CN103040446A - Neural feedback training system and neural feedback training method on basis of optical brain imaging - Google Patents

Abstract

The invention provides a neurofeedback training system and a neurofeedback training method based on optical brain imaging. In this neurofeedback training method, the trainee achieves the training goal by completing the training task; during the completion of the training task, the trainee's neural activity data is collected through the optical brain imaging device; the specific functional system of the brain is extracted from the neural activity data The intensity index of neural activity is presented to the trainee as feedback information; the trainee adjusts the training strategy according to the feedback information obtained, so that the neural activity of its specific functional system can be trained, so as to develop towards the goal. In this neurofeedback training method, the neural activity data of the trainee is collected through an optical brain imaging device. Compared with EEG and MRI, optical brain imaging has strong targeting, and the cost of optical brain imaging equipment is low, which is suitable for long-term neurofeedback training.

Description

Neurofeedback training system and neurofeedback training method based on optical brain imaging

technical field

The invention relates to a neurofeedback training system based on optical brain imaging, and at the same time relates to a neurofeedback training method based on optical brain imaging.

Background technique

Neurofeedback is to collect the individual's brain neural activity online and feed it back to itself, so that it can autonomously adjust the brain activity and achieve the purpose of changing its cognition and behavior. Through the intervention of specific brain functions, the treatment and rehabilitation of patients with brain diseases can be realized, or the cognitive abilities (such as learning and memory) of healthy people can be improved.

Researchers use electroencephalography (EEG) or functional magnetic resonance imaging (fMRI) to observe the neural activity indicators of the target brain area that they want to adjust, and feed them back to the trainees through audiovisual and other channels, so as to guide the trainees to try to adjust The neural activity index is regulated autonomously. Through repeated training for a certain period of time, trainees can master this ability of self-regulation. Since the neural activity of the adjusted brain area is related to specific cognitive functions, this long-term training can promote the improvement of corresponding cognitive abilities, or play a therapeutic role in certain neurological and mental diseases. For example, it has been reported that adjusting the neural activity patterns of the visual cortex through neurofeedback can significantly improve the sensitivity of visual perception learning; while patients with chronic pain can reduce pain through neurofeedback adjustment of the neural activity of the anterior cingulate cortex (see Kazuhisa Shibata et al. ,Perceptual Learning Incepted by Decoded fMRI NeurofeedbackWithout Stimulus Presentation,SCIENCE,VOL.334(2011) and deCharms et al.,Control over brain activation and pain learned by using real-time functional MRI,PNAS,VOL.102,2NO0.51,( )).

Devices for neurofeedback training are mainly focused on EEG-based or fMRI-based neurofeedback training systems. For example, the Chinese invention patent application with publication number CN101912255A discloses a neurofeedback system based on real-time functional magnetic resonance signals, which detects the activation state of the brain online through functional magnetic resonance signals, and feeds back to the trainees in real time, and regulates the brain through repeated training. Cognitive activity level, improve or restore the corresponding cognitive function of trainees. Another example is the neurofeedback training instrument based on EEG signals for improving brain memory function disclosed in the Chinese invention patent application with the publication number CN102319067A, which can use the scalp EEG signals collected during the brain activity process to monitor the immediate state of memory. Quantitatively detect and present the EEG rhythm wave representing the memory level to the user, and guide the user to consciously adjust the EEG rhythm wave to achieve the purpose of improving the memory level.

However, there are still many problems to be solved in the existing neurofeedback system. For the neurofeedback system based on EEG, because the spatial resolution of EEG is extremely low, it is difficult to locate the training brain area, and the relationship between EEG rhythm components and cognitive function is not yet clear, so the training target performance is poor, and its application is greatly limited. Although the neurofeedback system based on magnetic resonance imaging overcomes the shortcomings of the EEG system to a certain extent, due to the high cost and use cost of magnetic resonance imaging equipment, the equipment is huge and cannot be moved at will, so it can only be used for laboratory research. , It is impossible to be used for clinical long-term treatment training.

