Graphene transistor system for measuring electrophysiological signals

Abstract

The object of the invention is based on a flexible skin layer and intra-skin array of graphene solution gated field effect transistors (gSGFETs) capable of recording ultra-slow signals as well as signals in the typical local field potential bandwidth. The object of the invention is based on a graphene transistor system for measuring electrophysiological signals, comprising a processing unit and at least one graphene transistor (gSGFET) comprising graphene as a channel material contacted by two terminals, a tunable voltage source on the drain and source terminals of the transistor (gSGFET) referred to as gate voltage, and at least one filter configured to acquire a signal from the transistor and split the signal into at least two frequency bands, a low frequency band and a high frequency band, wherein a first signal and a second signal are amplified with a gain value, respectively.

Description

TECHNICAL FIELD

[0001] The object of the present invention belongs to the field of physical technology, more precisely to the field of measuring electrical signals.

[0002] The object of the present invention is a device for measuring and recording certain electrophysiological signals and a method of using the device. BACKGROUND

[0003] There is an urgent need for flexible, large-scale and high-density arrays with a wide electrophysiological recording bandwidth. Flexible, large-scale and high-density electrode arrays are the latest technology. However, these arrays cannot provide high-fidelity recordings in the entire frequency bandwidth of electrophysiological signals.

[0004] Electrophysiological signals have a wide range of frequencies and amplitudes: from high-amplitude signals that last for minutes (such as cortical spreading depression) to millivolt spikes that last for milliseconds. Recording the full range of electrophysiological signals with high spatio-temporal resolution will help to reveal their relationships and interactions and ensure that no meaningful information is lost.

[0005] Most microelectrode arrays suffer from voltage drift and oscillations that affect their recording performance of ultra-slow signals with frequencies below 0.1 Hz. It is well known that most recording systems include a high-pass filter to address saturation problems due to baseline drift, at the cost of not recording potentially physiological and pathological information.

[0006] In the last few years, there has been particular interest in the fluctuations of brain activity at frequencies below 0.1 Hz, often referred to as very slow, ultra-slow or infra-slow activity (ISA). It is suggested that they are indicative of brain states (e.g. sleep, anaesthesia, coma, wakefulness) and are related to resting-state networks in functional magnetic resonance imaging. They can also greatly contribute to the high variability observed in the temporal course of physiological signals.

[0007] There are some reported ultra-slow signals, such as cortical propagating waves called "cortical spreading depression" (CSD) that are recorded at very low frequencies only, so it is very difficult to study them in the usual way due to the obstruction of current electrodes. CSD is defined as a slow propagating wave of depolarization of neurons and astrocytes, followed by a period of inhibition of brain activity, and is usually triggered when a brain seizure occurs, for example in patients with vascular or traumatic strokes, as well as migraine and other brain diseases. Monitoring or detecting them can improve diagnosis, but most importantly, it can influence changes in therapy.

[0008] Traditionally, non-invasive techniques such as electroencephalography (EEG) and magnetoencephalography (MEG) have been used to perform full-band recordings, including sub-low frequencies. However, their limited spatial resolution and average signal strength impose serious limitations; for example, EEG alone is insufficient for non-invasive CSD detection. For these reasons, invasive electrophysiological techniques are the most commonly used methods for recording ultraslow brain waves.

[0009] Accurate ISA recording requires the use of directly coupled amplifiers and extremely stable, low-impedance invasive electrodes. Traditionally, liquid-filled glass micropipettes have been used, allowing only one or a few measurements. To achieve higher spatial resolution and mapping, non-polarizable silver / silver chloride (Ag / AgCl) electrodes can be used, preventing charge buildup at the interface and thus preventing voltage drift. However, the toxicity of silver makes such electrodes unsuitable for in vivo monitoring in humans or chronically ill animals. While no alternative microelectrode material has yet been found to provide performance comparable to Ag / AgCl electrodes, it has spurred research into alternative microelectrode materials with low impedance and drift. Therefore, current human ISA recordings are performed using platinum electrodes, which present challenges for CSD detection due to artifacts and transients. Importantly, baseline drift, in the form of sub-low frequency baseline oscillations, hinders the determination of its "true" characteristics (e.g., amplitude or waveform), as any high-pass filter used to eliminate this effect alters the shape of the signal.

