A magnetoencephalography compatible multi-channel near-infrared high sampling rate modulation method and system

Abstract

The application discloses a magnetoencephalography compatible multi-channel near-infrared high sampling rate modulation method and system, and belongs to the field of multi-modal brain function imaging research.The method comprises the following steps: modulating a driving signal of an fNIRS light source to a high-frequency carrier; adopting a multi-channel frequency division multiplexing strategy, transmitting the modulated driving signal to each fNIRS light source, so that each fNIRS light source emits infrared light rays for detecting a target; and demodulating the detected infrared light rays to obtain the amplitude of the detected infrared light rays.The application can realize non-contact sensing of the target.The application can reduce electromagnetic interference in the process of MEG and fNIRS synchronous imaging, utilize specific frequency modulation technology to realize synchronous acquisition of magnetoencephalography signals and multi-channel high sampling rate near-infrared signals, and accurately and quickly demodulate the near-infrared signals.

Description

Technical Field

[0001] This invention relates to the field of multimodal brain functional imaging research, specifically to a brain magneto-compatible multichannel near-infrared high sampling rate modulation method and system. Background Technology

[0002] Brain functional imaging technology is an effective tool for revealing the mechanisms of brain activity. However, single-modal techniques, due to limitations in temporal / spatial resolution and detection depth, struggle to meet the needs of complex neuroscience research and precise clinical diagnosis. Multimodal brain functional imaging technology, by integrating complementary techniques, enables the synergistic analysis of multidimensional data and has become a key development direction in neuroscience. Multimodal imaging has the advantage of complementary spatiotemporal resolution. Functional magnetic resonance imaging (fMRI) has high spatial resolution (millimeter-level) but low temporal resolution (second-level); electroencephalography (EEG) has millisecond-level temporal resolution but insufficient spatial resolution; functional near-infrared spectroscopy (fNIRS) strikes a balance between the two, but its penetration depth is limited. Multimodal fusion can overcome the bottleneck of single-technical approaches. Secondly, multimodal imaging technology can achieve multidimensional coverage of physiological signals. EEG and magnetoencephalography (MEG) can acquire information on neuronal electrical activity, while near-infrared and ultrasound imaging can obtain information on blood oxygen metabolism, enabling multi-parameter joint analysis and comprehensive analysis of brain functional networks.

[0003] Magnetoencephalography (MEG) based on optically pumped magnetometers (OPM) utilizes the spin polarization effect of alkali metal atoms (such as rubidium and cesium) in a magnetic field. It achieves extremely weak magnetic fields (10⁻⁶) through laser pumping and optical detection. -14 Measurements are measured on the order of terabytes (T). Compared to traditional magnetoencephalography (MEG) based on a superconducting quantum interference device (SQUID), this method eliminates the limitations of liquid helium cooling and operates without cryogenics. The sensor is placed close to the scalp, significantly improving signal sensitivity in deep brain regions. Simultaneously, the wearable design is greatly simplified, utilizing a miniaturized OPM probe (<5cm). 3 ( / unit), supports natural head movement, and improves compatibility with other modalities. Active compensation technology can operate in partially shielded or even unshielded environments, reducing equipment deployment costs. However, compared to SQUID, OPM-MEG measurements require a near-zero magnetic environment, with the magnetic field in most measurement environments needing to be controlled below 10 nT. The requirements for magnetic shielding and resistance to surrounding magnetic field interference are higher than for SQUID magnetoencephalography.

[0004] fNIRS utilizes the absorption characteristics of near-infrared light (650-950nm) in brain tissue to reflect local cerebral hemodynamic responses by measuring changes in the concentrations of oxyhemoglobin and deoxyhemoglobin. Near-infrared imaging requires no magnetic shielding and can be used in real-time under natural conditions (such as during movement and social interaction), with a temporal resolution of approximately 0.1-1Hz and a spatial resolution of 2-3cm, making it suitable for cortical functional localization. Single-modal near-infrared imaging devices use fiber optic or LED light sources, resulting in lightweight equipment suitable for portable detection and multimodal fusion. Traditional continuous-wave near-infrared brain functional imaging devices are limited by the modulation frequency of the light source, with sampling rates typically at 10Hz or lower, making it difficult to capture high-frequency neural oscillation signals.