Contents of the invention

The primary technical problem to be solved by the present invention is to provide a neurofeedback training method based on optical brain imaging.

Another technical problem to be solved by the present invention is to provide a neurofeedback training system based on optical brain imaging.

In order to achieve the above-mentioned purpose of the invention, the present invention adopts following technical scheme:

A neurofeedback training method based on optical brain imaging, through which the trainee completes the training task to achieve the training purpose, including the following steps:

(1) During the completion of the training task, the trainee’s neural activity data is collected through optical brain imaging equipment; the neural activity intensity index of the specific functional system of the brain is extracted from the neural activity data; and the The neural activity intensity index of the specific functional system of the brain is presented to the trainee as feedback information; enter step (2);

(2) The trainee makes further training according to the feedback information obtained in step (1); enter step (3);

(3) Repeat the process in step (1); until the training task ends.

Preferably, in the step (1), the concentration of oxyhemoglobin, the concentration of deoxygenated hemoglobin, task marks and time stamp information at the current moment are extracted by analyzing the neural activity data, and combined with the start time of the training task and end time to calculate the neural activity intensity index of the specific functional system of the brain.

Preferably, the training task adopts a block task design paradigm, including alternate rest phases and task phases. In the step (1), the neural activity intensity index of the specific brain function system refers to the task The relative SpO2 value of the phase relative to the rest phase.

A neurofeedback training system for realizing the above-mentioned neurofeedback training method, comprising an optical brain imaging device, a central processing unit and a display device, the optical brain imaging device is used to collect the neural activity data of the trainee, and the collected The neural activity data is transmitted to the central processing unit, and the central processing unit is used to analyze the neural activity data in combination with the training task, obtain the neural activity intensity index of the specific functional system of the brain, and transmit it to the display device , the display device is used to present feedback information to the trainee.

Preferably, the central processing unit includes a task module, an acquisition module, a decoding module and a feedback module; wherein, the task module is used to generate a task flow based on the training task and control the execution of other modules; the acquisition The module is used to obtain the neural activity data from the optical brain imaging device in real time, and transmit the neural activity data to the decoding module; the decoding module is used to preprocess the neural activity data, and The neural activity intensity index of the specific brain function system is extracted; the feedback module is used to feed back the neural activity intensity index of the brain specific functional system to the display device.

Preferably, the acquisition module is used to extract the oxygenated hemoglobin concentration, deoxygenated hemoglobin concentration, task mark and time stamp information at the current moment from the optical brain imaging device in real time, and store the oxygenated hemoglobin concentration, the The deoxygenated hemoglobin concentration, the task mark and the time stamp information are transmitted to the decoding module.

Preferably, the training task includes alternate rest phases and task phases, the task module is used to notify the feedback module to alternately enter the rest phase or task phase; and the task module is used to combine the rest phase and the task phase The time start point and the end time point of the task phase are notified to the decoding module.

Preferably, the decoding module is used to preprocess the neural activity data; and extract the average signal intensity of the corresponding area of the brain specific functional system from the result obtained by the preprocessing, and then according to the information from the task module The task start time information and the task end time information are used to calculate the neural activity intensity index of the specific brain functional system, and the neural activity intensity index of the specific brain functional system refers to the relative blood pressure of the task stage relative to the rest stage. Oxygen concentration value.

Preferably, the feedback module is used to feed back the neural activity intensity index of the specific brain function system obtained in the decoding module to the display device in the form of a picture.

Preferably, the optical brain imaging device is a functional near-infrared spectrometer.

