Intracranial multi-modal signal detection apparatus and method based on field effect transistors

Abstract

This disclosure provides a device and method for intracranial multimodal signal detection based on field-effect transistors (FETs). The device includes: a neural probe comprising multiple parallel FETs, each FET configured to acquire extracellular potential signals and brain chemical concentration signals at different locations within the intracranial cavity, and to generate corresponding composite electrical signals using the extracellular potential signals and brain chemical concentration signals at each location; and a decoupling unit electrically connected to the neural probe, configured to acquire each composite electrical signal from the neural probe and decouple each composite electrical signal into a high-frequency physiological electrical signal corresponding to the extracellular potential signal and a low-frequency chemical electrical signal corresponding to the brain chemical concentration signal. This embodiment can simultaneously and accurately acquire high-frequency physiological electrical signals and low-frequency chemical electrical signals at the same location within the intracranial cavity.

Description

Technical Field

[0001] The embodiments of this application relate to the technical fields of signal sensing and processing as well as biomedical engineering, and particularly to an intracranial multimodal signal detection device and method based on field-effect transistors. Background Technology

[0002] In neuroscience, the ability to accurately and synchronously acquire information about brain activity, that is, the neural signals generated by intracranial neural activity, is crucial for neuroscientific research and the diagnosis and treatment of neurological diseases.

[0003] Among the methods for detecting relevant intracranial signals, intracranial signals can be divided into two categories: one is the action potential of neurons, i.e., the discharge signal of neurons, also known as the extracellular potential signal; the other is the chemical concentration signal related to the concentration of neurotransmitters, ions, and / or glucose and other chemical substances between neurons.

[0004] Therefore, extracellular potential signals of neurons can be recorded using electrophysiological probes equipped with microelectrode arrays, and chemical concentration signals can be detected using electrochemical sensors, such as microelectrode-modified voltammetric sensors.

[0005] However, since electrophysiological probes and electrochemical sensors are two different detection devices, it is usually necessary to use them independently to record and detect the relevant signals.

[0006] However, when different signals are detected by two different detection devices, time asynchrony and spatial position deviation often occur between the two detection devices. This makes it impossible to accurately reflect the dynamic real-time correlation between the extracellular potential signal of neurons and the chemical concentration signal in the same local brain region. Therefore, it seriously restricts the in-depth study of neural circuit mechanisms and brain functional connections. Moreover, repeated implantation into the brain can easily cause brain tissue damage.

[0007] In the detection of relevant intracranial signals, the method of integrating the functions of recording the extracellular potential signal of neurons and detecting the concentration signal of chemicals into a single probe usually adopts a separate electrode combination. That is, the relevant signal is obtained by two different electrodes set on the same probe. However, this method has problems such as low integration, signal crosstalk, large size and complex manufacturing process. It is also difficult to achieve long-term stable synchronous monitoring with high spatiotemporal resolution. In other words, it is impossible to accurately locate the signal source in space for a long time, and it is also impossible to capture the rapid dynamic changes of the signal in time. Summary of the Invention

[0008] In view of this, embodiments of the present disclosure propose an intracranial multimodal signal detection device and method based on field-effect transistors.

[0009] In a first aspect, embodiments of this disclosure provide an intracranial multimodal signal detection device based on a field-effect transistor, the device comprising: The neural probe includes multiple parallel field-effect transistors, each configured to acquire extracellular potential signals and brain chemical concentration signals at different locations within the brain, and to generate corresponding composite electrical signals using the extracellular potential signals and brain chemical concentration signals at each location. A decoupling unit is electrically connected to the neural probe. The decoupling unit is configured to acquire each composite electrical signal from the neural probe and decouple each composite electrical signal into a high-frequency physiological electrical signal corresponding to the extracellular potential signal and a low-frequency chemical electrical signal corresponding to the brain chemical concentration signal.

[0010] In some alternative implementations, each field-effect transistor includes: The source is configured to receive the static electrical signal inherent in the neural probe; The drain, electrically connected to the decoupling unit, is configured to output a corresponding composite electrical signal; A channel is connected between the source and the drain, and the channel is configured to acquire the static electrical signal of the source, acquire the extracellular potential signal in the brain, and acquire the concentration signal of brain chemicals. The channel is also configured to generate and output a corresponding composite electrical signal by superimposing the extracellular potential signal and the brain chemical concentration signal onto the static electrical signal.

[0011] In some alternative implementations, the decoupling unit includes multiple parallel conditioning paths, each of which is electrically connected to a corresponding field-effect transistor. Each conditioning pathway is configured to decouple the corresponding composite electrical signal; In some alternative implementations, each conditioning pathway includes: A high-pass filter is electrically connected to a corresponding field-effect transistor. The high-pass filter is configured to receive the corresponding composite electrical signal and perform high-frequency filtering on the corresponding composite electrical signal to obtain the corresponding high-frequency physiological electrical signal. A low-pass filter is electrically connected to a corresponding field-effect transistor. The low-pass filter is configured to receive the corresponding composite electrical signal, perform low-frequency filtering on the corresponding composite electrical signal, and obtain the corresponding low-frequency chemical electrical signal.