[0010] Another inherent limitation of microelectrode technology is based on the relationship between the microelectrode impedance and the input impedance of the recording device (Z′, respectively). e and Z′ a The relationship between ).

[0011] Recorded signal (V) in The voltage is determined by a voltage divider formed by two impedances:

[0012]

[0013] Equation (1) implies that when Z′ a In essence, it is no greater than Z′. e At that time, relative to V sig The recorded signal will be attenuated and delayed. Even with a high input impedance amplifier, attenuation is expected to exceed 50% for a 50μm diameter gold microelectrode. It is important to emphasize that, due to the inverse relationship between electrode impedance and its area, resulting in high-pass filtering of the recorded signal, a voltage gain Z′ equal to 1 is achieved when the electrode area is scaled down proportionally. a >>Z′ e The demands have been compromised.

[0014] Thus, miniaturization of electrode size to achieve higher spatial resolution results in inherent high-pass filtering of the ISA due to the associated increase in electrode impedance.

[0015] Invasive optical techniques, such as calcium imaging, are also used to monitor the ISA, but still face challenges in addressing the large number of neurons 24,25 The severe challenge of high-frequency activity, with its inherent indicator requirement, limits translation to the clinic. Thus, there is still a lack of technology that allows the measurement of large-scale, high-spatiotemporal resolution recordings, including ultra-slow frequencies, in a potentially fully implantable, non-toxic, clinical-scale system.

[0016] In addition to the commonly used microelectrode technology, recording electrophysiological signals with field effect transistors (FETs) has many advantages, including less sensitivity to environmental noise due to its inherent voltage-to-current amplification function, and easy multiplexing 26 Nonetheless, the difficulty of combining high-gate capacitance and carrier mobility silicon FETs with flexible materials has historically hindered their use in in vivo recordings. Graphene solution-gated field effect transistors (gSGFETs) have been proposed to potentially overcome most of the previous shortcomings. The flexibility of graphene allows gSGFETs to be embedded in ultra-soft and flexible substrates without losing performance, while its wide electrochemical window and biocompatibility allow it to be directly in contact with biological fluids and tissues and ensure safe operation under in vivo conditions. In addition, the two-dimensional nature of graphene provides the highest surface-to-volume ratio, making graphene very sensitive to the charges on its surface. Importantly, the frequency response of the gSGFET transconductance is flat over a wide bandwidth, including sub-low frequencies.

[0017] On the other hand, graphene-based solution-gated field effect transistors (G-SgFETs) have been extensively studied as potential biosensors for a variety of analytes, such as the sensor for detecting the presence of at least one biological molecule and the method for producing such a sensor, which includes a patterned graphene structure, at least two electrical contacts arranged in contact with the patterned graphene structure to determine the electrical conductivity; and at least one linker connected to at least part of the patterned graphene structure, wherein the at least one linker has a binding affinity for the at least one biological molecule, as disclosed in WO2011004136A1. SUMMARY

[0019] The present invention addresses the need for flexible, large scale and high density arrays with wide electrophysiological recording bandwidth. The object of the present invention is based on graphene solution gated field effect transistors (gSGFETs), preferably arrays of graphene solution gated field effect transistors (gSGFETs) that are capable of recording ultra-slow signals as well as signals in the typical local field potential bandwidth. The graphene solution gated field effect transistors (gSGFETs) are preferably placed at epidermal locations and intracortical locations.

[0020] The present invention overcomes the challenges still present in the prior art by providing a substantially increased baseline stability arising from the electrochemical inertness of graphene, while at the same time, by using transistors as recording elements, it also exceeds the signal attenuation due to the impedance divisor present in electrode recording systems.

[0021] The graphene solution gated field effect transistors (gSGFETs) of the present invention are fabricated using flexible substrates to overcome the difficulty of adapting to the geometry of different biological structures, and therefore the graphene solution gated field effect transistors (gSGFETs) are preferably flexible. Likewise, when arranged in arrays, the arrays are designed in an expandable manner so that the transistors can be scaled from the microscale to the macroscale as needed for different kinds of electrical contacts, such as those located on the surface of the tissue (as opposed to penetrating the tissue).