In the neurofeedback training system and neurofeedback training method provided by the present invention, the neural activity data of the trainee is collected through the optical brain imaging device during the training process, and the neural activity intensity index of the specific functional system of the brain of the trainee is fed back to the trainee, So that the trainee can adjust the training strategy according to the feedback information obtained, so that the neural activity of its specific functional system can be trained and develop towards the goal. Among them, the optical brain imaging equipment can non-destructively detect the hemodynamic activity of the cerebral cortex by using the difference in the absorption rate of near-infrared light of different wavelengths by hemoglobin in brain tissue, and then study the neural activity of the brain. Compared with EEG, optical brain imaging has a certain spatial resolution (1-3cm), which can more accurately locate the observed brain signals and improve the targeting of training. Compared with magnetic resonance imaging, optical brain imaging is cheap, and the equipment is light and mobile, and can be used in hospitals, homes, schools, etc.; the scanning environment is safe and comfortable, and can be repeated for multiple measurements, suitable for feedback training that requires long-term multiple scans .

Description of drawings

Fig. 1 is a schematic diagram of the composition of the neurofeedback training system based on optical brain imaging provided by the present invention;

Fig. 2 is an example of the running interface of the neurofeedback training game in the embodiment of the present invention;

Fig. 3 is an example of experimental task design in an embodiment of the present invention;

Fig. 4 is in the experimental task shown in Fig. 3, the trainee's No. 12 relative oxyhemoglobin concentration sequence diagram;

Fig. 5 is in the experimental task shown in Fig. 3, the spatial activation diagram of the parietal lobe optode of the trainee;

Fig. 6 is the spatial activation map of the occipital lobe optode of the trainee in the experimental task shown in Fig. 3 .

Detailed ways

The content of the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

The neurofeedback training system based on optical brain imaging (fNIRS) provided by the present invention realizes the training purpose through the trainees completing training tasks. During the process of the trainee completing the training task, the optical brain imaging device captures the neural activity of the specific functional system in the brain of the trainee in real time, and presents the intensity of the neural activity of the specific functional system to the trainee in a friendly manner. The trainee adjusts the training strategy according to the feedback information obtained, so that the neural activity of its specific functional system can be trained, so as to develop towards the goal. The neurofeedback training method can be applied to the regulation of cognitive functions such as movement, language, and emotion, and can also be used for exercise rehabilitation training of stroke patients. Of course, the neurofeedback training method based on optical brain imaging, in addition to having medical treatment value, can also be used to improve the neural activity of ordinary people, so that the neural activity of ordinary people can be exercised.

Specifically, when using the neurofeedback training system for training, the training process is realized through the following steps: Step (1): During the completion of the training task, the neural activity data of the trainee is collected through the optical brain imaging device, and the neural activity The neural activity intensity index of the specific functional system of the brain is extracted from the data, and the neural activity intensity index of the specific functional system of the brain is presented to the trainee as feedback information, and enters step (2); step (2): the trainee according to step (1 ) for further training, and enter step (3); step (3): repeat the process in step (1) until the end of the training task.

Optical brain imaging equipment is a non-invasive device that uses the difference in the absorption rate of near-infrared light of different wavelengths by hemoglobin in brain tissue to non-destructively detect the hemodynamic activity of the cerebral cortex, and then study the neural activity of the brain. In the above step (1), the concentration of oxygenated hemoglobin, deoxygenated hemoglobin, task mark and time stamp information at the current moment are extracted by analyzing the neural activity data, and combined with the start time and end time of the training task, the specific function of the brain is calculated An indicator of the intensity of neural activity of the system. In this neurofeedback training method, the training activity includes alternating rest phases and task phases, and by calculating the relative blood oxygen concentration value of the task phase relative to the rest phase, the neural activity intensity index of the specific functional system of the brain can be obtained. Preferably, in the neurofeedback training method, the training task adopts a block design paradigm (block design), and by adopting different block task designs, researchers can easily use this method to provide trainees with relevant neurofeedback train.

The neurofeedback training method based on optical brain imaging has been briefly introduced above, and the neurofeedback training system based on optical brain imaging provided by the present invention and the training process using the neurofeedback training system will be introduced in detail below. The goal of using the neurofeedback training system for training is to conveniently give trainees feedback on their own neural activity intensity so that they can master the ability to regulate this activity, thereby bringing about behavioral changes.