[0012] In some alternative implementations, the decoupling unit includes: The analog-to-digital converter is electrically connected to each field-effect transistor and is configured to obtain the corresponding composite electrical signal from each field-effect transistor and convert each composite electrical signal into the corresponding composite digital signal. A digital filter, electrically connected to the analog-to-digital converter, is configured to acquire each composite digital signal from the analog-to-digital converter, simultaneously extract the corresponding high-frequency signal and the corresponding low-frequency signal from each composite digital signal, determine each high-frequency signal as the corresponding high-frequency physiological electrical signal, and determine each low-frequency signal as the corresponding low-frequency chemical electrical signal.

[0013] In a second aspect, embodiments of this disclosure provide a method for detecting intracranial multimodal signals based on field-effect transistors, applied to an intracranial multimodal signal detection device based on field-effect transistors as described in any implementation of the first aspect, the method comprising: Acquire extracellular potential signals and brain chemical concentration signals at different locations within the brain; The extracellular potential signals and brain chemical concentration signals at each location are used to generate corresponding composite electrical signals; Each composite electrical signal is decoupled into a high-frequency physiological electrical signal corresponding to the extracellular potential signal and a low-frequency chemical electrical signal corresponding to the brain chemical concentration signal.

[0014] In some optional implementations, a corresponding composite electrical signal is generated using extracellular potential signals and brain chemical concentration signals at each location, including: When each field-effect transistor of the intracranial multimodal signal detection device based on field-effect transistors is connected to the same and constant static electrical signal, the extracellular potential signal and the corresponding brain chemical concentration signal of each field-effect transistor are superimposed on the corresponding static electrical signal to obtain the corresponding composite electrical signal.

[0015] Accordingly, the extracellular potential signals and corresponding brain chemical concentration signals of each field-effect transistor are superimposed on the corresponding static electrical signals to obtain the corresponding composite electrical signals, including: The channel conductivity of the field-effect transistor at the corresponding location is modulated at high frequency by using the extracellular potential signal at the location of each field-effect transistor. By using the concentration signals of brain chemicals at the locations of each field-effect transistor, the channel conductivity of the corresponding field-effect transistor is modulated at low frequency to obtain the channel conductivity after the superposition of high-frequency modulation and low-frequency modulation. By adjusting the conductivity of the superimposed channels to obtain the corresponding static electrical signal, the corresponding composite electrical signal is obtained.

[0016] In some optional embodiments, each composite electrical signal is decoupled into a high-frequency physiological electrical signal corresponding to the extracellular potential signal and a low-frequency chemoelectric signal corresponding to the brain chemical concentration signal, including: The high-pass filter corresponding to each field-effect transistor in the preset decoupling unit is used to perform high-frequency filtering on the corresponding composite electrical signal to obtain the corresponding high-frequency physiological electrical signal. The low-pass filter corresponding to each field-effect transistor in the preset decoupling unit is used to perform low-frequency filtering on the corresponding composite electrical signal to obtain the corresponding low-frequency physiological electrical signal.

[0017] In some optional embodiments, each composite electrical signal is decoupled into a high-frequency physiological electrical signal corresponding to the extracellular potential signal and a low-frequency chemoelectric signal corresponding to the brain chemical concentration signal, including: Convert each composite electrical signal into a corresponding composite digital signal; The corresponding high-frequency signal and the corresponding low-frequency signal are extracted simultaneously from each composite digital signal. Each high-frequency signal is identified as the corresponding high-frequency physiological electrical signal, and each low-frequency signal is identified as the corresponding low-frequency chemical electrical signal.

[0018] To address the issue that separate electrode combinations of neural probes cannot accurately reflect the extracellular potential signals and chemical concentration signals of neurons in the same local brain region, the embodiments of this disclosure provide an intracranial multimodal signal detection device and method based on field-effect transistors. Through integrated design, this device achieves simultaneous acquisition and decoupling of two types of key signals from different locations within the brain. On one hand, the device utilizes multiple parallel structures of neural probes to simultaneously acquire extracellular potential-related signals and brain chemical concentration-related signals from different locations, generating a composite electrical signal. Then, a decoupling unit precisely separates the two types of signals, effectively avoiding the temporal asynchrony and spatial positional deviations inherent in traditional separate detection devices. This accurately reflects the dynamic real-time correlation between the two types of signals in the same brain region, providing more reliable data support for neuroscience research and the diagnosis and treatment of neurological diseases. On the other hand, this device eliminates the need for multiple intracranial implantations, reducing the risk of brain tissue damage. Simultaneously, the integrated detection and decoupling design simplifies the signal acquisition process, improves detection efficiency, and broadens the applicability of the device. Attached Figure Description

[0019] Other features, objects, and advantages of this disclosure will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings. The drawings are for illustrative purposes only and are not intended to limit the invention. In the drawings: Figure 1 This is a structural diagram of one embodiment of an intracranial multimodal signal detection device based on a field-effect transistor disclosed herein; Figure 2 This is a structural diagram of an embodiment of the field-effect transistor of this disclosure; Figure 3 This is a structural diagram of one embodiment of the decoupling unit of this disclosure; Figure 4 This is a structural diagram of another embodiment of the decoupling unit of this disclosure; Figure 5A flowchart of one embodiment of the intracranial multimodal signal detection method based on field-effect transistors according to the present disclosure; Figure 6A This is a flowchart of an embodiment of the decomposition process 6030A according to step 603 of the present disclosure; Figure 6B This is a breakdown flowchart of an embodiment of the breakdown process 6030B according to one embodiment of step 603 of the present disclosure.