[0005] Fiber-free fNIRS significantly improves resistance to motion interference by using electrical signals instead of optical signals transmitted through optical fibers. Its integrated design of probes and electronic modules effectively reduces motion artifacts caused by limb movements or fiber dragging, making it particularly suitable for children, ADHD patients, or dynamic behavior research (such as real-time monitoring of cerebral blood flow in motor rehabilitation). However, it faces magnetic compatibility challenges when used in conjunction with magnetoencephalography (MEG): the electronic components integrated into fiber-free devices (such as light source driving modules and photoelectric conversion modules) may generate broadband electromagnetic noise. This noise can intrude into the extremely weak magnetic field signals detected by MEG, especially interfering with the extraction of key signals such as neural oscillations in the 1-100Hz frequency band. In contrast, traditional fiber-optic fNIRS, due to the absence of active electronic components, is more likely to meet the stringent weak magnetic field requirements of MEG.

[0006] Although MEG and fNIRS have complementary potential in terms of spatiotemporal characteristics and system configuration, there are still technical conflicts when combining them for fiber-optic near-infrared devices. The core objective of this invention is to overcome the limitations of multi-channel near-infrared light source driving signals and MEG ultra-weak magnetic field measurement (10 -14To address the spectral conflicts between signals on the order of terabytes (T), an electromagnetically compatible synchronous acquisition architecture is constructed. Traditional continuous-wave near-infrared imaging (fNIRS) employs a time-division multiplexing strategy for driving the light source, essentially using square waves for modulation. The light source undergoes high-frequency switching, and the transient current changes in the driving circuit are coupled to the OPM probe through electromagnetic induction. The resulting switching noise frequency falls within the magnetic field measurement band of the OPM-MEG (0.1-100Hz), submerging neural signals and preventing normal measurement of magnetoencephalogram (MEG) signals. As the number of fNIRS channels increases, the duty cycle limitation of the modulation square wave forces the modulation frequency to rise above 50kHz. High-frequency switching noise further exacerbates low-frequency interference through harmonic components of the Fourier transform (e.g., the third harmonic of a 10kHz square wave is 30kHz, which is down-converted to the OPM measurement bandwidth after mixing by a nonlinear circuit). Continuous modulation of the driving signal requires differentiation among numerous near-infrared channels based on the modulation frequency. Besides high-frequency switching noise, in magnetoencephalography (MEG)-near-infrared (NIRS) experiments, the proximity of the MEG detector and the near-infrared light source makes it easy for the driving light source signal to couple into the measurement of the MEG signal, causing mixing with its internal signals and generating interference frequencies that fall into the MEG measurement bandwidth. Therefore, the challenge lies in balancing the performance of the signal output device with the impact of frequency differences between different channels on the interference frequencies within the MEG bandwidth. Furthermore, how to quickly and accurately demodulate and process the near-infrared signal under frequency modulation is also a challenge. Existing technologies use physical isolation to reduce electromagnetic interference, but sacrifice the synchronization of multimodal data. Low-frequency modulation techniques reduce the modulation frequency of the fNIRS light source to avoid the MEG measurement bandwidth, but this leads to a decrease in the sampling rate, failing to meet the requirements of high-dynamic brain activity detection.

[0007] Therefore, existing technologies have failed to effectively balance the requirements of multi-channel operation, high sampling rate, low electromagnetic interference, and multimodal synchronization. This patent proposes a magnetoencephalography (MEG)-compatible near-infrared high sampling rate frequency modulation method. By optimizing the light source driving strategy and signal demodulation algorithm, the fNIRS sampling rate is increased to over 100Hz, while maintaining compatibility with MEG measurements, achieving precise spatiotemporal alignment of cross-modal data. This technological breakthrough will promote the application of multimodal brain imaging in cutting-edge fields such as neural decoding and brain-computer interfaces. Summary of the Invention

[0008] In view of the above, the purpose of this invention is to provide a multi-channel near-infrared high sampling rate modulation method and system compatible with magnetoencephalography (MEG), which can reduce electromagnetic interference during the synchronous imaging process of MEG and fNIRS (functional near-infrared spectroscopy), and achieve synchronous acquisition of MEG signals and multi-channel high sampling rate near-infrared signals using specific frequency modulation techniques, and accurately and quickly demodulate the near-infrared signals.