[0022] Therefore, the graphene transistor system for measuring electrophysiological signals of the present invention comprises a processing unit, and at least one graphene transistor (gSGFET) containing graphene as a channel material, which is contacted by two terminals, an adjustable voltage source on the drain terminal and the source terminal of the transistor (gSGFET) refers to the gate voltage, and

[0023] with at least one filter (low pass filter (LPF) with a gain of 10 4 configured to produce a low pass filtered band with a frequency set between 0 Hz and 0.16 Hz, or a band pass filter (BPF) with a gain of 10 6 configured to produce a frequency band filtered with a frequency between 0.16 Hz and 10 kHz), configured to acquire the signal from the transistor and divide the signal from the transistor into at least two frequency bands, a low frequency band and a high frequency band, connected; and is the first signal and the second signal amplified with a gain value, respectively.

[0024] The method and related devices of the present invention meet the aforementioned needs in the art by providing amplification of the signal and the ability to measure the transistor transfer curve at the recording location. This allows both the selection of the optimal working point of the transistor and the application of a calibration method (current to voltage conversion of the recorded signal) to ensure high fidelity recording in a wide bandwidth.

[0025] The main application of the object of the present invention is in research or clinical implementation, for example in neurology, monitoring full-band brain signals. These same advantages apply to other biological systems outside the brain, such as the heart, kidney, stomach, cranial nerves and other regions. The flexibility and versatility of graphene transistor arrays allow a variety of applications and deployments, ranging from subdural, epidural and intracortical devices to brain, peripheral and cranial nerves, heart, blood vessels, spinal cord and other biological structures or other non-invasive locations similar to electroencephalography.

[0026] The method for measuring electrophysiological signals of the present invention using the described graphene transistor system can comprise the following steps:

[0027] a. dividing the input signal into low frequency signals and high frequency signals by a filter,

[0028] b. merging the low frequency signals and high frequency signals weighted by respective gains, and

[0029] c. converting the signals to voltage according to the intrinsic gain of the transistor.

[0030] The conversion to voltage signals can be performed by using an interpolation of the graphene transistor transfer curve I ds -V gs . BRIEF DESCRIPTION OF DRAWINGS

[0031] To complement the description being made and in order to help a better understanding of the characteristics of the present invention, according to a preferred embodiment of a practical implementation thereof, a set of drawings is attached as an integral part of said description, in which the illustrative and non-limiting character has been represented as follows:

[0032] Figures la-1gRepresentations of flexible graphene solution gated field effect transistor array technology and its characterization are shown. la: Schematic of a graphene transistor polarized in common gate mode. lb: Optical microscope images of the active area of a 4x4 gSGFET array and a 15 channel intracortical array. lc: Photograph of a neural probe. Id: Steady state characteristics of a 100 x 50-μm2gSGFET array in 10 mM phosphate buffered saline (PBS) with a drain-source voltage bias (Vds) of 50 mV. Id: This plot shows the gSGFET transfer curve, drain-source current (Ids) versus gate-source voltage (Vgs) and mean (dark curve) and standard deviation (lighter curve). Boxplot inset shows the charge neutral point dispersion (midline, median; box limits, upper and lower quartiles). le: Plot of the leakage current (Igs) of all gSGFETs in the array. If: Plot of the transfer curve (blue squares and line) of a gSGFET and its first derivative (transconductance (gm), black line). Ig: Plot of the transconductance frequency response at two different points of the transfer curve; (e): Vgs below CNP (green), where gm is negative, resulting in signal inversion (phase of 180°); Vgs above CNP (orange), where gm is positive, so there is no inversion (phase of 0°). The modulus of gm is independent of the branch of the transfer curve of the gSGFET polarization, and the modulus of gm is similar to a wide bandwidth (~0-1 kHz) steady state value.

[0033] Figures 2a to 2d An exemplary embodiment of the present invention is shown, which combines gSGFETs, custom electronic circuitry and post-processing methods, also as an example of recorded signals: ultra-low, local field potential and wide-band in vivo gSGFET recordings of neural signals. Figure 2a is a schematic of the gSGFET recording setup and signal post-processing methods. Custom electronic circuitry is used to perform in vivo characterization (transfer curve) and record transistor current in low pass filtered (LPF) and band pass filtered (BPF) frequency bands. From the combination of these two signals and considering the current to voltage conversion, a wide-band signal (V sig ) can be obtained. Figure 2b , Electrophysiological recordings obtained with a gSGFET epicortical array during induction of four CSD events (blue shading). From top to bottom: current LPF signal, current BPF and voltage converted wide-band signal.