[0020] Explanation of reference numerals / symbols in the attached diagram: 100: Intracranial multimodal signal detection device based on field-effect transistor; 101: Neural probe; 1011: Field-effect transistor; 10111: Source; 10112: Drain; 10113: Channel; 102: Decoupling unit; 1021: Conditioning path; 10211: High-pass filter; 10212: Low-pass filter; 1022: Analog-to-digital converter; 1023: Digital filter. Detailed Implementation

[0021] The present disclosure will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.

[0022] It should be noted that, unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other. This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0023] Figure 1 An embodiment of an intracranial multimodal signal detection device 100 based on a field-effect transistor of the present disclosure is shown.

[0024] like Figure 1 As shown, the intracranial multimodal signal detection device 100 based on field-effect transistors includes a neural probe 101 and a decoupling unit 102.

[0025] The main body of the neural probe 101 is made of a flexible material, which can be a flexible micro- or nano-fabricated substrate, such as polyimide. In other cases, the neural probe can also be a rigid probe. It should be noted that the terms "rigid" and "flexible" here are unrelated to field-effect transistors, but only refer to the mechanical strength of the probe.

[0026] The neural probe 101 has a slender implantable portion at the front end and a circuit adapter board at the rear end.

[0027] The implant is designed for intracranial placement, thereby exposing the neural probe 101 to the physiological environment of the brain, which is conductive cerebrospinal fluid.

[0028] Furthermore, a plurality of field-effect transistors 1011 are disposed in the front end of the neural probe 101. Each field-effect transistor 1011 can be arranged in a line from the front end to the rear end of the neural probe 101. Each field-effect transistor 1011 is immersed in conductive cerebrospinal fluid. Accordingly, when the neural probe 101 is exposed to the physiological environment of the brain in a vertical or tilted position, each field-effect transistor 1011 can be located at different depths in the intracranial brain.

[0029] The field-effect transistors 1011 can be connected in parallel, so that each field-effect transistor 1011 can simultaneously acquire intracranial signals at different depths of the brain.

[0030] Specifically, each field-effect transistor 1011 can acquire extracellular potential signals and brain chemical concentration signals at corresponding locations within the brain.

[0031] The extracellular potential signal can be, for example, a signal of extracellular potential change caused by the neuron at the location of the field-effect transistor 1011 generating electrical activity.

[0032] The brain chemical concentration signal can be, for example, a signal of a change in the concentration of a predetermined brain chemical substance at the location of the field-effect transistor 1011.

[0033] Based on this, each field-effect transistor 1011 can superimpose the extracellular potential signal at the corresponding location and the brain chemical concentration signal at the corresponding location to obtain the composite electrical signal corresponding to that location.

[0034] Furthermore, at each moment, each field-effect transistor 1011 can simultaneously output the composite electrical signal acquired at the corresponding position, and the composite electrical signal at each position can be transmitted from the corresponding field-effect transistor 1011 to the back end of the neural probe 101.

[0035] In this embodiment, the decoupling unit 102 of the intracranial multimodal signal detection device 100 based on field-effect transistors is electrically connected to the rear end of the neural probe 101, thereby obtaining composite electrical signals from various locations from the neural probe 101.

[0036] Furthermore, the decoupling unit 102 can be used to decouple various composite electrical signals to obtain high-frequency physiological electrical signals and low-frequency chemical electrical signals, thereby completing the detection of intracranial signals.

[0037] Among them, the signal of extracellular potential change caused by the electrical activity of neurons can be, for example, local field potential and / or action potential. The frequency of local field potential is usually above 0.5 Hz and below 500 Hz, and the frequency of action potential is usually above 1000 Hz. The frequency of the signal of brain chemical concentration change, i.e., brain chemical concentration signal, is usually below 0.1 Hz. Therefore, relative to the frequency of brain chemical concentration signal, extracellular potential signal is a high-frequency physiological electrical signal, while brain chemical concentration signal is a low-frequency chemical electrical signal.

[0038] Therefore, the decoupling unit can be an electronic device with frequency filtering or filtering functions, such as a computer device capable of filtering a specified frequency.

[0039] Furthermore, the computer device serving as decoupling unit 102 can filter high-frequency physiological electrical signals above 0.5Hz and / or 1000Hz for each composite electrical signal it receives, and the resulting high-frequency physiological electrical signals can be identified as corresponding high-frequency extracellular potential signals; the computer device serving as decoupling unit 102 can filter low-frequency chemical electrical signals below 0.1Hz for each composite electrical signal it receives, and the resulting low-frequency chemical electrical signals can be identified as corresponding low-frequency brain chemical concentration signals.

[0040] Based on this, the synergistic design of the neural probe 101 and the decoupling unit 102 achieves high efficiency and accuracy in intracranial multimodal signal detection based on field-effect transistors. Multiple parallel field-effect transistors 1011 on the neural probe 101 can simultaneously acquire extracellular potential signals and brain chemical concentration signals from different locations within the brain, generating composite electrical signals. This eliminates the need for separate detection by multiple independent devices, avoiding the temporal asynchrony and spatial location deviations inherent in traditional separate detection methods. It accurately reflects the dynamic correlation between the two types of signals in the same brain region, providing reliable data support for neuroscience research and the diagnosis and treatment of neurological diseases. Simultaneously, the decoupling unit 102 can accurately separate the composite electrical signals into high-frequency physiological electrical signals and low-frequency chemical electrical signals, completely preserving the original information of both types of signals. Furthermore, the device only requires a single implantation to complete the synchronous detection of multiple locations and types of signals, reducing the risk of brain tissue damage and improving the safety and practicality of the detection.