As shown in FIG. 1 , the neurofeedback training system includes an optical brain imaging device 1 , a central processing unit 2 and a display device 3 . Wherein, the optical brain imaging device 1 is used to collect the neural activity data of the trainee, and transmit the collected neural activity data to the central processing unit 2, and the central processing unit 2 analyzes the neural activity data in combination with the executed training tasks to obtain the analysis results, and The analysis results are transmitted to the display device 3, and the display device 3 is used to present feedback information to the trainee, the feedback information refers to the neural activity intensity index of the specific functional system of the brain of the trainee.

Wherein, the optical brain imaging device 1 can be realized by a functional near-infrared spectrometer, for example, the ETG-4000 near-infrared brain functional imaging device of Hitachi can be used; the central processing unit 2 can be realized by a computer host running system software, and the display device 3 can be realized by an LCD LCD or other display implementations. In the central processing unit 2, it also includes a task module 21, an acquisition module 22, a decoding module 23 and a feedback module 24; the task module 21 is used to generate a task flow based on the block task design provided by the main tester, and to control the execution of other modules ; The collection module 22 is used to obtain the neural activity data from the optical brain imaging device 1 in real time, that is, the oxygenated hemoglobin concentration value and the deoxygenated hemoglobin concentration value, and transmits the neural activity data to the decoding module 23; the decoding module 23 is used to use the collection module The neural activity data obtained in 22 is preprocessed, and the neural activity intensity index of the specific functional system of the brain is extracted; the feedback module 24 is used to feed back the neural activity intensity index obtained in the decoding module 23 to the display device 3, so as to present it to the trainee .

In the central processing unit 2, the specific implementation process of each functional module is as follows. The task module 21 generates a time interval sequence and a task sequence based on the block task design parameters provided by the examiner, and maintains a timer. The timer counts down according to the time in the time interval sequence. When the timer is timed out, modify the current experimental conditions according to the task sequence, and notify the feedback module 24 to enter the rest phase or the task phase; at the same time, notify the decoding module 23, because the decoding module 23 needs to know the rest to calculate the relative blood oxygen concentration value. The start and end times of phases and task phases. The acquisition module 22 establishes a network connection with the optical brain imaging device 1 through the TCP/IP protocol and receives the neural activity data in real time, analyzes the received neural activity data according to the preset data transmission format, and extracts the oxygenation at the current moment. Hemoglobin concentration, deoxyhemoglobin concentration, task token and timestamp information. The decoding module 23 receives the neural activity data from the acquisition module 22, and performs sliding window average filtering, oxygenation and deoxygenation hemoglobin concentration preprocessing; and extracts the region corresponding to the specific functional system from the preprocessing results According to the average signal strength of the task module 21, the relative blood oxygen concentration value of the task phase relative to the rest phase is calculated according to the task start time information and task end time information. This relative blood oxygen concentration value is an indicator of the intensity of neural activity in a specific functional system of the brain. The feedback module 24 is divided into two phases to appear cyclically: phase 1 is the rest phase, presenting rest prompt information, at this time the trainee does not need to do anything, and relaxes physically and mentally; The relative blood oxygen concentration value is presented to the trainees in a friendly way such as game screens. At this time, the trainee responds according to the pre-given training method, thereby further controlling the direction of the game. For example, trainees can issue pre-specified training instructions as required, and obtain brain neural activity data by analyzing optical brain imaging of trainees during vocalization exercises to further control the direction of the game.

Here, the implementation process of the above-mentioned neurofeedback training system is described by taking the example of adjusting the neural activity of the trainee's right supplementary motor area (rSMA) by means of neurofeedback.

The image shown in Fig. 2 is the human-computer interaction interface presented on the display device 3 in this embodiment, wherein the area where the stone is located in the figure is the area corresponding to the auxiliary motor area on the right side in the collection area, expressed by the height of the stone The intensity of neural activity in this neural area, the higher the height of the stone, the stronger the intensity of neural activity in this area. From the picture presented on the display device 3 , the trainee can clearly see the height of the stone reflecting the neural activity intensity of his right supplementary motor area during the training process, so as to understand the neural activity intensity of the training area. The human-computer interaction interface consists of two parts: one part is a signal light, the red light on the left indicates rest, and the green light on the right indicates that the task is in progress; the other part is a stone, and the height of the stone is controlled by the input of the collected neural activity intensity.