[0034] Figure 3 An exemplary embodiment of the custom electronic circuitry is shown. a, Schematic of the custom electronic instrument used to control the polarization of gSGFETs (V gs , V ds ) and to amplify the two aforementioned frequency bands in different ways: LPF (~0-0.16 Hz, gain = 104 ) and BPF (0.16 Hz - 10 kHz, gain = 10 6 ). We used custom-built electronics to characterize the steady-state behaviour of the gSGFETs and to AC modulate the graphene transistors.

[0035] Figure 4 shows the calibration procedure for recovering the voltage signal at the gate of a gSGFET from the current recordings. a, gSGFET current recordings of a 10 Hz, 0.85 mV peak sinusoidal gate signal applied through the reference electrode. The bias voltages of the graphene transistor were V ds = 50 mV and V gs = 250 mV. b, transfer curve of the same graphene transistor at V ds = 50 mV. The dashed line indicates the V gs bias voltage used in a. c, voltage signal obtained by interpolating the current signal (a) of each transistor to its respective transfer curve and removing the V gs offset.

[0036] Figure 5 shows the cortical spreading depression mapped with graphene transistors. a, sublow frequency signals recorded by a 4x4, 400 pm grid pitch, gSGFET array (black lines) during the onset of a CSD event, as indicated in the top left panel. The contour plot shows the time delay of the CSD onset relative to the average time, illustrating the spatiotemporal course of the CSD. b, interpolated spatial voltage map showing the propagation of the same CSD event measured by the gSGFET array. a, b include a high-pass filtered at 0.1 Hz recording (red lines in a and bottom spatial voltage map in b) to illustrate the loss of signal information in conventional microelectrode recordings.

[0037] Figure 6a Figure 6b depicts the depth profile of the sublow frequency voltage changes caused by the cortical spreading depression in the rat cortex. a, layout of a fabricated 15 channel graphene intracortical probe and the ordered local field potential recordings. Sublow frequency recordings (black lines) during the onset of a CSD event. Dashed lines are interpolated from nearby transistors. b, colour map of the temporal course of the ultra-slow changes at the depth of the rat cortex during a CSD event. a-b, include the same signals high-pass filtered at 0.1 Hz (red lines) and their spatiotemporal colour maps to illustrate the loss of information in conventional microelectrode recordings. DETAILED DESCRIPTION

[0039] The first aspect of the present invention aims at a system for recording electrophysiological ultra-slow signals, such as Cortical Spreading Depression (CSD) signals, i.e. those signals with frequency values lower than 0.1 Hz; the device comprises a processing unit associated with or embedded in the device, and at least one graphene field effect transistor (gSGFET), preferably an array of graphene field effect transistors, comprising graphene as channel material contacted by source and drain terminals, and with a reference as gate terminal. Said graphene field effect transistor is connected to at least one filter, such as a low pass filter (LPF). The recorded current signal is converted into a voltage signal using the transfer curve of the transistor recorded to the start of the recording ds -V gs , the recorded current signal is converted into a voltage signal.

[0040] In an alternative embodiment of the present invention, at least one band pass filter (BPF) is arranged in a sequential or cascaded arrangement with the low pass filter (LPF). But both configurations of the two filters (LPF, BPF) should have the same value for the respective cut-off point.