[0041] In some alternative implementations, refer to Figure 2 This illustrates one embodiment of the field-effect transistor 1011 of this disclosure.

[0042] like Figure 2 As shown, each field-effect transistor 1011 includes a source 10111, a drain 10112, and a channel 10113.

[0043] Among them, the source 10111 can be connected to a built-in static electrical signal.

[0044] Specifically, since each field-effect transistor 1011 is essentially a semiconductor device that requires power to operate, a baseline current can be applied during the operation of the neural probe 101. This baseline current does not originate from the neural environment of the brain, nor is it actively generated by the probe. Instead, it can be externally applied to the intracranial multimodal signal detection device 100 based on field-effect transistors and remain constant without the influence of the brain's physiological environment. This baseline current can be directly input to the source 10111 of each field-effect transistor 1011, thereby providing a bias power supply signal, i.e., a static electrical signal, to drive each field-effect transistor 1011 in the neural probe 101.

[0045] The channel 10113 of each field-effect transistor 1011 is connected between the source 10111 and the drain 10112 of the field-effect transistor 1011. After a static electrical signal is connected to its source 10111, the static electrical signal can be input into the channel 10113.

[0046] Each channel 10113 has a specific recognition layer on its surface. The material of the specific recognition layer can be, for example, hydrogel, enzyme, selective thin film or covalent organic framework material. The specific recognition layers of each channel 10113 can be the same or different. Different types of specific recognition layers can be used to selectively detect corresponding chemical substances, such as neurotransmitters such as dopamine, glutamate, serotonin, or other chemical substances such as ions and / or glucose.

[0047] Furthermore, in the absence of the influence of the brain's physiological environment, the channel 10113 of each field-effect transistor 1011 has a constant conductivity.

[0048] Under the influence of the brain's physiological environment, the conductivity of the channel 10113 of each field-effect transistor 1011 can be changed by the extracellular potential signal and the concentration signal of brain chemicals at the location of the field-effect transistor 1011.

[0049] Specifically, on the one hand, the extracellular potential signal generated when the neuron generates electrical activity will affect the conductivity of the corresponding channel 10113, thereby causing the baseline current in the channel 10113, i.e. the static electrical signal, to change.

[0050] On the other hand, changes in the concentration of predetermined brain chemicals in the neural environment, i.e., brain chemical concentration signals, will bind to or react with the specific recognition layer of the corresponding channel 10113, thereby causing changes in the conductivity of the channel 10113, which in turn causes changes in the baseline current in the channel 10113, i.e., the static electrical signal.

[0051] In other cases, the neural probe 101 also includes a gate that is also immersed in the neural environment. In this case, the various field-effect transistors 1011 of the neural probe 101 share the same gate, that is, the gate can simultaneously control the turning on and off of each field-effect transistor 1011.

[0052] Accordingly, the channel 10113 of each field-effect transistor 1011 may not be provided with a specific recognition layer, and the specific recognition layer may be provided on the surface of the gate. In this way, when the concentration change of a predetermined brain chemical substance in the neural environment, i.e., the brain chemical substance concentration signal, combines with or reacts with the specific recognition layer of the gate, the potential of the gate is changed, thereby causing the baseline current in each field-effect transistor 1011, i.e., the static electrical signal, to change.

[0053] Based on this, for any field-effect transistor 1011, the extracellular potential signal and the brain chemical concentration signal at its corresponding position can be simultaneously superimposed on the static electrical signal of the same channel 10113, thereby changing the static electrical signal and obtaining a composite electrical signal after the superposition of the extracellular potential signal and the brain chemical concentration signal.

[0054] Furthermore, the channel 10113 of each field-effect transistor 1011 can output the composite electrical signal to the drain 10112. The drain 10112 of each field-effect transistor 1011 is electrically connected to the decoupling unit 102. Accordingly, the corresponding composite electrical signal can be output to the decoupling unit 102 from each drain 10112.

[0055] Based on this, by optimizing the structure of the field-effect transistor 1011, efficient integration and precise output of two types of intracranial signals were achieved. The static electrical signal connected to the source 10111 provides a stable reference for signal acquisition. The channel 10113, as the core signal interaction component, can simultaneously capture intracranial extracellular potential signals and brain chemical concentration signals, and generate a composite electrical signal through signal superposition, eliminating the need for additional signal integration components and simplifying the signal acquisition process. Simultaneously, the channel 10113 can change its conductivity through interaction with brain chemicals or by the influence of extracellular potential, thereby precisely modulating the static electrical signal. This ensures that the composite electrical signal fully retains the characteristics of both extracellular potential and brain chemical concentration signals, providing a high-quality input basis for signal separation in the subsequent decoupling unit 102, and improving the signal acquisition accuracy and reliability of the entire detection device. Furthermore, the integrated structural design of the field-effect transistor 1011 avoids the signal crosstalk problem of discrete components, and the flexible configuration of the gate and channel 10113 enhances the device's adaptability to different brain chemicals, broadening the detection range.

[0056] In some alternative implementations, see below. Figure 3 This illustrates one embodiment of the decoupling unit 102 of this disclosure.