In this training task, the trainees adjusted the height of the stone through the motor imagery strategy without physical activity, so as to exercise the neural activity ability of the specific nervous system corresponding to the acquisition area. In this embodiment, the block task design paradigm of the training task is shown in Figure 3, including 8 blocks, and each block has two parts, a rest stage and a task stage, wherein the rest stage is 20 seconds long, and the task stage is 20 seconds long. 20 seconds. In this training task, Hitachi ETG-4000 optical brain imaging equipment was used to complete the training. The optical brain imaging equipment was equipped with two 3×5 optical pole pieces, which were respectively worn on the parietal lobe and occipital lobe of the trainee. Part of the motor area covered by the leaf includes the right supplementary motor area. By analyzing the collected neural activity intensity of the area corresponding to the parietal lobe, the neural activity ability of the right supplementary motor area can be obtained, and by comparing the neural activity intensity of the corresponding areas of the parietal lobe and the occipital lobe, the specificity of neurofeedback training can be determined. sex.

During the completion of the training task, the trainee looks at the game screen on the display device 3. When the red signal light is on, the trainee is in a resting state; when the green signal light is on, the trainee starts motor imagery adjustment to make the height of the stone rise as much as possible .

In the task module 21, based on the block task design parameters provided by the examiner, a sequence of time intervals is generated. Set a timer to respond every 20 seconds, and run 2*8=16 times in total. When the task module 21 collects the timer response, it switches the progress state of the training task. If the training state switched is the rest phase, then notify the feedback module 24 to switch to the rest phase; if the switched training state is the task phase, then notify the feedback module 24 to enter the task phase, and notify the encoding module 23 to recalculate the baseline and start to Feedback module 24 provides feedback information.

During the process of the trainee completing the training task, the optical brain imaging device 2 captures the trainee's neural activity data.

The collection module 22 establishes a network connection with the ETG-4000 through the TCP protocol and receives the neural activity data collected by the optical brain imaging device 2 in real time. First receive 4 bytes of 32-bit integer data. If the value is 12, it means that the following is a data packet with the format shown in Table 1. In this data packet, the blood oxygen concentration data is divided into two parts. The first half The content is the oxygenated hemoglobin concentration, and the second half is the deoxygenated hemoglobin concentration, and each concentration value is an 8-byte single-precision floating-point number. The acquisition module 22 analyzes the received data according to the above-mentioned format, extracts the concentration of oxygenated hemoglobin, deoxygenated hemoglobin, task mark and time stamp information at the current moment, and sends the above data to the decoding module 23 .

size (bytes) content type of data 4 packet number integer 4 packet size integer Packet Size - 12 blood oxygen concentration data single precision floating point 2 data tag integer 10 timestamp integer

Data format in the data packet in Table 1

The decoding module 23 receives the data from the acquisition module 22, and performs a preprocessing process of sliding window average filtering, oxygenation minus deoxygenated hemoglobin concentration. Among them, the window length parameter of the sliding window average filter is set to 1 second, and the preprocessing formula of oxygenated minus deoxygenated hemoglobin concentration is as follows:

$\mathrm{<span\; class="notranslate">\; \&alpha;</span>}<span\; class="notranslate">\; =</span>\sqrt{\frac{{\mathrm{<span\; class="notranslate">\; \&Sigma;x</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}{\mathrm{<span\; class="notranslate">\; the\; <figure-callout\; id="2"\; label="y"\; filenames="HDA00002698316300032.png,HDA00002698316300033.png"\; state="\{\{state\}\}">y</figure-callout></span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; std</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; std</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span>}$

${\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; \&alpha;y</span>}<span\; class="notranslate">\; )</span>$

${\mathrm{<span\; class="notranslate">\; the\; <figure-callout\; id="0"\; label="y"\; filenames="HDA00002698316300032.png,HDA00002698316300033.png"\; state="\{\{state\}\}">y</figure-callout></span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; -</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}$

where x is the concentration of oxyhemoglobin, y is the concentration of deoxygenated hemoglobin, and α is the ratio of the standard deviations of the two hemoglobin concentrations. x ₀ , y ₀ are the concentrations of pretreated oxygenated hemoglobin and deoxygenated hemoglobin, respectively.