[0041] The gSGFETs are devices in which graphene is used as channel material, contacted by two metal leads (source and drain terminals) and immersed in an electrolyte, with a reference electrode as gate terminal. Figure la A flexible probe containing an array of gSGFETs designed for cortical and intracortical recordings was produced. In particular, a 4x4 array of 100 pm wide x 50 pm long was designed for cortical recordings, while a design consisting of a linear array of 15 graphene channels (80 pm wide, 30 pm long) was designed for intracortical recordings. Figure lb Both array designs were fabricated on a 10 pm thick polyimide layer coated on a 4-inch silicon wafer. The flexible gSGFET arrays were placed in zero insertion force connectors for interfacing with recording electronics. Figure lc The transfer curves, drain current (I ds) vs. gate-source voltage (V gs), of all gSGFETs in each array were measured using a fixed drain-source voltage (V ds). The dispersion of the charge neutrality point (CNP = 243.6 ± 6.1 mV) is the minimum of the transfer curves, indicating the uniformity of the transistors. Figure Id Importantly, the small CNP dispersion allows for near-optimal recording performance of all gSGFETs in the same array, since the V gs and V ds bias are shared. Figure le The sum of the leakage currents (I gs) of all gSGFETs in the array was shown to be in the nA range throughout the voltage sweep, indicating a good insulation of the passivation layer and negligible reactivity of the graphene. Furthermore, we measured the frequency response of the transconductance (gm) of the gSGFETs, which indicates the efficiency of the signal coupling A constant value was obtained across a wide bandwidth, including sub-low frequencies. Figure If -g). If the negative gm of the Vgs value is lower than CNP, the signal measured under this bias will be out of phase (180° phase). For Vgs values ​​higher than CNP, the signal phase will be preserved.

[0042] The apparatus of the present invention is compared with conventional high-pass filtered recordings. To this end, the propagation of cortical diffusion suppression (CSD) events using a 4×4 epidermal gSGFET array is mapped and then compared with those observed in conventional high-pass filtered recordings. Figure 5a -b). Recording the entire CSD event using a gSGFET array showed that although the negative shift episodes were similar across all gSGFETs, subsequent recovery varied more, with the second negative shift amplitude being higher than the first for some transistors. Spatial map of gSGFET recordings coexisting in recovered and still-inhibited brain regions ( Figure 5b This effect can also be observed in the last frame of the recording (corresponding to 80s and 90s, respectively). Importantly, this information is lost in conventional microelectrode recordings, where only CSD episodes are observed due to the high-pass filter in the recording electronics. The following results pertain to 10 CSD samples collected from two different subjects in the somatosensory cortex: we found that the mean duration of CSD events was 47.24 ± 7.65 s, and the propagation speed was 7.68 ± 1.35 mm / min, consistent with the literature that defines CSD as ultraslow brain waves.

[0043] To further illustrate the potential of the device of the present invention and to utilize the design versatility offered by this technology, a linear array of 15g SGFETs spanning the entire cortical depth was provided. Figure 6a From ordered records or space-time voltage diagrams () Figure 6b This demonstrates how CSD occurs throughout the cortical depth. These results highlight the ability of the device of the present invention to reveal rich patterns of ultraslow signals in the cortex. In this particular case, a transition from long depolarization to shorter depolarization in the surface layer can be clearly observed, preceded and followed by hyperpolarization in deeper layers. The origin of this depth-related effect is not well understood and will be the target of further research utilizing the proven capabilities of gSGFET technology to monitor ISA at high spatial resolution.

[0044] In a second aspect of the application, a method for recording ultra-slow brain signals, those with frequency values below 0.1 Hz, is provided, the Cortical Spreading Depression (CSD) being chosen to illustrate the ability of the present application to record with a wide bandwidth. Experimentally, two craniotomies were performed on the left hemisphere of a Wistar rat anesthetized with isoflurane: a larger craniotomy was performed on the main somatosensory cortex, where a cortical probe was placed, and a smaller craniotomy was performed in the frontal cortex, where 5 mM KCl was locally applied to induce CSD Figure 2b ). Custom electronic circuits allowed us to record simultaneously two frequency bands: a low-pass filtered band (LPF, ~0-0.16 Hz) with different gain and a band-pass filtered band (BPF, 0.16 Hz-10 kHz) (10 4 and 10 6 , respectively), avoiding amplifier saturation due to the high amplitude CSD signal, respectively. In a first set of experiments, we recorded the LPF and BPF current signals with the cortical gSGFET array during the induction of CSD events Figure 2c ). The graphene transistors were polarized in the hole conduction regime, i.e. V gs < CNP (negative g m ); therefore, the recorded LPF and BPF current signals were inverted with respect to the voltage signal appearing at the gate. The LPF signal showed very slow CSD events, while the BPF signal corresponded to the local electric field potential, revealing the activity silence characteristic of the cortical spreading depression. After summing the LPF and BPF signals, the current was converted into a voltage signal (using the transistor transfer curve I ds -V gs recorded in vivo before starting the recording), a wide-band electrophysiological signal could be obtained (see Figure 2a , c). In each CSD event, a small positive shift of 1-2 mV was usually observed before the depression, followed by a sharp negative change (~ -20 mV) immediately after, which slowly recovered in the following minute or so. The CSD-related high-frequency activity silence and its gradual recovery are shown in the voltage wave and spectrogram of Figure 2d .