[0057] like Figure 3 As shown, the decoupling unit 102 is provided with multiple conditioning pathways 1021.

[0058] Each conditioning path 1021 is independent of each other and is connected in parallel. Accordingly, each conditioning path 1021 is electrically connected to the drain 10112 of a corresponding field-effect transistor 1011, so that the corresponding composite electrical signal can be received from the drain 10112 of the corresponding field-effect transistor 1011 and the composite electrical signal can be decoupled independently.

[0059] Specifically, such as Figure 3 As shown, each conditioning path 1021 includes a high-pass filter 10211 with a high-speed wide-bandwidth amplifier and a low-pass filter 10212 with a low-noise amplifier and an ultra-low cutoff frequency.

[0060] Accordingly, the decoupling unit 102 can copy each of the composite electrical signals it receives to obtain two identical composite electrical signals, so that one of the composite electrical signals can be input to the high-pass filter 10211 and the other identical composite electrical signal can be input to the low-pass filter 10212 at the same time.

[0061] Because extracellular potential signals are high-frequency, the high-pass filter 10211 can accurately and losslessly extract the high-frequency physiological electrical signal corresponding to the high-frequency extracellular potential signal from the composite electrical signal.

[0062] Because the brain chemical concentration signal has a low frequency characteristic, the low-pass filter 10212 can accurately and losslessly extract the low-frequency chemical electrical signal corresponding to the low-frequency brain chemical concentration signal from the composite electrical signal.

[0063] Based on this, efficient and accurate decoupling of composite electrical signals is achieved through the design of multiple parallel conditioning pathways 1021 in the decoupling unit 102. Each conditioning pathway 1021 corresponds one-to-one with a field-effect transistor 1011, enabling independent processing of a single composite electrical signal, avoiding mutual interference during multi-signal processing, and ensuring the independence and accuracy of signal decoupling. Simultaneously, the high-pass filter 10211 and low-pass filter 10212 in the conditioning pathway 1021 can respectively target the high-frequency characteristics of extracellular potential signals and the low-frequency characteristics of brain chemical concentration signals, completely preserving the key information of both types of original signals, achieving precise separation of high-frequency physiological electrical signals and low-frequency chemical electrical signals, and providing high-quality data support for subsequent signal analysis. This modular decoupling design not only simplifies the signal processing flow but also improves the stability and reliability of the entire detection device, adapting to the needs of simultaneous multi-location detection.

[0064] In some alternative implementations, refer to Figure 4 This illustrates another embodiment of the decoupling unit 102 of this disclosure.

[0065] like Figure 4 As shown, the decoupling unit 102 may include an analog-to-digital converter 1022 and a digital filter 1023.

[0066] The analog-to-digital converter 1022 can be electrically connected to the drain 10112 of each field-effect transistor 1011, so that the analog-to-digital converter 1022 can receive the corresponding composite electrical signal from each field-effect transistor 1011.

[0067] Furthermore, since the composite electrical signal of each field-effect transistor 1011 is an analog signal, the analog-to-digital converter 1022 can convert each composite electrical signal into a composite digital signal, thereby enabling the converted composite digital signal to be applied to the digital filter 1023.

[0068] The digital filter 1023 of the decoupling unit 102 is electrically connected to the analog-to-digital converter 1022.

[0069] The digital filter 1023 can be pre-configured with a digital high-pass filter 10211 and a digital low-pass filter 10212.

[0070] The digital high-pass filter 10211 can be pre-set with a corresponding digital signal filtering algorithm, such as a discrete Fourier transform algorithm or an infinite impulse response algorithm for filtering high-frequency signals. Accordingly, since the extracellular potential signal has a high frequency characteristic, the digital high-pass filter 10211 can extract the high-frequency physiological electrical signal corresponding to the high-frequency extracellular potential signal from each composite electrical signal.

[0071] Furthermore, a corresponding digital signal filtering algorithm can be pre-set in the digital low-pass filter 10212, such as a wavelet transform algorithm for filtering low-frequency signals. Accordingly, since the brain chemical concentration signal has the characteristic of low frequency, the digital low-pass filter 10212 can extract the low-frequency chemical electrical signal corresponding to the low-frequency brain chemical concentration signal from the composite electrical signal.

[0072] Based on this, precise digital decoupling of composite electrical signals is achieved through the collaborative design of analog-to-digital converter 1022 and digital filter 1023. The analog-to-digital converter 1022 efficiently receives the composite electrical signals output from each field-effect transistor 1011 and accurately converts the analog composite electrical signals into composite digital signals, providing highly adaptable input data for subsequent steps and avoiding interference problems that may occur during analog signal transmission. The digital filter 1023 selectively extracts high-frequency and low-frequency signals from the composite digital signals. Using a preset digital signal filtering algorithm, it accurately separates the high-frequency physiological electrical signals corresponding to extracellular potential signals and the low-frequency chemical electrical signals corresponding to brain chemical concentration signals, completely preserving the original characteristics of both types of signals. This digital decoupling method not only improves the accuracy and stability of signal separation but also adapts to the needs of multi-channel synchronous processing, forming an efficient combination with multiple parallel field-effect transistors 1011, further ensuring the reliability and efficiency of detecting multiple types of signals at different locations within the brain.