[0009] To achieve the above objectives, the technical solution of the present invention includes the following:

[0010] A magnetoencephalography-compatible multichannel near-infrared high sampling rate modulation method, the method comprising:

[0011] The driving signal of the fNIRS light source is modulated onto a high-frequency carrier wave;

[0012] A multi-channel frequency division multiplexing strategy is adopted to transmit the modulated driving signal to each fNIRS light source so that each fNIRS light source emits infrared light to detect the target.

[0013] The amplitude of the detected infrared light is obtained by demodulating the infrared light.

[0014] Furthermore, the algorithm for modulating the driving signal of the fNIRS light source onto a high-frequency carrier includes: a prime number frequency modulation algorithm or a frequency point modulation algorithm with a difference greater than a set value.

[0015] Furthermore, when employing the aforementioned multi-channel frequency division multiplexing strategy, the frequency interval of each modulated driving signal is calculated through the following steps:

[0016] Obtain the sampling rate of the modulation output device, the total number of channels in the multi-channel frequency division multiplexing strategy, and the cutoff frequency of the filter used for demodulation;

[0017] The frequency interval of each modulated drive signal is obtained based on the sampling rate of the modulation output device, the total number of channels in the multi-channel frequency division multiplexing strategy, and the cutoff frequency of the filter used for demodulation.

[0018] Furthermore, the amplitude of the detected infrared light is obtained by demodulating the infrared light, including:

[0019] The infrared light after detection Where t represents time, ω c It is the target frequency, H c (t) represents the amplitude of the detected infrared light as a function of time. H(t) is the phase of the target signal, H(t) is the amplitude of other frequency signals that vary with time, and ω is the frequency of the other frequency signals. It is the phase of other frequency signals, which include: low-frequency ambient noise and other received modulated drive signals;

[0020] Infrared light Y c respectively with cos(ω) c t) and sin(ω c After multiplying by t), a low-pass filter is used to filter the result. and filtering results

[0021] based on The amplitude H of the infrared light after detection is obtained. c (t).

[0022] Further, the model of the low-pass filter is selected through the following steps:

[0023] The minimum value of the frequency difference used in modulation is Δω = |ω - ω. c |;

[0024] The model of the low-pass filter is selected based on this minimum value Δω.

[0025] Furthermore, the GPU is used to demodulate and detect the infrared light.

[0026] Furthermore, the method also includes:

[0027] Magnetoencephalography (MEG) signals are acquired using optically pumped magnetoencephalography (OPM) or SQUID MEG.

[0028] A magnetoencephalography-compatible multi-channel near-infrared high sampling rate modulation system, the system comprising:

[0029] The high-frequency modulation module is used to modulate the drive signal of the fNIRS light source onto a high-frequency carrier using prime-number frequency modulation.

[0030] The multi-channel carrier generation module is used to transmit the modulated drive signal to each fNIRS light source using a multi-channel frequency division multiplexing strategy, so that each fNIRS light source emits infrared light to detect the target.

[0031] The signal demodulation module is used to demodulate the detected infrared light to obtain the amplitude of the detected infrared light.

[0032] An electronic device includes: a processor and a memory storing computer program instructions; the processor, when executing the computer program instructions, implements the MEG-compatible multichannel near-infrared high sampling rate modulation method described above.

[0033] A computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement the MEG-compatible multichannel near-infrared high sampling rate modulation method described above.

[0034] A computer program product, when run on a computer device, causes the computer device to execute the MEG-compatible multichannel near-infrared high sampling rate modulation method described above.

[0035] Compared with the prior art, the present invention has at least the following beneficial effects.

[0036] 1. High sampling rate and high channel number compatibility: Through high-frequency modulation technology and frequency division multiplexing strategy of prime frequency points, synchronous driving of multi-channel near-infrared light source is realized, and the sampling rate is increased to more than 100Hz. At the same time, it supports high-density detection of 128 channels and below, which meets the needs of high dynamic brain activity detection. By controlling the frequency point spacing, the performance requirements of hardware output device are reduced.

[0037] 2. Low electromagnetic interference design: High-frequency prime number frequency modulation technology is adopted to greatly reduce the noise of the light source drive signal within the MEG measurement bandwidth (0.1-100Hz), significantly reducing electromagnetic interference and ensuring the measurement accuracy of the brain magnetoencephalogram (MEG) signal.

