterised in that step c) parameter calibrations and parameter optimization are to combine Neuromodulation device, optimizes stimulation parameter, comprises 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) in obtain regulation and control strength optimization stimulation parameter.

10. method as claimed in claim 9, it is characterised in that the hardware device that the parameter calibration step needs includes：Magnetic The compatible neuromodulation device in resonance image-forming equipment, magnetic field.

11. methods as claimed in claim 9, it is characterised in that described step c2) stimulation parameter determined brain network regulation Mark, comprises the following steps：

C21) by the magnetic resonance compatible part of neuromodulation equipment by between waveguide introducing magnet, using the thorn of magnetic resonance compatible Excitation device, by the full brain function magnetic resonance data acquisition synchronous with stimulation, in the different phase of functional MRI data collection, Different frequency of stimulation, voltage magnitude, pulse width parameter combination are set, corresponding brain function network matrix is obtained；

12. methods as claimed in claim 9, it is characterised in that the step c3) according to step b12) or b22) in obtain Regulation and control strength optimization stimulation parameter, comprises the following steps：

C31) assessed and by quantifying to screen the candidate for obtaining in index screening neuromodulation target spot according to the step c) regulation and control Target spot, can obtain the regulation and control intensity for each target spot；

C32) contrast candidate network regulation and control intensity, in the corresponding relation calibrated, finds incentive condition combination, feeds back to stimulation Device carries out parameter optimization.

A kind of 13. devices for screening the related cerebral disease therapy target of neuromodulations, it is characterised in that described device employ as The method of the optimization neuromodulation described in claim any one of 1-12 carries out screening the related cerebral disease therapeutic target of neuromodulation Point.

14. a kind of devices for screening the related cerebral disease therapy target of neuromodulation, it is characterised in that described device includes：

Wherein, the neuromodulation module is used for the analog neuron regulation and control on the basis of macroscopical brain function network connection；The tune Control outcome evaluation module is used to go out neuromodulation therapy target by quantifying index screening；

15. devices as claimed in claim 14, it is characterised in that described device also includes：

Magnetic resonance data acquisition and functional network build module,

Wherein, it is based on MR data constructing function network square that the magnetic resonance data acquisition and functional network build module Battle array.

16. devices as claimed in claim 15, it is characterised in that the magnetic resonance data acquisition and functional network build module In functional network include disease group functional network and healthy control group functional network.

17. devices as claimed in claim 14, it is characterised in that the subject is individual level or population level.

18. device as described in claim any one of 14-17, it is characterised in that described analog neuron regulation and control module includes：

Wherein, the linear scale unit is used for the pre-treatment step of network Deconvolution Algorithm Based on Frequency；The network warp product unit, be For obtaining the straight-forward network corresponding with functional network；The neuromodulation unit, is the regulation and control strength range based on setting Bilateral neuromodulation is carried out on straight-forward network to each target spot；The network convolution unit, is for by after neuromodulation Straight-forward network obtains the functional network after neuromodulation using network convolution；

Wherein, linear scale is to be based on being carried out after the disease group functional network that MR data builds.

19. devices as claimed in claim 18, it is characterised in that described network warp product unit, including：

Wherein, the first described singular value decomposition unit, is that functional network is carried out into singular value decomposition；The first described fraction line Property converter unit, is to carry out fractional linear transformation to all of singular value；Described straight-forward network obtaining unit, is based on all The fractional linear transformation of singular value obtains straight-forward network.

20. devices as claimed in claim 18, it is characterised in that described network convolution unit, including：

Wherein, the second described singular value decomposition unit, is that the straight-forward network after neuromodulation is carried out into singular value decomposition；It is described Second fractional linear transformation's unit, be that fractional linear transformation is carried out to all of singular value；Described functional network obtains single Unit, is that the fractional linear transformation based on all singular values obtains the functional network after neuromodulation.

21. device according to claim any one of 14-17, it is characterised in that described regulation and control outcome evaluation module, bag Include：

Population level assessment unit and individual level assessment unit；

Wherein, the regulation and control outcome evaluation is that the full brain Macro-Functions network matrix based on healthy control group is carried out.

22. devices as claimed in claim 21, it is characterised in that the population level assessment unit, including：

Population level quantitative evaluation unit, regulation and control intensity acquiring unit and target spot effect prediction unit；

Wherein, described population level quantitative evaluation unit, is that disease group is average before difference calculating simulation regulates and controls, after simulation regulation and control The similarity of functional network matrix and healthy control group average function network matrix, and calculate its ratio come quantify weigh treatment Effect；Described regulation and control intensity acquiring unit, is to choose regulation and control intensity by maximizing therapeutic effect；The target spot effect prediction Unit, is to screen therapy target according to therapeutic effect under the regulation and control intensity.

23. devices as claimed in claim 21, it is characterised in that the individual level assessment unit, including：

Individual level quantitative evaluation unit, regulation and control intensity acquiring unit and target spot effect prediction unit；

Wherein, described individual level quantitative evaluation unit, is individual subject before difference calculating simulation regulates and controls, after simulation regulation and control The similarity of functional network matrix and healthy control group average function network matrix, and calculate its ratio come quantify weigh treatment Effect；Described regulation and control intensity acquiring unit, is to choose regulation and control intensity by maximizing therapeutic effect；Described target spot effect is pre- Unit is surveyed, is that therapy target is screened according to therapeutic effect under the regulation and control intensity.

24. a kind of devices for optimizing neuromodulation therapeutic scheme, it is characterised in that described device includes：

The neuromodulation device of device, magnetic resonance compatible as described in claim any one of 13-23；

Wherein, the device described in any one of claim 13-23 is used to screen the candidate therapeutic target spot of cerebral disease；The magnetic resonance Equipment and neuromodulation device are used for parameter calibration and parameter optimization.

25. methods as described in claim any one of 1-13, the device as described in claim any one of 13-24, its feature exist In the cerebral disease includes：Such as juvenile's self-closing disease, middle aged disturbance of emotion class disease, old nerve degenerative diseases.

26. method or apparatus as claimed in claim 25, it is characterised in that described middle aged disturbance of emotion class disease includes suppression Strongly fragrant disease, obsession, addiction, apositia.

27. method or apparatus as claimed in claim 25, it is characterised in that described old nerve degenerative diseases include handkerchief Jin Sen, Alzheimer disease.