[0073] In some alternative implementations, refer to Figure 5 The diagram illustrates a flow chart 500 of an embodiment of the intracranial multimodal signal detection method based on field-effect transistors (FETs) of this disclosure. This FET-based intracranial multimodal signal detection method is applied to the FET-based intracranial multimodal signal detection device of any of the foregoing embodiments and includes the following steps 501 to 503: Step 501: Obtain extracellular potential signals and brain chemical concentration signals at different locations within the brain.

[0074] In this step, the neural probe can be placed in the neural environment of the intracranial brain, that is, immersed in the cerebrospinal fluid. Since the cerebrospinal fluid has the property of conducting electricity, the extracellular potential signal caused by the electrical activity of brain neurons, as well as the concentration change of predetermined brain chemicals in the neural environment, that is, the brain chemical concentration signal, can be transmitted to the various field-effect transistors of the neural probe through the cerebrospinal fluid.

[0075] based on Figure 1 The vertical arrangement of multiple field-effect transistors in the neural probe allows each field-effect transistor to detect extracellular potential signals and brain chemical concentration signals at different depths.

[0076] Step 502: Generate corresponding composite electrical signals using extracellular potential signals and brain chemical concentration signals at each location.

[0077] In this step, a constant baseline current can be provided to the neural probe in advance. When the neural probe is connected to the baseline current and the various field-effect transistors are connected in parallel, when the baseline current is connected to each field-effect transistor, a bias power supply signal can be provided to drive each field-effect transistor in the neural probe to work. That is, the same and constant static electrical signal is formed in each field-effect transistor.

[0078] Furthermore, based on the extracellular potential signal and brain chemical concentration signal obtained by each field-effect transistor in step 501 above, each field-effect transistor can superimpose the extracellular potential signal and brain chemical concentration signal near its position onto the static electrical signal of the field-effect transistor, thereby adjusting the static electrical signal of the field-effect transistor into a composite electrical signal.

[0079] Specifically, since the extracellular potential signal generated by the neuron when it generates electrical activity affects the conductivity of the channel at the corresponding location, the baseline current connected to the channel of the field-effect transistor, i.e., the static electrical signal, will change with the conductivity of the channel.

[0080] Since the extracellular potential signal is high frequency, the modulation of the channel conductivity by the extracellular potential signal is also high frequency, thereby achieving high frequency modulation of the static electrical signal in each channel.

[0081] Since the concentration signal of brain chemicals is low frequency, the modulation of the conductivity of the channel by the extracellular potential signal is also low frequency, thus achieving low frequency modulation of the static electrical signal in each channel.

[0082] Based on this, the conductivity of the channel of each field-effect transistor is simultaneously subjected to composite modulation of high-frequency modulation and low-frequency modulation, thus obtaining the conductivity after superimposed modulation.

[0083] Based on the conductivity after superposition modulation, the static electrical signal in the channel also changes accordingly. That is, the conductivity after superposition modulation will regulate the static electrical signal and adjust it into a composite electrical signal that corresponds to the conductivity after superposition modulation, which superimposes high-frequency extracellular potential signals and low-frequency brain chemical concentration signals.

[0084] Step 503: Decouple each composite electrical signal into a high-frequency physiological electrical signal corresponding to the extracellular potential signal and a low-frequency chemical electrical signal corresponding to the brain chemical concentration signal.

[0085] In this step, based on the composite electrical signals of each field-effect transistor obtained in step 502, since each composite electrical signal of a field-effect transistor is obtained by superimposing a high-frequency extracellular potential signal and a low-frequency brain chemical concentration signal, the decoupling unit of the intracranial multimodal signal detection device based on field-effect transistors can decouple the composite electrical signals of each field-effect transistor, thereby extracting the high-frequency and low-frequency signals from the composite electrical signals respectively, and using the high-frequency signal as the extracellular potential signal and the low-frequency signal as the brain chemical concentration information signal superimposed on the extracellular potential signal.

[0086] Based on this, multiple field-effect transistors on the neural probe are used to simultaneously capture extracellular potential signals and brain chemical concentration signals at different locations within the brain. This eliminates the need for separate equipment and steps, avoiding the temporal asynchrony and spatial bias problems of traditional detection methods, and enabling precise correlation of the dynamic changes of the two types of signals in the same brain region. Then, by superimposing the two types of signals to generate a composite electrical signal, subsequent decoupling processing separates the high-frequency physiological electrical signal and the low-frequency chemical electrical signal. This process not only fully preserves the key features of the original signal but also simplifies the signal processing flow, ensuring the accuracy and integrity of the detection data. This provides reliable technical support for neuroscience research and the diagnosis and treatment of neurological diseases. Furthermore, a single detection can complete signal acquisition at multiple locations, reducing the risk of brain tissue damage and improving the safety and practicality of the detection method.

[0087] In some alternative implementations, the composite electrical signals can be decoupled using physical filters, which include high-pass and low-pass filters. (Continue to the previous section) Figure 6A This illustrates a decomposition process 6030A of one embodiment of step 603 of this disclosure. The decomposition process 6030A includes the following steps 6031A to 6032A: Step 6031A: High-frequency filtering of the corresponding composite electrical signal is performed using the high-pass filter corresponding to each field-effect transistor in the preset decoupling unit to obtain the corresponding high-frequency physiological electrical signal.

[0088] In this step, multiple conditioning paths can be pre-set in the decoupling unit, and a high-pass filter can be set in each conditioning path. Each conditioning path is used to decouple a corresponding composite electrical signal.