[0038] 3. Synchronous acquisition of multimodal data: High-precision time alignment of near-infrared and magnetoencephalography (MEG) signals can be achieved through high-frequency clock synchronous acquisition, providing a reliable foundation for joint analysis of multimodal data.

[0039] 4. Flexibility and scalability: Allows for flexible adjustment of modulation and demodulation schemes according to experimental needs, such as combining GPU acceleration optimization with phase-preserving coherent demodulation technology, which is suitable for different scales of brain science research and clinical application scenarios, and provides the possibility of adding other imaging modalities and experimental devices. Attached Figure Description

[0040] Figure 1 A flowchart of a multi-channel near-infrared high sampling rate modulation method compatible with magnetoencephalography (MEG).

[0041] Figure 2 This is a flowchart of near-infrared signal demodulation.

[0042] Figure 3 This is a scheme for modulation frequencies of 32 dual-wavelength light sources. Detailed Implementation

[0043] In the following description, the modulation method of the present invention is further described through specific embodiments to enable those skilled in the art to have a more thorough understanding of the features and advantages of the present invention. It should be noted that the following description is only a representative typical application. Obviously, the present invention is not limited to any specific structure, function, device, and method described herein, and may have other embodiments or combinations of other embodiments. The software / hardware modules described in the present invention or shown in the accompanying drawings can also be flexibly adjusted as needed.

[0044] This invention achieves compatibility between fNIRS and optically pumped magnetometer magnetoencephalography (EMG) through prime-number frequency modulation, multi-channel frequency division multiplexing strategy, and a specific demodulation algorithm. It also achieves a multi-channel functional near-infrared spectral intensity modulation and fast demodulation method with high sampling rate and high signal-to-noise ratio.

[0045] Specifically, the magnetoencephalography-compatible multi-channel near-infrared high sampling rate modulation method of the present invention, such as Figure 1 As shown, it includes the following steps 1 to 3.

[0046] Step 1: Modulate the driving signal of the fNIRS light source onto a high-frequency carrier.

[0047] This invention modulates the driving signal of the fNIRS light source onto a high-frequency carrier (e.g., 2-100kHz), so that the circuit noise energy is concentrated outside the MEG measurement bandwidth (0.1-100Hz).

[0048] In one embodiment, the present invention can use a modulation algorithm with prime frequencies or large interpolation points for modulation. The proximity of the magnetoencephalogram (MEG) and near-infrared (NII) circuits causes signal coupling and mixing, resulting in frequency differences falling into the MEG measurement bandwidth and causing interference. Using prime frequencies allows for different values ​​to be controlled between the modulation frequencies, distributing these differences across the MEG measurement bandwidth. This weakens single interfering frequencies falling within the measurement bandwidth and reduces noise from frequency differences within the measurement bandwidth.

[0049] Step 2: Employ a multi-channel frequency division multiplexing strategy to transmit the modulated drive signal to each fNIRS light source, so that each fNIRS light source emits infrared light to detect the target.

[0050] This invention employs a multi-channel frequency division multiplexing strategy, allocating an independent modulation frequency to each near-infrared light source and distinguishing different detection channels through frequency coding. This avoids the sampling rate loss and electromagnetic interference caused by traditional time division multiplexing. This technology can increase the fNIRS sampling rate to over 100Hz while reducing crosstalk between adjacent channels.

[0051] In one embodiment, the present invention reduces the time resolution performance requirements of the output device by controlling the frequency interval, alleviating the pressure on the filter performance during demodulation, while supporting the driving of more light sources. For example, when using a device with a 100kHz sampling rate for modulated signal output and a 4th-order Butterworth filter with a cutoff frequency of 200Hz for demodulation, the minimum interval between the modulation frequencies used by the two light source channels is greater than or equal to 450Hz, which can guarantee the high sampling rate requirement of 100Hz-200Hz for near-infrared data from 32 light sources.

[0052] Step 3: Demodulate the detected infrared light to obtain the amplitude of the detected infrared light.