Extract the average signal intensity of a specific brain region (corresponding to a specific functional system of the brain) from the preprocessing results, and calculate the current blood oxygen concentration value relative to it based on the blood oxygen concentration value calculated at the end of the rest Relative blood oxygen concentration value. This relative blood oxygen concentration value is the neural activity intensity of the specific functional system of the brain. In this embodiment, the specific brain region is known from anatomical positioning: the position of the right supplementary motor area on the scalp is between Cz and C4 in the international 10-20 positioning system for positioning on the scalp.

The feedback module 24 communicates with the decoding module 23 through the TCP protocol, and is used to present the analysis result of the decoding module 23 to the trainee. In this embodiment, the feedback module 24 presents the intensity index of the neural activity of the specific functional system to the trainee as an independent floating stone game picture. In the stage of the task, it receives the result from the decoding module 23, and converts the data within the range of 0 to 1 into the height of the stone. When the training phase of the task module 21 is switched from the task phase to the rest phase, the stones will naturally fall to the ground.

Two results can be obtained during the completion of the training task: one is the time series map of the target brain area activity, which is used to reflect whether the activity is related to the training task; the other is the spatial activation map of the observed area of the brain imaging device, which is used to Determining the Specificity of Neurofeedback Debugging.

Figure 4 is a time-series diagram of the target functional area (i.e., the right supplementary motor area located in lead 12) during the experiment for the response activity process. It can be seen that the activity has a strong correlation with the task design, and the blood oxygen concentration is enhanced during the task phase (gray background), while the blood oxygen concentration is weakened during the rest phase (white background), thus indicating that through neurofeedback, trainees can Finely control the intensity of neural activity in specific functional systems of the brain.

Figures 5 and 6 are the spatial activation maps of the corresponding regions of the two optodes worn by the trainee, respectively. It can be seen that the positions with relatively strong activation in space are all near the target brain area (see the spatial activation map of the parietal lobe in Figure 5), while the occipital lobe, which is not related to the task, mainly the visual area, does not show activation (see Figure 6 Spatial activation map of the occipital lobe). From the above two figures, it can be judged that using the optical brain imaging-based neurofeedback training system for training can specifically regulate the activity of the target brain region. In the process of completing the training task, the trainee can selectively adjust the activity of the target brain area through the strategy of motor imagery. This selective regulation can bring clinical and scientific value. For example, clinically, exercise rehabilitation training for stroke patients can combine actual exercise with brain motor function training, effectively solving the drawbacks of traditional rehabilitation training that only trains muscles and does not focus on the brain; in scientific research, for researchers, with the help of This method can selectively activate the brain regions of the subjects, and by observing the behavioral changes it brings about, it can provide a causal relationship between brain activity and behavior, and provide new ideas for cognitive neuroscience research.

To sum up, the neurofeedback training system and neurofeedback training method based on optical brain imaging provided by the present invention, wherein the optical brain imaging device involved is a non-invasive device, which uses brain tissue hemoglobin to react to near The differential characteristics of infrared light absorption rate can non-destructively detect the hemodynamic activity of the cerebral cortex, and then study the neural activity of the brain. Compared with EEG, optical brain imaging has a certain spatial resolution (1-3cm), which can more accurately locate the observed brain signals and improve the targeting of training. Compared with magnetic resonance imaging, optical brain imaging is cheap, and the equipment is light and mobile, and can be used in hospitals, homes, schools, etc.; the scanning environment is safe and comfortable, and can be repeated for multiple measurements, suitable for feedback training that requires long-term multiple scans .