Claims

1. Graphene transistor system for measuring electrophysiological signals, comprising: a. a processing unit, and b. at least one graphene field effect transistor (gSGFET) comprising graphene as channel material contacted by two terminals, characterized in that the graphene transistor system comprises the following components connected to the graphene field effect transistor (gSGFET): a. an adjustable voltage source connected to the drain terminal and the source terminal of the graphene field effect transistor (gSGFET), referred to as gate voltage, and b. an electronic circuit comprising at least one low pass filter (LPF) and at least one band pass filter (BPF) configured to obtain a signal from the at least one graphene field effect transistor and to split the signal into at least a low frequency band signal and a high frequency band signal, wherein the low frequency band signal is amplified by the low pass filter (LPF) with a first gain value and the high frequency band signal is amplified by the band pass filter (BPF) with a second gain value, wherein the first gain value of the low pass filter (LPF) is lower than the second gain value of the band pass filter (BPF).

2. The graphene transistor system for measuring electrophysiological signals of claim 1, wherein, The electronic circuit is configured to generate: a. a low pass filtered band with a frequency set between 0 Hz and 0.16 Hz, and b. a filtered band with a frequency between 0.16 Hz and 10 kHz.

3. The graphene transistor system for measuring electrophysiological signals of claim 2, wherein, The low pass filter (LPF) and the band pass filter (BPF) have different gains of 10 4 and 10 6 respectively.

4. The graphene transistor system for measuring electrophysiological signals of claim 1, wherein, The electronic circuit is further configured to combine the low frequency band signal and the high frequency band signal, each signal weighted by its corresponding gain value.

5. A method of measuring an electrophysiological signal using the graphene transistor system of any one of claims 1-3, characterized in that comprising: a. splitting an input signal into a low frequency band signal and a high frequency band signal using the electronic circuit, b. combining the low frequency band signal and the high frequency band signal weighted by the respective gain values into a combined signal, the first gain value of the low pass filter (LPF) being lower than the second gain value of the band pass filter (BPF), and c. converting the combined signal into a voltage signal according to the intrinsic gain of the graphene field effect transistor.

2. Graphene transistor system according to claim 1, wherein the graphene field effect transistor (gSGFET) is a graphene field effect transistor (gSGFET) according to any one of claims 2 to 7.

3. Graphene transistor system according to any one of claims 1 to 2, wherein the graphene field effect transistor (gSGFET) is a graphene field effect transistor (gSGFET) according to any one of claims 8 to 14.

4. Graphene transistor system according to any one of claims 1 to 3, wherein the graphene field effect transistor (gSGFET) is a graphene field effect transistor (gSGFET) according to any one of claims 15 to 21.

5. Graphene transistor system according to any one of claims 1 to 4, wherein the graphene field effect transistor (gSGFET) is a graphene field effect transistor (gSGFET) according to any one of claims 22 to 28.

6. Graphene transistor system according to any one of claims 1 to 5, wherein the graphene field effect transistor (gSGFET) is a graphene field effect transistor (gSGFET) according to any one of claims 29 to 35.

7. Graphene transistor system according to any one of claims 1 to 6, wherein the graphene field effect transistor (gSGFET) is a graphene field effect transistor (gSGFET) according to any one of claims 36 to 42.

6. The method of claim 5, wherein, By using a graphene transistor transfer curve I of the graphene transistor ds -V gs of the interpolation, a conversion to a voltage signal is performed, wherein I ds is the drain-source current of the graphene transistor, V gs is the gate-source voltage of the graphene transistor.

7. The method of claim 6, wherein, producing the transfer curve I of the graphene transistor with a fixed drain-source voltage (V ds) of the graphene transistor ds - V gs .

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