[0053] This invention uses coherent demodulation. However, unlike traditional coherent demodulation, this invention incorporates phase-preserving filtering technology to extract the light intensity information of the target frequency band during the signal demodulation stage, enabling rapid demodulation while effectively suppressing aliasing effects caused by environmental noise (such as power line interference and motion artifacts). The steps for demodulating near-infrared signals are as follows: Figure 2 As shown. The acquired near-infrared signal can be represented as

[0054]

[0055] Where t represents time, ω c It is the target frequency, H c (t) is the amplitude obtained from demodulation, representing the light intensity as a function of time. It is the phase of the target signal, H(t), ω, These represent the amplitude, frequency, and phase of other frequency signals, respectively. It includes low-frequency ambient noise and other modulated frequency signals that may be received.

[0056] First, let equation 1 and cos(ω) be used in this invention. c Multiplying t) together, and combining with the product-to-sum formulas for trigonometric functions, we get

[0057]

[0058] Let equation 1 and sin(ω) c Multiplying t) together, and combining with the product-to-sum formulas for trigonometric functions, we get

[0059]

[0060] Next, low-pass filtering is applied to equations (2) and (3). The parameters of the low-pass filter are determined based on the signal component with the lowest frequency value in equations (2) and (3). The cutoff frequency should be lower than this frequency value. The smaller this frequency value, the higher the order should be to ensure the filtering effect. When high-frequency modulation is used, the lowest frequency in equations (2) and (3) should be |ω-ω c |, which is the minimum difference between the frequency points used in high-frequency modulation. If the lowest frequency is 500Hz, a Butterworth filter with a cutoff frequency of 200Hz and an order of 4 can be used to ensure the filtering effect. After filtering, equations (4) and (5) are obtained, and A and B are used to represent the results respectively, so as to show the next step of calculation. This step can filter out ω, which is the noise and other modulation frequency part contained in equation (1), and effectively suppress environmental noise while extracting the target frequency.

[0061] It should be noted that traditional coherent demodulation does not consider the phase of the signal to be demodulated. and Equation (5) in this step will become... This means that the amplitude of the target frequency signal is assumed to be obtained. However, in actual signal acquisition, due to the performance of the signal output device and the circuit components involved, the received signals from different channels often have a certain phase difference, and the obtained B will not be the accurate amplitude of the target signal. Therefore, it is necessary to consider... and The impact of demodulation will be calculated in the next step.

[0062] Finally, through calculation That is, the formula (5) contains Partial elimination yields the accurate amplitude H corresponding to the target frequency in the signal. c (t), based on the target sampling rate, downsampling and smoothing filtering are performed, and the result is used as light intensity for near-infrared signal preprocessing;

[0063] In one optimized embodiment of the present invention, GPU acceleration can be applied to the above steps to optimize demodulation, thereby achieving real-time demodulation and improving experimental efficiency.

[0064] The modulation and demodulation methods described above enable both frequency-division driving of near-infrared light sources and rapid analysis of multimodal data. In practical applications, the implementation of each module can be flexibly adjusted according to actual conditions and requirements.

[0065] Furthermore, the brain magnetoencephalography (MEG) signal processing part of the present invention can use OPM-MEG (optically pumped magnetometer magnetoencephalography) and is also applicable to conventional SQUID magnetoencephalography.

[0066] The present invention will now be explained using the modulation frequency of a near-infrared light source actually used in a magnetoencephalography-near-infrared imaging experiment.

[0067] The number of modulation frequencies is determined by the number of light sources. The number of modulation frequencies is the product of the number of light sources and the number of wavelengths used by a single light source. For example, using 32 dual-wavelength light sources requires 64 modulation frequencies. Prime-number modulation frequencies are allocated based on the relative positions of the light sources and detectors. The detector distinguishes light sources at different positions based on the modulation frequency; that is, all light sources received by a single detector cannot use the same modulation frequency. A prime-number frequency of 2687Hz is chosen as the starting point. To achieve a high sampling rate of 200Hz after demodulation, a prime-number frequency selection standard of 450Hz or higher is chosen. Based on the highest sampling rate of 100kHz used for acquiring the modulation signal, the modulation frequency is controlled to be less than one-quarter of the highest sampling rate to prevent frequency aliasing. Ultimately, frequencies up to 24967Hz can be obtained. Specific frequencies are as follows: Figure 3As shown, there are a total of 50 prime frequencies, and the total number of selected modulation frequencies is less than 64. In order to distinguish all the light sources that the same detector may receive, seven light sources are further selected for frequency reuse based on the relative position and distance between the light source and the detector. Among all detectors that can receive seven light sources, the spacing between each pair is controlled within 9 cm, and the final arrangement of modulation frequencies is completed.