The neurofeedback training system and neurofeedback training method based on optical brain imaging provided by the present invention have been introduced in detail above. For those skilled in the art, any obvious changes made to it without departing from the essence of the present invention will constitute an infringement of the patent right of the present invention and will bear corresponding legal responsibilities.

Claims (10)

1. the neural feedback training method based on the imaging of optics brain is characterized in that comprising the steps:

(1) in the training mission complete process, gathers trainee's neural activity data by optics brain imaging device; Go out the neural activity intensity index of brain specific function system from described neural activity extracting data, and the neural activity intensity index of described brain specific function system is presented to described trainee as feedback information; Enter step (2);

(2) described trainee makes further training according to the described feedback information that obtains in the step (1); Enter step (3);

(3) process in the repeating step (1); Until described training mission finishes.

2. neural feedback training method as claimed in claim 1 is characterized in that:

In described step (1), extract HbO2 Oxyhemoglobin concentration, deoxyhemoglobin concentration, task mark and the timestamp information of current time by analyzing described neural activity data, and in conjunction with time started and concluding time of described training mission, calculate the neural activity intensity index of described brain specific function system.

3. neural feedback training method as claimed in claim 1 is characterized in that:

Described training mission adopts chunk task design normal form, comprise the rest period and the task phase that hocket, in described step (1), the neural activity intensity index of described brain specific function system refers to the relative blood oxygen concentration value of described task phase with respect to the described rest period.

4. neural feedback training system that is used for realizing neural feedback training method claimed in claim 1 is characterized in that:

Comprise optics brain imaging device, CPU and display device, wherein, described optics brain imaging device is used for gathering trainee's neural activity data, and the described neural activity transfer of data that will collect is given described CPU, described CPU is used for the described neural activity data of combined training task analysis, obtain the neural activity intensity index of brain specific function system, and it is transferred to described display device, described display device is used for presenting feedback information to described trainee.

5. neural feedback training system as claimed in claim 4 is characterized in that:

Described CPU comprises task module, acquisition module, decoder module and feedback module; Wherein, described task module is used for generating flow of task based on described training mission, and controls the implementation status of other modules; Described acquisition module is used for obtaining described neural activity data from described optics brain imaging device in real time, and with described neural activity transfer of data to described decoder module; Described decoder module is used for described neural activity data are carried out pretreatment, and extracts the neural activity intensity index of described brain specific function system; Described feedback module is used for the neural activity intensity index of described brain specific function system is fed back to described display device.

6. neural feedback training system as claimed in claim 5 is characterized in that:

Described acquisition module is used for extracting from described optics brain imaging device in real time HbO2 Oxyhemoglobin concentration, deoxyhemoglobin concentration, task mark and the timestamp information of current time, and described HbO2 Oxyhemoglobin concentration, described deoxyhemoglobin concentration, described task mark and described timestamp information are transferred to described decoder module.

7. neural feedback training system as claimed in claim 5 is characterized in that:

Described training mission comprises rest period and the task phase that hockets, and described task module is used for notifying described feedback module alternately to enter rest period or task phase; And described task module is used for notifying described decoder module with the time starting point of described rest period and described task phase and concluding time point.

8. neural feedback training system as claimed in claim 7 is characterized in that:

Described decoder module is used for described neural activity data are carried out pretreatment; And from the result that pretreatment obtains, extract the average signal strength of the corresponding region of brain specific function system, again according to task time started information and task concluding time information from described task module, calculate the neural activity intensity index of described brain specific function system, the neural activity intensity index of described brain specific function system refers to the relative blood oxygen concentration value of described task phase with respect to the described rest period.

9. neural feedback training system as claimed in claim 7 is characterized in that:

The neural activity intensity index that described feedback module is used for described brain specific function system that described decoder module is obtained feeds back to described display device with the form of picture.

10. neural feedback training system as claimed in claim 4 is characterized in that:

Described optics brain imaging device is the function near infrared spectrometer.

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