[0089] Accordingly, the decoupling unit can input each composite electrical signal it receives into the corresponding conditioning path.

[0090] Furthermore, the intracranial multimodal signal detection device based on field-effect transistors can use each conditioning path to replicate the received composite electrical signal to obtain two identical composite electrical signals, and input one of the composite electrical signals into a high-pass filter.

[0091] Because extracellular potential signals are high-frequency, high-pass filters can accurately and non-destructively extract high-frequency physiological electrical signals corresponding to high-frequency extracellular potential signals from composite electrical signals.

[0092] Step 6032A: Use the low-pass filter corresponding to each field-effect transistor in the preset decoupling unit to perform low-frequency filtering on the corresponding composite electrical signal to obtain the corresponding low-frequency physiological electrical signal.

[0093] In this step, based on the two identical composite electrical signals replicated in each conditioning pathway, the intracranial multimodal signal detection device based on field-effect transistors can input the other composite electrical signal into the low-pass filter of the corresponding conditioning pathway.

[0094] Because brain chemical concentration signals are low-frequency, low-pass filters can accurately and losslessly extract the low-frequency chemical electrical signals corresponding to the low-frequency brain chemical concentration signals from composite electrical signals.

[0095] Based on this, precise and efficient decoupling of composite electrical signals was achieved through the coordinated design of high-pass and low-pass filters. Each field-effect transistor's corresponding conditioning pathway can independently process the composite electrical signal. The signal is first copied and then input into the two types of filters, ensuring both the independence of signal processing and avoiding mutual interference between multiple signals. The high-pass filter can specifically extract high-frequency components from the composite electrical signal, accurately restoring the high-frequency physiological electrical signals corresponding to the extracellular potential signal; the low-pass filter focuses on capturing low-frequency components, completely preserving the low-frequency chemical electrical signals corresponding to the brain chemical concentration signal. The specialized filtering design of the two types of filters ensures that the original signal characteristics are not lost, providing high-quality data support for subsequent neuroscience research and diagnostic analysis. Simultaneously, this physical filter-based decoupling method is simple in process and has a fast response, forming an efficient combination with the synchronous detection function of multiple parallel field-effect transistors, further improving the stability and practicality of the entire field-effect transistor-based intracranial multimodal signal detection device.

[0096] In some alternative implementations, composite electrical signals can be decoupled using digital filtering, wherein the decoupling unit may include an analog-to-digital converter and a digital filter. (Continue to refer to...) Figure 6B This illustrates a decomposition process 6030B of another embodiment of step 603 of this disclosure. The decomposition process 6030B includes the following steps 6031B to 6032B: Step 6031B: Convert each composite electrical signal into a corresponding composite digital signal.

[0097] In this step, the intracranial multimodal signal detection device based on field-effect transistors can also decouple the composite electrical signal through the digital filter set in its decoupling unit. Since the composite electrical signal is an analog signal, the intracranial multimodal signal detection device based on field-effect transistors can convert the composite electrical signal of each field-effect transistor into a composite digital signal through an analog-to-digital converter, so that each composite digital signal after conversion can be used in the digital signal filtering algorithm in the digital filter.

[0098] Step 6032B: Simultaneously extract the corresponding high-frequency signal and the corresponding low-frequency signal from each composite digital signal, determine each high-frequency signal as the corresponding high-frequency physiological electrical signal, and determine each low-frequency signal as the corresponding low-frequency chemical electrical signal.

[0099] Based on the composite digital signal obtained in step 6031B above, the intracranial multimodal signal detection device based on field-effect transistors can decouple the composite digital signal through a digital signal filtering algorithm.

[0100] Specifically, digital filters include discrete Fourier transform algorithms or infinite impulse response algorithms for filtering high-frequency signals, as well as wavelet transform algorithms for filtering low-frequency signals.

[0101] Since extracellular potential signals are characterized by high frequency, while brain chemical concentration signals are characterized by low frequency, digital filters can extract high-frequency physiological electrical signals corresponding to high-frequency extracellular potential signals from each composite electrical signal using digital signal filtering algorithms that filter high-frequency signals, and extract low-frequency physiological electrical signals corresponding to low-frequency brain chemical concentration signals from each composite electrical signal using digital signal filtering algorithms that filter low-frequency signals.

[0102] Based on this, a precise and efficient decoupling of composite electrical signals was achieved through a digital processing workflow. The analog-to-digital converter (ADC) accurately converts the analog composite electrical signals output from the field-effect transistor (FET) into composite digital signals, avoiding the interference issues that occur during analog signal transmission and deprocessing, and providing stable and reliable input data for subsequent signal separation. The digital filter, with its preset digital signal filtering algorithm, can simultaneously and accurately extract high-frequency and low-frequency signals from the composite digital signals, respectively restoring extracellular potential signals and brain chemical concentration signals, fully preserving the key features of both types of original signals and ensuring the accuracy of signal analysis. This digital decoupling method is not only convenient to operate and has a fast response time, but it can also be efficiently adapted to the synchronous detection function of multiple parallel FETs, supporting parallel processing of signals from multiple locations. This further improves the overall efficiency and reliability of intracranial multimodal signal detection based on FETs, providing high-quality data support for neuroscience research and clinical diagnosis.