[0068] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can make modifications and changes to the above embodiments without departing from the spirit and scope of the invention. Therefore, the scope of protection of the present invention should be as set forth in the claims.

Claims

1. A multi-channel near-infrared high sampling rate modulation method compatible with magnetoencephalography (MEG), characterized in that, The method includes: The driving signal of the fNIRS light source is modulated onto a high-frequency carrier wave; A multi-channel frequency division multiplexing strategy is adopted to transmit the modulated driving signal to each fNIRS light source so that each fNIRS light source emits infrared light to detect the target. Demodulate the detected infrared light to obtain the amplitude of the detected infrared light; The amplitude of the detected infrared light, obtained by demodulating the infrared light, includes: The infrared light after detection Where t represents time, ω c It is the target frequency, H c (t) represents the amplitude of the detected infrared light as a function of time. H(t) is the phase of the target signal, H(t) is the amplitude of other frequency signals that vary with time, and ω is the frequency of the other frequency signals. It is the phase of other frequency signals, which include: low-frequency ambient noise and other received modulated drive signals; Infrared light Y c respectively with cos(ω) c t) and sin(ω c After multiplying by t), a low-pass filter is used to filter the result. and filtering results based on The amplitude H of the infrared light after detection is obtained. c (t); The model of the low-pass filter is selected by following these steps: The minimum value of the frequency difference used in modulation is Δω = |ω - ω. c |; The model of the low-pass filter is selected based on this minimum value Δω.

2. The method according to claim 1, characterized in that, Algorithms for modulating the driving signal of the fNIRS light source onto a high-frequency carrier include: prime number frequency modulation algorithm or frequency point modulation algorithm with a difference greater than a set value.

3. The method according to claim 1, characterized in that, When employing the aforementioned multi-channel frequency division multiplexing strategy, the frequency interval of each modulated driving signal is calculated through the following steps: Obtain the sampling rate of the modulation output device, the total number of channels in the multi-channel frequency division multiplexing strategy, and the cutoff frequency of the filter used for demodulation; The frequency interval of each modulated drive signal is obtained based on the sampling rate of the modulation output device, the total number of channels in the multi-channel frequency division multiplexing strategy, and the cutoff frequency of the filter used for demodulation.

4. The method according to claim 1, characterized in that, The GPU is used to demodulate and detect the infrared light.

5. The method according to claim 1, characterized in that, The method further includes: Magnetoencephalography (MEG) signals are acquired using optically pumped magnetoencephalography (OPM) or SQUID MEG.

6. A magnetoencephalography-compatible multi-channel near-infrared high sampling rate modulation system, characterized in that, The system includes: The high-frequency modulation module is used to modulate the driving signal of the fNIRS light source onto a high-frequency carrier wave; The multi-channel carrier generation module is used to transmit the modulated drive signal to each fNIRS light source using a multi-channel frequency division multiplexing strategy, so that each fNIRS light source emits infrared light to detect the target. The signal demodulation module is used to demodulate the detected infrared light to obtain the amplitude of the detected infrared light. The amplitude of the detected infrared light, obtained by demodulating the infrared light, includes: The infrared light after detection Where t represents time, ω c It is the target frequency, H c (t) represents the amplitude of the detected infrared light as a function of time. H(t) is the phase of the target signal, H(t) is the amplitude of other frequency signals that vary with time, and ω is the frequency of the other frequency signals. It is the phase of other frequency signals, which include: low-frequency ambient noise and other received modulated drive signals; Infrared light Y c respectively with cos(ω) c t) and sin(ω c After multiplying by t), a low-pass filter is used to filter the result. and filtering results based on The amplitude H of the infrared light after detection is obtained. c (t); The model of the low-pass filter is selected by following these steps: The minimum value of the frequency difference used in modulation is Δω = |ω - ω. c |; The model of the low-pass filter is selected based on this minimum value Δω.

7. An electronic device, characterized in that, The electronic device includes: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, it implements the MEG-compatible multichannel near-infrared high sampling rate modulation method as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions, which, when executed by a processor, implement the MEG-compatible multichannel near-infrared high sampling rate modulation method as described in any one of claims 1-5.

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