[0103] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

Claims

1. A field-effect transistor-based intracranial multimodal signal detection device, comprising: The neural probe includes multiple parallel field-effect transistors, each configured to acquire extracellular potential signals and brain chemical concentration signals at different locations within the brain, and to generate corresponding composite electrical signals using the extracellular potential signals and brain chemical concentration signals at each location. A decoupling unit is electrically connected to the neural probe. The decoupling unit is configured to acquire each composite electrical signal from the neural probe and decouple each composite electrical signal into a high-frequency physiological electrical signal corresponding to the extracellular potential signal and a low-frequency chemical electrical signal corresponding to the brain chemical concentration signal.

2. The device according to claim 1, wherein, Each field-effect transistor includes: The source is configured to receive the static electrical signal inherent in the neural probe; The drain, electrically connected to the decoupling unit, is configured to output a corresponding composite electrical signal; A channel is connected between the source and the drain, and the channel is configured to acquire the static electrical signal of the source, acquire the extracellular potential signal in the brain, and acquire the concentration signal of brain chemicals. The channel is also configured to generate and output a corresponding composite electrical signal by superimposing the extracellular potential signal and the brain chemical concentration signal onto the static electrical signal.

3. The device according to claim 1, wherein, The decoupling unit includes multiple parallel conditioning paths, each of which is electrically connected to a corresponding field-effect transistor. Each conditioning pathway is configured to decouple the corresponding composite electrical signal.

4. The device according to claim 3, wherein, Each treatment pathway includes: A high-pass filter is electrically connected to a corresponding field-effect transistor. The high-pass filter is configured to receive the corresponding composite electrical signal and perform high-frequency filtering on the corresponding composite electrical signal to obtain the corresponding high-frequency physiological electrical signal. A low-pass filter is electrically connected to a corresponding field-effect transistor. The low-pass filter is configured to receive the corresponding composite electrical signal, perform low-frequency filtering on the corresponding composite electrical signal, and obtain the corresponding low-frequency chemical electrical signal.

5. The device according to claim 1, wherein, The decoupling unit includes: The analog-to-digital converter is electrically connected to each field-effect transistor and is configured to obtain the corresponding composite electrical signal from each field-effect transistor and convert each composite electrical signal into the corresponding composite digital signal. A digital filter, electrically connected to the analog-to-digital converter, is configured to acquire each composite digital signal from the analog-to-digital converter, simultaneously extract the corresponding high-frequency signal and the corresponding low-frequency signal from each composite digital signal, determine each high-frequency signal as the corresponding high-frequency physiological electrical signal, and determine each low-frequency signal as the corresponding low-frequency chemical electrical signal.

6. A method for detecting intracranial multimodal signals based on a field-effect transistor, applied to the intracranial multimodal signal detection device based on a field-effect transistor as described in any one of claims 1-5, the method comprising: Acquire extracellular potential signals and brain chemical concentration signals at different locations within the brain; The extracellular potential signals and brain chemical concentration signals at each location are used to generate corresponding composite electrical signals; Each composite electrical signal is decoupled into a high-frequency physiological electrical signal corresponding to the extracellular potential signal and a low-frequency chemical electrical signal corresponding to the brain chemical concentration signal.

7. The method according to claim 6, wherein, The method of generating corresponding composite electrical signals using extracellular potential signals and brain chemical concentration signals at various locations includes: When each field-effect transistor of the intracranial multimodal signal detection device based on field-effect transistors is connected to the same and constant static electrical signal, the extracellular potential signal and the corresponding brain chemical concentration signal of each field-effect transistor are superimposed on the corresponding static electrical signal to obtain the corresponding composite electrical signal.

8. The method according to claim 7, wherein, The step of superimposing the extracellular potential signals and corresponding brain chemical concentration signals of each field-effect transistor onto the corresponding static electrical signal to obtain the corresponding composite electrical signal includes: The channel conductivity of the field-effect transistor at the corresponding location is modulated at high frequency by using the extracellular potential signal at the location of each field-effect transistor. By using the concentration signals of brain chemicals at the locations of each field-effect transistor, the channel conductivity of the corresponding field-effect transistor is modulated at low frequency to obtain the channel conductivity after the superposition of high-frequency modulation and low-frequency modulation. By adjusting the conductivity of the superimposed channels to obtain the corresponding static electrical signal, the corresponding composite electrical signal is obtained.

9. The method according to claim 6, wherein, The process of decoupling each composite electrical signal into a high-frequency physiological electrical signal corresponding to the extracellular potential signal and a low-frequency chemical electrical signal corresponding to the brain chemical concentration signal includes: The high-pass filter corresponding to each field-effect transistor in the preset decoupling unit is used to perform high-frequency filtering on the corresponding composite electrical signal to obtain the corresponding high-frequency physiological electrical signal. The low-pass filter corresponding to each field-effect transistor in the preset decoupling unit is used to perform low-frequency filtering on the corresponding composite electrical signal to obtain the corresponding low-frequency physiological electrical signal.

10. The method according to claim 6, wherein, The process of decoupling each composite electrical signal into a high-frequency physiological electrical signal corresponding to the extracellular potential signal and a low-frequency chemical electrical signal corresponding to the brain chemical concentration signal includes: Convert each composite electrical signal into a corresponding composite digital signal; The corresponding high-frequency signal and the corresponding low-frequency signal are extracted simultaneously from each composite digital signal. Each high-frequency signal is identified as the corresponding high-frequency physiological electrical signal, and each low-frequency signal is identified as the corresponding low-frequency chemical electrical signal.

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